ethical guidelines for medical research involving human subjects

WMA Declaration of Helsinki – Ethical Principles for Medical Research Involving Human Subjects

Adopted by the 18 th WMA General Assembly, Helsinki, Finland, June 1964 and amended by the: 29 th WMA General Assembly, Tokyo, Japan, October 1975 35 th WMA General Assembly, Venice, Italy, October 1983 41 st WMA General Assembly, Hong Kong, September 1989 48 th WMA General Assembly, Somerset West, Republic of South Africa, October 1996 52 nd WMA General Assembly, Edinburgh, Scotland, October 2000 53 rd WMA General Assembly, Washington DC, USA, October 2002 (Note of Clarification added) 55 th WMA General Assembly, Tokyo, Japan, October 2004 (Note of Clarification added) 59 th WMA General Assembly, Seoul, Republic of Korea, October 2008 64 th WMA General Assembly, Fortaleza, Brazil, October 2013

1.         The World Medical Association (WMA) has developed the Declaration of Helsinki as a statement of ethical principles for medical research involving human subjects, including research on identifiable human material and data.

The Declaration is intended to be read as a whole and each of its constituent paragraphs should be applied with consideration of all other relevant paragraphs.

2.         Consistent with the mandate of the WMA, the Declaration is addressed primarily to physicians. The WMA encourages others who are involved in medical research involving human subjects to adopt these principles.

General Principles

3.         The Declaration of Geneva of the WMA binds the physician with the words, “The health of my patient will be my first consideration,” and the International Code of Medical Ethics declares that, “A physician shall act in the patient’s best interest when providing medical care.”

4.         It is the duty of the physician to promote and safeguard the health, well-being and rights of patients, including those who are involved in medical research. The physician’s knowledge and conscience are dedicated to the fulfilment of this duty.

5.         Medical progress is based on research that ultimately must include studies involving human subjects.

6.         The primary purpose of medical research involving human subjects is to understand the causes, development and effects of diseases and improve preventive, diagnostic and therapeutic interventions (methods, procedures and treatments). Even the best proven interventions must be evaluated continually through research for their safety, effectiveness, efficiency, accessibility and quality.

7.         Medical research is subject to ethical standards that promote and ensure respect for all human subjects and protect their health and rights.

8.         While the primary purpose of medical research is to generate new knowledge, this goal can never take precedence over the rights and interests of individual research subjects.

9.         It is the duty of physicians who are involved in medical research to protect the life, health, dignity, integrity, right to self-determination, privacy, and confidentiality of personal information of research subjects. The responsibility for the protection of research subjects must always rest with the physician or other health care professionals and never with the research subjects, even though they have given consent.

10.       Physicians must consider the ethical, legal and regulatory norms and standards for research involving human subjects in their own countries as well as applicable international norms and standards. No national or international ethical, legal or regulatory requirement should reduce or eliminate any of the protections for research subjects set forth in this Declaration.

11.       Medical research should be conducted in a manner that minimises possible harm to the environment.

12.       Medical research involving human subjects must be conducted only by individuals with the appropriate ethics and scientific education, training and qualifications. Research on patients or healthy volunteers requires the supervision of a competent and appropriately qualified physician or other health care professional.

13.       Groups that are underrepresented in medical research should be provided appropriate access to participation in research.

14.       Physicians who combine medical research with medical care should involve their patients in research only to the extent that this is justified by its potential preventive, diagnostic or therapeutic value and if the physician has good reason to believe that participation in the research study will not adversely affect the health of the patients who serve as research subjects.

15.       Appropriate compensation and treatment for subjects who are harmed as a result of participating in research must be ensured.

Risks, Burdens and Benefits

16.       In medical practice and in medical research, most interventions involve risks and burdens.

Medical research involving human subjects may only be conducted if the importance of the objective outweighs the risks and burdens to the research subjects.

17.       All medical research involving human subjects must be preceded by careful assessment of predictable risks and burdens to the individuals and groups involved in the research in comparison with foreseeable benefits to them and to other individuals or groups affected by the condition under investigation.

Measures to minimise the risks must be implemented. The risks must be continuously monitored, assessed and documented by the researcher.

18.       Physicians may not be involved in a research study involving human subjects unless they are confident that the risks have been adequately assessed and can be satisfactorily managed.

When the risks are found to outweigh the potential benefits or when there is conclusive proof of definitive outcomes, physicians must assess whether to continue, modify or immediately stop the study.

Vulnerable Groups and Individuals

19.       Some groups and individuals are particularly vulnerable and may have an increased likelihood of being wronged or of incurring additional harm.

All vulnerable groups and individuals should receive specifically considered protection.

20.       Medical research with a vulnerable group is only justified if the research is responsive to the health needs or priorities of this group and the research cannot be carried out in a non-vulnerable group. In addition, this group should stand to benefit from the knowledge, practices or interventions that result from the research.

Scientific Requirements and Research Protocols

21.       Medical research involving human subjects must conform to generally accepted scientific principles, be based on a thorough knowledge of the scientific literature, other relevant sources of information, and adequate laboratory and, as appropriate, animal experimentation. The welfare of animals used for research must be respected.

22.       The design and performance of each research study involving human subjects must be clearly described and justified in a research protocol.

The protocol should contain a statement of the ethical considerations involved and should indicate how the principles in this Declaration have been addressed. The protocol should include information regarding funding, sponsors, institutional affiliations, potential conflicts of interest, incentives for subjects and information regarding provisions for treating and/or compensating subjects who are harmed as a consequence of participation in the research study.

In clinical trials, the protocol must also describe appropriate arrangements for post-trial provisions.

Research Ethics Committees

23.       The research protocol must be submitted for consideration, comment, guidance and approval to the concerned research ethics committee before the study begins. This committee must be transparent in its functioning, must be independent of the researcher, the sponsor and any other undue influence and must be duly qualified. It must take into consideration the laws and regulations of the country or countries in which the research is to be performed as well as applicable international norms and standards but these must not be allowed to reduce or eliminate any of the protections for research subjects set forth in this Declaration.

The committee must have the right to monitor ongoing studies. The researcher must provide monitoring information to the committee, especially information about any serious adverse events. No amendment to the protocol may be made without consideration and approval by the committee. After the end of the study, the researchers must submit a final report to the committee containing a summary of the study’s findings and conclusions.

Privacy and C onfidentiality

24.       Every precaution must be taken to protect the privacy of research subjects and the confidentiality of their personal information.

Informed Consent

25.       Participation by individuals capable of giving informed consent as subjects in medical research must be voluntary. Although it may be appropriate to consult family members or community leaders, no individual capable of giving informed consent may be enrolled in a research study unless he or she freely agrees.

26.       In medical research involving human subjects capable of giving informed consent, each potential subject must be adequately informed of the aims, methods, sources of funding, any possible conflicts of interest, institutional affiliations of the researcher, the anticipated benefits and potential risks of the study and the discomfort it may entail, post-study provisions and any other relevant aspects of the study. The potential subject must be informed of the right to refuse to participate in the study or to withdraw consent to participate at any time without reprisal. Special attention should be given to the specific information needs of individual potential subjects as well as to the methods used to deliver the information.

After ensuring that the potential subject has understood the information, the physician or another appropriately qualified individual must then seek the potential subject’s freely-given informed consent, preferably in writing. If the consent cannot be expressed in writing, the non-written consent must be formally documented and witnessed.

All medical research subjects should be given the option of being informed about the general outcome and results of the study.

27.       When seeking informed consent for participation in a research study the physician must be particularly cautious if the potential subject is in a dependent relationship with the physician or may consent under duress. In such situations the informed consent must be sought by an appropriately qualified individual who is completely independent of this relationship.

28.       For a potential research subject who is incapable of giving informed consent, the physician must seek informed consent from the legally authorised representative. These individuals must not be included in a research study that has no likelihood of benefit for them unless it is intended to promote the health of the group represented by the potential subject, the research cannot instead be performed with persons capable of providing informed consent, and the research entails only minimal risk and minimal burden.

29.       When a potential research subject who is deemed incapable of giving informed consent is able to give assent to decisions about participation in research, the physician must seek that assent in addition to the consent of the legally authorised representative. The potential subject’s dissent should be respected.

30.       Research involving subjects who are physically or mentally incapable of giving consent, for example, unconscious patients, may be done only if the physical or mental condition that prevents giving informed consent is a necessary characteristic of the research  group. In such circumstances the physician must seek informed consent from the legally authorised representative. If no such representative is available and if the research cannot be delayed, the study may proceed without informed consent provided that the specific reasons for involving subjects with a condition that renders them unable to give informed consent have been stated in the research protocol and the study has been approved by a research ethics committee. Consent to remain in the research must be obtained as soon as possible from the subject or a legally authorised representative.

31.       The physician must fully inform the patient which aspects of their care are related to the research. The refusal of a patient to participate in a study or the patient’s decision to withdraw from the study must never adversely affect the patient-physician relationship.

32.       For medical research using identifiable human material or data, such as research on material or data contained in biobanks or similar repositories, physicians must seek informed consent for its collection, storage and/or reuse. There may be exceptional situations where consent would be impossible or impracticable to obtain for such research. In such situations the research may be done only after consideration and approval of a research ethics committee.

Use of Placebo

33.       The benefits, risks, burdens and effectiveness of a new intervention must be tested against those of the best proven intervention(s), except in the following circumstances:

Where no proven intervention exists, the use of placebo, or no intervention, is acceptable; or

Where for compelling and scientifically sound methodological reasons the use of any intervention less effective than the best proven one, the use of placebo, or no intervention is necessary to determine the efficacy or safety of an intervention

and the patients who receive any intervention less effective than the best proven one, placebo, or no intervention will not be subject to additional risks of serious or irreversible harm as a result of not receiving the best proven intervention.

Extreme care must be taken to avoid abuse of this option.

Post-Trial Provisions

34.       In advance of a clinical trial, sponsors, researchers and host country governments should make provisions for post-trial access for all participants who still need an intervention identified as beneficial in the trial. This information must also be disclosed to participants during the informed consent process.

Research Registration and Publication and Dissemination of Results

35.       Every research study involving human subjects must be registered in a publicly accessible database before recruitment of the first subject.

36.       Researchers, authors, sponsors, editors and publishers all have ethical obligations with regard to the publication and dissemination of the results of research. Researchers have a duty to make publicly available the results of their research on human subjects and are accountable for the completeness and accuracy of their reports. All parties should adhere to accepted guidelines for ethical reporting. Negative and inconclusive as well as positive results must be published or otherwise made publicly available. Sources of funding, institutional affiliations and conflicts of interest must be declared in the publication. Reports of research not in accordance with the principles of this Declaration should not be accepted for publication.

Unproven Interventions in Clinical Practice

37.       In the treatment of an individual patient, where proven interventions do not exist or other known interventions have been ineffective, the physician, after seeking expert advice, with informed consent from the patient or a legally authorised representative, may use an unproven intervention if in the physician’s judgement it offers hope of saving life, re-establishing health or alleviating suffering. This intervention should subsequently be made the object of research, designed to evaluate its safety and efficacy. In all cases, new information must be recorded and, where appropriate, made publicly available.

Policy Types

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Related WMA Policies

Wma declaration of venice on end of life medical care, wma international code of medical ethics.

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• Published: 10 May 2021

Looking back: three key lessons from 20 years of shaping Japanese genome research regulations

• Jusaku Minari   ORCID: orcid.org/0000-0002-6773-4741 1 ,
• Megumu Yokono 2 ,
• Kayo Takashima 1 ,
• Minori Kokado 3 ,
• Ryuichi Ida 4 &
• Yutaka Hishiyama 5  

Journal of Human Genetics volume  66 ,  pages 1039–1041 ( 2021 ) Cite this article

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Since August 2018, a governmental committee in Japan formed jointly by three relevant ministries has reviewed two existing governmental ethical guidelines for revision: Ethical Guidelines for Human Genome/Gene Analysis Research (Genome Guidelines) and Ethical Guidelines for Medical and Health Research Involving Human Subjects. A single set of guidelines integrating the two, keeping the latter as the main framework, was released in March 2021. The Genome Guidelines, established in 2001 ahead of two other governmental ethical guidelines on epidemiological research (2002) and clinical research (2003), have largely contributed to regulating genome research in Japan. This article, which reviews 20 years of experience regarding the Genome Guidelines, suggests three key lessons for future regulatory debates and practices. Through this article, the authors, who have been closely involved either in elaborating and/or in applying the Genome Guidelines, advocate for inquiring into the true nature of ethical regulation from the perspective of experts in the field of biomedical research ethics.

The first lesson concerns how to manage relationships between fundamental concepts and specific procedures. In 2000, the Bioethics Committee of the Council for Science and Technology established the Fundamental Principles of Research on the Human Genome (Fundamental Principles), thereby clarifying the conceptual ethical framework for the human genome and its related research. The 2001 Genome Guidelines presented concrete practical procedures, including the requirements for informed consent, research protocols and ethical review. Over the last 20 years, these principles and guidelines have been recognised as national norms, but their respective roles have gradually changed. While the fundamental principles have remained unchanged (only becoming less referenced in the practice of genome research), the 2001 Genome Guidelines have been repeatedly and dynamically revised to address scientific, ethical and social issues, becoming more detailed and procedurally concretised. These phenomena could be partly regarded as a formalisation of the principles elaborated upon in the Fundamental Principles and an increase in the procedural formalities (not necessarily linked with the conceptual background) of the 2001 Genome Guidelines. To emphasise the guidelines as practical, ethical and social instruments—not as mere checklists and flow charts—regulation drafters should continuously consider and present the historical background, reasons and implications underlying major stipulations, with connecting fundamental ideas and specific procedures, for their future developments.

The second lesson concerns the specificity of the non-legally binding nature of the guidelines. Until recently, soft laws (i.e., non-legally binding guidelines) have been widely adopted in Japanese medical research [ 1 , 2 ] to ensure regulatory responsiveness and flexibility regarding scientific advancement and societal changes. The Genome Guidelines have undergone three complete and four partial revisions, two of which were prompted by the enactment (2003) and revision (2015) of the Act on the Protection of Personal Information (APPI) [ 3 , 4 , 5 ]. Although the APPI was intended to address commercial or business activities, rather than academic research, it has significantly influenced the Genome Guidelines’ provisions regarding the collection, storage and transfer of genetic/personal data. Incorporating the APPI’s provisions into the Genome Guidelines could ensure legal protection. However, it could also cause regulatory instability and confusion for research developments, given that provisions regarding research-related genetic/personal data handling may be irregularly changed due to the APPI’s amendment and related regulations, which are also influenced by the enactments and their revisions in other jurisdictions (e.g., the European Union General Data Protection Regulation ). Specific hard laws may be necessary to stabilise an appropriate genome research environment while considering international regulatory coordination. Legislation by the Diet members could enable the public to be involved in the creation of regulations. Furthermore, new establishments and frequent revisions of various governmental guidelines and recent legislations in specific fields, such as clinical research and regenerative medicine, could create excessive burdens for the rapid implementation of a particular regulation within the research community and for the governmental administration and management of numerous regulations. To avoid creating a regulation ‘maze’ and to build sustainable regulatory research environments, key stakeholders should consider harmonising the relevant regulations and optimising ethical research developments.

The last lesson concerns the ethical framework of biomedical data research to protect human subjects. While the conventional ethical framework of biomedical research is based on considerations of physical rather than informational harm [ 6 ], genome research development, including data sharing and biobanking, has increasingly questioned the privacy, confidentiality and security of genome information in light of research ethics. Conversely, influenced by the 1980 Organisation for Economic Co-operation and Development Guidelines on the Protection of Privacy and Transborder Flows of Personal Data, Japan enacted the APPI to ensure the appropriate use and protection of personal data. Consequently, these two streams of research ethics and personal data protection have been incorporated into the Genome Guidelines, as represented in the coexistence of ‘informed consent’ (concerning research) and ‘consent’ (concerning data protection). Simultaneous duplication of the rules of applying legally binding privacy legislation and observing nonbinding ethical regulations has made it more difficult to adjust research ethics and privacy protection. To solve this issue, at least the ethical and legal norms of ‘data subjects’ should be explored, specifically in the case of research using human-derived data without intervention on human subjects or invasion of privacy (secondary use research) [ 7 , 8 ]. In addition, the implications of applying traditional ethical principles on human subject research to this type of research should be examined while considering matters regarding family, community and ethnicity, where online approaches, including dynamic consent, may contribute to addressing these challenges [ 9 ].

Although some issues remain unresolved, the new guidelines embody several major changes: introducing online consent; clarifying returning research results; and promoting single/central ethics review(s) in multi-centre research. Given the increasing growth of life sciences, the newly integrated guidelines were renamed Ethical Guidelines for Life Science, Medical, and Health Research Involving Human Subjects. Notably, governmental guidelines are shaped with an ‘administrative drafting technique’, so their language, expressions and embodiments are often constrained. Thus, when research communities proactively interpret and apply the new guidelines in a practical sense while carefully considering the situation of research participants, these new guidelines must be useful and effective. Finally, since the protection of human subjects and data is related to the public at large, public trust and engagement initiatives [ 10 ] could contribute to further sustainable development in biomedical research fields.

Slingsby BT, Nagao N, Akabayashi A. Administrative legislation in Japan: guidelines on scientific and ethical standards. Camb Q Health Ethics. 2004;13:245–53. https://doi.org/10.1017/s0963180104133070 .

Article   Google Scholar  

Tashiro S. Unintended consequences of “soft” regulations: the social control of human biomedical research in Japan. Int J Jpn Sociol. 2010;19:4–17.

Minari J, Chalmers D, Kato K. Return of genetic research results: the Japanese experience and its implications for the international debate. SCRIPTed. 2014;11:180–92.

Nagai H. Development of personal data handling policy in human genome research: a historical perspective in Japan. Asian Bioeth Rev. 2017;9:183–97.

Yamamoto N, Fujita T, Kawashima M, Wittig J, Suzuki M, Kato K. The inclusion of genomic data in the 2015 revision of Japan’s Protection of Personal Information Act: protection of wider range of genomic data as our next challenge. J Hum Genet. 2018;63:537–8. https://doi.org/10.1038/s10038-017-0409-4 .

Article   PubMed   Google Scholar  

Kaye J. From single biobanks to international networks: developing e-governance. Hum Genet. 2011;130:377–82. https://doi.org/10.1007/s00439-011-1063-0 .

Article   CAS   PubMed   PubMed Central   Google Scholar  

Metcalf J, Crawford K. Where are human subjects in Big Data research? The emerging ethics divide. BDS. 2016; https://doi.org/10.1177/2053951716650211 .

Nicol D, Eckstein L, Bentzen HB, Borry P, Burgess M, Burke W, et al. Consent insufficient for data release. Science. 2019;364:445–6. https://doi.org/10.1126/science.aax0892 .

Article   CAS   PubMed   Google Scholar  

Teare HJA, Prictor M, Kaye J. Reflections on dynamic consent in biomedical research: the story so far. Eur J Hum Genet. 2020;1–8. https://doi.org/10.1038/s41431-020-00771-z .

Hishiyama Y, Minari J, Suganuma N. The survey of public perception and general knowledge of genomic research and medicine in Japan conducted by the Japan Agency for Medical Research and Development. J Hum Genet. 2019;64:397–407. https://doi.org/10.1038/s10038-019-0587-3 .

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Acknowledgements

JM, KT, and MY are supported by the SECOM Science and Technology Foundation, JM and MK are supported by JSPS Grant-in-Aid for Challenging Research (Exploratory) (19K21566), and MY is supported by JST RISTEX (JPMJRX19B5, JPNJRX20JE).

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Jusaku Minari & Kayo Takashima

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Megumu Yokono

Laboratory of Social Sciences, Kobe Pharmaceutical University, Hyogo, Japan

Minori Kokado

Shiga University, Shiga, Japan

Ryuichi Ida

National Institute of Science and Technology Policy, Tokyo, Japan

Yutaka Hishiyama

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Minari, J., Yokono, M., Takashima, K. et al. Looking back: three key lessons from 20 years of shaping Japanese genome research regulations. J Hum Genet 66 , 1039–1041 (2021). https://doi.org/10.1038/s10038-021-00923-z

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Received : 19 February 2021

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Published : 10 May 2021

Issue Date : November 2021

DOI : https://doi.org/10.1038/s10038-021-00923-z

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Federal Policy for the Protection of Human Subjects ('Common Rule')

The current U.S. system of protection for human research subjects is heavily influenced by the Belmont Report , written in 1979 by the National Commission for the Protection of Human Subjects of Biomedical and Behavioral Research. The Belmont Report outlines the basic ethical principles in research involving human subjects. In 1981, with this report as foundational background, HHS and the Food and Drug Administration revised, and made as compatible as possible under their respective statutory authorities, their existing human subjects regulations.

The Federal Policy for the Protection of Human Subjects or the “Common Rule” was published in 1991 and codified in separate regulations by 15 Federal departments and agencies, as listed below. The HHS regulations, 45 CFR part 46 , include four subparts: subpart A, also known as the Federal Policy or the “Common Rule”; subpart B, additional protections for pregnant women, human fetuses, and neonates; subpart C, additional protections for prisoners; and subpart D, additional protections for children. Each agency includes in its chapter of the Code of Federal Regulations [CFR] section numbers and language that are identical to those of the HHS codification at 45 CFR part 46, subpart A. For all participating departments and agencies the Common Rule outlines the basic provisions for IRBs, informed consent, and Assurances of Compliance. Human subject research conducted or supported by each federal department/agency is governed by the regulations of that department/agency. The head of that department/agency retains final judgment as to whether a particular activity it conducts or supports is covered by the Common Rule. If an institution seeks guidance on implementation of the Common Rule and other applicable federal regulations, the institution should contact the department/agency conducting or supporting the research.

The list below displays the agencies and departments that have signed onto the Common Rule and their CFR numbers. Hyperlinks are to areas of a department or agency Web site that have been suggested to HHS as entry points for those interested in human subject protection activities of the department or agency.

General information:

• Of these, 15 agencies are official signatories with the rule codified in their own Code of Federal Regulations (CFR) sections
• 4 departments and agencies follow the Pre-2018 Common Rule because of executive order or statutory mandate (Department of Homeland Security, Social Security Administration, Office of the Director of National Intelligence, and Central Intelligence Agency)
• There is 1 new signatory to the revised Common Rule (Department of Labor)
• 2 agencies that followed the pre-2018 Common Rule because of executive order or statutory mandate have become official signatories to the revised Common Rule (Department of Homeland Security and Social Security Administration)
• 1 original signatory (Department of Justice) intends to become an official signatory to the revised Common Rule
• You can find more information about the FDA regulations here

Common Rule Departments and Agencies:

For additional details about the agencies and departments that have signed onto the Common Rule, including contact information and links to relevant webpages/resources, please visit https://www.hhs.gov/ohrp/education-and-outreach/revised-common-rule/common-rule-departments-agencies/index.html .

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Nih clinical research trials and you, guiding principles for ethical research.

Pursuing Potential Research Participants Protections

“When people are invited to participate in research, there is a strong belief that it should be their choice based on their understanding of what the study is about, and what the risks and benefits of the study are,” said Dr. Christine Grady, chief of the NIH Clinical Center Department of Bioethics, to Clinical Center Radio in a podcast.

Clinical research advances the understanding of science and promotes human health. However, it is important to remember the individuals who volunteer to participate in research. There are precautions researchers can take – in the planning, implementation and follow-up of studies – to protect these participants in research. Ethical guidelines are established for clinical research to protect patient volunteers and to preserve the integrity of the science.

NIH Clinical Center researchers published seven main principles to guide the conduct of ethical research:

Social and clinical value

Scientific validity, fair subject selection, favorable risk-benefit ratio, independent review, informed consent.

• Respect for potential and enrolled subjects

Every research study is designed to answer a specific question. The answer should be important enough to justify asking people to accept some risk or inconvenience for others. In other words, answers to the research question should contribute to scientific understanding of health or improve our ways of preventing, treating, or caring for people with a given disease to justify exposing participants to the risk and burden of research.

A study should be designed in a way that will get an understandable answer to the important research question. This includes considering whether the question asked is answerable, whether the research methods are valid and feasible, and whether the study is designed with accepted principles, clear methods, and reliable practices. Invalid research is unethical because it is a waste of resources and exposes people to risk for no purpose

The primary basis for recruiting participants should be the scientific goals of the study — not vulnerability, privilege, or other unrelated factors. Participants who accept the risks of research should be in a position to enjoy its benefits. Specific groups of participants  (for example, women or children) should not be excluded from the research opportunities without a good scientific reason or a particular susceptibility to risk.

Uncertainty about the degree of risks and benefits associated with a clinical research study is inherent. Research risks may be trivial or serious, transient or long-term. Risks can be physical, psychological, economic, or social. Everything should be done to minimize the risks and inconvenience to research participants to maximize the potential benefits, and to determine that the potential benefits are proportionate to, or outweigh, the risks.

To minimize potential conflicts of interest and make sure a study is ethically acceptable before it starts, an independent review panel should review the proposal and ask important questions, including: Are those conducting the trial sufficiently free of bias? Is the study doing all it can to protect research participants? Has the trial been ethically designed and is the risk–benefit ratio favorable? The panel also monitors a study while it is ongoing.

Potential participants should make their own decision about whether they want to participate or continue participating in research. This is done through a process of informed consent in which individuals (1) are accurately informed of the purpose, methods, risks, benefits, and alternatives to the research, (2) understand this information and how it relates to their own clinical situation or interests, and (3) make a voluntary decision about whether to participate.

Respect for potential and enrolled participants

Individuals should be treated with respect from the time they are approached for possible participation — even if they refuse enrollment in a study — throughout their participation and after their participation ends. This includes:

• respecting their privacy and keeping their private information confidential
• respecting their right to change their mind, to decide that the research does not match their interests, and to withdraw without a penalty
• informing them of new information that might emerge in the course of research, which might change their assessment of the risks and benefits of participating
• monitoring their welfare and, if they experience adverse reactions, unexpected effects, or changes in clinical status, ensuring appropriate treatment and, when necessary, removal from the study
• informing them about what was learned from the research

More information on these seven guiding principles and on bioethics in general

This page last reviewed on March 16, 2016

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International Ethical Guidelines for Biomedical Research Involving Human Subjects

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• isbn: 9290360755
• Year of publication: 2002
• Number of pages: 60

This text has been replaced by the CIOMS International ethical guidelines for health-related research involving humans (2016).

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The 2002 International Ethical Guidelines for Biomedical Research Involving Human Subjects superseded the 1993 Guidelines and were the third in the series of biomedical-research ethical guidelines issued by CIOMS since 1982. They were replaced by the International ethical guidelines for health-related research involving humans published by CIOMS in 2016.

The 2002 text consists of 21 guidelines with commentaries. A prefatory section outlines the historical background and the revision process, and includes an introduction, an account of earlier instruments and guidelines, a statement of ethical principles and a preamble. An Appendix lists the items to be included in the research protocol to be submitted for scientific and ethical review and clearance. Appendices include also the World Medical Association’s Declaration of Helsinki.

The Guidelines relate mainly to ethical justification and scientific validity of research; ethical review; informed consent; vulnerability ­ of individuals, groups, communities and populations; women as research subjects; equity regarding burdens and benefits; choice of control in clinical trials; confidentiality; compensation for injury; strengthening of national or local capacity for ethical review; and obligations of sponsors to provide health-care services.

Their scope reflects the changes, the advances and the controversies that have characterized biomedical research ethics in the last two decades. Like those of 1982 and 1993, the 2002 CIOMS Guidelines are designed to be of use to countries in defining national policies on the ethics of biomedical research involving human subjects, applying ethical standards in local circumstances, and establishing or improving ethical review mechanisms. A particular aim is to reflect the conditions and the needs of low-resource countries, and the implications for multinational or transnational research in which they may be partners.

Ethical principles for medical research involving human subjects

• PMID: 11587468
• DOI: 10.1097/00063110-200109000-00010

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Ethics in Medical Research and Publication

Department of Family Medicine, Faculty of Medicine, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

Ajla Hodzic

Smaila mulic.

To present the basic principles and standards of Ethics in medical research and publishing, as well as the need for continuing education in the principles and ethics in science and publication in biomedicine. An analysis of relevant materials and documents, sources from the published literature. Investing in education of researches and potential researches, already in the level of medical schools. Educating them on research ethics, what constitutes research misconduct and the seriousness of it repercussion is essential for finding a solution to this problem and ensuring careers are constructed on honesty and integrity.

INTRODUCTION

Science is a key link in the educational system, it is part of the culture of the nation, further on it contributes to overall well-being and security in everyday life, and represents a source of real knowledge of mankind. In most cases, the scientist is a person of exceptional diligence, which is at the same time, very focused on what it does. If one deals with the scientific work, can significantly improve the human condition; thus, it will make a great effort and sacrifice many daily pleasures.[ 1 ]

PRINCIPLES OF WRITING A SCIENTIFIC PAPER

Scientific research demands precision.[ 2 , 3 , 4 ] Scientific writing should respect this precision in the form of clarity. Unfortunately, a glance at almost any scientific journal will reveal that the above-stated ideal is often not attained in the real world of scholarly publication.[ 5 , 6 ] Indeed, many of the accusations by nonscientific of “obscurity” and “elitism” within the scientific community probably originate in the sad fact that many scientists are not capable of expressing their hypotheses and conclusions clearly and simply.[ 7 ]

The scientific way of thinking and application of scientific methods require honesty, criticality, trust, creativity and openness, and acceptance of these principles as desirable prerequisites for successful engagement in science by students and young researchers, qualifying research institution that produces competent promoters (initiators) for the future technological cultural and political development of society.[ 1 ]

Defining principles of good scientific and good laboratory practice should encourage the development of standardized principles and guidelines for accurate and quality data in scientific research.[ 1 ]

The text of observational and experimental articles is usually divided into sections in accordance with so-called “IMRAD” structure: Introduction, Methods, Results, and Discussion. Papers related to public health programs and practice might have different than IMRAD structure (drug). There is a key question for each section of the IMRAD structure of the paper, which an author needs to keep in mind, while writing the manuscript.[ 6 ]

Title of the scientific paper contains a brief description of the content. The title should accurately describe the content of the article. There are two types of titles: Indicative title talks about the work that covers and informative title-convey the message of the article and recommended for beginners. A good title should be: (a) Short, (b) correct, (c) a clear, (d) complete, (e) informing, (d) attractive. It should also include: Characteristics of the article, showing what is most important in the work. It is necessary to specify the names of the authors and their affiliations.

Abstract/summary and title can be written in two forms: Reference and Information. It can be written in author's native language and English. The structure of the summary should look like this: Introduction, goal, materials and methods, the location of the study, measuring the outcomes of the study, the results and conclusions.

Summary is the distillate of which will be presented and should show: What has been done, what are the results, what the results means. Writing an introduction has its own rules: A clear definition of a the problem, why exactly this issue was explored, there is no need to explain what can be found in the textbooks, do not need to explain the terms of the title.

Materials and Methods describe how the study was conducted and the characteristics of the sample (experimental group, controls, and their properties). It is necessary to explain what is researched, asked, tested as follows: Sampling (random, consecutive, and representative), the sample size (patient gender, age), the control group, and the criteria for exclusion from the study, the control group if any.

It should be described how the research was done: Type of study (prospective, retrospective or combined), data collection (surveys, inventory or checkup), the technique of measuring results (operative treatment, laboratory tests). It is necessary to specify where the research was conducted. Results are an important part of writing an article.

The research results are usually most carefully read and should be a detailed plan, well-documented at the optimal dose. Discussion is a critical review of the data described in the results. He results should be compared with other findings and discuss the theoretical and practical research outcome. Conclusion should be short, clear and precise. It is necessary to: Make the final statement of what logically follows from the results of the work, list only the most important and give the message. Good conclusions should not surprise attentive reader. The reader should get the impression that he himself had written it. References should be in accordance with the instructions provided by the journal, and otherwise used Vancouver or Harvard citation style.[ 8 ]

Papers related to public health programs and practice might have different than IMRAD structure. Anyhow, the paper should be written in logical order consisting informative or indicative title, an introductory section with description of the subject or public health problem and objectives, the current status or situation, recommended or realized program and activities, lessons learned, experiences, results and recommendations, and finally conclusions and a list of references. Special importance and validity have papers which describe new practice, approach and activities, have clear description, design of the practice, approach and activities, offers possibilities for implementation of the practice, approach and activities in other settings and environments, presents the experiences gained, lessons learned, and recommendations.[ 7 ]

ETHICAL PRINCIPLES FOR MEDICAL RESEARCH INVOLVING HUMAN SUBJECTS

The World Medical Association (WMA) has developed the Declaration of Helsinki [ Figure 1 ] as a statement of ethical principles for medical research involving human subjects, including research on identifiable human material and data. Consistent with the mandate of the WMA, the declaration is addressed primarily to physicians. The WMA encourages others who are involved in medical research involving human subjects to adopt these principles:[ 9 ]

The Declaration of Helsinki. Retrieved from: New edition of Declaration of Helsinki Available: http://www. hopitalmontfort.com/en/new-edition-declaration-helsinki

General principles

The Declaration of Geneva of the WMA binds the physician with the words, “The health of my patient will be my first consideration”, and the International Code of Medical Ethics declares that, “A physician shall act in the patient's best interest when providing medical care”.

It is the duty of the physician to promote and safeguard the health, well-being and rights of patients, including those who are involved in medical research. The physician's knowledge and conscience are dedicated to the fulfillment of this duty.

Medical progress is based on research that ultimately must include studies involving human subjects. The primary purpose of medical research involving human subjects is to understand the causes, development and effects of diseases and improve preventive, diagnostic and therapeutic interventions (methods, procedures, and treatments). Even the best proven interventions must be evaluated continually through research for their safety, effectiveness, efficiency, accessibility, and quality.

Medical research is subject to ethical standards that promote and ensure respect for all human subjects and protect their health and rights.

While the primary purpose of medical research is to generate new knowledge, this goal can never take precedence over the rights and interests of individual research subjects.

It is the duty of physicians who are involved in medical research to protect the life, health, dignity, integrity, right to self-determination, privacy, and confidentiality of personal information of research subjects. The responsibility for the protection of research subjects must always rest with the physician or other health care professionals and never with the research subjects, even though they have given consent.

Physicians must consider the ethical, legal and regulatory norms and standards for research involving human subjects in their own countries as well as applicable international norms and standards. No national or international ethical, legal or regulatory requirement should reduce or eliminate any of the protections for research subjects set forth in this declaration.

Medical research should be conducted in a manner that minimizes possible harm to the environment. Medical research involving human subjects must be conducted only by individuals with the appropriate ethics and scientific education, training and qualifications. Research on patients or healthy volunteers requires the supervision of a competent and appropriately qualified physician or other health care professional.

Groups that are underrepresented in medical research should be provided appropriate access to participation in research.

Physicians who combine medical research with medical care should involve their patients in research only to the extent that this is justified by its potential preventive, diagnostic or therapeutic value and if the physician has good reason to believe that participation in the research study will not adversely affect the health of the patients who serve as research subjects.

Appropriate compensation and treatment for subjects who are harmed as a result of participating in research must be ensured.

Risks, burdens and benefits

In medical practice and in medical research, most interventions involve risks and burdens. Medical research involving human subjects may only be conducted if the importance of the objective outweighs the risks and burdens to the research subjects.

All medical research involving human subjects must be preceded by careful assessment of predictable risks and burdens to the individuals and groups involved in the research in comparison with foreseeable benefits to them and to other individuals or groups affected by the condition under investigation. Measures to minimize the risks must be implemented. The risks must be continuously monitored, assessed and documented by the researcher. Physicians may not be involved in a research study involving human subjects unless they are confident that the risks have been adequately assessed and can be satisfactorily managed.

When the risks are found to outweigh the potential benefits or when there is conclusive proof of definitive outcomes, physicians must assess whether to continue, modify or immediately stop the study.

Vulnerable groups and individuals

Some groups and individuals are particularly vulnerable and may have an increased likelihood of being wronged or of incurring additional harm. All vulnerable groups and individuals should receive specifically considered protection.

Medical research with a vulnerable group is only justified if the research is responsive to the health needs or priorities of this group and the research cannot be carried out in a nonvulnerable group. In addition, this group should stand to benefit from the knowledge, practices or interventions that result from the research.

Scientific requirements and research protocols

Medical research involving human subjects must conform to generally accepted scientific principles, be based on a thorough knowledge of the scientific literature, other relevant sources of information, and adequate laboratory and as appropriate, animal experimentation. The welfare of animals used for research must be respected. The design and performance of each research study involving human subjects must be clearly described and justified in a research protocol.

The protocol should contain:

• A statement of the ethical considerations involved and should indicate how the principles in this declaration have been addressed
• Information regarding funding, sponsors, institutional affiliations, potential conflicts of interest, incentives for subjects and information regarding provisions for treating and/or compensating subjects who are harmed as a consequence of participation in the research study.

In clinical trials, the protocol must also describe appropriate arrangements for posttrial provisions.

Research ethics committees

The research protocol must be submitted for consideration, comment, guidance and approval to the concerned Research Ethics Committee before the study begins. This committee must be transparent in its functioning, must be independent of the researcher, the sponsor and any other undue influence and must be duly qualified. It must take into consideration the laws and regulations of the country or countries in which the research is to be performed as well as applicable international norms and standards, but these must not be allowed to reduce or eliminate any of the protections for research subjects set forth in this declaration.

The committee must have the right to monitor ongoing studies. The researcher must provide monitoring information to the committee, especially information about any serious adverse events. No amendment to the protocol may be made without consideration and approval by the committee. After the end of the study, the researchers must submit a final report to the committee containing a summary of the study's findings and conclusions.

Privacy and confidentiality

Every precaution must be taken to protect the privacy of research subjects and the confidentiality of their personal information.

Informed consent

Participation by individuals capable of giving informed consent as subjects in medical research must be voluntary. Although it may be appropriate to consult family members or community leaders, no individual capable of giving informed consent may be enrolled in a research study unless he or she freely agrees.

In medical research involving human subjects capable of giving informed consent, each potential subject must be adequately informed of the aims, methods, sources of funding, any possible conflicts of interest, institutional affiliations of the researcher, the anticipated benefits and potential risks of the study and the discomfort it may entail, poststudy provisions and any other relevant aspects of the study. The potential subject must be informed of the right to refuse to participate in the study or to withdraw consent to participate at any time without reprisal. Special attention should be given to the specific information needs of individual potential subjects as well as to the methods used to deliver the information.

After ensuring that the potential subject has understood the information, the physician or another appropriately qualified individual must then seek the potential subject's freely-given informed consent, preferably in writing. If the consent cannot be expressed in writing, the nonwritten consent must be formally documented and witnessed. All medical research subjects should be given the option of being informed about the general outcome and results of the study.

When seeking informed consent for participation in a research study the physician must be particularly cautious if the potential subject is in a dependent relationship with the physician or may consent under duress. In such situations the informed consent must be sought by an appropriately qualified individual who is completely independent of this relationship.

For a potential research subject who is incapable of giving informed consent, the physician must seek informed consent from the legally authorized representative. These individuals must not be included in a research study that has no likelihood of benefit for them unless it is intended to promote the health of the group represented by the potential subject, the research cannot instead be performed with persons capable of providing informed consent, and the research entails only minimal risk and minimal burden. When a potential research subject who is deemed incapable of giving informed consent is able to give assent to decisions about participation in research, the physician must seek that assent in addition to the consent of the legally authorized representative. The potential subject's dissent should be respected.

Research involving subjects who are physically or mentally incapable of giving consent, for example, unconscious patients, may be done only if the physical or mental condition that prevents giving informed consent is a necessary characteristic of the research group. In such circumstances the physician must seek informed consent from the legally authorized representative. If no such representative is available and if the research cannot be delayed, the study may proceed without informed consent provided that the specific reasons for involving subjects with a condition that renders them unable to give informed consent have been stated in the research protocol and the study has been approved by a Research Ethics Committee. Consent to remain in the research must be obtained as soon as possible from the subject or a legally authorized representative.

The physician must fully inform the patient, which aspects of their care are related to the research. The refusal of a patient to participate in a study or the patient's decision to withdraw from the study must never adversely affect the patient-physician relationship.

For medical research using identifiable human material or data, such as research on material or data contained in bio banks or similar repositories, physicians must seek informed consent for its collection, storage and/or reuse. There may be exceptional situations where consent would be impossible or impracticable to obtain for such research. In such situations, the research may be done only after consideration and approval of a Research Ethics Committee.

Use of placebo

The benefits, risks, burdens and effectiveness of a new intervention must be tested against those of the best proven intervention(s), except in the following circumstances:

Where no proven intervention exists, the use of placebo, or no intervention, is acceptable; or where for compelling and scientifically sound methodological reasons the use of any intervention less effective than the best proven one, the use of placebo, or no intervention is necessary to determine the efficacy or safety of an intervention and the patients who receive any intervention less effective than the best proven one, placebo, or no intervention will not be subject to additional risks of serious or irreversible harm as a result of not receiving the best proven intervention. Extreme care must be taken to avoid abuse of this option.

Posttrial provisions

In advance of a clinical trial, sponsors, researchers and host country governments should make provisions for posttrial access for all participants who still need an intervention identified as beneficial in the trial. This information must also be disclosed to participants during the informed consent process.

Research registration and publication and dissemination of results

Every research study involving human subjects must be registered in a publicly accessible database before recruitment of the first subject. Researchers, authors, sponsors, editors and publishers all have ethical obligations with regard to the publication and dissemination of the results of research. Researchers have a duty to make publicly available the results of their research on human subjects and are accountable for the completeness and accuracy of their reports. All parties should adhere to accepted guidelines for ethical reporting. Negative and inconclusive as well as positive results must be published or otherwise made publicly available. Sources of funding, institutional affiliations and conflicts of interest must be declared in the publication. Reports of research not in accordance with the principles of this declaration should not be accepted for publication.

Unproven interventions in clinical practice

In the treatment of an individual patient, where proven interventions do not exist or other known interventions have been ineffective, the physician, after seeking expert advice, with informed consent from the patient or a legally authorized representative, may use an unproven intervention if in the physician's judgment it offers hope of saving life, re-establishing health or alleviating suffering. This intervention should subsequently be made the object of research, designed to evaluate its safety and efficacy. In all cases, new information must be recorded and where appropriate, made publicly available.[ 9 ]

PUBLICATION ETHICS

Academic publishing depends, to a great extent, on trust. Editors trust peer reviewers to provide fair assessments, authors trust editors to select appropriate peer reviewers, and readers put their trust in the peer-review process. Academic publishing also occurs in an environment of powerful intellectual, financial, and sometimes political interests that may collide or compete. Good decisions and strong editorial processes designed to manage these interests will foster a sustainable and efficient publishing system, which will benefit academic societies, journal editors, authors, research funders, readers, and publishers.

Good publication practices do not develop by chance, and will become established only if they are actively promoted.[ 10 ]

The general principles of publication ethics are:

Transparency

Sources of funding for research or publication should always be disclosed. Editors should state this directly in their editorial policy. Authors should routinely include information about research funding in all papers they prepare for publication. Where a clinical trial registration number is available, this should be included.

Authorship acknowledgment

The International Committee of Medical Journal Editors (ICMJE) provides a definition of authorship that is applicable beyond the medical sector. The ICMJE authorship criteria state ‘authorship credit should be based on:

• Substantial contributions to conception and design, or acquisition of data, or analysis and interpretation of data;
• Drafting the article or revising it critically for important intellectual content; and
• Final approval of the version to be published.

Authors of research papers should state whether they had complete access to the study data that support the publication. Contributors who do not qualify as authors should also be listed and their particular contribution described. This information should appear as an acknowledgment. Sample authorship description/acknowledgment. Collecting authorship information for research papers, authorship should be decided at the study launch. Policing authorship is beyond the responsibilities of an editor. Editors should demand transparent and complete descriptions of who has contributed to a paper.

Editors should employ appropriate systems to inform contributors about authorship criteria (if used) and/or to obtain accurate information about individuals’ contributions.

Editors should ask authors to submit, as part of their initial submission package, a statement that all individuals listed as authors meet the appropriate authorship criteria, that nobody who qualifies for authorship has been omitted from the list, and that contributors and their funding sources have been properly acknowledged, and that authors and contributors have approved the acknowledgment of their contribution.

Attributing authorship to a group

The ICMJE provides guidance for instances where a number of authors report on behalf of a larger group of investigators.[ 1 ]

This guidance is applicable outside the medical sector.

International Committee of Medical Journal Editors guidance states: “When a large, multi-center group has conducted the work, the group should identify the individuals who accept direct responsibility for the manuscript. These individuals should fully meet the criteria for authorship defined above… When submitting a group author manuscript, the corresponding author should clearly indicate the preferred citation and should clearly identify all individual authors as well as the group name”. The individual authors who accept direct responsibility for the manuscript should list the members of the larger authorship group in an appendix to their acknowledgment.

Protecting research subjects

Journals should ask authors to state that the study they are submitting was approved by the relevant Research Ethics Committee or Institutional Review Board. If human participants were involved, manuscripts must be accompanied by a statement that the experiments were undertaken with the understanding and appropriate informed consent of each.

Editors should reserve the right to reject papers if there is doubt whether appropriate procedures have been followed. If a paper has been submitted from a country where there is no Ethics Committee, Institutional Review Board, or similar review and approval, editors should use their own experience to judge whether the paper should be published. If the decision is made to publish a paper under these circumstances a short statement should be included to explain the situation.[ 10 ]

THE MAIN FORMS OF SCIENTIFIC AND PUBLISHING MISCONDUCT

The Oxford English Dictionary describes fraud as “wrongful or criminal deception intended to result in financial or personal gain” and deceit as “the action or practice of deceiving someone by concealing or misrepresenting the truth”.[ 11 ]

Research organizations and the literature have defined these behavioral patterns within the umbrella title of “Research Misconduct”.[ 12 ]

There are three major and most severe forms of scientific fraud, scientific and publishing dishonesty or misconduct, in proposing, conducting or evaluation of research and presentation of the research results:

• Inventing data and results (fabrication);
• Alteration or changing the results (falsification); and
• Plagiarism (plagiarism), including self-plagiarism (self-plagiarism), fragmented, repetitive and double publication (duplicate publication).

Besides these, there are a number of other kinds of misconduct that scientists should know how to recognize and avoid that is, “pathology” of authorship, conflict of interest, conflicts of loyalty, “pathological” science, etc.

In the process of publishing scientific papers, it is important to know how a completed research should be described in a scientific paper.[ 6 ]

Falsification/fabrication of data

The integrity of research depends on the integrity of the data and the data record. As falsification and fabrication call into question the integrity of data and the data record, they represent serious issues in scientific ethics. Falsification is the practice of omitting or altering research materials, equipment, data, or processes in such a way that the results of the research are no longer accurately reflected in the research record. Fabrication is the practice of inventing data or results and recording and/or reporting them in the research record. Both of these schemes are probably among the most serious offenses in scientific research as they challenge the credibility of everyone and everything involved in a research effort.[ 13 ]

However, it is questionable whether a clinical researcher who fabricates data to enroll a terminally ill patient into a trial that ultimately may lead to that individual receiving treatment that may prolong their life should receive the same penalty as someone fabricating data for their own professional gain.[ 14 ]

These offenses make it very difficult for scientists to move forward as it is unclear to anyone what if anything is true and can be trusted-can lead students and colleagues to waste precious time, effort, and resources investigating dead ends.[ 13 ]

The term plagiarism stems from the Latin word plagium, meaning kidnapping a man. It literary means theft, taking material authored by others and presenting as someone else’ Plagiarism is basically intended to deceive the reader's. Izet Masic reminded of the comment of Samuel Johnson, dealing with a manuscript that he sent for evaluation: “Your work is both good and original. Unfortunately the parts that are good are not original, and the parts that are original are not good”.[ 13 ]

Referring to the United States’ Office of Research Integrity (ORI) definition of plagiarism, which is “unattributed textual copying”, many have questioned its applicability in real life situations. One definition of plagiarism suggests it is the repetition of 11 words or the overlap of 30 letter strings, although this is by no means a standard definition. Furthermore, “salami-slicing”-the selective use of research-project results to maximize the number of presentations possible-has also been classed as a type of plagiarism by some, but not by others.[ 14 ]

Plagiarism can be divided into direct (plagiarism of the text); mosaic (the borrowing ideas and opinions from original source and a few verbatim words of phrases without crediting the author) and self-plagiarism (which refers to re-using one's own work without citations).[ 15 ]

Researchers rely on the published data, and have to be skilled to selectively process these data, to incorporate previous knowledge into a new paper, and to distinguish original ideas and research results from already publicized ones. Authors are obliged to follow ethical, moral, and legal regulations acceptable by the scientific community. To do so, they must properly cite relevant publications and quote borrowed published or unpublished ideas and words. Simply, when an author copies others’ text word for word, the borrowed passage should be enclosed in the quotation marks (inverted commas). The reader should be clearly informed over what is original and recycled from other sources.[ 15 ]

Redundant (multiple) publication

Journal instructions should clearly explain what is, and what is not, considered to be prior publication. Journals may choose to accept (i.e. consider “not redundant”) the re-publication of materials that have been accurately translated from an original publication in a different language. Journals that translate and publish material that has been published elsewhere should ensure that they have appropriate permission (s), should indicate clearly that the material has been translated and re-published, and should indicate clearly the original source of the material. Editors may request copies of related publications if they are concerned about overlap and possible redundancy. Re-publishing in the same language as primary publication with the aim of serving different audiences is more difficult to justify when primary publication is electronic and therefore easily accessible, but if editors feel that this is appropriate they should follow the same steps as for translation. Editors should ensure that sub-group analyses, meta-and secondary analyses are clearly identified as analyses of data that have already been published, that they refer directly to the primary source, and that (if available) they include the clinical trial registration number from the primary publication.[ 16 ]

NATIONAL BODIES

One of the oldest organizations dealing with research misconduct is the ORI in the United States. Set up in 1992, it oversees and directs Public Health Service research integrity activities. With a huge budget of $30 billion, it provides significant funds in the areas of health, research, and development, and oversees bodies such as The National Institute of Health and The Office of Public Health and Science.[ 14 ]

The Committee on Publication Ethics (COPE) was established in 1997 by a small group of medical journal editors in the UK, but now has over 7000 members worldwide from all academic fields. Membership is open to editors of academic journals and others interested in publication ethics. Several major publishers (including Elsevier, Wiley-Blackwell, Springer, Taylor and Francis, Palgrave Macmillan and Wolters Kluwer) have signed up some, if not all, of their journals as COPE members. COPE provides advice to editors and publishers on all aspects of publication ethics and in particular, how to handle cases of research and publication misconduct. It also provides a forum for its members to discuss individual cases. COPE does not investigate individual cases, but encourages editors to ensure that cases are investigated by the appropriate authorities (usually a research institution or employer).[ 17 ]

The UK Research Integrity Office is another body representing the interests of over 50 universities and organizations dedicated to scientific research. Set up in 2006, its aims are to:

• Promote the good governance, management, and conduct of academic, scientific, and medical research;
• Share good practice on how to address poor practice, misconduct, and unethical behavior; and
• Give confidential, independent, and expert advice and guidance about the conduct of academic, scientific, and medical research.[ 18 ]

CONCLUSIONS

If one wants to create a scientific work, must have on his mind that creating a scientific work requires creativity and openness, honesty, trust, and obeying the ethical principles for writing a scientific paper.

As well an author in medical sciences should always follow the words; “The health of my patient will be my first consideration”, (Declaration of Geneva, Adopted by the 2 nd General Assembly of the WMA, Geneva, Switzerland, September 1948).[ 19 ]

While working on a an biomedical research involving human subjects medical workers should have on mind that it is the duty of the physician to remain the protector of the life and health of that person on whom biomedical research is being carried out.

The subjects should be volunteers-either healthy persons or patients for whom the experimental design is not related to the patient's illness.

The investigator or the investigating team should discontinue the research if in his/her or their judgment it may, if continued, be harmful to the individual.

In research on man, the interest of science and society should never take precedence over considerations related to the well-being of the subject.

Investing in education of researches and potential researches already in the level of medical schools, educating them on research ethics, what constitutes research misconduct and the seriousness of it repercussion is essential for finding a solution to this problem and ensuring careers are constructed on honesty and integrity.

Source of Support: Nil

Conflict of Interest: None declared.

Developing a Framework for Self-regulatory Governance in Healthcare AI Research: Insights from South Korea

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• Published: 25 March 2024

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• Junhewk Kim   ORCID: orcid.org/0000-0002-9109-270X 1 ,
• So Yoon Kim   ORCID: orcid.org/0000-0001-7015-357X 2 ,
• Eun-Ae Kim   ORCID: orcid.org/0000-0002-6989-559X 3 ,
• Jin-Ah Sim   ORCID: orcid.org/0000-0002-3494-3002 4 ,
• Yuri Lee   ORCID: orcid.org/0000-0003-0584-650X 5 &
• Hannah Kim   ORCID: orcid.org/0000-0003-2938-9745 2  

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This paper elucidates and rationalizes the ethical governance system for healthcare AI research, as outlined in the ‘Research Ethics Guidelines for AI Researchers in Healthcare’ published by the South Korean government in August 2023. In developing the guidelines, a four-phase clinical trial process was expanded to six stages for healthcare AI research: preliminary ethics review (stage 1); creating datasets (stage 2); model development (stage 3); training, validation, and evaluation (stage 4); application (stage 5); and post-deployment monitoring (stage 6). Researchers identified similarities between clinical trials and healthcare AI research, particularly in research subjects, management and regulations, and application of research results. In the step-by-step articulation of ethical requirements, this similarity benefits from a reliable and flexible use of existing research ethics governance resources, research management, and regulatory functions. In contrast to clinical trials, this procedural approach to healthcare AI research governance effectively highlights the distinct characteristics of healthcare AI research in research and development process, evaluation of results, and modifiability of findings. The model exhibits limitations, primarily in its reliance on self-regulation and lack of clear delineation of responsibilities. While formulated through multidisciplinary deliberations, its application in the research field remains untested. To overcome the limitations, the researchers’ ongoing efforts for educating AI researchers and public and the revision of the guidelines are expected to contribute to establish an ethical research governance framework for healthcare AI research in the South Korean context in the future.

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Introduction

The rapid progress of machine learning and artificial intelligence (AI) poses new and unprecedented challenges to the entire healthcare sector. Particularly, as a critical extension of the foundational discussions on the technology adoption in healthcare (Rajpurkjar et al. 2022 ), the focus now shifts towards the practical governance and regulation of AI development and its application in healthcare landscape. South Korea has swiftly embraced biomedical technologies, showcasing a clear inclination in integrating AI in healthcare. The ‘2022 Medical Device License Report’ from the Ministry of Food and Drug Safety (MFDS) of the Republic of Korea unveils that a total of 149 AI-based medical devices obtained approval and certification in the country, with 10 receiving approval and 38 attaining certification in 2022 (MFDS 2023 ).

Corresponding with this trend, the Korean National Institutes of Health (KNIH) published the ‘Research Ethics Guidelines for AI Researchers in Healthcare’ in August 2023, marking an initial effort to offer an actionable guidance to healthcare AI researchers in the country (KNIH 2023 ). The guidelines aim to establish ethical standards for all stages of healthcare AI development by presenting ethical principles and detailed values. The researchers mainly participated in developing the guidelines using robust research methodologies, such as literature reviews, interdisciplinary consultations, and a public hearing as well as providing empirical research evidence from surveys for the lay public and experts. Consequently, the guidelines present six principles with corresponding codes and explanations. The principles, stemmed from the World Health Organization (WHO) report ‘Ethics and governance of artificial intelligence for health’, are tailored for the national context, providing a framework for researchers to evaluate their research practices. Importantly, it is noted that while bioscientists are well-versed in the ethical procedures and legal regulations related to human subjects research, those in computer science and data science engaged in healthcare AI research may lack familiarity with these standards (Metcalf and Crawford 2016 ; Throne 2022 ). Consequently, these guidelines are designed to assist support healthcare AI researchers in conducting ethical research by presenting providing part I principles to consider in relation to research, part II corresponding relevant research codes, regulations and related ethical cases, and part III an expanded framework, aligning with that applies for the existing governance framework for phase I–IV clinical research, tailored for to the context of healthcare AI research.

The purpose of this paper is to outline and provide rationales for the ethical governance system introduced in the part III of the guidelines. At present, we are in the process of translating the guidelines for an official English version. Amidst this ongoing endeavour, this paper preliminarily introduces the final section of the guidelines, which is under linguistic review. Subsequently, we describe the governance framework, comprising six steps, accompanied by ethical and institutional explanations for each stage. In conclusion, this paper presents a healthcare AI research governance system, expanding upon the existing human subjects research. It advocates for the establishment of a robust, secure, and sustainable research governance structure by adapting the clinical research system prevalent in countries where such approaches are already established to the domain of healthcare AI research governance.

Procedural Considerations for Conducting Healthcare AI Research

Aforementioned, part I of the guidelines provide background, developing process and methodologies, aims, scope, and key terms. Next, part II reviews the existing legal frameworks related to safety and effectiveness, liability for errors and negligence, privacy laws for patient data protection, and legal frameworks responding to bias and discrimination. Based on the legal background, part III introduces a six principle-based framework and explanations with specific ethical cases, aligning with the procedural considerations when researchers conduct healthcare AI research.

Particularly, part III of the guidelines is grounded in six ethical principles: (a) respect for and protection of human autonomy; (b) promotion of human well-being, safety, and the public interest; (c) ensuring transparency, explainability, and reliability; (d) upholding accountability and legal obligations; (e) promoting inclusivity and equity; and (f) fostering responsiveness and sustainability (Kim et al. 2023 ). While these principles align with those of the WHO, specific codes and applications have been tailored to suit the national context. The healthcare AI research governance framework presented herein also follows this approach, incorporating relevant principles to be considered at each stage.

The guidelines restructured the principles by the steps of the research process as a form of a checklist. This checklist provides a baseline for all stakeholders the field to voluntarily identify and assess the ethical considerations pertinent to practical research and development (Table  1 ).

Healthcare AI research and development begins with the establishment of a robust ethical framework, grounded in the aforementioned six ethical principles. A multidisciplinary team collaborated to establish the ethical considerations for research and development and delineate the requisite compliance measures. The AI development process comprises distinct stages: data collection, algorithm development, model training integration, and evaluation. Each steps follows a structured ethical framework, integrating the principles, thereby ensuring the ethical integrity of healthcare AI research and development. Periodic evaluations are conducted to assess ethical compliance and identify areas for improvement. Furthermore, continuous feedback is sought following the application of the developed model in real-world environment.

For research institutions, the guidelines play a pivotal role in ensuring ethical standards of healthcare AI research and development. The research institutions can utilize the guidelines to evaluate the design procedure, algorithm development, and application of AI technologies in their own research endeavours. This assessment entails evaluating the alignment of the guidelines with domestic laws, international norms, and societal dialogues. Additionally, it is advisable for review committees and institutions that oversights healthcare AI research and development to implement reasonable and responsible regulations to manage research activities, educating and informing stakeholders about these regulations, and maintaining open communication for ongoing revisions and amendments as required.

Furthermore, through such feedback and societal discussion, the developers of this guidelines strive for continuous refinement, aiming to foster a research environment that esteems ethical principles and values.

Stage 1. Preliminary Ethics Review

Prior to the commencement of healthcare AI research and development, it is imperative to establish a clear ethical framework guided by specific guidelines. This preliminary stage is the responsibility of the organization, tasked with laying the foundational groundwork. They should actively seek advice through public participation action from a diverse array of stakeholders, including patients, the public, and expert groups such as medical ethicists and legal scholars, to ensure a well-rounded perspective through public participation action. Additionally, it is essential to establish and consider ethical guidelines that are particularly relevant to the research and development process, setting a strong foundation for responsible and ethical AI innovation in healthcare.

Related questions:

Does the plan include sensitive objectives? Is the objective to develop a medical device or other health and public health objectives? (Specify clinical diagnosis-treatment decision, patient decision support, prevention, behavioural intervention, public health, and if others, additional descriptions should be included in the protocol.)

Is it human subject research or research utilizing datasets? (check bioethics exemptions and compliance requirements.) If human subjects research, does the plan include interventions or interactions?

Does the plan address potential or manifest harms? (Provide a risk-benefit analysis.)

Is there evidence or potential for sample bias in the plan?

Stage 2. Creating Datasets

In the process of collecting and processing data for healthcare AI model development, several key considerations must be addressed. Initially, it is essential to evaluate the collectability, availability, and intended use of the data. Depending on the potential risk for privacy infringement, appropriate measures such as anonymization or pseudonymization should be employed for the dataset. A detailed data collection plan is crucial to outline the methods and objectives clearly. Additionally, conducting ongoing quality control is imperative to minimize data bias and ensure the diversity and representativeness of the datasets, which are fundamental for the development of fair and effective healthcare AI systems.

Is the data collection plan comprehensive? (identification and consultation with data subjects or maintaining organizations, data types and details, collection techniques, frequency selection, inclusion and appropriateness of purposes of use)

Are anonymization measures considered? (detailed technical and administrative/physical measures; if not anonymized, justification and additional measures required)

Is the dataset size aligned with the learning task and model complexity?

Is the data quality recognized as high?

Are the data appropriately visualized and exploratory analyses conducted?

Is the raw data collected according to approved clinical standards and protocols, utilizing valid and reliable techniques?

Are regular and continuous data quality control measures implemented?

Stage 3. Model Development

Configuring algorithms to align with research objectives and applying preliminary data to assess appropriateness is a critical phase in AI development. Developers should build the model using decision-making algorithms aimed at achieving specific, predefined goals. To ensure transparency, a concise description of the development plan should be publicized, detailing the steps and intentions behind the model’s construction. Standardizing the data before training the model is essential to ensure consistency and accuracy. Additionally, it is crucial to specify any methodological considerations that might reveal bias within the dataset, thereby allowing for adjustments and improvements to maintain integrity and fairness in the model's outcomes.

Related question (considerations in Stage 1 should be considered in conjunction with those below)

Does the plan provide an adequate accounting of human subjects and data subjects?

Are the methods of split cross-validation of datasets and datasets utilized in the plan appropriate? (correcting erroneous data, resolving inconsistencies in data, deleting unnecessary data, ensuring quality assurance and accuracy of data)

Are potential issues with privacy addressed? (review for possible data breach)

Does the plan assess the sources or likelihood of sampling/evaluation/algorithmic bias? (considering resampling, algorithmic fairness, etc.)

Stage 4. Training, Validation, and Evaluation

The phase of training and validating algorithms using the collected data, followed by an evaluation of their applicability for research purposes, is crucial for crafting robust AI systems. Training AI models meticulously is fundamental to boost their reliability and accuracy. It is also critical to ensure that the AI models undergo thorough internal validation through appropriate procedures to confirm its effectiveness and safety in practical applications. Moreover, implementing measures to assess clinical reliability is necessary for healthcare AI development. This includes evaluating the AI’s accuracy, its relevance to clinical applications, the fairness of its decision-making processes, and the level of trust or acceptance these systems receive from both patients and healthcare professionals.

Does the model use a transparent methodology for AI data mining and project implementation? (e.g., CRISP-DM, Footnote 1 KDD, Footnote 2 SEMMA, Footnote 3 CPMAI Footnote 4 )

What is the model’s purpose? (specify predictive models, text mining, automation, record abstraction, biometrics, and if others, additional descriptions should be in the protocol)

What kind of technology is utilized? (specify machine learning, deep learning, natural language processing, unsupervised learning, reinforcement learning, and if others, additional descriptions should be included in the protocol.)

Can any unexpected results be analysed or tracked?

Stage 5. Application

Ensuring compliance with ethical frameworks and legal regulations is paramount when governing AI models in the real-world application. AI models functioning as medical devices, tasked with analysing data for disease diagnosis, management, and prediction, must comply with approval and review protocols established by relevant regulatory bodies. Those covered by health insurance require safety, effectiveness, and economic evaluations by designated authorities. Implementing an external validation process that involves public participation can further reinforce the model’s integrity and social acceptance.

Furthermore, it becomes crucial that clinical AI algorithms to prioritize user-friendliness, requiring minimal training to lessen cognitive load and streamline decision-making. Supervising and maintaining the models involve assessing their ethical integrity and making continuous improvements as necessary. Clearly designate a specific individual or entity responsible for the ethical management of the model.

Is there a match between the dataset and the population setting for model application?

Are the results interpretable?

Have they been assessed for major biases? (e.g., gender, race)

Has the model been externally validated using datasets from other settings?

Has the model been empirically evaluated for validity, clinical utility, and cost-effectiveness?

Stage 6. Post-deployment Monitoring

Continuing engagement with model users and refining the model based on their feedback is essential in this stage. It involves regularly reviewing the model’s performance in real-world applications, aligning with the self-constructed ethical framework previously established. Maintaining open communication and collaboration with all stakeholders, including AI providers, users, patients, the public, and government agencies, is crucial for ongoing development and alignment with user needs and ethical standards. Furthermore, ensuring that the models can be seamlessly integrated into existing production environments is vital for effective decision-making based on real data. This stage emphasizes the importance of adaptability and responsiveness to the evolving landscape of AI applications and societal impacts.

Do you regularly monitor the product whether the entire data process is correctly aligned or when the entire process is performed automatically without the need for human intervention?

Does the user (healthcare provider), user organization (healthcare organization) regularly disclose usage results, both positive and negative?

Are there communication and recovery protocols established for model application errors?

Are there improvements needed in the relevant ethical framework and guidelines?

A Step-by-Step Explanation of Healthcare AI Research Governance Framework

The healthcare AI research governance framework delineated above adapts and extends the phase I–IV process for human clinical research to healthcare AI research. This adaptation allows guideline developers to manage and regulate research more reliably by extending existing research governance procedures, thus reducing the need for designing new schema for healthcare AI research ethics. This approach reduces training efforts and provides a foundation for researchers to quickly comprehend and apply the governance framework. Additionally, many of the administrative resources already established for human subjects research can be leveraged for healthcare AI research.

However, it is imperative to analyse the commonalities and divergences between clinical trials and healthcare AI research. This paper presents the similarities in terms of (a) research subjects, (b) areas of research management and regulation, and (c) application of research results. On the other hand, there are differences between clinical trials and healthcare AI research, including (a) the research and development process, (b) evaluation of research results, and (c) the modifiability of research results.

Firstly, human subjects, biospecimens, or populations in clinical trials share qualitative similarity with health data, their constructs, or databases utilized in healthcare AI research. For instance, biospecimens are recognized for their uniqueness—characteristics derived from the individuals they originate from—and then, health data collected from human subjects possess the same ontological nature as derivatives of individuals. They inherently refer to persons and are intricately connected to them (Cha and Kim 2022 ). Health datasets encapsulate various biological, behavioural, and socioeconomic records of a specific data subject, directly linked with the human body. The linkage of whole genome sequencing (WGS) data to personal identity intertwines the human body with the data presenting (Li et al. 2014 ). In population studies, the population database reflects the target population group, and eventually, they should become ontologically and practically identical.

Secondly, both clinical trials and healthcare AI research aim to derive results that benefit humans—whether it is treatments, new drugs, medical technologies, and biomaterials in clinical trials, or algorithms and applications in healthcare AI research. Just as clinical research with human subjects has established protocols to ensure respect and protection of individuals involved and affected by research process and its outcome (National Commission for the Protection of Human Subjects of Biomedical & Behavioral Research 1978 ), healthcare AI research also confronts to address ethical considerations arising from both the research process and the utilization of its outcomes. The considerations encompass aspects ranging from the respecting and protection of individuals to issue of accountability and sustainability. Similar to the human subjects research oversight by Institutional Review Boards (IRBs), which review and monitor all biomedical research, healthcare AI research necessitates a robust review and monitoring process. This process is crucial even when certain research activities might be exempt from regulatory requirements, acknowledging the unique challenges and potential risks associated with AI. A tailored oversight mechanism for healthcare AI is imperative that all research involving human subjects—or their data—is conducted responsibly and ethically. As human clinical trials aim to apply developed treatments and new drugs to humans by assessing efficacy and safety, healthcare AI research endeavours to apply developed algorithms and applications to humans to demonstrate effectiveness.

Recognizing the identified similarities, it could be argued that the governance framework established for human clinical research can be directly applied to healthcare AI research. However, significant differences between human clinical research and healthcare AI research necessitate a tailored approach.

Primarily, a distinction lies in the development process between human clinical research and healthcare AI research. Human clinical research focuses on developing of treatments or new drugs, validated through assessments of safety and effectiveness and comparative benefit analyses. Upon affirming these steps, a treatment or drug is considered developed, thereafter maintained through post-marketing/application monitoring or management. Conversely, healthcare AI research entails an iterative process of development, refinement, and validation of algorithms or applications, inherently characterized by their modifiability (Higgins and Madai 2020 ). This research paradigm encompasses a series of stages from data collection to algorithm application and continual revision through feedback loops. Throughout the progress, algorithms are expected to continuously learn, revise, and evolve (Pianykh et al. 2020 ). Therefore, a governance approach tailored to this process, spanning from data collection and algorithm development to model training integration, and evaluation becomes essential.

The primary difference consequently leads to variations in how research outcomes are evaluated and modified. Clinical trials typically employ statistical validation methods like randomized controlled trials (RCTs) or equivalent methodologies to confirm effectiveness. In contrast, healthcare AI research assesses performance using metrics such as the area under the receiver operating characteristic (ROC) curve (AUC) derived from collected data (Wu et al. 2021 ), which involves trade-offs between false positives and false negatives. In addition, drugs and medical devices approved through clinical trials are subject to re-evaluation if modifications are made. However, in healthcare AI research, accepting modifications poses a challenge due to its continuous learning nature, disrupting the notion of a consistent “product-based view” (Gerke et al. 2020 ). Therefore, it is practical for governing healthcare AI research governance to consider adopting elements maintainable from the human subjects clinical research governance system while modifying them to suit the development and application dynamics of healthcare AI.

Six-Stage Process for Healthcare AI Research

Given these considerations, this guidance extends the traditional four-phase clinical research process (phase I: safety; phase II: efficacy and side-effects; phase III: large trials; phase IV: post-market surveillance) by introducing a six-stage process for healthcare AI research. The introduction of <Stage 1: preliminary ethics review > and < Stage 2: creating datasets > reflects the unique nature of healthcare AI research and emphasizes the necessity for comprehensive and sustainable research guidelines from data collection stage onwards. < Stage 3: model development > , < Stage 4: training, validation, and evaluation > , < Stage 5: application > , and < Stage 6: post-deployment monitoring > align with the concepts of phases I–IV of clinical research but are specifically tailored to address the characterized process of developing and applying healthcare AI algorithms.

Stage 1 necessitates researchers and developers to establish an ethical framework tailored to their research objectives. This endeavour enables the research organizations and their members to review and establish their own ethical frameworks and establish and operate a framework that is appropriate for their research purposes. Given the diverse nature of healthcare AI, the selection and explicit delineation of an appropriate ethical framework are crucial. The first stage supports engagement of a diverse array of experts and the public, including ethicists, legal scholars, patients, and laypersons to take an interest in the AI research process as necessary. Their collective input serves to establish guiding principles and rules crucial for the ethical conduct of research. This proactive approach aims to promote self-regulated ethical practices among researchers, distinct from mere compliance with legal regulations. Notably, the established ethical framework in stage 1 should be consistently referenced in most subsequent documentation.

Stage 2 specifies plans for data collection and processing, mandating the creation of suitable datasets by designated data creator or “data curators” responsible for assembling and maintaining datasets (Leonelli 2016 ). The data collection and processing activities of researchers undergo to review by the Data Review Boards (DRBs). This board, established to oversight the ethical conduct of data-related procedures, evaluated data collection plan, anonymization methods, dataset size, quality, and management. The DRB operates within the research institution or as an independent body. Proposed by the Ministry of Health and Welfare of South Korea in the “Guidelines for Utilization of Healthcare Data,” the DRBs function as a committee of five or more individuals. Its responsibilities include assessing the suitability of processing pseudonymized information within an institution, reviewing the adequacy of pseudonymization, and managing the use of pseudonymized information within and outside the institution (Ministry of Health and Welfare of South Korea Dec 2022 ). This paper proposes that the DRB or a data appropriateness review entity comprising researchers, developers, and external members. This entity would review the data collection and management system before commencing healthcare AI research. Such proactive review aims to ensure the safety, appropriateness, feasibility, and absence of biases in data utilization for healthcare AI research.

Stage 3 involves the selection and preliminary assessment of algorithms, making the initiation of full-scale research. At this stage, researchers and developers undergo an IRB review encompassing all facets of conducting the study. They are required to provide extensive justifications concerning the study’s objectives, data standardization, and potential biases. The IRB, compared to the DRB, evaluates the appropriateness of the algorithm, the predictability and validity of results based on initial dataset, the reliability and safety of data management, and ensures the unbiased use of algorithm and data. Researchers, for reporting their conduct to the IRB, should consistently refer to the ethical framework established in stage 1. Considering that data utilization might vary concerning the algorithm used, distinct review rules are set by the DRBs and the IRBs. The former focuses on data management practice, while the latter oversees data utilization practices. This stage functions similar to phase I where the accuracy and appropriateness of the algorithm are determined and reviewed based on validated preliminary data. It can be paralleled with phase I safety assessments in clinical trials, wherein the interaction of an experimental medical device or drug with the human body is examined based on a small number of research subjects.

Stage 4 encompasses the training, validation, and evaluation of the algorithm using the collected real-world data. The training data should be divided into train and test sets, and a pre-prepared validation set, distinct from the training data, is essential for validating healthcare AI algorithms to prevent overfitting and assess real-world applicability. The management of the validation process is imperative to avoid the exportation of models that are only useful during the training process to the actual application phase. and it is recommended that the research and development organization check this process. In the context of healthcare AI applications such as diagnostic imaging, patient risk prediction, and personalized treatment planning, each employing base algorithms ranging from deep learning to decision trees, the need for tailored validation processes becomes clear. For diagnostic imaging or patient risk prediction models, the validation process should primarily focus on rigorous statistical evaluation to ensure accuracy and reliability. Personalized treatment planning systems necessitate validation that emphasizes clinical relevance and the improvement of patient outcomes. These validation processes are essential for assessing the reliability of healthcare AI models. This stage can be seen as akin to phase II in clinical research, the phase that evaluates the effectiveness of a medical device or drug against a placebo. The emphasis is particularly placed on validating the trained algorithm and its relevance to clinical procedures.

Stage 5 involves the deployment of the developed healthcare AI algorithm into practical settings. The regulatory landscape governing healthcare AI implementation may vary based on its real-world application within a country. In South Korea, for example, AI model is evaluated and approved as a medical device by the Ministry of Food and Drug Safety. Moreover, for seeking for the National Health Insurance reimbursement, assessing safety, effectiveness, and economic evaluation from responsible regulators are mandatory. Throughout the step, the organization requires to pursue external validation for its development process, algorithms, and applications while prioritizing transparency. Furthermore, since the nature of healthcare AI includes continuous learning and development as part of its attributes, stage 5 also assigns responsibility for ongoing monitoring, identifying the entity accountable for managing the model. This stage corresponds to phase III, large trials, in clinical trials, where large-scale RCTs are used to determine the applicability of a treatment or new drug, in terms of determining the real-world applicability of a healthcare AI algorithm and putting it to work in the field.

Stage 6 mandates all parties involved to review the process of the continued deployment and ongoing development once the developed algorithm or model has been put into operation in a healthcare setting. Continuous review of use of the model and the functionality of the ethical framework remains pivotal. Maintaining transparent and collaborative communication among all stakeholders emerges as a necessity. In addition, vigilant monitoring of ongoing evolution of the model is imperative to prevent that decision-making based on real-world data might lead to unintended harms. This phase emphasized the follow-up and surveillance of algorithms and models post-launch, analogous to phase IV, post-market Surveillance in clinical research, which refers to the follow-up phase after clinical implementation of a medical device or drug.

The six-stage healthcare AI research governance proposed in this study can be compared to the five-phase standard, BS30440, recently proposed by the UK (Sujan et al. 2023 ). Set to take effect in the second quarter of 2023, BS30440 provides guidelines for validating AI systems in healthcare in the UK context. The guidelines reflect the product life-cycle of healthcare AI, which consists of inception, development, validation, deployment, and monitoring. Compared to the UK guidelines, the six stages presented in this paper add a preliminary ethical framework design and committee verification of data collection and management, distinguishing stages between algorithm determination and subsequent training, validation, and evaluation. BS30440 lacks stipulations for preliminary procedures or data management, integrates algorithm determination and training as a singular process, and makes validation as a separate process. Notably, our study’s governance procedure is designed to extend existing clinical research management procedures, whereas BS30440 establishes novel procedures. This study only examines these distinctions not to favour one framework over the other but to underscore the global development and application of similar governance procedures, extending beyond South Korea.

Limitations and Future Research

The governance guidelines bear inherent limitations. Foremost, they do not decisively address the liability associated with possible harm resulting from healthcare AI applications. In the case of healthcare AI research and application involving multiple parties, it is necessary to examine whether the harm caused can be assumed the same as the existing medical liability process. For example, if a patient is physically harmed in the process of utilizing a healthcare AI device, but it turns out to be a problem with the algorithm rather than the fault of the medical practitioner or device user, who should be held liable?

Navigating liability questions amidst the overlapping influences of various actors poses challenges (Kim 2017 ). While the governance of healthcare AI research needs to address the issue of liability, it is limited by the fact that the guidelines in the study focus on proposing an ethical model grounded in self-regulation, addressing the intricacies of liability remains a significant challenge. Moreover, the procedures are set to be adjusted according to each country’s regulatory procedures, which is because the procedures correspond to existing clinical research guidelines, but it is necessary to examine whether they can be properly operated in real-life situations. This is an area that requires empirical verification by applying the guidelines to actual healthcare AI research governance. Therefore, this paper calls for further research on the healthcare AI governance guidelines presented here to address the issues identified above, especially linking it the legal standard to regulation.

To address the identified limitations, researchers are actively engaged in ongoing efforts in education of AI researchers and the public, social communication, and the revision of the guidelines. These initiatives will ensure a comprehensive societal understanding and adoption of healthcare AI research ethics, encourage researchers and developers to accept the need to conduct research ethically, and thereby facilitate the operationalization of ethical governance systems at both institutional and national levels within the South Korean context. As a result, these endeavours will significantly contribute to the establishment of a robust ethical normative framework for healthcare AI research in this country.

Since the governance settings presented in this study are from the perspective of a specific country, it is necessary to collect the opinions of researchers and bioethicists from other countries through international discussions and reviews. In order to facilitate such discussions, this study aims to inform other countries about the governance system established in South Korea and, using this study as a starting point, collect multi-perspective and multi-disciplinary views on healthcare AI research governance that have not yet been organized and provide basic data on the establishment of cross-border healthcare AI research governance.

The aims of this study are to present a healthcare AI research governance system founded on the South Korean ‘Research Ethics Guidelines for AI Researchers in Healthcare’ and to elucidate each procedural step. The six-stage healthcare AI research governance framework mirrors the healthcare AI research and development process, and is designed in harmony with the existing clinical research management systems. This parallel structure facilitates the utilization of established research management resources and foster mutual understanding among researchers and institutions for conducting ethical research procedures. Nonetheless, the guidelines are likely to reflect the specificities of the Korean healthcare environment, emphasizing the need for further international dialogue and refinement.

Data Availability

The framework employed in our research is included in the English version of “Research Ethics Guidelines for Healthcare AI Researchers” (KNIH 2023 ). This document is currently in the process of being published. Upon its publication, we will promptly provide the relevant link.

Cross-Industry Standard Process for Data Mining

Knowledge Discovery in Database

Sample, Explore, Modify, Model, and Assess

Cognitive Project Management for AI

Cha, Hyun-Jae., and Junhewk Kim. 2022. The ethical approach to health data donation and sharing: From the process of human tissue donation. Bio, Ethics and Policy 6 (2): 101–137.

Google Scholar  

Gerke, Sara, Boris Babic, I. Theodoros Evgenious, and Glenn Cohen. 2020. The need for a system view to regulated artificial intelligence/machine learning-based software as medical device. NPJ Digital Medicine  3: 53. https://doi.org/10.1038/s41746-020-0262-2 .

Higgins, David, and Vince I. Madai. 2020. From bit to bedside: A practical framework for artificial intelligence product development in healthcare. Advanced Intelligent Systems 2 (10): 2000052. https://doi.org/10.1002/aisy.202000052 .

Article   Google Scholar  

Kim, Junhewk. 2017. Autonomous decision medical system and moral responsibility. Philosophy of Medicine 24: 147–182.

Kim, Hannah, Jung Im Lee, Jinah Sim, Yuri Lee, So Yoon Kim, Eun-Ae Kim, Soo Min Kim, and Junhewk Kim. 2023. Ethical guidelines for artificial intelligence research in healthcare: Introducing South Korean Perspectives. Korean Journal of Medicine and Law 31 (1): 85–110. https://doi.org/10.17215/kaml.2023.06.31.1.85 .

Korean National Institute of Health. 2023. Research ethics guidelines for AI researchers in healthcare . Cheongju: Korea Disease Control and Prevention Agency.

Leonelli, Sabina. 2016. Data-centric biology: A philosophical study . Chicago: The University of Chicago Press.

Book   Google Scholar  

Li, Hong, Gustavo Glusman, Hao Hu, Shankaracharya, Juan Caballero, and Robert Hubley, et al. 2014. Relationship estimation from whole-genome sequence data. PLoS Genetics 10(1): e1004144. http://dx.doi.org/10.1371/journal.pgen.1004144.

Metcalf, Jacob, and Kate Crawford. 2016. Where are human subjects in Big Data research? The emerging ethics divide. Big Data & Society 3 (1): 1–14. https://doi.org/10.1177/2053951716650211

Ministry of Food and Drug Safety of the Republic of Korea. 2023. 2022 Medical device license report . Cheongju: Ministry of Food and Drug Safety of the Republic of Korea.

Ministry of Health and Welfare of South Korea. 2022. Guidelines for utilization of healthcare data . Sejong: Ministry of Health and Welfare of South Korea.

National Commission for the Protection of Human Subjects of Biomedical & Behavioral Research. 1978. The Belmont report: Ethical principles and guidelines for the protection of human subjects of research . Bethesda, MD: National Commission for the Protection of Human Subjects of Biomedical & Behavioral Research.

Pianykh, Oleg S., Georg Langs, Marc Dewey, Dieter R. Enzmann, Christian J. Herold, and Stefan O. Schoenberg, et al. 2020. Continuous learning AI in radiology: Implementation principles and early application. Radiology 297 (1): 6–14. https://doi.org/10.1148/radiol.2020200038 .

Rajpurkjar, Pranav, Emma Chen, Oishi Banerjee, and Eric J. Topol. 2022. AI in health and medicine. Nature Medicine 28: 31–38. https://doi.org/10.1038/s41591-021-01614-0 .

Sujan, Mark, Cassius Smith-Frazer, Christina Malamateniou, Joseph Connor, Allison Garner, Harriet Unsworth, et al. 2023. Validation framework for the use of AI in healthcare: Overview of the new British standard BS30440. BMJ Health & Care Informatics 30: e100749. https://doi.org/10.1136/bmjhci-2023-100749 .

Throne, Robin. 2022. Adverse trends in data ethics: The AI Bill of Rights and Human Subjects Protections. SSRN , 30 November 2022. https://doi.org/10.2139/ssrn.4279922 .

Wu, Eric, Kevin Wu, Roxana Daneshjou, David Ouyang, Daniel E. Ho, and James Zou. 2021. How medical AI devices are evaluated: Limitations and recommendations from an analysis of FDA approvals. Nature Medicine 27: 582–584. https://doi.org/10.1038/s41591-021-01312-x .

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Acknowledgements

The authors wish to thank Dr Jung-Im Lee and Dr Sumin Kim for their contribution in developing the guidelines. The first project (2022-ER0807-00) conducted consultation meetings of two panels of interdisciplinary expert participants from law, public health policy, ethics, AI, and patients group for four times from August, 2022, to February, 2023, and a public hearing at February 2023. We deeply express our gratitude for all participants for their valuable opinions.

This work was supported by the ‘Development of Ethics Guidelines and Education Program for the Use of Artificial Intelligent in Healthcare Research’ and ‘Operation of Education Program and Improvement of Ethics Guidelines for the Use of Artificial Intelligent in Healthcare Research’ from the Korean National Institutes of Health (Grant numbers: 2022-ER0807-00 and 2023-ER0808-00).

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Department of Dental Education, College of Dentistry, Yonsei University, Seoul, South Korea

Junhewk Kim

Asian Institute for Bioethics and Health Law, Department of Medical Humanities and Social Sciences, College of Medicine, Yonsei University, Seoul, South Korea

So Yoon Kim & Hannah Kim

Center for Research Compliance, Ewha Womans University, Seoul, South Korea

Department of AI Convergence, Hallym University, Chuncheon, South Korea

Department of Health and Medical Information, Myongji College, Seoul, South Korea

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J. K. and H. K. were responsible for the conception, design, acquisition of data or analysis, and interpretation of data. J. K. was responsible for manuscript writing, subsequent revisions of the manuscript and funding (2023-ER0808-00). H. K. was responsible for reviewing the manuscript, funding (2022-ER0807-00), and developing the guidelines. S. Y. K., E. A. K., J. A. S., and Y. L. participated in developing the guidelines and reviewing the manuscript. All authors have read and agreed to the published version of the manuscript.

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Correspondence to Hannah Kim .

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Kim, J., Kim, S.Y., Kim, EA. et al. Developing a Framework for Self-regulatory Governance in Healthcare AI Research: Insights from South Korea. ABR (2024). https://doi.org/10.1007/s41649-024-00281-w

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Received : 30 September 2023

Revised : 11 January 2024

Accepted : 12 January 2024

Published : 25 March 2024

DOI : https://doi.org/10.1007/s41649-024-00281-w

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Glycosylation state of vWF in circulating extracellular vesicles serves as a novel biomarker for predicting depression.

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The clinical diagnosis of major depressive disorder (MDD), a heterogeneous disorder, still depends on subjective information in terms of various symptoms regarding mood. Detecting extracellular vesicles (EVs) in blood may result in finding a diagnostic biomarker that reflects the treatment stage of patients with MDD. Here, we report the results on the glycosylation pattern of enriched plasma EVs from patients with MDD and age-matched healthy subjects. In this cohort, the levels of Triticum vulgaris (wheat germ) agglutinin (WGA), N-acetyl glucosamine (GlcNAc) and N‐acetylneuraminic acid (Neu5Ac, sialic acid) - binding lectin, were significantly decreased in patients with MDD in the depressive state compared in remission state (area under the curve (AUC): 0.88 (95% confidence interval (CI) 0.72 - 1.00)) and healthy subjects (AUC: 0.87 (95% CI 0.76 - 0.97)). Furthermore, proteome analysis revealed that von Willebrand factor (vWF) was a significant factor recognized by WGA. WGA-binding vWF differentiated patients with MDD in the depression state versus the remission state (AUC: 0.92 (95% CI 0.82 - 1.00)) and patients with MDD versus healthy subjects (AUC: 0.98 (95% CI 0.93 - 1.00)). In this study, the change patterns in the glycoproteins contained in plasma EVs support the usability of testing to identify patients who are at increased risk of depression during antidepressant treatment.

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The authors have declared no competing interest.

Funding Statement

This research was supported partly by Japan Agency for Medical Research and Development (grant number 22dk0307103h0002) and the the Strategic Research Program for Brain Sciences (Integrated Research on Neuropsychiatric Disorders). K.T. received support from SENSHIN Medical Research Foundation, Japan and The Finding-Out & Crystallization of Subliminals (FOCS) project by the Yamaguchi University of Medicine. This work was also the result of using program for supporting construction of core facilities in MEXT Project for promoting public utilization of advanced research infrastructure (grant number JPMXS0440400023).

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