Artificial Intelligence in Medical Research: Ethical and Regulatory Challenges in Developing Economies
Charles Ntungwen Fokunang
*
Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Cameroon and National Ethical Committee for Research on Human Health, Cameroon.
Marceline Djuidje Ngounoue
Department of Biochemistry, Faculty of Sciences, University of Yaoundé 1, Cameroon.
Joseph Fokam
Department of Biomedical Sciences, Faculty of Health Sciences, University of Buea, Cameroon.
Estella Achick Tembe-Fokunang
Department of Pharmacotoxicology and Pharmacokinetics, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Cameroon.
Basile Ngono
National Ethical Committee for Research on Human Health, Cameroon.
Innocente Mantsana
National Ethical Committee for Research on Human Health, Cameroon.
Mfochive Njindam Illiasou
National Ethical Committee for Research on Human Health, Cameroon.
Christie Tiwoda
National Ethical Committee for Research on Human Health, Cameroon.
Francis Ndongo Ateba
National Ethical Committee for Research on Human Health, Cameroon.
Tchinda Tiabou
National Ethical Committee for Research on Human Health, Cameroon.
Lowe Gnintedem Patrick Juvet
National Ethical Committee for Research on Human Health, Cameroon.
Pasteur Sap Jacques Duclaire
National Ethical Committee for Research on Human Health, Cameroon.
Mgr Etoundi Jean
National Ethical Committee for Research on Human Health, Cameroon.
Mpah Wanga Julien Eymard
National Ethical Committee for Research on Human Health, Cameroon.
Ngu Paul Nembo
Division for Health Research Operations, Ministry of Health, Cameroon.
Jerome Ateudjio
Department of Public Health, Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, Cameroon.
Charles Kouanfack
National Ethical Committee for Research on Human Health, Cameroon.
Eboumbou Moukoko Caroline Else
National Ethical Committee for Research on Human Health, Cameroon.
Leopold Lehman
National Ethical Committee for Research on Human Health, Cameroon.
Binan Fidele Ange
National Ethical Committee for Research on Human Health, Cameroon.
Lovet Benyella Fokunang
GE Life Sciences CYTIVA, Logan, Utah, USA.
Atanga Benjamin
National Ethical Committee for Research on Human Health, Cameroon.
Zoung-Khanyi Bisseck Anne Cécile
National Ethical Committee for Research on Human Health, Cameroon.
Marie Claire Assoumou Okomo
National Ethical Committee for Research on Human Health, Cameroon.
Dickson Shey Nsagha
Department of Public Health and Hygiene, Faculty of Health Sciences, University of Buea, Cameroon.
Mbacham Fon Wilfred
National Ethical Committee for Research on Human Health, Cameroon.
Marie Therese Obama Abena Ondoua
Department of Pediatrics, Faculty of Medicine and Biomedical Sciences, University of Yaoundé 1, Cameroon.
Zintchem Roger
Laboratory of Educations and Health Practices, Nursing Sciences Research Chair, Sorbonne Paris Nord University; (EA 3412), UFR SMBH, F-93017, Bobigny, France Avicenne-Jean Verdier Nursing Training, Institute, CFDC, Assistance Publique-Hôpitaux de Paris, F-93000, Bobigny, France.
Vincent Pryde Kehdingha Titanji
Biotechnology Unit, Faculty of Science, University of Buea, SW Region, Cameroon.
*Author to whom correspondence should be addressed.
Abstract
Introduction: Clinical research is a key area in which the use of AI in healthcare data seen a significant increase, even though met with great ethical, legal and regulatory challenges. Artificial Intelligence (AI) concerns the ability of algorithms encoded in technology to learn from data, to be able to perform automated tasks without every step in the process being explicitly to be programmed by a human. AI development relies on big data collected from clinical trials to train algorithms, that requires careful consideration of consent, data origin and ethical standards. When data is acquired from third-party sources, transparency about collection methods, geographic origin and anonymization standards becomes critical. While consent forms used in clinical trials can offer clearer terms for data use, ambiguity remains about how this data can be reused for AI purposes after the trial ends. There are very few or no laws on the use of AI especially in developing countries. Also, there are a lot of misconceptions on the global use of AI.
Statement of Objectives: Artificial intelligence as an innovative technology has contributed to a shift in paradigm in conducting clinical research. Unfortunately, AI faces ethical, and regulatory challenges especially in limited resource countries where the technology is still to be consolidated. One of the main concerns of AI involves data re-identification, in which anonymized data can potentially be traced back to individuals, especially when linked with other datasets. Data ownership is also a complex and often controversial area within the healthcare sector. AI developers needs to clearly explain the value of data collection to hospitals and cybersecurity teams to ensure that they understand how the data will be secured and used ethically
Methodology: The World Health Organization (WHO) recognizes that AI holds great promise for clinical health research and in the practice of medicine, biomedical and pharmaceutical sciences. WHO also recognizes that, to fully maximize the contribution of AI, there is the need to address the ethical, legal and regulatory challenges for the health care systems, practitioners and beneficiaries of medical and public health services. In this study we have pulled data from accessible websites, peered reviewed open-access publications that deal with the ethical and regulatory concerns of AI, that we have discussed in this writeup. We have attempted to place our focus on the development of AI and applications with particular bias in the ethical and regulatory concerns. We have discussed and given an insight on whether AI can advance the interests of patients and communities within the framework of collective effort to design and implement ethically defensible laws and policies and ethically designed AI technologies. Finally, we have investigated the potential serious negative consequences of ethical principles and human rights obligations if they are not prioritized by those who fund, design, regulate or use AI technologies for health research.
Results: From our data mining and access to multiple documentations, vital information has been pooled together by a systematic online search to show that AI is contributing significantly in the growth of global clinical research and advancement of medicine. However, we observed many ethical and regulatory challenges that has impacted health research in developing economies. Ethical challenges include AI and human rights, patient’s privacy, safety and liability, informed consent and data ownership, bias and fairness.
For the legal and regulatory challenges, we observed issues with data security compliance, data monitoring and maintenance, transparency and accountability, data collection, data storage and use. The role of third-party vendors in AI healthcare solutions and finally AI development and integration into the health systems has also been reviewed.
Conclusion: The advancement of AI, coupled with the innovative digital health technology has made a significant contribution to address some challenges in clinical research, within the domain of medicine, biomedical and pharmaceutical products development. Despite the challenging ethical and regulatory challenges AI has impacted significant innovation and technology in clinical research, especially within the domain of drug discovery and development, and clinical trials studies.
Keywords: Ethical, regulatory, clinical research, Artificial intelligence, big data, health systems