Journals / Yildiz Social Science Review / 2026 / Cilt: 12 Sayı: 1

AI-Enabled Drug Discovery Platforms: Navigating the Confluence of Software, Medical Device, and Pharmaceutical Regulation in Sino-African Trade Relations

Yapay Zeka Destekli İlaç Keşif Platformları: Çin-Afrika Ticaret İlişkilerinde Yazılım, Tıbbi Cihaz ve İlaç Mevzuatının Kesişim Noktasında Yol Bulmak

Sema Yılmaz(YILDIZ TEKNİK ÜNİVERSİTESİ)0000-0002-3138-1622
Rahmi Deniz Özbay(İSTANBUL TİCARET ÜNİVERSİTESİ)0000-0002-3927-8216
Pages
40–54
Publication Date
2026-06-30
🏛️Bibliographic metadata and full text access for this article are provided via DergiPark.
DergiPark Record ↗
✨

AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

The article concludes with concrete recommendations for harmonized approaches, South-South regulatory cooperation mechanisms, and African-specific adaptation of global AI governance principles.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:The integration of artificial intelligence into drug discovery platforms presents a fundamental challenge to established regulatory taxonomies worldwide, raising a deceptively simple question with profound implications: Should AI-enabled drug discovery platforms be regulated as software, as medical devices, or as pharmaceuticals?
📊
Key Findings & Data:For African regulatory environments, where the African Medicines Agency is newly operational and most National Regulatory Authorities function at WHO Maturity Level 3, this global fragmentation presents both peril and opportunity.
💡
Conclusion & Impact:The article concludes with concrete recommendations for harmonized approaches, South-South regulatory cooperation mechanisms, and African-specific adaptation of global AI governance principles.
🔬Design:Araştırma Makalesi
📍Scope:Comprehensive Sample
⚙️Variables:Yapay zeka destekli ilaç keşfi · düzenleyici sınıflandırma · tıbbi cihaz mevzuatı

Abstract

The integration of artificial intelligence into drug discovery platforms presents a fundamental challenge to established regulatory taxonomies worldwide, raising a deceptively simple question with profound implications: Should AI-enabled drug discovery platforms be regulated as software, as medical devices, or as pharmaceuticals? This article examines this regulatory trilemma through the dual lens of comparative global frameworks and Sino-African trade relations. The analysis reveals that major jurisdictions—including the United States, European Union, and China—have adopted hybrid approaches that defy simple categorization, with the FDA emphasizing Predetermined Change Control Plans for adaptive algorithms, the EU layering AI Act requirements atop Medical Device Regulation frameworks, and China advancing a specialized AI medical device guidance architecture. For African regulatory environments, where the African Medicines Agency is newly operational and most National Regulatory Authorities function at WHO Maturity Level 3, this global fragmentation presents both peril and opportunity. The article argues that China's emergence as a leading developer of AI-enabled drug discovery technologies, combined with its deepening pharmaceutical trade relationships across Africa under FOCAC frameworks, creates unprecedented possibilities for regulatory leapfrogging through Sino-African cooperation. By examining trade patterns, investment flows, and capacity-building initiatives, this research demonstrates that the regulatory classification question is not merely a technical matter of legal taxonomy but a strategic determinant of market access, technology transfer, and ultimately, health equity across the African continent. The article concludes with concrete recommendations for harmonized approaches, South-South regulatory cooperation mechanisms, and African-specific adaptation of global AI governance principles.

Özet

Yapay zekanın ilaç keşif platformlarına entegrasyonu, dünya çapında yerleşik düzenleyici sınıflandırma sistemleri için temel bir zorluk teşkil etmekte ve görünüşte basit ancak derin etkileri olan bir soruyu gündeme getirmektedir: Yapay zeka destekli ilaç keşif platformları yazılım, tıbbi cihaz veya ilaç olarak mı düzenlenmelidir? Bu makale, bu düzenleyici üçlü ikilemi, küresel karşılaştırmalı çerçeveler ve Çin-Afrika ticaret ilişkileri olmak üzere iki farklı bakış açısıyla incelemektedir. Analiz, ABD, Avrupa Birliği ve Çin dahil olmak üzere başlıca yargı bölgelerinin, basit bir sınıflandırmaya uymayan melez yaklaşımlar benimsediğini ortaya koymaktadır. FDA, uyarlanabilir algoritmalar için Önceden Belirlenmiş Değişiklik Kontrol Planlarını vurgulamakta, AB, Tıbbi Cihaz Yönetmeliği çerçevelerinin üzerine AI Yasası gerekliliklerini eklemekte ve Çin, özel bir AI tıbbi cihaz kılavuz mimarisi geliştirmektedir. Afrika İlaç Ajansı'nın yeni faaliyete geçtiği ve çoğu Ulusal Düzenleme Otoritesinin WHO Olgunluk Seviyesi 3'te işlev gördüğü Afrika düzenleme ortamları için bu küresel parçalanma hem tehlike hem de fırsat sunmaktadır. Makale, Çin'in AI destekli ilaç keşif teknolojilerinin önde gelen geliştiricisi olarak ortaya çıkmasının, FOCAC çerçeveleri altında Afrika genelinde derinleşen ilaç ticareti ilişkileriyle birleşerek, Çin-Afrika işbirliği yoluyla düzenleme alanında benzeri görülmemiş bir sıçrama için olanaklar yarattığını savunmaktadır. Ticaret modelleri, yatırım akışları ve kapasite geliştirme girişimlerini inceleyen bu araştırma, düzenleyici sınıflandırma sorununun yalnızca yasal taksonominin teknik bir meselesi değil, aynı zamanda Afrika kıtası genelinde pazar erişimi, teknoloji transferi ve nihayetinde sağlık eşitliğinin stratejik bir belirleyicisi olduğunu göstermektedir. Makale, uyumlu yaklaşımlar, Güney-Güney düzenleyici işbirliği mekanizmaları ve küresel yapay zeka yönetişim ilkelerinin Afrika'ya özgü uyarlanması için somut önerilerle son bulmaktadır.

🔖

Cite This Article

Katterbauer, K., Yılmaz, S., Özbay, R. D. (2026). AI-Enabled Drug Discovery Platforms: Navigating the Confluence of Software, Medical Device, and Pharmaceutical Regulation in Sino-African Trade Relations. Yildiz Social Science Review, Cilt: 12 Sayı: 1, 40–54. https://doi.org/10.51803/yssr.1937910

📄 Full Text PDF Viewer

📄

PDF görüntüleyici hazırlanıyor...

References (20)

  1. Abdulwahab, A. A., Okafor, U. G., Adesuyi, D. S., Miranda, A. V., Yusuf, R. O., & Eliseo Lucero-Prisno, D. (2024). The African Medicines Agency and medicines regulation: Progress, challenges, and recommendations. Health Care Science, 3(5), 350–359. [CrossRef]
  2. African Union. (2014). African Union convention on cyber security and personal data protection. African Union.
  3. Aniche, E. T. (2023). African continental free trade area and african union agenda 2063: The roads to Addis Ababa and Kigali. Journal of Contemporary African Studies, 41(4), 377–392. [CrossRef]
  4. Atacan, C., & Açık, A. (2023). Impact of geopolitical risk on international trade: Evidence from container throughputs. Transactions on Maritime Science, 12(2). [CrossRef]
  5. Cerf, M. E. (2018). The Sustainable Development Goals: Contextualizing Africa's economic and health landscape. Global Challenges, 2(8), 1800014. [CrossRef]
  6. Daneshjou, R., Smith, M. P., Sun, M. D., Rotemberg, V., & Zou, J. (2021). Lack of transparency and potential bias in artificial intelligence data sets and algorithms: A scoping review. JAMA Dermatology, 157(11), 1362–1369. [CrossRef]
  7. de Villiers, K. (2021). Bridging the health inequality gap: An examination of South Africa's social innovation in health landscape. Infectious Diseases of Poverty, 10, 19. [CrossRef]
  8. European Parliament & Council of the European Union. (2024). Regulation (EU) 2024/1689 of the European Parliament and of the Council laying down harmonised rules on artificial intelligence (Artificial Intelligence Act). https://eur-lex.europa.eu/legal-content/EN/TXT/?uri=CELEX:32024R1689 Accessed on Jun 08, 2026.
  9. Ibáñez Antolín, A. (2021). Applications of machine learning in drug discovery and development. Proceedings of MOL2NET'21. Conference on Molecular, Biomedical & Computational Sciences and Engineering (7th ed.). USE.DAT- 07: USA-Europe Data Analysis Trends Congress, Cambridge, UK-Bilbao, Basque Country-Miami, USA, 2021. [CrossRef]
  10. International Medical Device Regulators Working Group. (2022). Machine learning-enabled medical devices: Key terms and definitions [IMDRF/AIMD WG/N67FINAL:2022]. International Medical Device Regulators Forum.
  11. Li, P., Williams, R., Gilbert, S., & Anderson, S. (2023). Regulating artificial intelligence and machine learning-enabled medical devices in Europe and the United Kingdom. Law, Technology and Humans, 5(2), 94–113. [CrossRef]
  12. Lognoul, M. (2025). Regulation (EU) 2024/1689 laying down harmonised rules on artificial intelligence (Artificial Intelligence Act–AI Act). Revue du Droit des Technologies de l'Information, 3–4, 145–189.
  13. Muehlematter, U. J., Daniore, P., & Vokinger, K. N. (2021). Approval of artificial intelligence and machine learning- based medical devices in the USA and Europe (2015–2020): A comparative analysis. The Lancet Digital Health, 3(3), e195–e203. [CrossRef] Ncube, C. B. (2015). Intellectual property policy, law and administration in Africa: Exploring continental and sub- regional co-operation. Routledge. [CrossRef]
  14. Niyungeko, G. (Ed.) (2019). Treaty for the establishment of the African Medicines Agency. In African Yearbook of International Law Online / Annuaire Africain de Droit International Online. 24(1), 396–415. [CrossRef]
  15. Nwauche, E. S. (2018). Intellectual property policy, law and administration in Africa: Exploring continental and sub- regional cooperation. South African Intellectual Property Law Journal, 6(1), 120–123.
  16. Obunike, C. L., & Nwakob, C. B. (2025). The role of intellectual property in the African continental free trade area: Opportunities and challenges. Chukwuemeka Odumegwu Ojukwu University Journal of Commercial and Property Law, 5(1).
  17. Rosen, K. L., & Mandl, K. D. (2025). Regulating flexibility for artificial intelligence: FDA experience with predetermined change control plans [Preprint]. medRxiv doi: 10.1101/2025.08.26.25334477 [CrossRef]
  18. United Nations Conference on Trade and Development. (2026). Pharmaceutical trade flows between China and Africa: Trends, projections, and policy implications. United Nations Conference on Trade and Development.
  19. Vieira, M., Andia, T., Karim, O., Srishti, S. A., Pineda, S. A., Alonso Ruiz, A., Large, K., Liu, Y., Moon, S., & Naher, N. (2023). Rising pharmaceutical innovation in the Global South: A landscape study. Journal of Pharmaceutical Policy and Practice, 16(1), 155. [CrossRef]
  20. Zhang, L., & Yan, J. (2026). Approval of AI-based medical devices in China from 2020 to 2025: Retrospective analysis. JMIR Medical Informatics, 14, e85538. [CrossRef]