Challenges of implementing AI solutions in the pharmaceutical industry

The article examines the problematic areas involved in integrating artificial intelligence (AI) solutions into the pharmaceutical industry. The relevance of this study is underscored by the rapid advancement of digital technologies that are fundamentally transforming the pharmaceutical sector. Against the backdrop of global digitalization, a pronounced shift is observed in the approaches to drug development, production, and distribution, thereby necessitating a comprehensive analysis of the emerging barriers and contradictions. The primary objective of this work is to identify the key challenges in the implementation of AI solutions within the pharmaceutical field, assess their impact on innovation processes, and systematize perspectives on future developments while taking historical trends into account. The literature reveals discrepancies between the assessments of the economic effectiveness of AI applications and the potential risks associated with factors such as the quality of input data, regulatory constraints, and ethical considerations. The author concludes that a multidisciplinary approach is essential for overcoming the identified challenges—an approach that integrates advanced technological solutions, enhanced regulatory frameworks, and the development of mechanisms for independent evaluation. The contribution of this study lies in the systematic organization of existing issues and the identification of underexplored aspects. The findings provide a foundation for further scientific inquiry and practical recommendations targeted at professionals in the pharmaceutical industry, developers of AI solutions, and regulatory bodies striving to ensure the effective integration of innovative technologies into modern healthcare systems.

1. Borisova OV, Gasparyan AA. The impact of automation on production in the past, present and future. Examples of automation in various industries. In Science and technology: trends in modern development. Collection of articles of the International Scientific and Practical Conference. Petrozavodsk; 2023;27-31. (In Russ.).

2. Vardomatskaya LP, Lilyukhin AM. Digital economy tools in the context of their impact on pharmaceutical efficiency. State and municipal management. Scholar notes. 2020;(2):112-117. (In Russ.).

3. Morozov DYu, Omelyanovsky VV. Is artificial intelligence necessary for healthcare system? Medical Technologies. Assessment and Choice. 2024;4(46):40-48. (In Russ.).

4. Orlova LV, Pervova YuV, Shafransky IE. Integration of neural networks into the pharmaceutical industry: improving efficiency and safety. In Socio-cultural factors of consolidation of modern society. Collection of articles based on the materials of the International Scientific and Practical Conference. Penza; 2024;288-293. (In Russ.).

5. Pogrebnyak AV. Artificial intelligence can bring tens of trillions of rubles to the pharmaceutical industry. Safety and risk of pharmacotherapy. 2023;11(4):367-371. (In Russ.).

6. Friedman D. AI helps to create new medicines. V mire nauki = In the world of science. 2020;(6);96-103. (In Russ.).

7. Shakhbazov K, Ibragimova E. The use of digital technologies in pharmaceutical marketing. In Proceedings of Azerbaijan High Technical Educational Institutions. 2024;39(4):416-424. (In Russ.).

8. Shpyakin MD. Risk management of pharmaceutical industrial enterprises in the context of the transformation of the economy of the Russian Federation. Finansovye rynki i banki = Financial markets and banks. 2024;(6):321-326. (In Russ.).

9. AI In Pharma Market Definition. Available from: https://www.thebusinessresearchcompany.com/report/ai-in-pharma-global-market-report [Accessed 14 February 2025].

10. Varol D. AI in the Pharmaceutical Industry: Innovations and Challenges. Available from: https://www.scilife.io/blog/ai-pharma-innovation-challenges [Accessed 14 February 2025].