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. Again...
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| Format: | Article |
| Language: | Russian |
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North-Caucasus Federal University
2025-06-01
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| Series: | Современная наука и инновации |
| Subjects: | |
| Online Access: | https://msi.elpub.ru/jour/article/view/1708 |
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| _version_ | 1849248671238979584 |
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| author | A. G. Borodich |
| author_facet | A. G. Borodich |
| author_sort | A. G. Borodich |
| collection | DOAJ |
| description | 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. |
| format | Article |
| id | doaj-art-aafe63fdb26b48d1864f51274c34a620 |
| institution | Kabale University |
| issn | 2307-910X |
| language | Russian |
| publishDate | 2025-06-01 |
| publisher | North-Caucasus Federal University |
| record_format | Article |
| series | Современная наука и инновации |
| spelling | doaj-art-aafe63fdb26b48d1864f51274c34a6202025-08-20T03:57:48ZrusNorth-Caucasus Federal UniversityСовременная наука и инновации2307-910X2025-06-010191710.37493/2307-910X.2025.1.11655Challenges of implementing AI solutions in the pharmaceutical industryA. G. Borodich0CitibankThe 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.https://msi.elpub.ru/jour/article/view/1708big datainnovationsartificial intelligenceclinical trialsregulatory barrierspharmaceutical industryeconomic efficiency |
| spellingShingle | A. G. Borodich Challenges of implementing AI solutions in the pharmaceutical industry Современная наука и инновации big data innovations artificial intelligence clinical trials regulatory barriers pharmaceutical industry economic efficiency |
| title | Challenges of implementing AI solutions in the pharmaceutical industry |
| title_full | Challenges of implementing AI solutions in the pharmaceutical industry |
| title_fullStr | Challenges of implementing AI solutions in the pharmaceutical industry |
| title_full_unstemmed | Challenges of implementing AI solutions in the pharmaceutical industry |
| title_short | Challenges of implementing AI solutions in the pharmaceutical industry |
| title_sort | challenges of implementing ai solutions in the pharmaceutical industry |
| topic | big data innovations artificial intelligence clinical trials regulatory barriers pharmaceutical industry economic efficiency |
| url | https://msi.elpub.ru/jour/article/view/1708 |
| work_keys_str_mv | AT agborodich challengesofimplementingaisolutionsinthepharmaceuticalindustry |