Main areas and prospects for using artificial intelligence and machine learning to accelerate the development of new medicines

Abstract


The article is dedicated to the directions and prospects of using artificial intelligence (AI) and machine learning (ML) in the development of new medicines. Innovative approaches have been presented that radically transform traditional processes of drug discovery and development. The main applications of AI/ML are presented: target identification and validation, molecular design, prediction of drug compound properties, and laboratory process automation. Technological solutions in this field are presented, such as Direct-to-Biology platforms, CRISPR technologies, high throughput imaging, and generative AI models. The key advantages of implementing AI/ML include accelerating medicines development, reducing costs, enhancing prediction accuracy, and expanding molecular design capabilities. To realize this potential, it is necessary to continue investing in technology and training specialists with an interdisciplinary profile. The integration of AI into research opens up new prospects for developing innovative, personalized treatment methods.

About the authors

Konstantin Aleksandrovich Koshechkin

Eurasian Academy of Good Practices, Moscow, Russia

Email: k.koshechkin@lpt.digital

Larisa Ivanovna Lavrenteva

Yaroslavl State Medical University of the Ministry of Healthcare of the Russian Federation, Yaroslavl, Russia

Email: Lavl2004@mail.ru

Philip Aleksandrovich Romanov

Yaroslavl State Medical University of the Ministry of Healthcare of the Russian Federation, Yaroslavl, Russia

Email: rfa2010@ya.ru

Alexandr Nikolaevich Yavorsky

Association of Participants in the Circulation of Medicines and Medical Devices, Moscow, Russia

Email: mail.ru

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