Artificial Intelligence Revolutionizes Pharmaceutical Sciences: A Comprehensive Review

Strategic Insights -

Recent research from Poona College of Pharmacy in Maharashtra, India, has shed new light on the transformative advancements in drug discovery, clinical development, and post-market surveillance fueled by the integration of artificial intelligence (AI) and machine learning (ML) into pharmaceutical sciences. According to the study, AI has revolutionized modern pharmacotherapy, with applications such as AlphaFold-driven protein modeling, natural language processing (NLP) for biomedical literature mining, and AI-augmented pharmacovigilance. However, challenges persist, including algorithmic bias, regulatory ambiguities, and the 'black-box' nature of deep learning models.

Key Takeaways:

  • The integration of AI and ML has catalyzed transformative advancements across drug discovery, clinical development, manufacturing, and post-market surveillance in pharmaceutical sciences.
  • AI has revolutionized modern pharmacotherapy with applications such as AlphaFold-driven protein modeling, NLP for biomedical literature mining, and AI-augmented pharmacovigilance.
  • Case studies have illustrated AI's capacity to compress drug development timelines, as seen in COVID-19 repurposing efforts and de novo kinase inhibitor design.
  • Despite the advancements, challenges persist, including algorithmic bias, regulatory ambiguities, and the 'black-box' nature of deep learning models.
  • The study emphasized the need for robust frameworks to ensure ethical, transparent, and clinically translatable AI deployment.
  • The research team highlighted the importance of interdisciplinary insights, synthesizing knowledge from peer-reviewed literature from 2013 to 2023.
  • The review underscored AI's potential to redefine pharmaceutical innovation while advocating for responsible AI deployment.

Statistics:

  • The review examined AI's role in modern pharmacotherapy, spanning from its historical evolution in life sciences to cutting-edge applications.
  • The study mentioned that AI has significantly compressed drug development timelines in COVID-19 repurposing efforts and de novo kinase inhibitor design.
  • The research was conducted by a team led by Priyanka Kandhare from Poona College of Pharmacy, in collaboration with Mrunal Kurlekar, Tanvi Deshpande, and Atmaram Pawar.
  • The review highlighted innovations in cheminformatics, including QSAR, RDKit, predictive toxicology, and personalized medicine.
  • The study cited the COVID-19 pandemic as an exemplar of AI's capacity to accelerate drug development timelines.

Sources:

  • Kandhare, Priyanka, et al. "Artificial intelligence in pharmaceutical sciences: A comprehensive review." Medicine in Novel Technology and Devices, 2025, 27(): 100375. doi: 10.1016/j.medntd.2025.100375
  • NewsRx. "Study Findings from Poona College of Pharmacy Advance Knowledge in Personalized Medicine (Artificial intelligence in pharmaceutical sciences: A comprehensive review)." Drug Week, September 12, 2025, p 318.