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Verma, Vaibhav
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Medicine & Pharmacology

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THE ROLE OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL RESEARCH AND INSTITUTIONAL EDUCATION: CURRENT CHALLENGES AND FUTURE PROSPECTS Panwar, M. S; Verma, Vaibhav; Sankala, Milan
Journal of Global Pharma Technology Volume 17 Issue 03 (2025) March 2025
Publisher : Journal of Global Pharma Technology

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Abstract

Artificial intelligence (AI) has emerged as a transformative tool in pharmaceutical research, enhancing drug discovery, development, and optimization. The integration of machine learning (ML) and deep learning (DL) models has expedited the identification of potential drug candidates, personalized medicine, and predictive analytics for clinical trials. However, despite its rapid advancement, AI in the pharmaceutical industry faces challenges such as data quality, regulatory compliance, and ethical considerations. This paper reviews the commonly used AI models in pharmaceutical research, current obstacles, and the future of AI-driven innovations in the field. Keywords: Artificial intelligence, Machine learning, Deep learning, Drug discovery, Pharmaceutical research, Clinical trials, Personalized medicine.
THE ROLE OF ARTIFICIAL INTELLIGENCE IN PHARMACEUTICAL RESEARCH AND INSTITUTIONAL EDUCATION: CURRENT CHALLENGES AND FUTURE PROSPECTS Panwar, M. S; Verma, Vaibhav; Sankala, Milan
Journal of Global Pharma Technology Volume 17 Issue 03 (2025) March 2025
Publisher : Journal of Global Pharma Technology

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

Artificial intelligence (AI) has emerged as a transformative tool in pharmaceutical research, enhancing drug discovery, development, and optimization. The integration of machine learning (ML) and deep learning (DL) models has expedited the identification of potential drug candidates, personalized medicine, and predictive analytics for clinical trials. However, despite its rapid advancement, AI in the pharmaceutical industry faces challenges such as data quality, regulatory compliance, and ethical considerations. This paper reviews the commonly used AI models in pharmaceutical research, current obstacles, and the future of AI-driven innovations in the field. Keywords: Artificial intelligence, Machine learning, Deep learning, Drug discovery, Pharmaceutical research, Clinical trials, Personalized medicine.
Co-Authors Panwar, M. S Sankala, Milan