Artificial Intelligence's Impact on Contemporary Drug Research and Pharmaceutical Formulation

Daniel Xavier Prasad*
Sree Krishna College of Pharmacy and Research Centre, Trivandrum, Kerala, India.
Periodicity:January - April'2024
DOI : https://doi.org/10.26634/jchem.4.1.21156

Abstract

This paper explores the multifaceted role of AI in contemporary drug research, emphasizing its ability to analyze vast datasets, predict molecular interactions, and optimize clinical trials. AI's application extends beyond basic research, influencing preclinical studies, pharmaceutical design, clinical trials, and post-approval activities. It also plays a pivotal role in drug repurposing and the advancement of personalized medicine, where treatments are tailored to individual genetic profiles. By integrating AI into various stages of drug development, the industry has achieved increased efficiency, cost-effectiveness, and accuracy. This paper also highlights the regulatory challenges and opportunities posed by AI, stressing the need for a flexible regulatory framework to balance innovation with patient safety. As AI continues to evolve, its impact on the pharmaceutical industry is expected to grow, driving further advancements in drug research and ultimately leading to improved patient outcomes and a more efficient healthcare system.

Keywords

Artificial Intelligence, Machine Learning, Preclinical Studies, Pharmaceutical Design, Clinical Trials, PostApproval Activities, FDA, CDER, CBER, CDRH.

How to Cite this Article?

Prasad, D. X. (2024). Artificial Intelligence's Impact on Contemporary Drug Research and Pharmaceutical Formulation. i-manager’s Journal on Chemical Sciences, 4(1), 36-44. https://doi.org/10.26634/jchem.4.1.21156

References

[6]. Pravalika, T., & Sandeep, K. (2023). Artificial intelligence in pharmaceutical technology and drug delivery design. World Journal of Pharmaceutical Research, 12 (18), 391-418.
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