Priyotosh Banerjee¹*, Dhriti Kumar Brahma², Indrani Devi Sarma³ and Namit Ray⁴

¹Assistant Professor, Department of Pharmacology, IIMSAR, Haldia, West Bengal, India ²Additional Professor, Department of Pharmacology, NEIGRIHMS, Shillong, India ³Senior Resident, Department of Pharmacology, AIIMS, Guwahati, India ⁴Post-Graduate Trainee, Department of Pharmacology, NEIGRIHMS, Shillong, India

*Corresponding Author: Priyotosh Banerjee, Assistant Professor, Department of Pharmacology, IIMSAR, Haldia, West Bengal, India.

Received: December 21, 2023; Published: January 10, 2024

Abstract

The integration of artificial intelligence (AI) in various spheres has revolutionized industries, and its impact on pharmacological science and medical research stands particularly profound. With AI's multidisciplinary applications, especially in drug development and clinical trials, this technology emerges as a pivotal tool to streamline the lengthy and costly process of traditional drug discovery. In the medical realm, AI algorithms are deployed for disease detection, medical imaging, clinical trial efficiency, and patient outcome predictions. Post-COVID, the surge in AI research underscores its relevance and potential in shaping the future of healthcare. However, challenges arise in accessing electronic medical records (EMRs) due to confidentiality regulations, hindering seamless data acquisition for AI-driven analyses. Despite its transformative potential, the application of AI in drug discovery and clinical trials faces hurdles concerning regulatory compliance and participant privacy. Addressing these challenges necessitates transparent AI mechanisms, fostering regulatory approval and instilling participant confidence in studies. In conclusion, while AI's integration in drug discovery promises enhanced efficacy and reduced complications in clinical trials, navigating legal obligations and ensuring transparent AI systems are pivotal for its sustainable implementation. As AI continues to evolve, its trajectory augurs well for resource optimization and minimized complexities in drug development and clinical trials.

Keywords: Artificial Intelligence; Pk-pd Studies; Electronic Medical Records; Data Analyses; Technology

References

Citation

Citation: Priyotosh Banerjee., et al. “Artificial Intelligence in Drug Development - Revolutionizing Drug Discovery and Clinical Trials".Acta Scientific Pharmaceutical Sciences 8.2 (2024): 19-21.

Copyright

Copyright: © 2024 Priyotosh Banerjee., et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.