On the brink of transformation: Clinical research

Sunil Shewale; Vaishali Undale; Akshata Kawaste; Vrushali Bhalchim; Maruti Shelar; Sachin Gundecha

doi:10.53730/ijhs.v6nS3.6722

Authors

Sunil Shewale [M. Pharm (QAT), MBA (HR & Marketing), PG-Clinical Trials]-Research scholar, Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, University of Pune. Maharashtra (India)
Vaishali Undale
vaishali.undale@dypvp.edu.in
[M. Pharm (Pharmacology), Ph.D. (Pharmacology)]- HOD, Department of Pharmacology, Dr. D. Y. Patil Institute of Pharmaceutical Sciences, & Research, University of Pune. Maharashtra (India)
Akshata Kawaste [B. Pharm]- Research Student, Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, University of Pune. Maharashtra (India)
Vrushali Bhalchim [M. Pharm (Pharmacology)]- Research scholar, Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, University of Pune. Maharashtra (India)
Maruti Shelar [M. Pharm (Pharmacognosy), Ph.D. (Pharmacognosy)]- Associate Professor, Dr. D. Y. Patil Institute of Pharmaceutical Sciences and Research, University of Pune. Maharashtra (India)
Sachin Gundecha [M. Pharm (Pharmaceutics)]- Research scholar, Dr. D. Y. Patil Institute of Pharmaceutical Sciences & Research, University of Pune. Maharashtra (India)

Keywords:

artificial intelligence, pharmacovigilance, clinical research, health, ADR

Abstract

The research on drug development life cycle and bringing sole new drug to the market is a million dollar question for pharmaceutical organization. Any clinical trial consumes average of 10 to 15 years and USD 1.5-2.0 billion with uncertainty of medications for its effectiveness for human use. Hardly, one out of 10 compounds entering into the clinical trial that reaches to the market rendering a major loss to pharmaceutical or biotech company in case of trial failure. Conversely, with changing time and an increase in the number of medicines approved by regulatory authorities, the regulatory teams are increasing networks for monitoring and assembling adverse event reports from varied sources. This in turn, has increases annual exponential rise in data volumes and the companies are facing a huge challenge in processing it. To meet such challenges, organizations must sharpen their ability to introduce new wearables for clinical trials and provide advanced cognitive solution to handle large and complex datasets. This has summoned concepts like Artificial Intelligence to expedite medical science and clinical trial and pharmacovigilance attain success.

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