Bioinformatics Tools for Pharmaceutical Drug Product Development

17Future Prospects and Challenges in the Implementation of AI and ML in Pharma Sector

Prashant Pokhriyal¹, Vivek P. Chavda² and Mili Pathak¹*

¹Process Science, Intas Pharmaceuticals Ltd. (Biopharma Division), Ahmedabad, Gujarat, India

²Department of Pharmaceutic and Pharmaceutical Technology, L. M. College of Pharmacy, Ahmedabad, India

Abstract

Drug manufacture is among the most significant businesses on the planet. For long, this business has been a key productive member of society, and it will remain to be for several years to come. It’s difficult to fathom living without pharmaceuticals that treat ailments and enable people live longer, better lives. Drug industry must improve their manufacturing techniques in order to guarantee that operation is both efficient and robust. Artificial intelligence may assist by offering a third-party view on how the medication manufacturing process should be run and recommending improvements in equipment for optimal efficiency. It’s vital to get through the jargon and cacophony as we approach closer to a future where AI/ML is more integrated into R&D. When forming judgments regarding data, it’s also critical to remember that the scientific process isn’t defunct. This will aid in distinguishing hope from hype and lead to more informed decisions on the best use of AI/ML in drug research. However, there are many challenges and hurdles to be handled for the successful AI/ML implementation in pharmaceutical industry.

Keywords: Artificial intelligence ...