Machine learning has been revolutionizing all fields and has helped make waves in the research and development of drugs, identifying drug properties, understanding patterns, and deriving intelligent results. Drug development and its lifecycle are very tedious and time-consuming. With the right application of machine learning algorithms, biotech and life science companies can fast-track drug development and pace themselves to newer discoveries. With the advent of large language models and neural networks, there are specific use cases, where machine learning proves highly effective. Even while there is much research going on and in progress, the potential impact of applying machine learning is huge to the needs of the pharmaceutical and life sciences sector.
Over 17 years of experience in life sciencesPrevious experience working with Pwc,KPMG and Deloitte,Oracle,MetricStream,Infosys Consulting, HTC and Siemens ResearchActive member of ISACAProfessional associations with ISPE,OCEG,GARP,Carnegie Mellon Swartz Center for entrepreneurshipMaster in Software Engineering, Carnegie Mellon University, Pittsburgh,USBachelors in Computer Science, University of Madras,India
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