Machine learning is changing drug research and development, helping teams identify drug properties, find patterns and draw useful conclusions from data. This 60-minute webinar on machine learning in pre-clinical research explains how it can help biotech and life science companies speed up a long, tedious development process.
You'll start with how an ML model works, then look at applications in pre-clinical research and specific use cases where ML, including large language models and neural networks, is especially effective.
The session also reviews ongoing research, companies working to fast-track pre-clinical work, the advantages ML brings, and data-related pitfalls to avoid.
Drug development takes a long time, and machine learning offers a way to move faster and reach new discoveries. Research is still in progress, but the potential impact for pharma and life sciences is large, so teams need to understand what it can and can't do.
This session suits life science leaders, regulatory compliance experts, business analysts and consultants, and machine learning enthusiasts.
Drug development takes a long time, and machine learning offers a way to move faster and reach new discoveries. Research is still in progress, but the potential impact for pharma and life sciences is large, so teams need to understand what it can and can't do.
This session suits life science leaders, regulatory compliance experts, business analysts and consultants, and machine learning enthusiasts.
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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