Clarkston’s Life Sciences and Emerging Technology Experts Discuss Implementing AI and ML in Clinical Trials
February 16, 2023 | Clarkston Consulting’s Laurie Stone and Elise Watson were recently featured as guest columnists with Clinical Leader for perspectives on 4 pitfalls to avoid when implementing artificial intelligence (AI)/machine learning (ML) in clinical trials. Read a few excerpts from the piece below or the full article here.
4 Pitfalls To Avoid When Starting Your AI/ML Journey
“Getting a new compound or drug to market today requires life sciences companies to push the boundaries of possibilities to improve trial operations at any stage of development. With less than a 14% overall chance that a drug tested in Phase 1 reaches approval,1 it is clear that clinical trials need the analytical power, speed, and innovation required for today’s more complex therapies and diverse populations.”
“The life sciences industry has certainly not scaled or realized the full potential of AI/ML, but several use cases are available today to help start the journey. Basic science and translational research can leverage ML to propose new therapeutic molecules, analyze research output, and propose next steps. Clinical trials and observational research can leverage ML for pretrial planning (protocol development, drug regimen selection, site selection), participant management (cohort selection, patient identification, participant retention), and data management (automate data collection, improve data quality, analyze large datasets, unlock novel biological features). With greater awareness of what is available in the AI/ML landscape and an understanding of what action to take, companies can get started now to prepare for what’s yet to come for their enterprise.”