Eight Drugs a Week, Episode 10 – Machine learning and AI for individualised therapy: Now and then

There was a time when we performed laborious pharmacokinetic hand calculations to tailor drug dosages and regimens – a practice that can still be useful for those brave enough to perform logarithmic calculator manipulations. Although we are fortunate to have an increasing number of software tools to help us with such tasks today, tomorrow, our work will undoubtedly be supported by artificial intelligence and machine learning approaches, which we have already started to see applied in the research arena.
 
In this episode, we are lucky to be joined by two experts from the field of pharmacokinetic and pharmacodynamic modelling, Prof Michael Neely and Prof Jean-Baptiste Woillard.
 

In this episode we hear about:

• The differences between traditional population pharmacokinetics and machine learning approaches in predicting drug exposure and optimizing dosing regimens.
• Some advantages of ML approaches, including in handling nonlinear patterns.
• The challenge of interpretability of results and dose recommendations from machine learning methods compared to traditional pharmacokinetic methods.
• Which clinical contexts we will soon see machine learning derived models applied to clinical care.
• The future of modelling and machine learning in pharmacology, including ethical considerations and the concept of augmented intelligence.

About our guests:

Jean-Baptiste is a Professor of Clinical Pharmacology in the Department of Pharmacology, Toxicology and Pharmacovigilance in the Limoges University Hospital, France where he leads the Pharmacometrics and Artificial Intelligence hospital functional unit. He is also Deputy Director of the Inserm Unit 1248 at the University of Limoges, France.

Michael Neely is a Professor of Pediatrics at the Keck School of Medicine of the University of Southern California, Chief of the Division of Infectious Diseases and Director of the Laboratory of Applied Pharmacokinetics and Bioinformatics, both at the Children’s Hospital Los Angeles.

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