Join us for this seminar by Frankie Patten-Elliott (Manchester) as part of the Maths in the Life Sciences seminar series (and the online North West Seminar Series in Mathematical Biology and Data Sciences in collaboration with Liverpool Universities).
Title: Modelling drug binding to biological ion channels
Abstract: In a healthy heart, ion channels in cardiac muscle cells ensure the heart pumps in a regular, coordinated manner. Pharmaceutical drug compounds are prone to binding to cardiac ion channels, disrupting healthy cardiac function and sometimes leading to the onset of cardiac arrhythmias. During drug development, significant time and money are spent on cardiac safety testing to avoid these potentially fatal side-effects. Much consideration is, therefore, given to improving cardiac safety testing methods to reduce uncertainty in risk predictions, while minimising time and cost.
Mathematical models can provide key insights into the underlying mechanisms that define complex biological systems. In the field of cardiac electrophysiology, models of ion channel gating and drug binding mechanisms can be effective tools for predicting drug-induced proarrhythmic risk. In this talk, I will describe methods to improve models of drug binding mechanisms, with a specific focus on binding in the hERG channel.
Recent technological advances have enabled the collection of high-frequency electrophysiology data that can be used to calibrate models of drug-channel binding. However, careful consideration must be given to ensure the collected data are sufficiently information-rich to discriminate between different proposed models of binding mechanisms. I present an approach that produces optimal experimental designs to aid model discrimination, thereby uncovering drug-specific mechanistic insights and assisting in cardiac risk assessment.
Time-permitting I will also discuss the potential directions of my current research focusing on modelling the neuroendocrine HPA axis.
The talk will be also be streamed via Teams, please contact carl.whitfield@manchester.ac.uk or igor.chernyavsky@manchester.ac.uk for the link, or sign up to the mailing list.
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