An introduction to Quantitative Systems Pharmacology

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• Marcus Tindall, University of Reading
• Thursday 19 March 2020, 12:00-13:00
• Biosciences 301.

If you have a question about this talk, please contact Fabian Spill.

Postponed due to COVID

Mathematical modelling has an established history in informing drug discovery and development. However, traditionally this has tended to be in the later stages of clinical trial testing via the use of compartmental pharmacokinetic pharmacodynamic (PKPD) and more recently physiologically based pharmacokinetic models (PBPK). Such models are formulated as systems of first order ordinary differential equations. In recent years, following the wealth of data now being collected at the individual cell and subcellular scales of cell biology, scales at which many drug compounds are designed to act, there has been an increased interest in the use of mathematical models to inform and elucidate pathways of drug action, either current or new ones plausible for investigation. Over the last 10 to 15 years, this has led to the emergence of the field of Quantitative Systems Biology (QSP).

In this talk I will outline the historical development of QSP in informing drug discovery and development, before moving onto current ongoing projects at Reading in this area. I will focus on the case example of cholesterol, considering both the use of single cell and multiscale models in informing both QSP and related areas of investigation, before moving onto work regarding model reduction of large scale cell signalling cell networks as a means of informing drug input and output related questions at the single cell scale. I will close by discussing our activities at Reading in leading the development of QSP both nationally and internationally and how this is informing the development of new areas of study, such as our new joint BSc Pharmacology programme with colleagues in Pharmacy.

This talk is part of the Applied Mathematics Seminar Series series.

This talk is included in these lists:

• Applied Mathematics Seminar Series
• Biosciences 301
• School of Mathematics events

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