Mechanistic model development to characterise drug effects on platelets over time in pharmaceutical research.

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• Shaun Flint, GSK
• Tuesday 06 February 2018, 13:00-14:00
• MR3 Centre for Mathematical Sciences.

If you have a question about this talk, please contact Dr Vivien Gruar.

Pharmacokinetic pharmacodynamic (PKPD) modelling is a powerful approach used extensively in pre-clinical and clinical drug development to quantitatively characterise drug candidates, aid go/no-go decisions, inform future clinical study design and determine optimal dosing regimens that maximise treatment benefits and minimise side effects. Mechanistic models such as Physiologically-Based Pharmacokinetic (PBPK) models are increasingly utilised to allow a more detailed description of the relevant physiological processes [1].

The aim of this project is to use mechanistic models to fully characterise the time-course of platelet count changes after drug administration and, in particular, to predict the onset and degree of thrombocytopenia (low platelet count). These are important questions for drug development because significant haematologic side effects, including thrombocytopaenia, may result in serious clinical consequences, such as bleeding or reduced efficacy as a result of delayed or missed doses. A key component of designing a dosing regimen that minimises these concerns is the ability to accurately model drug effects on platelet counts (and other haematologic parameters) over time. Semi-mechanistic models able to mimic maturation and circulation of platelets and other haematologic cell lineages incorporating drug effects are available in the literature (e.g. [2-3]). These models use empiric approaches to describe relevant processes and might be not be suitable to extrapolate drug effects to new dosing regimens (e.g. extrapolation of a model based on single-dose data to a repeat-dose regimen).

This project would explore the fundamental properties of, and differences between, semi-mechanistic models and mechanistic models such as the one proposed in [4]. It will include a theoretical exploration of model performance using simulations and access to a human clinical study dataset to allow the model to be assessed against real-life data.

References:

1. Zhao P, Zhang L, Grillo JA, et al. Applications of physiologically based pharmacokinetic (PBPK) modeling and simulation during regulatory review. Clinical Pharmacology & Therapeutics. 2011;89(2):259-67.
2. Wang Y.M., Krzyzanski W., Doshi S., et al. Pharmacodynamics-mediated drug disposition (PDMDD) and precursor pool lifespan model for single dose of romiplostim in healthy subjects. The AAPS journal 2010; 12(4): 729-740.
3. Bender B.C., Schaedeli-Stark F., Koch R., et al. A population pharmacokinetic/pharmacodynamic model of thrombocytopenia characterizing the effect of trastuzumab emtansine (T-DM1) on platelet counts in patients with HER2 -positive metastatic breast cancer. Cancer chemoth pharm 2012; 70(4): 591-601.
4. Harker L.A., Roskos L.K., Marzec U.M., et al. Effects of megakaryocyte growth and development factor on platelet production, platelet life span, and platelet function in healthy human volunteers. Blood. 2000;95(8):2514-22.

This talk is part of the Cambridge Mathematics Placements Seminars series.

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