An Introduction to QSP
An opportunity to learn about recent advances in Quantitative Systems Pharmacology (QSP) and how it is informing drug discovery and development, network with QSP researchers in industry and academia and become involved in the UK QSP Network
In-person and online 17-20hrs 24th October 2024,Discovery Centre,
AstraZeneca, Cambridge,
UK.
REGISTRATION CLOSES 20TH OCTOBER 2024
Programme
- 17.00-17.30 Registration
- 17.30-17.40 Welcome & introduction
Marcus Tindall (University of Reading) and Mark Penney (AstraZeneca)
- 17.40-18.15 What is QSP?
James Yates (GSK)
- 18.15-18.50 Prediction of first-in-human dose for T-cell engagers: mechanistic modeling
vs MABEL PK-driven approach
Oleg Demin Jr (InSysBio)
While the minimal anticipated biological effect level (MABEL) PK-driven approach is recommended for determining the safe clinical starting dose for T-cell engagers (TCE), this method can sometimes yield a low minimal recommended starting dose (MRSD) resulting in treatment of patients with sub-therapeutic doses and multiple dose escalations. Quantitative Systems Pharmacology (QSP) modeling is another approach to predict MRSD for TCE with potentially higher predictive power. In my presentation, I will discuss the advantages and challenges of mechanistic modeling for the selection of MRSD and compare it with the MABEL PK-driven approach using a case study on HPN536, a TCE targeting mesothelin.
- 18.50-19.25 Combining advanced cell systems with mathematical modelling to predict clinical safety of
novel therapeutics
Carmen Pin (AstraZeneca)
Mathematical modelling represents the strategy of choice to find safe clinical dosing schedules of new therapeutic agents, however models are often developed using data from clinical studies, therefore, they are usually retrospective, clinical data-driven with limited capacity to impact on early clinical decisions. Advanced cell systems have rapidly developed in recent years providing a large experimental platform to accurately quantify the response of human organs/diseases to new therapies. Modern drug safety assessment strategies aim to integrate advanced cell systems and modelling approaches to predict clinical outcomes at early stages of the development of novel therapeutics. Thus, they can effectively replace animal experimentation and reduce drug development costs associated with clinical trials.
We will discuss the development of mathematical models that enable the translation of drug-induced responses measured in advanced cell systems into quantitative predictions of clinical toxicity associated with a given therapy and dosing schedule. We will focus on haematotoxicity, and gastrointestinal toxicity induced by oncology treatments and show that this strategy leads to superior predictive performance compared to in vivo-based predictions. These models are available at early stages of the drug development pipeline, prior to clinical trials, and used to inform dosing concentrations and scheduling, benchmark safety risk versus competitors and optimise combination therapies.
Importantly, this type of strategy enables the early assessment of toxicity and efficacy of new therapeutic modalities, such as biologics, gene, and cell therapies for which preclinical species often fail to be predictive.
- 19.25-20.00 Drinks reception
Registration
Please register here. The event is free, but registration is required.Registration closes 20th October 2024.
