Opportunities for quantitative translational modelling in Oncology

Yates, James W T, Byrne, Helen Byrne, Chapman, Sonya C, Chen, Tao, Cucurull-Sanchez, Lourdes, Delgado-SanMartin, Juan, Di Veroli, Giovanni, Dovedi, Simon J, Dunlop, Carina, Jena, Rajesh et al, Jodrell, Duncan, Martin, Emma, Mercier, Francois, Ramos-Montoya, Antonio, Struemper, Herbert and Vicini, Paolo (2020) Opportunities for quantitative translational modelling in Oncology Clinical Pharmacology & Therapeutics.

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Abstract

A two-day meeting was held by members of the UK Quantitative Systems Pharmacology Network (http://www.qsp-uk.net/) in November 2018 on the topic of Translational Challenges in Oncology. Participants from a wide range of backgrounds were invited to discuss current and emerging modelling applications in non-clinical and clinical drug development, and to identify areas for improvement. This resulting perspective explores opportunities for impactful quantitative pharmacology approaches. Four key themes arose from the presentations and discussions that were held, leading to the following recommendations:

- Evaluate the predictivity and reproducibility of animal cancer models through pre-competitive collaboration

- Apply mechanism of action (MoA) based mechanistic model derived from nonclinical data to clinical trial data

- Apply MoA reflective models across trial data sets to more robustly quantify the natural history of disease and response to differing interventions

- Quantify more robustly the dose and concentration dependence of adverse events through mathematical modelling techniques and modified trial design

Item Type:	Article
Divisions :	Faculty of Engineering and Physical Sciences > Chemical and Process Engineering
Authors :	Name Email ORCID Yates, James W T Byrne, Helen Byrne Chapman, Sonya C Chen, Tao T.Chen@surrey.ac.uk Cucurull-Sanchez, Lourdes Delgado-SanMartin, Juan Di Veroli, Giovanni Dovedi, Simon J Dunlop, Carina c.dunlop@surrey.ac.uk Jena, Rajesh Jodrell, Duncan Martin, Emma Mercier, Francois Ramos-Montoya, Antonio Struemper, Herbert Vicini, Paolo
Date :	2020
Funders :	Cancer Research UK
Grant Title :	RadNet Radiotherapy research infrastructure
Copyright Disclaimer :	© 2019 John Wiley & Sons Ltd. This article is protected by copyright. All rights reserved.
Uncontrolled Keywords :	Pharmacokinetics; Pharmacodynamics; Oncology; Drug Development; Mathematical Modelling; Translation
Related URLs :	Publisher
Depositing User :	Clive Harris
Date Deposited :	15 Jun 2020 19:35
Last Modified :	15 Jun 2020 19:35
URI:	http://epubs.surrey.ac.uk/id/eprint/857983

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