Abstract
Quantitative Systems Toxicology (QST) models, recapitulating pharmacokinetics and mechanism of action together with the organic response at multiple levels of biological organization, can provide predictions on the magnitude of injury and recovery dynamics to support study design and decision-making during drug development. Here, we highlight the application of QST models to predict toxicities of cancer treatments, such as cytopenia(s) and gastrointestinal adverse effects, where narrow therapeutic indexes need to be actively managed. The importance of bifurcation analysis is demonstrated in QST models of hematologic toxicity to understand how different regions of the parameter space generate different behaviors following cancer treatment, which results in asymptotically stable predictions, yet highly irregular for specific schedules, or oscillating predictions of blood cell levels. In addition, an agent-based model of the intestinal crypt was used to simulate how the spatial location of the injury within the crypt affects the villus disruption severity. We discuss the value of QST modeling approaches to support drug development and how they align with technological advances impacting trial design including patient selection, dose/regimen selection, and ultimately patient safety.
Highlights
In the past 10 years, this field has seen an unprecedented development with the emergence of Quantitative Systems Pharmacology/ Toxicology (QSP/T) models
QSP/T models have arisen from the integration of pharmacokinetics (PK) with systems biology approaches to enable the quantification of dynamic interactions between drug(s) and biological processes, intended or unintended, in the organism as a whole [2]
The modeling approaches we have used in our examples focus on the quantification of cell dynamics in the bone marrow and intestinal epithelium during anti-cancer treatment and recovery
Summary
Quantitative methods are well established across many therapeutic areas to evaluate the safety and efficacy of an investigational drug during development [1]. QSP/T models have arisen from the integration of pharmacokinetics (PK) with systems biology approaches to enable the quantification of dynamic interactions between drug(s) and biological processes, intended or unintended, in the organism as a whole [2]. QSP/T modeling aims at merging the drug disposition kinetics in plasma, tissues, and cells with the multiscale nature of interplaying organic systems and lead to a paradigm shift from scale-specific reductionistic approaches to multiscale models [4,5]. This paradigm shift is further endorsed by the increasingly available wealth of information within complex data of multiscale nature that spans levels of organization from cells to whole organisms. In vitro systems provide a variety of dynamic, high-resolution
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
