A Survey of Software Tool Utilization and Capabilities for Quantitative Systems Pharmacology: What We Have and What We Need

Abstract

Quantitative systems pharmacology (QSP) is a rapidly emerging discipline with application across a spectrum of challenges facing the pharmaceutical industry, including mechanistically informed prioritization of target pathways and combinations in discovery, target population, and dose expansion decisions early in clinical development, and analyses for regulatory authorities late in clinical development. QSP's development has influences from physiologic modeling, systems biology, physiologically‐based pharmacokinetic modeling, and pharmacometrics. Given a varied scientific heritage, a variety of tools to accomplish the demands of model development, application, and model‐based analysis of available data have been developed. We report the outcome from a community survey and resulting analysis of how modelers view the impact and growth of QSP, how they utilize existing tools, and capabilities they need improved to further accelerate their impact on drug development. These results serve as a benchmark and roadmap for advancements to the QSP tool set.

Open Models for Clinical Pharmacology

“…The software packages used in QSP model coding are similarly diverse. While MATLAB (MathWorks, Natick, MA) and its dependent SimBiology are the most common, at least a dozen other software packages are in use and active development . Considerable time and resources are spent developing this plethora of software.…”

Applications of Quantitative Systems Pharmacology in Model‐Informed Drug Discovery: Perspective on Impact and Opportunities

“…In the spirit of standardization, these models should be published with all equations and parameters written in a standard format such that they can be coded in any software of choice. We recommend this path as there are many software options for building and applying QSP models, but no clear frontrunner …”

Quantitative Systems Pharmacology: A Regulatory Perspective on Translation

“…Interestingly, scientists in the field have also recently remarked that QSP seems to be progressing on a hope‐hype path . QSP is arguably on an expedited pathway because of the very thoughtful work being conducted by drug development, regulatory, and academic scientists (further discussed in the next section).…”

“…We learned of the wide range of QSP modeling definitions and resource investments, the stage at which QSP modeling is initiated, model size and complexity, perceived and actual impact of QSP modeling along with success/failure determinants, and perhaps most importantly the contexts of use for QSP. Ermakov et al . performed additional survey work wherein they provided useful insights into the platform capabilities needed to robustly develop and apply QSP models.…”