QSP

QSP most commonly stands for Quantitative Systems Pharmacology, a field that integrates pharmacology with systems biology and mathematical modeling to study how drugs interact with biological systems. QSP uses mechanistic, network-based models to describe drug effects across scales, from molecular targets and signaling pathways to tissues and whole organisms. These models couple pharmacokinetics, describing drug concentrations over time, with pharmacodynamics, describing biological responses, within structured networks of cellular processes and disease mechanisms.

The goal of QSP is to improve drug discovery and development by enabling simulations of dosing regimens, combination therapies, and patient variability. Applications include dose optimization, forecasting efficacy and safety outcomes, translating preclinical findings to clinical expectations, and informing experimental design and regulatory discussions. Compared with traditional PK/PD modeling, QSP emphasizes mechanistic representations of pathways and networks, allowing exploration of hypothetical interventions and identification of critical control points in disease processes.

Data used in QSP come from in vitro assays, omics datasets, literature-derived pathways, animal studies, and clinical data. Models are implemented in computational platforms such as MATLAB/SimBiology, R, and Python, and may integrate with PBPK tools and network analysis libraries. QSP is applied across therapeutic areas including oncology, immunology, neurology, and metabolism, among others. The field has grown since the early 2000s and is characterized by collaboration among biologists, pharmacologists, and clinicians, with increasing emphasis from industry and regulatory bodies as a source of mechanistic evidence for decision-making.

In other contexts, QSP is a rare acronym; when used, it most often refers to Quantitative Systems Pharmacology.