02. What & When
What is QSP?

QSP is the discipline of building mathematical models to mechanistically simulate the dynamics of diseases and treatments. In this approach, we write systems of equations that represent the best scientific understanding of cause-and-effect, mathematically capturing detailed interactions occurring at sub-cellular, cellular, organ, and physiological scales. These equations are then calibrated using both public and proprietary data, including in vitro, pre-clinical, and clinical studies. This results in an interpretable and validated predictive model founded on solid and explicit first principles.

By incorporating disease pathophysiology, clinical presentation, and clinical outcomes into a unified framework, QSP models provide a powerful tool for evaluating therapies. The mechanisms of action for compounds are represented directly in QSP models, enabling them to mechanistically account for both pharmacokinetic and pharmacodynamic effects. Additionally, the QSP approach allows us to define virtual patients who, like real patients, differ in ways that affect the course of disease and treatment. Simulating diverse, realistic virtual populations under different treatments, we can predict how clinical outcomes vary across patients and alternative treatment strategies. Using this information, researchers and decision makers can understand the strengths and weaknesses of therapies, and design their compounds, trials, or treatment protocols to maximize efficacy.

When should I use QSP?

QSP can be utilized at any stage of R&D. When you use it depends on what question you’re trying to answer. QSP is capable of helping you…

  • Optimize clinical trial protocols by determining favorable dosing paradigms and outcomes (eg, measurement frequency)
  • Evaluate efficacy and safety potential for targets and/or specific compounds utilizing key laboratory and/or clinical data describing DMPK, pharmacodynamic, and mechanism of action characteristics
  • Interpret preclinical and clinical data to provide improved mechanistic understand of observed responses to compounds
  • Prioritize compounds and targets
  • Determine responsive and non-responsive patient subsets to support clinical trial patient recruitment
  • Predict efficacy for novel combinations of treatments
  • Evaluate the impact of drug sequencing and holidays

Our QSP experts are ready to help you get the data you need to make confident decisions about your drug development program.

03. Experts
Meet the Experts
05. QSP Publications
Peer-reviewed Publications