Applications of QSP in Drug Development

The podcast provides a deep dive into how Quantitative Systems Pharmacology (QSP) is transforming drug development by offering a systems-level view of disease biology and drug action. Key points discussed include:Understanding Mechanism of Action (MoA): QSP models enable detailed exploration of how drugs interact dynamically with biological systems, moving beyond static target identification.Simulating Disease Progression: Building "virtual disease models" allows researchers to understand and predict the natural course of a disease and simulate drug interventions.Virtual Patient Populations: QSP enables the creation of diverse virtual patients, capturing variability in genetics, physiology, and disease, crucial for predicting heterogeneous drug responses.Dose Optimization: QSP helps optimize dosing strategies rather than simply identifying the maximum tolerated dose, aligning with modern regulatory expectations like the FDA’s Project Optimus.Bridging Preclinical to Clinical: QSP supports translational modeling, helping bridge the gap between animal studies and human clinical outcomes by modeling key biomarkers and pathways.Model Qualification: Ensuring models are “fit-for-purpose” is critical—through rigorous validation, transparent assumptions, and biological plausibility checks.Decision-Making Support: Well-qualified QSP models inform early go/no-go decisions, optimize trial designs, and reduce risk in drug development.The episode concludes by emphasizing the importance of interdisciplinary collaboration (biology, modeling, pharmacology, mathematics) to fully realize QSP’s transformative potential.

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