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Updated: Jun 16, 2026

Biosensor-based High Throughput Biopanning and Bioinformatics Analysis Strategy for the Global Validation of Drug-protein Interactions
Published on: December 1, 2020
Applying physiological and biochemical concepts to optimize biological drug development.
1Modelling and Simulation, Novartis Pharma AG, Basel, Switzerland. phil.lowe@novartis.com
Posology, the science of drug dosage and regimen, is crucial for drug development. Quantifying target capture with mathematical models allows for rapid simulation of potential drug dosages, enhancing clinical benefit and reducing adverse effects.
Area of Science:
- Pharmacology
- Drug Development
- Biotechnology
Background:
- Posology, the science of dose and regimen, is fundamental to drug development.
- Ensuring optimal clinical benefit while minimizing adverse effects is a key challenge.
- Recent advancements allow direct quantification of target engagement for biologics.
Purpose of the Study:
- To explore the application of quantitative methods in determining optimal drug posology.
- To demonstrate how target capture can be linked to clinical outcomes.
- To highlight the potential of mathematical modeling in accelerating drug development.
Main Methods:
- Utilizing mathematical models that integrate pharmacokinetic/pharmacodynamic (PK/PD) principles.
- Quantifying target occupancy or capture for specific biologic drugs.
- Correlating target engagement metrics with observed clinical responses.
Main Results:
- Demonstrated a direct relationship between target capture and clinical efficacy for certain biologics.
- Mathematical models enabled rapid simulation and exploration of various dosing regimens.
- Simulations provided insights into potential posologies, reducing the need for extensive traditional studies.
Conclusions:
- Quantitative methods and mathematical modeling significantly enhance the efficiency of posology determination.
- This approach facilitates faster exploration of potential drug dosages, stimulating innovation in drug development.
- Linking target capture directly to clinical response optimizes the balance between efficacy and safety.
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