Managing Immunogenicity Using Quantitative Systems Pharmacology

Biologic drug development is a rapidly evolving sector in the biopharmaceutical industry. Immunogenicity is an inherent challenge with this complex class of drugs. A quantitative systems pharmacology approach can be used to predict and better manage immunogenicity, and as a tool to guide clinical and regulatory decision-making in biologics drug development.

Using Model-based Meta-analysis to Improve Decision-making in Drug Development

Making the right choices in drug development often means the difference between getting a new medication to patients and it ending up in the scrap heap of failed programs. There is a surfeit of publicly available information on approved drugs as well as those currently in development. How can sponsors turn clinical trial data into understanding that helps chart the course for investigational drugs?

Model-based Meta-analysis: An Innovative Methodology Comes of Age

MBMA integrates internal and external drug development data to inform proprietary commercial and R&D decisions. The insights gained via MBMA support designing less costly and more precise trials with an eye toward achieving commercial success for both the drug and portfolio.

Three Questions, Piet van der Graaf

Staff writer Ron Rosenberg interviewed Piet van der Graaf, PharmD, PhD, vice president of quantitative systems pharmacology at Certara and former director of XenologiQ, a QSP consultancy.

Physiologically-based Modeling Supports Drug Development Decisions, Regulatory Interactions and Drug Labeling

Today’s powerful and actively evolving computational tools enable sponsors and regulators to understand potential drug characteristics and subject responses earlier in development, with greater certainty. Model-based approaches support timely, confident decisions across the development and regulatory life cycle by gathering disparate sources of information about a drug, its competitors, target disease and patients into a … Continued

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