Modeling and simulation have become indispensable in drug development. The FDA and EMA have both included modeling and simulation among their highest priorities to support efficient drug development and facilitate regulatory decision making. Together, the information and insights gleaned from modeling and simulation provide not only opportunities for a more efficient drug development program, but they also provide key support for marketing application submissions.
Using modeling and simulation, existing data can be leveraged to provide critical insights on product safety and effectiveness as related to drug concentration. The knowledge gained from modeling can be used to inform clinical trial designs, predict trial outcomes, select appropriate dosing regimens, understand clinically relevant factors contributing to variability in exposure and/or response, predict the impact of formulation changes on drug performance, and much more.
Allucent’s expert team of pharmacometricians have experience across a wide array of modeling tools/techniques and build models tailored to guide your drug development program’s specific needs. As part of these services, our team will create a custom, model-informed drug development plan that will outline the spectrum of information available and recommend data to be collected during development to facilitate the selection of the most salient models for your compound and disease area. Our custom modeling plan will inform decisions, probability of success, dosing strategy, and design efficient trials along the entire development journey from candidate selection to registration and beyond.
Modeling and Simulation Services:
- Model-Informed Drug Development Plan
- Population PK/PD, Exposure-Response Analysis
- Dose Selection and Justification
- Allometric Scaling
- Physiologically Based Pharmacokinetics (PBPK)
- Quantitative Systems Pharmacology (QSP)
- Concentration QT (cQT) Modeling
- In Vitro, In Vivo Correlation (IVIVC)
- Comparator PK/PD Analysis, Model-based Meta-analysis (MBMA)
- Clinical Trial Simulations (CTS)