Modeling and simulation have become indispensable in drug development. Using modeling and simulation, existing data can be leveraged to provide important insights on product safety and effectiveness as related to drug concentration. These insights can be used to inform clinical trial design and predict trial outcomes. They can also help drug developers select appropriate doses for first in human clinical trials or in special populations, such as renal and hepatic impairment or pediatric patients.
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. Indeed, the FDA and EMA have both included modeling and simulation among their highest priorities to support efficient drug development and facilitate regulatory decision making.
With modeling and simulation, your existing data can answer many important questions and save significant time and money. Model-based drug development consists of the use of mathematical and statistical methods to:
- Understand how various dosing choices (e.g., dose, dose frequency, dosing duration) affect drug concentrations
- Clarify the relationship between drug concentration and desired or undesired pharmacodynamic responses
- Characterize the PK/PD variability of drugs and assist in understanding the clinically relevant factors contributing to variability
- Predict the impact of formulation changes on drug performance (i.e., in vivo bioavailability) using in vitro/in vivo correlations (IVIVC)
Nuventra has an expert team of pharmacometricians who can build appropriate models to guide your drug development decisions. As part of these services, our team will create a tailored, model-based drug development plan that will facilitate rational selection of the most salient model for your compound and disease area.
Modeling and Simulation Services
- Population Pharmacokinetics (Population PK)
- Candidate Selection
- Allometric Scaling
- Dose Selection and justification
- Clinical Study Design Simulations
- Exposure-Response Analysis
- Identify & confirm predictive covariates
- Comparator PK/PD Analysis
- Concentration QT (cQT) Modeling
- TQT Waiver
- Model Risk
- Large-scale NONMEM
- DARWIN – Automated Model Selection