Support quantitative systems pharmacology approaches that couple biological network and pathway analyses with mechanistic systems models and integrate data from disparate sources (e.g., preclinical and clinical; in vitro, ex vivo, in vivo; acute and chronic intervention) to enable predictive drug development. These efforts should:
- encourage precompetitive academic-industry collaborations,
- ensure full-transparency of data and analytical methods development, and
- support cross-disciplinary training in all aspects of quantitative systems pharmacology, spanning experimental and clinical work to various types of modeling and simulation.
Create a network of translational centers that will develop and apply the principles of quantitative and systems pharmacology to AD and ADRD drug development.
These centers will bring together expertise and technology needed for integration of multi-modal data analysis, mathematical modeling and empirical testing and apply a systems biology/systems pharmacology approach to the most challenging aspects in preclinical therapy development such as:
- therapeutic target selection and initial target validation,
- predictive toxicology,
- rigorous preclinical efficacy testing and development of translatable, preclinical biomarkers,
- comprehensive success and failure analyses,
- implementing precision medicine principles in clinical trial design.
The centers will also provide training in all aspects of quantitative systems pharmacology, spanning experimental and clinical work to various types of modeling and simulation for the next generation of translational scientists.
- Research Implementation Area
- Translational Tools, Infrastructure and Capabilities
- In Progress
- RFA-AG-14-017: Planning Grants for Alzheimer's Disease Translational Centers for Predictive Drug Development (R34)
- RFA-AG-19-010: Alzheimer Centers for Discovery of New Medicines (U54)