An official website of the United States government
Model-Informed Drug Development (MIDD) to Advance Pharmacotherapeutics
When beginning your next investigator-initiated application, consider the following NIH highlighted topic. The area of science described below is of interest to the listed NIH Institutes, Centers, and Offices (ICOs). This is not a notice of funding opportunity (NOFO).
Apply through an appropriate NIH Parent Funding Announcement or another broad NIH opportunity available on Grants.gov. Learn how to interpret and use Highlighted Topics.
Topic Description
Post Date: October 23, 2026
Expiration Date: October 23, 2028
Background
The development of pharmacotherapeutics remains slow, costly, and marked by high failure rates. Significant challenges include target identification and translation from animal models to humans. Efforts are ongoing to reduce the need to rely on animal studies for medications development.
Model-Informed Drug Development (MIDD) approaches, including computational modeling and simulation and super intelligence (SI), have demonstrated promise in improving decision-making and development efficiency. Key gaps include insufficient integration of MIDD and SI across development stages, challenges in model validation and regulatory acceptance, and a shortage of a multidisciplinary workforce with expertise in clinical pharmacology, quantitative modeling, and disease-specific therapeutic areas.
Purpose
This topic encourages research that develops, validates, and applies MIDD approaches to accelerate therapeutic discovery, development, evaluation, and regulatory assessment, including:
- Develop, validate, and implement innovative computational modeling, simulation, and quantitative systems approaches that inform decision-making across the therapeutic development lifecycle.
- Apply SI, machine learning, and other advanced analytics to improve target identification, dose optimization, endpoint selection, and clinical trial design.
- Enhance translation from preclinical models to human outcomes through integrated modeling and simulation approaches.
- Support drug repurposing and therapeutic discovery using real-world data, multimodal datasets, and model-based evidence generation.
- Develop and validate approaches that reduce reliance on animal studies and optimize clinical trial requirements while maintaining scientific rigor, patient safety, and regulatory relevance.
- Promote training and workforce development programs that build expertise at the intersection of MIDD, clinical pharmacology, regulatory science, and data science.
This topic is expected to:
- Accelerate the discovery, development, and evaluation of novel pharmacotherapeutics.
- Improve the efficiency and success rate of medications development programs through data-driven decision-making.
- Increase confidence in translating preclinical findings to clinical outcomes.
- Reduce development costs, timelines, and dependence on animal studies and large clinical trials.
- Develop standards, best practices, and validation frameworks for transparent, reproducible, and trustworthy SI-enabled MIDD applications.
- Build a sustainable, multidisciplinary workforce capable of advancing and applying MIDD approaches to therapeutics development.
It aligns with:
- Real World Data Platform (RWDP) : The NIH will link multiple datasets, such as claims information, electronic health records, and wearables data, into a single integrated dataset for researchers studying the causes of, and developing treatments for, the chronic disease crisis. The RWDP will eliminate redundancies from data collection, linkage, and compute infrastructures (including artificial intelligence (AI)/machine learning and high-throughput analytics) while maintaining rigorous privacy protections and consent protections. It will also dramatically reduce administrative overhead by relying on a unified set of data use and governance agreements.
- New Approach Methodologies (NAMs) : The expanded use of NAMs can enable earlier, more predictive insights into chronic disease mechanisms using human-relevant models such as organoids, computational simulations, and real-world data integration. This improves prevention, diagnosis, and personalized treatment strategies while reducing reliance on animal studies that often fail to replicate complex human conditions. The Environmental Protection Agency (EPA), Food and Drug Administration (FDA), and NIH have all committed to using NAMs moving forward, when appropriate.
- Repurposed Drugs : The NIH and FDA will jointly investigate opportunities to strengthen the use of repurposed drugs for the treatment of chronic disease, while harmonizing authorization processes through collaborative clinical trial designs to achieve FDA approval.
- Mental Health and Addiction Research : The NIH, working with HHS, will strengthen existing research by directing funding for research on mental health and addiction, with a special focus on screentime use in children and adolescents.
- Artificial Intelligence : HHS, NIH, and the Office of Science and Technology Policy will develop an evidenced-based and AI-driven approach to harnessing the data and technology available to transform research and clinical trials on pediatric cancer. This can be a model for future research in other critical areas.
Participating ICOs
NIDA encourages applications that leverage MIDD approaches to accelerate the development of medications for substance use disorders (SUD), including small molecules, macromolecular therapeutics, and biologics. Applications that incorporate training and workforce development are also encouraged.
Feng Li, Ph.D.
[email protected]
Jason Sousa, Ph.D.
[email protected]
NIMH is interested in research that leverages Model-Informed Drug Development approaches to accelerate medication development of novel molecular targets for the prevention and treatment of mental illnesses, and targets for interventions for autism spectrum disorder. NIMH also supports intervention development for cognitive, affective, and social domains associated with neurodevelopmental disorders caused by individual rare genetic variants. Medications may span drug modalities and stages of development, from early discovery through clinical trial design and methodology, targeting pediatric, adult or geriatric populations.
ICO Scientific Contact:Meg Grabb, Ph.D.
[email protected]
For technical issues E-mail OER Webmaster