Project Grant R44LM015020
- Federal Project Grant Award Summary The National Institute of Environmental Health Sciences (NIEHS), through the Medical Library Assistance program (CFDA 93.879), awarded $139,836 to The Feinstein Institutes for Medical Research for the period of July 1, 2026 through June 30, 2029. This Project Grant supports the development and dissemination of artificial intelligence-driven software tools designed to enable early prediction of clinical deterioration in hospitalized patients within non-critical...
- Federal Project Grant Award Summary The National Institute of Environmental Health Sciences (NIEHS), under the Medical Library Assistance program (CFDA 93.879), awarded The Johns Hopkins University a $588,676 Project Grant (awarded July 14, 2026, with completion targeted for April 30, 2031) to develop automated quantitative dataset audit methods for identifying bias, shortcuts, and robustness risks in data-driven healthcare artificial intelligence (AI) and machine learning (ML) applications. The...
- Federal Project Grant Award Summary Clairyon, Inc. received a $410,924 Project Grant from the National Institute of Environmental Health Sciences under the Medical Library Assistance program (CFDA 93.879), awarded on September 1, 2025, with a completion date of February 28, 2026. The award supports development and prospective validation of QUALLM (an automated quality measure abstraction toolset), which leverages Fast Healthcare Interoperability Resources (FHIR) standards and generative...
- Federal Project Grant Award Summary The National Institute of Environmental Health Sciences (NIEHS), under the Medical Library Assistance program (CFDA 93.879), awarded Lawrence Berkeley National Laboratory $1,164,870 on September 27, 2025, for a project titled "Modernizing the Hierarchical Data Modeling Framework to Advance FAIR Data for Science." The project, which extends through August 31, 2027, focuses on enhancing the Hierarchical Data Modeling Framework (HDMF)—an open-source...
- Federal Grant Award Summary The National Institute of Environmental Health Sciences (NIEHS) awarded The Leland Stanford Junior University a $652,850 Project Grant under the Medical Library Assistance program (CFDA 93.879) on June 15, 2026, with completion targeted for April 30, 2031. This award funds systematic evaluation and validation of large language models (LLMs) and foundation models (FMs) in clinical medicine. Stanford will develop and deliver three primary products: (1) shared...
- Federal Grant Award Summary The National Institute of Environmental Health Sciences awarded Cedars-Sinai Medical Center a $3.48 million Project Grant under the Medical Library Assistance program (CFDA 93.879) on September 15, 2025, with a completion date of August 31, 2029. This research initiative develops artificial intelligence and machine learning methods to conduct large-scale epidemiological studies using patient-generated reports of medication adherence and tolerability. The project...
- Federal Project Grant Award Summary The National Institute of Environmental Health Sciences awarded Brigham & Women's Hospital Inc. a Project Grant totaling $402,750 (awarded August 1, 2025, with completion targeted for July 31, 2029) under the Medical Library Assistance program (CFDA 93.879) to develop large language models (LLMs) for drug safety and effectiveness causal analysis. The project addresses a critical gap in pharmacoepidemiologic research by creating an LLM-based analytical...
- Federal Grant Award Summary Hominin.ai Inc. received a $302,668 Small Business Innovation Research (SBIR) Phase I award from the National Science Foundation (NSF) Technology, Innovation, and Partnerships (TIP) program (CFDA 47.084) on August 1, 2025, for a twelve-month performance period concluding July 31, 2026. The company will develop a software system and machine learning models that translate ordinary human walking patterns into movement-based biomarkers of personal health using...
- Federal Project Grant Award Summary The National Institute of Environmental Health Sciences (NIEHS) awarded The Leland Stanford Junior University a $1.39 million Project Grant under the Medical Library Assistance program (CFDA 93.879) to develop advanced artificial intelligence systems for aligning and interpreting multimodal biological imaging data. The award, obligated on June 1, 2026, with performance through May 31, 2030, targets a critical gap in biomedical data analysis: the integration of...
- Federal Grant Award Summary Panacea Interactive LLC received a $350,000 Project Grant from the National Institute of General Medical Sciences (NIGMS) under the Biomedical Research and Research Training program (CFDA 93.859), awarded on September 3, 2025, with a completion date of February 28, 2027. The grant funds development of an innovative digital platform designed to enhance health literacy among secondary and medical students through the integration of game-based learning (GBL), mnemonic...
Mountain Biometrics, Inc. received a $306,721 Project Grant from the National Institute of Environmental Health Sciences (NIEHS) under the Medical Library Assistance program (CFDA 93.879) awarded August 1, 2026, with completion targeted for January 31, 2027. The grant funds development of a scalable, privacy-preserving annotation platform designed to address critical gaps in high-quality, annotated physiological datasets necessary for advancing medical artificial intelligence (AI). The platform will enable efficient labeling of complex clinical time-series data from wearables, bedside monitors, and electronic health records while maintaining Health Insurance Portability and Accountability Act (HIPAA) compliance and interoperability standards. Phase 1 deliverables focus on demonstrating technical feasibility through enhanced multi-signal data visualization with sub-second latency performance, implementation of robust privacy frameworks for secure handling of sensitive health information, and user-centric design validation with clinicians and researchers. Phase 2 extends the effort to validate scalability and real-world applicability through concurrent user support, standardized Electronic Health Record (EHR) integration using Fast Healthcare Interoperability Resources (FHIR) protocols, and clinical deployment. The platform is expected to accelerate AI-driven healthcare solution development by resolving existing challenges in data quality, reproducibility, and irregular sampling rates inherent in clinical datasets.Federal Grant Award Summary
Mod # | Description | ReasonForModification | Federal Obligation | Date |
|---|---|---|---|---|
| Not listed | $306.7k | 7/16/26 |