Simpler Grants.gov #RFA-AI-27-017

NIH Solicitation for Innovative Clinical Transplantation Modeling Research

The National Institutes of Health (NIH), through the National Institute of Allergy and Infectious Diseases (NIAID), is seeking proposals for the Cooperative Program for Modeling Clinical Transplantation. - Government Buyer: - National Institutes of Health (NIH) - National Institute of Allergy and Infectious Diseases (NIAID) - Scope of Work: - Development of innovative in-vitro and in-vivo models to advance human solid organ transplantation research - Encourages new approach methods (NAMs), such as: - Immune-competent microphysiological systems - Organoids - Ex-vivo perfused human organs - Precision-cut tissue slices - Computational systems biology models - Refined mouse models - Models should address clinical translation obstacles, reduce reliance on nonhuman primates, and demonstrate clinical relevance - Strong emphasis on data sharing, reproducibility, and establishing best practices - Products/Services Requested: - No specific products, part numbers, or OEMs are listed - Main service is research and development in modeling clinical transplantation - Notable Requirements: - Proposals must focus on clinically translatable models and data sharing - Estimated total program funding is $1,280,000 for approximately three awards

Description

The National Institute of Allergy and Infectious Diseases (NIAID) is supporting the Cooperative Program for Modeling Clinical Transplantation to advance new therapeutics and success in human solid organ transplantation. The program seeks applications for innovative and clinically translatable in-vitro and in-vivo systems, including new approach methods (NAMs) and refined mouse models, to model immune responses and promote translation of new therapies to clinical practice. Applicants must propose models that overcome obstacles to clinical translation, reduce reliance on nonhuman primates, and demonstrate clinical relevance. Emphasis on data sharing aims to facilitate reproducibility and establish standards and best practices.

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