Abstract & Details
Description
Award ID: 2151522
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve drug safety. This project advances software to identify the potential of new drugs to provoke dangerous cardiac side-effects. Because sudden cardiac death is an infrequent and relatively rare phenomenon, predicting it with conventional tools is either impractical or impossible. The proposed technology will make the development of all new classes of drugs safer, faster, and less expensive. This will be integrated into investigational new drug submission packages for submission to the FDA for drug approval. This will improve pharmaceutical safety and clinical outcomes. This Small Business Innovation Research (SBIR) Phase II project will address the critical problem of predicting the arrhythmogenic potential of new drugs seeking FDA approval. Current basic science research methods are based on trying to reproduce exact and infrequently encountered in vivo phenomena in an in vitro setting. The economic and practical constraints on drug development therefore requires industry to use proxies, primarily drug binding to the HERG potassium channel, as a predictor arrhythmogenicity. The intellectual challenge in this project is to combine mathematical modeling and quantitative analysis of rigorous experimental protocols to bridge this gap and identify underlying features which are strong predictors of arrhythmogenic behavior. Key to understanding this is the rapid development and deployment of state-dependent Markov models of drug action based on limited patch clamp data, which is both time-consuming and expensive to obtain. This project combines mathematical analysis directly to direct patch-clamp assay protocols to minimize time and expense while increasing predictive accuracy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Alastair Monk
The broader impact /commercial potential of this Small Business Innovation Research (SBIR) Phase II project is to improve drug safety. This project advances software to identify the potential of new drugs to provoke dangerous cardiac side-effects. Because sudden cardiac death is an infrequent and relatively rare phenomenon, predicting it with conventional tools is either impractical or impossible. The proposed technology will make the development of all new classes of drugs safer, faster, and less expensive. This will be integrated into investigational new drug submission packages for submission to the FDA for drug approval. This will improve pharmaceutical safety and clinical outcomes. This Small Business Innovation Research (SBIR) Phase II project will address the critical problem of predicting the arrhythmogenic potential of new drugs seeking FDA approval. Current basic science research methods are based on trying to reproduce exact and infrequently encountered in vivo phenomena in an in vitro setting. The economic and practical constraints on drug development therefore requires industry to use proxies, primarily drug binding to the HERG potassium channel, as a predictor arrhythmogenicity. The intellectual challenge in this project is to combine mathematical modeling and quantitative analysis of rigorous experimental protocols to bridge this gap and identify underlying features which are strong predictors of arrhythmogenic behavior. Key to understanding this is the rapid development and deployment of state-dependent Markov models of drug action based on limited patch clamp data, which is both time-consuming and expensive to obtain. This project combines mathematical analysis directly to direct patch-clamp assay protocols to minimize time and expense while increasing predictive accuracy. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.
NSF Program Director: Alastair Monk
| Status | Closed |
|---|---|
| Effective start/end date | 03/01/22 → 02/28/25 |
Lead and Sub-Awardee Organization(s)
Funding
- SBIR Phase II: $1,000,000.00
Active Fiscal Year
- FY2024
- FY2023
- FY2022
- FY2025
Start Fiscal Year
- FY2022
TIP Programs
- SBIR Phase II
Small Business
- Yes
Key Technology Areas
- Biotechnology
- (confidence score: 100%)
Technology Foci
- Biotechnology (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 23 of New York
Current Congressional District
- District n. 23 of New York
United States
- New York
Core Based Statistical Area (CBSA)
- Buffalo-Cheektowaga, NY
County
- County: Niagara, NY
Fingerprint
Explore the research topics touched on by this project. These labels are generated based on the underlying awards/grants. Together they form a unique fingerprint. Learn more about Elsevier's Fingerprint Engine here: https://beta.elsevier.com/products/elsevier-fingerprint-engine