Abstract & Details
Description
Award ID: 2335206
The broader impact of this Small Business Technology Transfer (STTR) Phase II project is potentially profound and could offer a transformative approach to quality assurance in pharmaceutical manufacturing that directly targets medicine supply chain vulnerabilities and cost structure in the United States. It aims to modernize the quality testing of the most widely used pharmaceutical dosage formtabletsthrough rapid ultrasonic testing techniques and innovative automation/robotics. This advancement may reduce the risk of quality failures, drug shortages, and recalls, ensuring more reliable access to essential medications for the public. Nearly 70% of Americans rely on prescription drugs, with a significant portion of these medications currently produced overseas. The projects commercial impact is in its potential to redefine quality assurance practices in the pharmaceutical industry, leading to improved efficiency, reduced costs, and enhanced product safety. Such improvements can contribute to national health security by reducing dependence on unreliable foreign drug manufacturing. Its societal benefits include improved healthcare outcomes through more dependable drug availability. Furthermore, the project offers significant educational benefits, providing hands-on training and research opportunities for students in advanced manufacturing technologies. The project focuses on inclusivity, attracting underrepresented groups into engineering, and fostering diversity in advanced research and innovation in pharmaceutical manufacturing. The proposed project aims to address the critical gap in the pharmaceutical manufacturing industry regarding the outdated quality assurance methods and equipment currently employed in producing compressed pharmaceutical tablets. The primary research objectives are to develop and validate innovative ultrasonic quality assurance and testing equipment that enables rapid, non-destructive, real-time release testing of pharmaceutical tablets. This NSF STTR II project seeks to overcome the limitations of existing manufacturing and quality assurance technologies by employing novel approaches and associated mathematical modeling techniques, including machine learning (ML), to analyze tablet microstructures for quality assurance. The research involves detailed mathematical modeling of the interactions between ultrasonic waves and the viscoelastic properties of tablet materials, leveraging both first-principles physics and ML-based modeling approaches. The anticipated technical results include the development of a reliable, cost-effective solution for the pharmaceutical industry, enhancing the quality assurance process for tablet manufacturing through improved accuracy, efficiency, and scalability. The project represents a significant advancement in the field, supporting the FDAs initiatives towards continuous manufacturing, Quality by Design, and Process Analytical Technology. 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: Erik Pierstorff
The broader impact of this Small Business Technology Transfer (STTR) Phase II project is potentially profound and could offer a transformative approach to quality assurance in pharmaceutical manufacturing that directly targets medicine supply chain vulnerabilities and cost structure in the United States. It aims to modernize the quality testing of the most widely used pharmaceutical dosage formtabletsthrough rapid ultrasonic testing techniques and innovative automation/robotics. This advancement may reduce the risk of quality failures, drug shortages, and recalls, ensuring more reliable access to essential medications for the public. Nearly 70% of Americans rely on prescription drugs, with a significant portion of these medications currently produced overseas. The projects commercial impact is in its potential to redefine quality assurance practices in the pharmaceutical industry, leading to improved efficiency, reduced costs, and enhanced product safety. Such improvements can contribute to national health security by reducing dependence on unreliable foreign drug manufacturing. Its societal benefits include improved healthcare outcomes through more dependable drug availability. Furthermore, the project offers significant educational benefits, providing hands-on training and research opportunities for students in advanced manufacturing technologies. The project focuses on inclusivity, attracting underrepresented groups into engineering, and fostering diversity in advanced research and innovation in pharmaceutical manufacturing. The proposed project aims to address the critical gap in the pharmaceutical manufacturing industry regarding the outdated quality assurance methods and equipment currently employed in producing compressed pharmaceutical tablets. The primary research objectives are to develop and validate innovative ultrasonic quality assurance and testing equipment that enables rapid, non-destructive, real-time release testing of pharmaceutical tablets. This NSF STTR II project seeks to overcome the limitations of existing manufacturing and quality assurance technologies by employing novel approaches and associated mathematical modeling techniques, including machine learning (ML), to analyze tablet microstructures for quality assurance. The research involves detailed mathematical modeling of the interactions between ultrasonic waves and the viscoelastic properties of tablet materials, leveraging both first-principles physics and ML-based modeling approaches. The anticipated technical results include the development of a reliable, cost-effective solution for the pharmaceutical industry, enhancing the quality assurance process for tablet manufacturing through improved accuracy, efficiency, and scalability. The project represents a significant advancement in the field, supporting the FDAs initiatives towards continuous manufacturing, Quality by Design, and Process Analytical Technology. 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: Erik Pierstorff
| Status | Closed |
|---|---|
| Effective start/end date | 09/01/24 → 04/25/25 |
Lead and Sub-Awardee Organization(s)
Funding
- STTR Phase II: $997,734.00
Active Fiscal Year
- FY2024
- FY2025
Start Fiscal Year
- FY2024
TIP Programs
- STTR Phase II
Small Business
- Yes
Key Technology Areas
- Artificial Intelligence
- (confidence score: 91%)
- Biotechnology
- (confidence score: 100%)
- Robotics and Advanced Manufacturing
- (confidence score: 100%)
Technology Foci
- Medical Technology
- (confidence score: 86%)
- Bio-manufacturing
- (confidence score: 100%)
- Advanced Manufacturing (excluding biomanufacturing and semiconductor manufacturing)
- (confidence score: 95%)
- Artificial Intelligence (Broad)
- (confidence score: 100%)
Congressional District at Award
- District n. 21 of New York
Current Congressional District
- District n. 21 of New York
United States
- New York
Core Based Statistical Area (CBSA)
- Massena-Ogdensburg, NY
County
- County: St. Lawrence, NY
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