Integrated Microfluidic-Mass Spectrometry Platform to Create Big Data for AI in Drug Discovery
Official title: Integrated High-Throughput Microfluidic-Mass Spectrometry for Enhanced Biomedical Data Generation and AI Model Training
Funded at Vivid Bioinnovations, Pbc · NIH-11316567 · Data updated 2026-11-12
A new micro-robotic, ultra-small-volume screening system paired with MALDI-MS imaging will generate enormous chemical reaction data to train AI models for faster drug discovery.
Quick facts
| Grant type | Sbir 2 grant |
|---|---|
| Study type | NIH-funded research |
| Funding institution | Vivid Bioinnovations, Pbc NIH-funded |
| Lab location | 1 site (San Francisco, UNITED STATES) |
| Project start | August 4, 2026 |
| Project end | July 31, 2027 |
| Funding year | 2026 |
| Award (this year) | $300,001 |
| NIH project number | 1R44GM163514-01 |
| Project ID | NIH-11316567 on NIH RePORTER |
Who could benefit from this research
✓Could help
This grant does not enroll patients; it develops data and tools to speed drug discovery that could ultimately benefit patients with various conditions.
✕Less likely to help
direct patient participation is not part of this project.
What this research studies
This project develops a scalable, automated platform that dispenses nanoliter droplets into densely packed nanowell arrays and uses MALDI-MS imaging to capture detailed data on reaction outcomes. The system combines precise on-demand dispensing, dielectrophoretic steering, and controlled incubation to run millions of tiny reactions in parallel. The rich spectral fingerprints produced will feed advanced AI models to predict optimal reaction conditions and accelerate development of new medicines. The work builds on peer-reviewed findings to dramatically reduce reaction volumes and processing time compared with conventional automation.
Why it matters
Potential benefit: If successful, patients could benefit from faster and more cost-effective drug development leading to earlier access to effective therapies.
How similar studies have gone: Previous work shows that micro-scale, automated screening with AI-ready data can substantially shorten drug-development timelines.
Where this research is happening
-
Vivid Bioinnovations, Pbc
San Francisco, United States Active
Researchers
- Principal investigator: Prince, Robin — Vivid Bioinnovations, Pbc
- Study coordinator: Prince, Robin
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About this research
- This is an active NIH-funded research project — typically early-stage science, not a clinical trial accepting patient enrollment.
- Some NIH-funded labs run parallel clinical studies or seek volunteers for related work. To check, contact the principal investigator or institution listed above.
- For full project details, budget, and progress reports, visit the official NIH RePORTER page.