# Chemical instruments-aware distributed blockchain based open AI platform to accelerate drug discovery

> **NIH NIH U18** · PURDUE UNIVERSITY · 2022 · $502,051

## Abstract

PROJECT SUMMARY
Artificial Intelligence (AI) and Automation has the potential to accelerate several stages of the drug discovery
process, including the design-make-test-analyze optimization cycle, typically faced by medicinal chemists.
However, several roadblocks exist resulting in too long timelines to deliver much needed innovation to patients
with unmet needs. Both human and AI face similar limitations mainly due to disjointed steps needed to obtain
and integrate the data that is generated by different organizations or laboratories and cannot be readily shared
without disclosing IP-sensitive information (e.g., non-patented novel chemical structures). In addition, there is
lack of negative (failures) data available publicly, which are critical for generating accurate AI models, but are
typically not made available outside of the originating institution or laboratory due to a variety of reasons related
to IP. And, even among positive results, greater reproducibility of protocols is desirable. A solution to develop a
fully integrated system in-house can be effective but it is hard to scale and not easily adopted mainly due to the
costs and infrastructure involved. Our solution encapsulates the vision of NCATS ASPIRE program of integrating
and automating laboratories to accelerate the drug discovery process while taking into account the above
problems that exist. Blockchain, a distributed ledger technology, coupled with AI and Automation has the
potential to solve all of the above problems as it has done in several other technology sectors, such as finance
and medicine to securely share and learn from data without revealing its identity. We will develop a blockchain
based open science AI framework as a decentralized laboratory cloud for the drug discovery community to
enhance collaboration and reproducibility. This includes decentralized performance of experiments and enabling
efficient multi-party analysis and learning on remote datasets using application programming interface (API) and
graphical user interface (GUI) to engage both computational and experimental scientists. Continuous learning
from measurements and accessible data (with GUI for humans and API for machines) will enable unprecedented
reproducibility. Our decentralized blockchain network will be interfaced across four sites (Purdue, IBRI, IU and
NCATS) in a modular manner that is extendable to large scale to accommodate several thousand laboratories
without affecting efficiency at scale. Our network solution is modular, in that, it works with multiple resources
(instruments, databases) either within one laboratory or across multiple laboratories and organizations. This
distributed blockchain network will enable secure multi-party joint training of AI model on databases at different
locations (cloud instances, IU and NCATS) and schedule experiments with a physical instrument (Purdue) with
data interpretation and secure sharing of results to enhance the efficiency of cross-organizatio...

## Key facts

- **NIH application ID:** 10448092
- **Project number:** 1U18TR004146-01
- **Recipient organization:** PURDUE UNIVERSITY
- **Principal Investigator:** GAURAV CHOPRA
- **Activity code:** U18 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $502,051
- **Award type:** 1
- **Project period:** 2022-07-15 → 2024-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10448092

## Citation

> US National Institutes of Health, RePORTER application 10448092, Chemical instruments-aware distributed blockchain based open AI platform to accelerate drug discovery (1U18TR004146-01). Retrieved via AI Analytics 2026-05-25 from https://api.ai-analytics.org/grant/nih/10448092. Licensed CC0.

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