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

点击翻译按钮获取中文摘要

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-organizational and collaborative research. The integrated API and GUI will be developed by utilizing core technology components from the NCATS Information Technology Resource Branch to facilitate transfer and integration with the ASPIRE platform. Collectively, this open-source solution will enhance cycle times to accelerate drug discovery research.