Empowering scientists: delivering AI tools through an ELN framework at the enterprise level

Artificial intelligence (AI) holds immense potential to revolutionize drug discovery, yet its widespread adoption within scientific enterprises faces significant hurdles. Key challenges include ensuring user-friendliness, managing complex workflows, and integrating diverse datasets. To address these issues, we propose a novel framework that leverages the familiar Electronic Lab Notebook (ELN) paradigm. By seamlessly integrating AI workflows as ELN protocols and AI job runs as ELN experiments, our approach provides a user-centric and scalable solution that aligns with established scientific practices. This ELN-based framework, implemented at Sygnature Discovery, adheres to FAIR principles, enhancing data findability, accessibility, interoperability, and reusability. By mirroring the intuitive ELN interface, our solution empowers bench scientists to easily access and utilize cutting-edge AI tools, accelerating drug discovery efforts and maximizing the return on AI investments.