Sapio Sciences expands AWS collaboration to enhance science-aware AI capabilities
The laboratory informatics company Sapio Sciences has announced a significant expansion of its partnership with Amazon Web Services (AWS), marking a potential watershed moment in the application of artificial intelligence to drug discovery and development workflows.
The enhanced collaboration centres on the integration of AWS Bedrock into Sapio’s laboratory management platform, providing researchers with secure access to multiple cutting-edge foundational AI models within their existing laboratory information management systems (LIMS) and electronic laboratory notebooks (ELN).
Secure deployment enhances research efficiency
This strategic development builds upon a decade-long relationship between the two organisations, during which AWS has served as Sapio’s preferred cloud provider. The integration promises to deliver several key advantages for research institutions, including natural language interactions with ELNs, AI-powered chatbot integration, automated experiment generation from prompts, and enhanced natural language search capabilities.
The partnership brings together multiple AI foundational models from providers including AI21 Labs, Anthropic, and Stability AI, all accessible within the same secure AWS environment that currently hosts Sapio’s laboratory informatics platform.
Focus on scientific workflow optimisation
Speaking about the collaboration, Sapio Sciences’ founder and CEO, Kevin Cramer, explained the rationale behind the development: “Science-aware AI is specifically designed to simplify the complexities of scientific research and the usage of our LIMS and ELN applications. This next generation of AI systems is seamlessly integrated into our lab informatics platform, empowering scientists to collect, manage, and analyse research data with unprecedented precision.”
Cramer further emphasised the potential impact on research efficiency, noting that the collaboration “will allow Sapio customers to accelerate R&D by harnessing the power of natural language interfaces and AI to free up bench time and to expedite the discovery of viable solutions”.
Implications for life sciences research
The development comes at a crucial time for the life sciences sector, where the integration of AI technologies is increasingly seen as vital for accelerating research outcomes and improving efficiency. Ben Schreiner, Head of Innovation for SMB at AWS, highlighted this significance: “The work conducted in the life sciences and drug discovery industries is some of the most critical research being conducted today and a perfect environment for AI to deliver real value.”
The platform’s no-code/low-code architecture is designed to maintain accessibility whilst providing advanced functionality, potentially democratising access to AI-powered research tools across the life sciences sector. This development could prove particularly valuable for smaller research institutions and laboratories that might otherwise lack the resources to implement sophisticated AI solutions independently.
