Institute briefing
AI Drug Discovery: Tempus and Recursion Expand Data Partnership
Tempus and Recursion have expanded their data licensing agreement, granting Tempus access to Recursion's RNA foundation model and continuing Recursion's use of Tempus's oncology data to accelerate AI-driven drug discovery.
What happened
Tempus and Recursion have announced an expansion of their existing data licensing relationship, alongside a new agreement focusing on Recursion's RNA foundation model. This development deepens the collaboration between the two companies, which initially began in 2021. The updated arrangement grants Tempus access to Recursion's advanced RNA foundation model, while Recursion will continue to leverage Tempus's extensive de-identified real-world oncology data. The extended partnership builds on a foundation established through previous collaborations, where Tempus's multimodal data was integrated into Recursion's AI-driven drug discovery platform. The new agreement specifically highlights the application of Recursion's RNA foundation model, suggesting an advanced approach to biological data analysis and drug development.
Why it matters
This collaboration underscores a growing trend in the life sciences sector: the strategic convergence of large-scale biological data with sophisticated AI models. For AI governance and ethics, such partnerships raise important considerations regarding data provenance, privacy, and the responsible application of advanced AI in healthcare. The use of de-identified real-world data, while crucial for research, necessitates robust governance frameworks to ensure ethical handling and prevent re-identification risks. From a business strategy perspective, the agreement illustrates the value of specialised data sets and proprietary AI models as key assets. Companies are increasingly forming alliances to combine these assets, accelerating drug discovery and development pipelines. This approach mitigates individual development costs and risks, while potentially speeding up the delivery of new therapies, but also demands clear intellectual property agreements and equitable benefit sharing.
By the numbers
- 2021: The year the initial data licensing agreement between Tempus and Recursion commenced.
The Institute take
This expanded partnership between Tempus and Recursion exemplifies the increasing reliance on data-driven AI in pharmaceutical research. While the immediate focus is on accelerating drug discovery, the deeper implication for responsible AI lies in how these complex data exchanges are governed.
The true challenge here isn't just the technical integration of data and models, but establishing transparent and auditable frameworks for data usage, model development, and the eventual deployment of AI-derived insights. Leaders must ensure that the pursuit of scientific advancement does not compromise patient privacy or introduce unintended biases into healthcare solutions. A robust ethical oversight committee, with diverse expertise, is crucial from the outset, not as an afterthought.
Briefing notes
Questions this story answers
01What is the nature of the expanded agreement between Tempus and Recursion?+
Tempus and Recursion have expanded their existing data licensing relationship, including a new agreement that provides Tempus with access to Recursion's RNA foundation model, while Recursion continues to utilise Tempus's de-identified real-world oncology data.
02When did the collaboration between Tempus and Recursion originally begin?+
The initial data licensing agreement between Tempus and Recursion commenced in 2021.
03What ethical considerations does this partnership raise for AI governance?+
This partnership highlights ethical considerations for AI governance, particularly concerning data provenance, patient privacy, and the responsible application of advanced AI in healthcare, especially with the use of de-identified real-world data.
04What is the strategic business implication of this collaboration?+
From a business strategy perspective, the agreement demonstrates the value of combining specialised data sets and proprietary AI models to accelerate drug discovery and development, mitigate individual costs, and potentially speed up new therapy delivery.