R&D organizations are increasingly adopting unified data platforms and AI to enhance research. Credit: Adobe Stock
More R&D-heavy organizations in sectors like biopharma are revamping their data plumbing. One such entity is Moderna, which is expanding its collaboration with Benchling to consolidate fragmented laboratory data into a unified, AI-primed platform. This move addresses an industry gap, as a 2024 Benchling report found that only 14% of large biopharma and a 3% of small companies consider themselves “AI-ready” owing to fragmented data and siloed workflows.
More biopharmas race to unify data with AI-powered platforms
“R&D teams are under constant pressure to move faster and work more efficiently,” said Sajith Wickramasekara, CEO and co-founder of Benchling, in an announcement. Wickramasekara went on to predict that R&D workflows of the future will be “fully digital” and “deeply integrated and built for intelligence and scale.”
FDA embraces genAI for efficiency, too
The Benchling-Moderna news is not isolated. Commissioner Marty Makary last week directed staff to deploy an agency-wide LLM by June 30 after early tests bolstered productivity. Jinzhong (Jin) Liu, a deputy director within Center for Drug Evaluation and Research (CDER) said that the technology could compress some tasks that took days down to minutes.
Other prominent examples within biopharma of this transformation include the likes of Big Pharmas like AstraZeneca and Sanofi, among others. For instance, the firm is fine-tuning its genomics foundation models with Amazon SageMaker. As part of this effort, the company is working to make its scientific data FAIR: Findable, Accessible, Interoperable, and Reusable, a common framework for moving beyond data silos. Similarly, Sanofi has stated its ambition to become “the first pharma company powered by AI at scale.” Incidentally, Sanofi announced plans in 2024 to have more than 1,500 of its scientists across about 30 teams log experiments in Benchling’s R&D cloud. Sanofi is also partnering with OpenAI and Formation Bio to develop bespoke AI-powered software tools.
A cross-industry R&D shift
This overhaul of R&D data infrastructure reaches beyond biopharma. In materials science and chemicals, for instance, BASF announced in 2023 that it was tapping high-performance computing and AI, with integrated experimental and simulation data, to speed discovery of new materials and sustainable processes. In automotive, organizations like BMW Group and Toyota (with NTT) are investing in AI and unified data platforms. In aerospace, firms such as GE Aerospace and Boeing apply data analytics and AI to optimize engine design, predict maintenance needs and tighten quality control. In AgriTech, John Deere, working with DataBricks, runs machine-learning models on combined machinery, sensor and agronomic data to power precision farming and lift crop yields. NASA is also training a 3-billion-parameter transformer, SatVision-TOA, on 100 million MODIS images. This will enable researchers to fill cloud-masked pixels and better analyze features relevant to climate and environmental understanding from 25 years of Earth-observation data.
