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MIT and Recursion Release Boltz-2: Next Generation AI Model to Predict Binding Affinity at Unprecedented Speed, Scale, and Accuracy

Key Takeaway: MIT and Recursion have launched Boltz-2, an advanced AI model designed to predict biomolecular binding affinities with unprecedented speed and accuracy. This open-source model significantly reduces the time and cost associated with drug discovery, allowing researchers to focus on promising compounds more effectively. Boltz-2's capabilities position it as a leading tool in the field, surpassing previous models.
Price reaction · baseline $4.91 (2025-06-06T13:59:00.000Z) · hit during market hours · 1 other RXRX headline(s) in the window, move may be shared
day 0 close · peak
+11.8%
day 1
+9.4%
day 3
+10%

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POSITIVE FACTORS

  • Boltz-2 achieves best-in-class accuracy in binding affinity predictions.
  • The model operates at speeds up to 1000x faster than traditional methods.
  • Open-source availability allows for widespread adaptation and use.
  • Collaboration between MIT and Recursion enhances drug discovery capabilities.

BiopharmaWatch Analysis

From our catalyst data and publicly available data · not financial advice
Best trade, last catalyst
+65%
120-day peak, hindsight
Typical move
3.8%
average across 3 past catalysts
Cash runway
~15 mo
Low dilution risk
Lead asset
REC-994
Phase 2 · Cerebral Cavernous Malformation

Full Press Release Details

Salt Lake City, UT, June 06, 2025 (GLOBE NEWSWIRE) -- Researchers at the Massachusetts Institute of Technology (MIT) Computer Science and Artificial Intelligence Lab (CSAIL) and Jameel Clinic, alongside TechBio company Recursion (NASDAQ: RXRX), today announced the open-source release of Boltz-2, a first of its kind biomolecular foundation model. Powered by Recursion's NVIDIA supercomputer for its training and validation, this next-generation AI model achieves best-in-class accuracy in jointly modeling complex structures and binding affinities. Boltz-2 represents the next step beyond existing biomolecular structure prediction models like AlphaFold3 and its predecessor, Boltz-1.
“Accurately predicting how strongly molecules bind has been a long-standing challenge in drug discovery—one that required novel machine learning and computer science techniques to address,” said Regina Barzilay, MIT School of Engineering Distinguished Professor for AI and Health, AI faculty lead at Jameel Clinic and CSAIL principal investigator. “Boltz-2 not only addresses this crucial problem but also helps scientists uncover new biological insights and ask questions they couldn't before with standard approaches that are more computationally intensive. Because Boltz-2 is open-source, including its training code, scientists can easily adapt it for specific types of molecules, making it even more powerful as a tool to accelerate discovery."
Specifically, Boltz-2 marks a new era forin silicoscreening, in standard benchmarks approaching the accuracy of physics-based free energy perturbation (FEP), an industry-standard computational method used to predict the binding affinity of molecules, atspeeds up to1000x faster. The decrease in cost and increase in speed and scale makes large-scale and accurate virtual screening more practical than previously possible, directly addressing a critical bottleneck in small molecule discovery.
"Selecting the right molecules early is one of the most fundamental challenges in drug discovery, with implications for whether R&D programs succeed or fail," said Najat Khan, Chief R&D Officer and Chief Commercial Officer at Recursion. “By predicting both molecular structure and binding affinity simultaneously with unprecedented speed and scale, Boltz-2 gives R&D teams a powerful tool to triage more effectively and focus resources on the most promising compounds. Collaborations like this, bridging academic innovation and industry application, play an important role in advancing the field and, ultimately, improving how we develop and deliver medicines for patients."
Below are key components and differentiators of Boltz-2 vs other methods of predicting biomolecular structures and affinities:
In line with MIT and Recursion’s commitment to making AI tools accessible for drug developers,Boltz-2 will be open-sourced under an MIT license, making the model, weights, and training pipeline available for both academic and commercial use.
Boltz-2’s development was led by the Boltz team at MIT under the supervision of Professors Regina Barzilay and Tommi Jaakkola alongside a team of researchers from MIT and Recursion. For more information, visit:https://boltz.bio/boltz2.
About RecursionRecursion (NASDAQ: RXRX) is a clinical stage TechBio company leading the space by decoding biology to radically improve lives. Enabling its mission is the Recursion OS, a platform built across diverse technologies that continuously generate one of the world’s largest proprietary biological and chemical datasets. Recursion leverages sophisticated machine-learning algorithms to distill from its dataset a collection of trillions of searchable relationships across biology and chemistry unconstrained by human bias. By commanding massive experimental scale — up to millions of wet lab experiments weekly — and massive computational scale — owning and operating one of the most powerful supercomputers in the world, Recursion is uniting technology, biology and chemistry to advance the future of medicine.
Recursion is headquartered in Salt Lake City, where it is a founding member of BioHive, the Utah life sciences industry collective. Recursion also has offices in Toronto, Montréal, New York, London, Oxford area, and the San Francisco Bay area. Learn more atwww.Recursion.com, or connect onX (formerly Twitter)and LinkedIn.

Frequently Asked Questions

What is Boltz-2?

Boltz-2 is an advanced AI model developed by MIT and Recursion for predicting biomolecular binding affinities.

How fast is Boltz-2 compared to traditional methods?

Boltz-2 operates at speeds up to 1000x faster than standard computational methods.

Is Boltz-2 open-source?

Yes, Boltz-2 is open-sourced under an MIT license, allowing for widespread adaptation.

What are the benefits of using Boltz-2?

Boltz-2 enhances drug discovery by accurately predicting molecular structures and affinities efficiently.

Who developed Boltz-2?

Boltz-2 was developed by researchers at MIT's CSAIL and Recursion.

Last updated: Jun 6, 2025