San Francisco, California — [September 25, 2026] — MarWell Bio Inc. today announced that it has been awarded a research contract under the Defense Advanced Research Projects Agency's (DARPA) [Network of Optimal Dynamic Energy Signatures (NODES)] program. As the prime performer, and in collaboration with the Gunner Laboratory at The City College of New York, MarWell Bio is developing advanced computational capabilities to support DARPA's objective of predicting protein function directly from amino acid sequence.
Understanding how proteins acquire biological function remains one of the most significant challenges in modern biology. While recent advances in artificial intelligence have dramatically improved protein structure prediction, accurately predicting how protein sequence gives rise to dynamic behavior and biological function remains one of the next major frontiers in computational biology. Recent peer-reviewed scientific literature has identified sequence-to-function prediction as an emerging frontier, emphasizing that realizing this vision will require integrating artificial intelligence with molecular biophysics, dynamics, energetics, and mechanistic modeling rather than relying solely on static protein structures.
Under the DARPA NODES program, MarWell Bio is developing predictive computational technologies that integrate artificial intelligence, molecular simulation, protein energetics, and high-performance computing to advance prediction of protein function from sequence. Through this research contract, the company is expanding its computational capabilities while contributing to DARPA's technical objectives. These advances also strengthen MarWell Bio's long-term technology platform for predictive biology, protein engineering, and therapeutic discovery, with the potential to accelerate the engineering of next-generation biologics and other protein-based medicines.
"Being awarded a DARPA NODES research contract represents an important milestone for MarWell Bio and provides an opportunity to contribute to one of the defining scientific challenges in computational biology," said Dr. Zara Hemmatian, Founder and Chief Executive Officer of MarWell Bio. "We believe that sequence-to-function prediction represents one of the defining scientific frontiers of our time. Across the biotechnology industry, it is becoming increasingly clear that artificial intelligence alone cannot fully address the complexity of biology. Our vision has always been to integrate AI with first-principles scientific modeling, molecular simulation, and experimental validation to create predictive technologies capable of transforming how proteins are understood, engineered, and ultimately translated into future biomedical and biotechnology applications."
MarWell Bio is collaborating with the Gunner Laboratory at The City College of New York, which contributes expertise in protein electrostatics, biomolecular energetics, and computational modeling to the project.
"This work extends beyond a single research program," added Dr. Hemmatian. "At MarWell, we are building an integrated technology platform for predictive biology that continuously learns from the interplay between computation and experimental validation. The knowledge and computational frameworks advanced through this effort have the potential to accelerate protein engineering, drug discovery, and precision medicine for years to come. We believe that investments in foundational technologies today will help shape the next generation of medicines tomorrow."
About MarWell Bio
MarWell Bio is a biotechnology company building an integrated technology platform for predictive biology, protein engineering, and therapeutic discovery. By combining artificial intelligence, first-principles scientific modeling, molecular simulation, and experimental validation, the company develops predictive technologies that accelerate the discovery and optimization of innovative biologics and precision medicines while helping bridge computation and biology.
About Gunner Laboratory
The Gunner Laboratory at The City College of New York develops computational methods for studying protein electrostatics, protonation states, pH-dependent behavior, and biomolecular energy landscapes. The laboratory contributes expertise in biomolecular energetics and computational modeling to the DARPA NODES project.
Disclaimer: This material is based upon work supported by the Defense Advanced Research Projects Agency (DARPA). Any opinions, findings, conclusions, or recommendations expressed herein are those of the authors and do not necessarily reflect the views of DARPA, the Department of Defense, or the U.S. Government.
