In a recent unveiling at the Single-Domain Antibodies 2023 Meeting, LabGenius, a forerunner in harnessing machine learning for antibody discovery, showcased compelling data from their innovative antibody discovery platform. The results highlighted a series of optimized NANOBODY^® candidates that not only met the collaboration's pre-set success benchmarks but also retained commendable production attributes.

Maria Wendt, Sanofi’s Global Head of Digital and Biologics Strategy and Innovation, commented on the breakthrough, “LabGenius successfully delivered an exciting and innovative example of NANOBODY optimization using ML. This perfectly complements Sanofi’s Large Molecule Research strategy to infuse all aspects of biologics discovery and development with the latest in computation and AI.”

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Rewinding to 2021, LabGenius and pharmaceutical giant Sanofi embarked on a multi-year alliance. This partnership sought to merge LabGenius' prowess in machine learning, robotic automation, and synthetic biology with Sanofi's seasoned expertise in the therapeutic crafting of NANOBODY heavy chain variable domains.

“Lead optimization remains a pivotal phase in antibody discovery. The results we've observed underscore our platform's capability to expedite the creation of molecules bearing distinct and crucial attributes,” noted Dr. Gino Van Heeke, LabGenius’ Chief Scientific Officer.

Fast forward ahead, and the recently released data by LabGenius was nothing short of promising. The top 10 enhanced NANOBODY variants exhibited a staggering 7-fold augmentation in the targeted property without compromising the potency of the original molecule. Notably, all these variants were efficiently expressed in Escherichia coli and displayed a minimal inclination towards aggregation. A deeper dive into mutational analysis unveiled that each variant bore distinct sets of non-obvious mutations, which were instrumental in their performance.

Dr. James Field, the visionary Founder and CEO of LabGenius, expressed his satisfaction, noting, “We’re delighted with the outcome of this research collaboration. These results further validate our platform’s unique capabilities, and we believe that continued efforts in this area will ultimately translate into a positive outcome for patients.”