ImmunoPrecise Antibodies Ltd. announced a new validation study supporting the generalizability of its proprietary epitope mapping platform, LENSai, powered by IPA's patented HYFT®? technology. The newly released benchmark shows that the platform consistently delivers high predictive performance, even on complexes not used during training.
LENSai Epitope Mapping uses artificial intelligence to pinpoint where antibodies are most likely to attach to disease-related proteins - helping scientists design better treatments faster. Unlike traditional methods that take months and require lab work, LENSai delivers results in hours - using just the digital sequences - cutting timelines, eliminating the need to produce expensive materials, reducing guesswork, and unlocking faster paths to new treatments. In a new benchmark study, LENSai was tested on 30 antibody-protein pairs, 17 of which the platform had never seen before.
Despite having no prior exposure to these molecules, LENSai achieved prediction scores nearly identical to those from its original training data. This score, known as AUC (Area Under the Curve), is a widely accepted measure of accuracy in computational biology. The consistent performance on entirely new, unseen complexes confirms that LENSai's artificial intelligence can reliably analyze and predict antibody binding - even for molecules outside its training set.
This breakthrough demonstrates LENSai's power to generalize across diverse biological structures, making it a valuable tool for accelerating real-world drug discovery. In the new study, LENSai delivered high accuracy results on 17 antibody-protein complexes the platform had never seen before as it did on familiar training examples - proving true generalization, not memorization. Because no new wet-lab work or x-ray structures were required, researchers gain speed, reproducibility, and major cost savings, while freeing scarce lab resources for confirmatory or downstream assays.
With LENSai already embedded in collaborations across big pharma and biotech, ImmunoPrecise is scaling access through secure APIs and custom partnerships. The platform helps researchers compress discovery timelines, reduce risk, and unlock previously unreachable targets - positioning the company and its investors at the forefront of AI-driven antibody therapeutics. For more technical detail and full benchmark results, explore two complementary case studies that illustrate the power and flexibility of LENSai Epitopes Mapping.
The first highlights performance on a "seen" target, where the system was trained on related data. The second - featured in this press release - demonstrates LENSai's breakthrough ability to accurately map binding sites on a completely "unseen" target, with no prior exposure to the antibody, the antigen, or their structure. New Case Study:LENSai Epitope M mapping on an "Unseen" Target.
Previous Case Study:Head-to-Head Benchmark on a "Seen" Target. These examples underscore how LENSai performs both in well-characterized systems and in novel, previously untrained scenarios--validating its generalizability and real-world readiness.
