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Infinimmune’s platform bypasses traditional discovery methods by reading antibodies directly from human memory B cells. The core insight is that the immune system has already spent a lifetime selecting and validating the most effective antibodies, providing a superior, de-risked starting point for new human therapeutics.

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To overcome the industry bottleneck of few validated solid tumor targets (15-20), Memo analyzes tumor-infiltrating B-cells from patients with superior outcomes. This approach aims to identify unique antibody-target pairs, unlocking new biological pathways for next-generation therapies like ADCs and CAR-Ts.

The relationship between a multi-specific antibody's design and its function is often non-intuitive. LabGenius's ML platform excels by exploring this complex "fitness landscape" without human bias, identifying high-performing molecules that a rational designer would deem too unconventional or "crazy."

Contrary to the popular belief that antibody development is a bespoke craft, modern methods enable a reproducible, systematic engineering process. This allows for predictable creation of antibodies with specific properties, such as matching affinity for human and animal targets, a feat once considered a "flight of fancy."

T-cell receptor (TCR) therapies offer a significant advantage over monoclonal antibodies by targeting intracellular proteins. They recognize peptides presented on the cell surface, effectively unlocking 90% of the proteome and requiring far fewer target molecules (5-10 copies vs. 1000+) to kill a cancer cell.

Despite initial hype in oncology where business models struggled, cell therapy is finding a major new application in treating autoimmune diseases. By resetting the immune system, it can offer functional cures for debilitating conditions—a powerful and unexpected pivot for the technology platform.

Traditional antibody optimization is a slow, iterative process of improving one property at a time, taking 1-3 years. By using high-throughput data to train machine learning models, companies like A-AlphaBio can now simultaneously optimize for multiple characteristics like affinity, stability, and developability in a single three-month process.

Frustration with traditional antibody discovery, which captures only 1% of a sample's B-cell diversity, led to Memo's microfluidics platform. CEO Erik van den Berg states their technology retains over 80% of the B-cell information, enabling the discovery of rare, super-potent human antibodies that would otherwise be lost.

The company not only identifies targets from its elite patient cohort but also isolates the corresponding T-cell receptors (TCRs). Because these TCRs have been circulating safely in patients for years, they offer a strong starting point for safety. They are also naturally "highly selected," providing significant initial affinity for their targets, which can accelerate development.

Infinitopes' platform uses immunopeptidomics to directly measure peptides on a tumor's surface. This contrasts with competitors like Moderna and BioNTech, who rely on computational predictions from DNA sequencing. This "measure, don't predict" approach aims for more reliable identification of potent immune targets.

Many innovative drug designs fail because they are difficult to manufacture. LabGenius's ML platform avoids this by simultaneously optimizing for both biological function (e.g., potency) and "developability." This allows them to explore unconventional molecular designs without hitting a production wall later.