MindWalk Screens 890,634 Antibody Sequences for Immune Risk in Under Five Hours
New white paper shows LensAI™ immunogenicity screening running at up to 43% lower cost per sequence on Amazon EC2 Hpc8a instances powered by AMD EPYC processors, making a critical drug-safety check practical at the scale AI-driven discovery now demands
AUSTIN, Texas, October 21, 2026--MindWalk Holdings Corp. ("MindWalk") (NASDAQ: HYFT), a Bio-Native AI company, today published a white paper showing that its LensAI™ immunogenicity screening ran across an entire public antibody database of 890,634 sequences in 4 hours and 41 minutes on Amazon EC2 Hpc8a instances powered by 5th Gen AMD EPYC™ processors, delivering up to 43% lower cost per sequence than a comparable Intel configuration running identical code.
"Every antibody drug carries a question: will the patient's own immune system attack it," said Dr. Jennifer Bath, President and Chief Executive Officer of MindWalk. "Answering that question late is one of the most expensive failures in this industry. Answering it early has been impractical, because AI now designs candidates far faster than anyone could screen them. This work shows LensAI screening all of them. Candidate selection and safety assessment are no longer the bottleneck. It also lowers what it costs us to deliver at this scale, so we can take on more volume without our costs rising in step with it."
The problem the paper addresses
When the body treats a therapeutic antibody as foreign, it produces anti-drug antibodies. These can blunt the drug's effect, change how it moves through the body, and raise safety concerns. Discovering that risk in late-stage development can delay or end a program after years of investment. Regulators increasingly expect the risk to be assessed at the start of discovery instead.
The obstacle has been volume. Modern AI design methods generate thousands of candidate molecules, and a single antibody heavy chain expands into 2,420 variants under a routine single-point mutation scan. Checking all of them has been too slow and too expensive to be part of everyday work.
What the benchmark measured
The paper reports LensAI immunogenicity screening run on three cloud configurations with no code changes between them, repeated five times and averaged.
On the identical workload, Amazon EC2 Hpc8a instances delivered 37% faster performance and approximately 43% lower cost per sequence compared with an Amazon EC2 C8i instance powered by Intel® Xeon® processors. A compute-optimized Amazon EC2 C8a configuration delivered 35% faster performance and approximately 29% lower cost per sequence.