Alchemab Selected to Access NVIDIA Cambridge-1 Supercomputer to Advance Machine Learning-Based Antibody Discovery

BOSTON & CAMBRIDGE, England–(BUSINESS WIRE)–Alchemab Therapeutics, a biotech company focused on the discovery and development of natural protective antibodies and immune repertoire-based patient stratification tools, has been selected by NVIDIA to harness the power of the world’s most powerful supercomputer of the United Kingdom, Cambridge-1. Alchemab will use the NVIDIA DGX SuperPOD supercomputing cluster, powered by NVIDIA DGX A100 systems, to better understand and better understand its large neurology and oncology datasets.

“We are honored to collaborate with NVIDIA to advance our work in applying machine learning to the prediction of antibody structure and function,” said Douglas A. Treco, PhD, CEO of Alchemab Therapeutics. “By using Cambridge-1, Alchemab will dramatically accelerate our capabilities and we are excited about the opportunity to collaborate with NVIDIA’s world-leading team to better understand the language of antibodies.”

Craig Rhodes, EMEA Industry Leader for Healthcare and Life Sciences at NVIDIA, said, “Cambridge-1 enables the application of machine learning to help solve the most pressing clinical challenges, advance health research through digital biology and enable a better understanding of diseases. The system drives workloads that are scaled and optimized for supercomputing and will help amazing organizations like NVIDIA Inception program member Alchemab continue their research into antibodies and other protective therapies for hard-to-treat diseases.

“Our collaboration with NVIDIA will open up countless opportunities to advance Alchemab’s cutting-edge platform, facilitating the discovery of new therapies and patient stratification techniques,” said Jake Galson, PhD, Chief Technology Officer, Alchemab Therapeutics. . “Machine learning is accelerating research in multiple therapeutic areas and will be key in helping Alchemab predict the function of new antibodies based solely on their sequence.”

An individual’s antibody repertoire encodes information about past immune responses and the potential for future protection against disease. Alchemab believes that deciphering the information stored in these antibody sequence datasets will transform fundamental understanding of disease and enable the discovery of new diagnostics and therapeutic antibodies. Using self-supervised machine learning, Alchemab developed the Antibody-specific Bi-directional Encoder Representation from Transformers (Antibody-specific Bi-directional Encoder Representation from Transformers) antibody-specific language model, a 12-layer transformer model that provides a contextualized digital representation of sequences of ‘antibody. AntiBERTa learns biologically relevant information and is primed for multiple downstream tasks that improve our understanding of antibody language.

Attend Alchemab’s session on Deciphering Antibody Language on March 24 at GTC, a free global AI conference. Find more details about the Nvidia Inception program here. Find project updates and more information about Cambridge-1 projects here.

About Alchemab

Alchemab has developed a highly differentiated platform that enables the identification of novel drug targets, therapies and patient stratification tools through the analysis of patient antibody repertoires. The platform uses well-defined patient samples, deep B-cell sequencing, and computational analysis to identify convergent protective antibody responses in individuals susceptible but resilient to specific diseases.

Alchemab is building a broad pipeline of protective therapies for hard-to-treat diseases, with an initial focus on neurodegenerative diseases and oncology. The highly specialized patient samples that power Alchemab’s platform are made available through valuable partnerships and collaborations with patient representative groups, biobanks, industry partners and academic institutions.

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Sherry J. Basler