"Helical's thesis is that bio foundation models, AI systems trained on vast genomic, transcriptomic, and proteomic datasets, have already crossed a quality threshold that makes computational hypothesis-testing meaningful in pharma research."
"What has not kept pace is the layer between a model's output and a scientific decision. In practice, this means bench scientists and ML engineers working in separate environments, teams recreating one-off notebooks for each programme, and analysis that is difficult to reproduce or transfer across disease areas."
Helical, a startup founded by three friends from Luxembourg, has raised $10 million in a seed round led by redalpine. The funding will facilitate expansion in top-20 pharma programs and growth of its science and engineering team. The founders have diverse backgrounds in technology, data science, and medicine. Helical aims to bridge the gap between bio foundation models and practical applications in pharma research, addressing challenges in reproducibility and collaboration among scientists and engineers.
Read at TNW | Startups-Technology
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