Helical, a virtual AI lab focused on pharmaceutical applications, has secured a US$10 million seed round led by redalpine. The funding round saw participation from Gradient, BoxGroup, Frst, and notable angel investors including Aidan Gomez, CEO of Cohere, Clement Delangue, CEO of HuggingFace, and footballer Mario Goetze.
Helical aims to transform biological foundation models into decision-ready, reproducible in-silico discovery workflows. The newly acquired funds will facilitate the company’s expansion across additional top-20 pharmaceutical programs and bolster its science engineering team.
“The models alone don’t discover drugs. The system does,” stated Rick Schneider, co-founder of Helical. He emphasized that pharmaceutical teams require a cohesive system that converts foundational models into workflows that scientists can run, validate, and defend. “We built Helical to make in-silico science reproducible at pharma scale, so teams can go from hypothesis to decision in days instead of months,” Schneider added.
The pharmaceutical industry grapples with a paradox: an abundance of innovative ideas exists, yet the industry faces a bottleneck in drug development. Approximately 50 new drugs receive approval each year, despite the fact that over 10,000 diseases are known, with many hypotheses stalled by the slow, costly nature of physical experimentation.
Helical addresses this issue by leveraging biological foundation models, allowing scientists to test hypotheses computationally before moving to the wet lab. This shift is crucial as many pharmaceutical teams experience fragmentation between model outputs and scientific decisions, often resulting in isolated efforts that lack reproducibility across different programs.
“Pharma teams are excited about the model layer, but many efforts stall because the work between a model output and a scientific decision is still fragmented,” Schneider explained. With new architectures constantly emerging, the collaboration between bench scientists and machine learning (ML) engineers often remains inefficient, leading to the creation of one-off notebooks and analyses that are hard to replicate.
Helical’s platform is designed to bridge this gap, featuring two main components: the Virtual Lab for biologists and translational scientists, and the Model Factory for ML engineers and data scientists. Both components operate on the same data, models, and results, facilitating a unified system where teams traditionally siloed can collaborate effectively.
“We are at a unique point in time where biological foundation models and general language reasoning models are converging,” noted Daniel Graf, General Partner at redalpine. He expressed confidence in Helical’s potential to create an orchestration platform that would facilitate a transition from isolated AI models to integrated virtual AI labs.
Looking ahead, Helical plans to deepen its deployments across various therapeutic areas and programs with existing clients while also aiming to expand its reach within other top-20 pharmaceutical organizations. The company is focused on building a compounding evidence layer to enhance performance across diseases. Its overarching mission is to enable every scientist to test hypotheses at the speed of inference, turning in-silico discovery into a robust engine for R&D throughput.
See also
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