Helical raises $10M to turn bio foundation models into production drug discovery systems

Helical closes $10M seed to turn bio foundation models into systems

The Luxembourg-founded startup is already in production with multiple top-20 global pharma companies, including a public collaboration with Pfizer. Its $10M seed round is led by redalpine, with the CEOs of Cohere and HuggingFace among the angel investors. Helical, a London-based pharma AI startup founded by three Luxembourgish childhood friends, has raised $10 million in a seed round led by redalpine, with participation from Gradient, BoxGroup, and Frst. Notable angel investors include Aidan Gomez, CEO of Cohere; Clément Delangue, CEO of HuggingFace; and Mario Goetze, a professional footballer. The funding will support expansion across more top-20 pharma programmes and growth of Helical's deployed science and engineering team. The company was founded by Rick Schneider, Maxime Allard, and Mathieu Klop, three school friends who took divergent paths into the same problem. Schneider built technology at Amazon before helping the German enterprise software company Celonis scale operations in France and Japan. Allard led data science teams at IBM before pursuing a PhD focused on reinforcement learning and robotics. Klop became a cardiologist and genomics researcher. When biological foundation models began emerging, the trio identified the same gap: models capable of transforming how pharma discovers drugs were arriving faster than the application infrastructure needed to make them usable at scale. 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 builds the infrastructure that closes that gap. Its platform has two surfaces: a Virtual Lab for biologists and translational scientists, and a Model Factory for ML engineers and data scientists, both running on shared data and models to produce consistent, auditable results. The company is already in production with multiple top-20 global pharma companies. Its publicly disclosed collaborations include work with Pfizer on predictive blood-based safety biomarkers, and with Tanabe Pharma America on AI-driven target discovery for neurodegenerative diseases including ALS. Across those deployments, Helical says teams have compressed discovery timelines from years to weeks. The broader industry context gives the ambition some scale: global pharma R&D spending exceeds $300 billion annually, bringing a single drug to market costs more than $2 billion on average, timelines stretch beyond a decade, and more than 90% of candidates entering clinical trials fail to reach approval.

Helical raises $10M to bridge the gap between foundation models and drug discovery decisions - SiliconANGLE

Helical raises $10M to bridge the gap between foundation models and drug discovery decisions Pharma artificial intelligence startup Helical Ltd. announced today that it has raised $10 million in new funding to expand its virtual AI lab platform, which turns biological foundation models into reproducible in-silico drug discovery workflows. Founded in 2024, Helical was built around a specific gap its founders identified as biological foundation models have gained traction in pharma. Biological foundation models are large AI systems trained on vast datasets of genomic, proteomic and other molecular data that can predict how biological systems behave, much as large language models predict text. The gap, as found by Helical's founders, is one whereby, as teams were excited about the model layer, they nonetheless struggled to turn computational outputs into decisions scientists could trust, reproduce and defend. Experiments lived in one-off notebooks, and bench scientists and machine learning engineers worked in separate environments, meaning that results rarely transferred cleanly across programs. Helical addresses that gap with an application layer that turns powerful models into systems scientists can run, trust and defend. Pitched as "the virtual AI lab for pharma," Helical's platform offers two product surfaces built on shared data and shared models: a Virtual Lab designed for biologists and translational scientists and The Model Factory, which serves machine learning engineers and data scientists. By putting both functions in the same system, the company aims to close the gap between computational predictions and biological decision-making. The three co-founders came to the problem from different directions. Rick Schneider built technology at Amazon.com Inc. and later helped German enterprise software company Celonis SE scale operations in France and Japan. Maxime Allard led data science teams at IBM Corp. before pursuing a doctorate focused on reinforcement learning and robotics. Mathieu Klop was a cardiologist and genomics researcher. When bio foundation models emerged, the trio saw the chance to build the missing application layer that would let pharma teams move from model experimentation to reproducible, production discovery. "The models alone don't discover drugs. The system does," said Schneider. "Pharma teams need a system that turns foundation models into workflows scientists can run, validate and defend." Helical is already in production with multiple top global pharma companies, including a public collaboration with Pfizer Inc. on predictive blood-based safety biomarkers. The company claims teams have compressed discovery timelines from years to weeks across deployments in target identification, biomarker discovery and therapeutic design. The seed funding round was led by Redalpine Venture Partners AG. Gradient, BoxGroup Ventures, Frst Capital and individual investors including Cohere Inc. CEO Aidan Gomez, Hugging Face CEO Clement Delangue and professional soccer player Mario Goetze also participated. "We are at a unique point in time where biological foundation models and general language reasoning models are converging" said Daniel Graf, general partner at Redalpine. "We backed Helical because we strongly believe they have what it takes to build the pharma AI orchestration platform that will drive this transition from siloed AI models to integrated virtual AI labs."