CRO Novalix and the AI drug discovery biotech OpenBench are partnering to deliver an experimentally validated chemical hit series through a fee-for-success model.
The model will work with OpenBench, which will first screen trillions of compounds, identify and synthesise the most promising hits, then pass these candidates to Novalix, which will use its in vitro screening and characterisation capabilities to "surface actionable, meaningful start-of-chemistry for the most challenging targets."
OpenBench will absorb all early-stage financial and scientific risk, pledging to charge a fee only if it delivers validated hits.
The pair say the model can deliver validated chemical hit series on novel targets in as little as six months, removing speculative discovery spending for clients, who can then direct resources towards advancing hits through Novalix's integrated, full-service drug development pipeline.
Why this matters
Traditional high-throughput screening often identifies "hits" that seem effective in vitro but do not engage the intended target under complex physiological conditions.
False positives often arise from nonspecific binding, molecule aggregation, or poor cellular permeability.
Thus, a vast portion of discovery budgets is wasted before a single wet-lab experiment is run.
Industry analysts estimate that around 30-40% of researcher time is taken up by locating, cleaning and validating disconnected datasets rather than executing novel biology.
Drug development costs are also rising in parallel — Deloitte estimated the average cost to progress a single molecule from discovery to market is now around $2.67bn.
This problem of declining R&D productivity and spiralling costs has been named 'Eroom's Law': the number of new drugs approved per billion dollars spent has halved approximately every nine years.
Computer models could help researchers bypass these traditional bottlenecks, replacing slow manual lab work with fast digital predictions that lower costs and shorten timelines.
"Combining OpenBench's AI-powered discovery platform with Novalix's experimental expertise creates a seamless path from computational hit identification to validated starting points," said Denis Zeyer, CEO, Novalix.
Together, we're helping clients accelerate early drug discovery while reducing the scientific and operational challenges of validating new compounds.
"OpenBench is committed to making high-quality hit discovery more accessible through our fee-for-success discovery collaborations," James Yoder, co-founder and CEO of OpenBench, added.
Working with Novalix allows us to connect our AI discovery platform with strong experimental capabilities, enabling clients to advance challenging programmes with greater confidence.
The pair said the new partnership gives life science companies a "direct path to high-quality, developable chemical starting points without the upfront cost and uncertainty" that typically comes with early drug discovery efforts.
