QuantHealth has raised $45 million in Series B funding to scale an ambitious idea: use AI to test clinical trials before drugmakers test them on patients. The round was led by Qumra Capital, with participation from Pitango HealthTech, Sanofi Ventures, Artofin Venture Capital Fund L.P., Bertelsmann Healthcare Investments (BHI), GC Ventures, NewHealth Ventures, Shoni Top Ventures, and Esplanade Ventures.
The funding arrives as pharmaceutical companies search for ways to attack one of drug development’s most stubborn problems. Clinical trials can consume years and enormous amounts of capital, yet most drugs entering clinical development never reach the market. QuantHealth wants drugmakers to learn more about the likely outcome before committing patients, time, and millions of dollars to a trial.
Instead of relying primarily on historical benchmarks and assumptions when designing studies, the Tel Aviv, Israel-based QuantHealth creates AI-powered simulations that let researchers test different trial designs and clinical decisions before patient enrollment begins.
Think of it as a computational test run for a clinical trial.
That distinction matters. AI has attracted billions of dollars into drug discovery, where companies use machine learning to identify targets, predict molecular behavior, and search for potential drug candidates. QuantHealth is applying AI farther down the drug-development pipeline, at the stage where promising science meets the expensive reality of human clinical testing.
With $45M in new funding, Israeli tech startup QuantHealth wants to simulate a clinical trial before the real trial begins
QuantHealth says it has simulated more than 600 clinical trials across 30 indications and has achieved predictive accuracy of up to 90%.
The company plans to extend coverage beyond 40 indications, with oncology, cardiometabolic diseases, and inflammation among its main therapeutic areas.
QuantHealth says its technology combines clinical trial simulation models with large real-world datasets to predict how different patient populations, endpoints, treatment arms, dosing decisions, and other trial parameters could affect an eventual study.
For pharmaceutical companies, the goal isn’t to replace clinical trials. It is to make better decisions about which trials to run and how to design them.
That distinction is significant. Clinical trials exist to establish whether therapies are safe and effective in real patients, and an AI prediction cannot substitute for that evidence. QuantHealth’s bet is that simulation can become an earlier decision layer, helping researchers identify weak trial designs or promising alternatives before millions of dollars have already been committed.
“Today, clinical development decisions are still largely made through real-world iteration—running trials, waiting for results, and adjusting at significant cost and risk. We’re fundamentally changing that model,” said Orr Inbar, CEO and co-founder of QuantHealth. “With our predictive simulations, teams can evaluate clinical and commercial decisions before enrolling a single patient or committing capital. This funding allows us to scale that approach, making simulation a standard step in development and fundamentally improving how drugs are brought to market.”
A costly problem hiding behind every new drug
The economics explain why investors see an opportunity.
More than 90% of drugs entering clinical development eventually fail, according to figures cited by QuantHealth, with roughly 75% of those failures tied to efficacy and safety.
A failed clinical trial can represent years of research, patient recruitment, regulatory work, manufacturing preparation, and investment. Later-stage failures can be particularly painful since companies have already committed substantial resources by the time a drug reaches larger studies.
This creates a compelling use case for predictive software.
A simulation doesn’t have to predict every outcome perfectly to have economic value. If it can reliably help researchers identify a poorly constructed study, select a better patient population, reconsider an endpoint, or abandon an unlikely program earlier, the savings can become substantial.
That is the business case QuantHealth is selling.
The company has worked with 12 of the world’s top 20 pharmaceutical companies, giving it something many AI drug-development startups still lack: adoption among large drugmakers.
From AI drug discovery to AI clinical development
The investment comes amid a broader shift in how the pharmaceutical industry is thinking about artificial intelligence.
Much of the first wave of AI investment in biotech centered on discovery. Startups promised to search huge chemical spaces, identify biological targets, design molecules, and shorten the earliest stages of drug development.
Clinical development presents a different challenge.
A molecule can look promising in a laboratory and still fail once tested across diverse groups of patients. Trial design introduces another set of variables, from eligibility criteria and endpoints to dosing schedules and patient characteristics.
QuantHealth is betting those variables can increasingly be modeled before researchers commit to a real-world study.
“AI has already transformed drug discovery, and clinical trials are the next frontier. It’s a market in which hundreds of billions of dollars are spent annually on clinical trials, and one that is ripe for a smarter, more efficient approach,” said Reut Yehuda Golan, partner at Qumra Capital. “QuantHealth is at a significant inflection point: their technology is mature, the market is ready for change, and the proof points are already there. At Qumra, we invest in companies that transform industries, and QuantHealth is exactly that, a company on its way to defining and leading a massive category, with groundbreaking technology that is already widely adopted across the world’s leading pharmaceutical companies.”
The new funding will go partly into research and development, including new AI models, larger datasets, scientific validation, and broader therapeutic coverage.
QuantHealth plans to grow its workforce to support pharmaceutical customers and extend its products beyond clinical trial design into other parts of the clinical and commercial drug lifecycle, including go-to-market positioning.
That broader strategy could turn the company from a clinical trial simulation vendor into a decision platform spanning several stages of drug development.
Sanofi Ventures returns as an investor
The investor list offers another signal about where QuantHealth sits in the pharmaceutical ecosystem.
Sanofi Ventures, the venture arm associated with pharmaceutical giant Sanofi, participated in the Series B after backing QuantHealth earlier in its development.
“As one of QuantHealth’s earliest investors, we have had the opportunity to watch the company help define an emerging category at the intersection of AI and clinical development,” said Cris De Luca, Partner at Sanofi Ventures. “As the pharmaceutical industry increasingly looks to leverage AI to improve decision-making across the development lifecycle, simulation technologies are becoming an important part of the drug development toolkit. QuantHealth has been an early pioneer in this space, and we look forward to the company’s continued growth and impact across the industry.”
Strategic investment from the pharmaceutical sector carries a different significance from venture funding alone. Large drugmakers are the customers QuantHealth needs to convince if simulation-first clinical development is going to move from an interesting AI application into standard industry practice.
The company says its existing relationships with 12 of the top 20 pharmaceutical companies already give it a foothold.
The harder question is whether predictive simulation can become trusted enough to influence high-stakes decisions involving programs worth hundreds of millions of dollars.
Why QuantHealth’s $45 million raise matters
AI’s next major test in pharmaceuticals may have less to do with discovering more molecules and more to do with figuring out which drugs have the best chance of surviving clinical development.
That’s where QuantHealth is positioning itself.
The company isn’t promising to eliminate clinical trials or predict human biology with certainty. Its opportunity rests on a more practical proposition: give drug developers better information before they make some of their most expensive decisions.
There is still a high bar to clear. Predictive accuracy across hundreds of simulations does not mean every future trial can be forecast with the same precision, and pharmaceutical companies will want extensive validation before allowing AI-generated predictions to influence major clinical programs.
Yet the economics create a strong incentive to try.
If simulation can expose a flawed trial design before hundreds of patients are recruited, the value isn’t simply faster software. It could mean avoiding months or years of work on a study that had a poor chance of succeeding from the start.
QuantHealth’s $45 million Series B gives the company more capital to prove that case.
And if simulation becomes a routine checkpoint before patient enrollment, the biggest change may happen long before anyone enters a clinic: the clinical trial could increasingly begin inside a computer.
