QuantHealth has unveiled its Large Real-World Drug Model (LRDM v1.0), the world's first clinical trial foundation model capable of simulating patient outcomes using data from over 100 million individuals and billions of therapeutic datapoints. The model is now available on AWS Marketplace, marking a significant advancement in applying AI to clinical trial design and execution.
Unlike most AI applications in pharmaceuticals that focus on drug discovery, QuantHealth's LRDM v1.0 specifically targets the clinical stage of drug development—a phase that consumes more than half of all drug development budgets and where 90% of drug candidates ultimately fail.
"Healthcare generates nearly 30% of the world's data—about 138 billion gigabytes per day—but leveraging this at scale for actionable insight has been a monumental challenge," said Orr Inbar, CEO and Co-Founder of QuantHealth. "We've invested over $10 million in R&D over four years to overcome this barrier through systems biology, novel AI architectures, and high-performance computing."
Technical Capabilities and Architecture
LRDM v1.0 employs an end-to-end transformer architecture that enables high-fidelity simulations to predict patient response to treatment across entire clinical trials. The model is trained on 100 million patients, 30 billion drug-patient pairs, and contains 138 million parameters—approximately 100 times larger than its predecessor while leveraging 500 times more data.
Eran Barash, Head of Machine Learning and Artificial Intelligence at QuantHealth, explained: "LRDM v1.0 can capture clinical patterns at a much greater temporal resolution and reason about drug mechanisms at a far greater depth. Furthermore, LRDM v1.0's AI architecture unlocks transfer learning, enabling generalization from large populations to rare diseases and small subpopulations."
Unlike traditional language-based models (LLMs), the foundation model is systems-biology-based, leveraging large biomedical knowledge graphs and extensive patient databases. This approach allows it to process complex healthcare data with greater accuracy and relevance to clinical applications.
Clinical Applications and Impact
The model supports critical decision-making processes in clinical trials, including:
- Go/no-go evaluations for trial progression
- Cohort optimization to identify ideal patient populations
- Drug repurposing opportunities
- Precision trial design
- Accelerated patient accrual
These capabilities directly address the pharmaceutical industry's most significant challenges: high failure rates, lengthy development timelines, and substantial financial waste. With 90% of drugs failing in the clinical stage, representing a direct $45 billion annual waste to pharmaceutical companies, QuantHealth's technology offers a potential solution to improve success rates and reduce costs.
Industry Adoption and Availability
QuantHealth currently works with eight of the top twenty pharmaceutical companies, supporting dozens of trials annually across all phases. The company's solutions span multiple therapeutic areas, including oncology, cardiovascular, and autoimmune diseases, and work with various modalities including biologics, small molecules, and cell and gene therapies.
"The collaboration between AWS and QuantHealth will further enable pharma companies to leverage clinical foundation models for their use cases, increasing the fidelity of their clinical programs and improving the probability of success in clinical trials," said Dan Sheeran, general manager, Health Care and Life Sciences, AWS.
Pharmaceutical companies can access QuantHealth's technologies through self-service simulation workflows, model APIs, and now through the AWS Marketplace. The company plans to announce future iterations of the model rapidly as it increases its data, size, and clinical performance.
Future Implications for Drug Development
The introduction of LRDM v1.0 represents a potential paradigm shift in how clinical trials are designed and executed. By enabling data-driven simulation and optimization of trial design, the technology could dramatically improve success rates, reduce costly mistakes, and accelerate the path from molecule to market.
As precision medicine continues to advance and therapies become more complex, the deep modeling capabilities offered by QuantHealth's foundation model may become increasingly crucial to advancing patient care and pharmaceutical innovation.
The company's approach addresses the clinical trial process at its core, potentially transforming one of the most challenging and expensive aspects of bringing new treatments to patients.
