QuantHealth
QuantHealth develops a clinical‑simulation platform that uses large‑scale real‑world data and AI to simulate patient‑level responses to therapies. The platform integrates multi‑modal biomedical and clinical data, a drug–biology knowledge graph, and outcome‑prediction models to support protocol design, enrollment forecasting, indication selection, portfolio prioritization, and business‑development analyses. The company reports prospective validation across numerous simulated trials and has published press about a large pharmaco‑clinical foundation model.
Industries
Nr. of Employees
small (1-50)
Products
Pharmaco‑clinical foundation model (large real‑world drug model)
A large foundation model that combines real‑world patient data and drug/mechanism data to represent drugs and predict patient responses at scale for in‑silico clinical simulations.
Pharmaco‑clinical foundation model (large real‑world drug model)
A large foundation model that combines real‑world patient data and drug/mechanism data to represent drugs and predict patient responses at scale for in‑silico clinical simulations.
Services
Cloud‑based platform to run virtual trials, optimize protocols, and compare design alternatives using patient‑level simulations and curated biomedical data.
Modular analyses to predict indication suitability, target product profile parameters, and probability of technical success to inform go/no‑go and design decisions.
Operational forecasting for site recruitment and market sizing to support feasibility, site selection, and commercial planning.
Analytics and data packages to support search & evaluation, deep comparative analyses, asset valuation, and out‑licensing decisions.
Tools to prioritize assets, assess inter‑asset synergy/overlap, and identify portfolio gaps using simulated study outputs and commercial metrics.
Cloud‑based platform to run virtual trials, optimize protocols, and compare design alternatives using patient‑level simulations and curated biomedical data.
Modular analyses to predict indication suitability, target product profile parameters, and probability of technical success to inform go/no‑go and design decisions.
Operational forecasting for site recruitment and market sizing to support feasibility, site selection, and commercial planning.
Analytics and data packages to support search & evaluation, deep comparative analyses, asset valuation, and out‑licensing decisions.
Tools to prioritize assets, assess inter‑asset synergy/overlap, and identify portfolio gaps using simulated study outputs and commercial metrics.
Expertise Areas
- Clinical trial simulation and design
- Clinical development optimization
- Real‑world data analytics
- Pharmacology and mechanism mapping
Key Technologies
- Clinical simulation engines (patient‑level)
- Biomedical knowledge graphs
- Digital twin and digital‑drug modeling
- Outcome prediction AI models
News & Updates
Participation planned at ESMO 2025 (oncology conference).
Announcement of a large real‑world drug model (LRDM v1.0) described as a pharmaco‑clinical foundation model capable of processing >100 million patients in a single simulation.
Coverage discussing the role of AI simulations in clinical trials.
Report on a funding round to support US expansion and platform development.
Coverage of a strategic investment from a major professional services firm to support the platform.
Reported prospective prediction accuracy of approximately 85% for primary endpoints across simulated trials.
Participation planned at ESMO 2025 (oncology conference).
Announcement of a large real‑world drug model (LRDM v1.0) described as a pharmaco‑clinical foundation model capable of processing >100 million patients in a single simulation.
Coverage discussing the role of AI simulations in clinical trials.
Report on a funding round to support US expansion and platform development.
Coverage of a strategic investment from a major professional services firm to support the platform.
Reported prospective prediction accuracy of approximately 85% for primary endpoints across simulated trials.