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

artificial-intelligence
clinical-trials
generative-ai
pharmaceutical

Nr. of Employees

small (1-50)

QuantHealth

Tel Aviv, Tel Aviv, Israel, Asia


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.


Services

Clinical trial simulation platform

Cloud‑based platform to run virtual trials, optimize protocols, and compare design alternatives using patient‑level simulations and curated biomedical data.

Clinical development modules (Indication selection, TPP, PTS)

Modular analyses to predict indication suitability, target product profile parameters, and probability of technical success to inform go/no‑go and design decisions.

Enrollment and market forecasting services

Operational forecasting for site recruitment and market sizing to support feasibility, site selection, and commercial planning.

Business development and asset diligence

Analytics and data packages to support search & evaluation, deep comparative analyses, asset valuation, and out‑licensing decisions.

Portfolio management analytics

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
  • Show More (5)

Key Technologies

  • Clinical simulation engines (patient‑level)
  • Biomedical knowledge graphs
  • Digital twin and digital‑drug modeling
  • Outcome prediction AI models
  • Show More (5)

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