Orr Inbar
CEO
QuantHealth
QuantHealth provides next-generation clinical AI for drug-patient simulations to guide clinical development decisions. The platform integrates biomedical, clinical, and epidemiological data into a unified framework for deep analysis. This enables optimization across clinical development, business development, and portfolio management use cases.
Updated 7 months ago
Funding
Raised to date
$2MRaised to date based on public sources. This may differ from the amount the company actually raised and is based only on what is publicly available on the internet.
Funding rounds are not available yet.
Founders
Product
Problem
The pharmaceutical industry faces significant challenges in accurately predicting patient responses to novel therapies, leading to inefficient clinical trial design, suboptimal asset valuation, and increased development costs. Traditional methods often lack the granularity to capture the complex interplay of biological factors and individual patient variability.
Solution
QuantHealth provides an AI-driven clinical simulation platform designed to predict patient responses to therapies, thereby optimizing drug development processes. The platform integrates multi-modal data, including biomedical information, clinical trial results, and epidemiological data, to construct detailed patient simulations. These simulations enable data-driven decision-making across clinical development, business development, and portfolio management functions. By offering predictive insights into trial outcomes and asset potential, QuantHealth facilitates more efficient trial design and more accurate asset valuation.
Target Audience
The primary customers are pharmaceutical and biotechnology companies, including teams involved in clinical development, business development, and portfolio management.
Features
- AI-powered simulation engine for predicting patient responses to diverse therapeutic interventions.
- Integrated data framework combining biomedical knowledge graphs, curated clinical trial data, and real-world epidemiological data.
- Multi-modal data ingestion capabilities, supporting over 100,000 drug entities and data from over 350 million lives.
- Modules for protocol optimization, including simulation of inclusion/exclusion criteria, treatment arms, and endpoints.
- Capabilities for indication selection, Target Product Profile (TPP) prediction, and Probability of Technical Success (PTS) assessment.
- Tools for market forecasting and enrollment prediction, leveraging historical data and protocol parameters.
- Business development modules for asset search and evaluation, comparative analysis, diligence, valuation, and out-licensing.
- Portfolio management features for asset prioritization, synergy analysis, and identification of strategic gaps.
- Prospectively validated simulation models demonstrating an 85% accuracy rate on primary endpoints.