QuantHealth Platform

QuantHealth is an AI-powered platform designed to simulate clinical trials with pinpoint accuracy, enabling end-to-end decision-making across the full spectrum of clinical development. Built on next-generation clinical AI technologies, the platform is purpose-built for pharmaceutical sponsors, business development teams, and portfolio managers seeking to accelerate drug development and reduce the risks associated with bringing new therapies to market.

The platform has been prospectively validated, demonstrating 85% accuracy in predicting trial primary endpoints before readout — and without requiring sponsor data. With over 350 trials simulated across more than 45 diseases, and data assets encompassing more than 10,000 data points per patient and over 100,000 drug and mechanism data points, QuantHealth's clinical simulation engine operates at a scale that supports meaningful, evidence-based decisions across the drug development lifecycle.

Clinical Development Use Cases

• Protocol Optimization: Refine trial designs to improve the probability of success before committing resources.
• Indication Selection: Identify the most promising indications for a given asset using AI-driven simulation.
• Target Product Profile (TPP): Define and evaluate the desired clinical profile of a drug candidate.
• Probability of Technical Success (PTS): Quantify the likelihood of achieving clinical endpoints.
• Market Forecasting: Project commercial potential based on simulated clinical outcomes.
• Enrollment Prediction: Anticipate patient enrollment rates to improve trial planning and timelines.

Business Development Use Cases

• Search and Evaluation (Many to Few): Rapidly screen a broad landscape of assets to identify the most promising candidates.
• Comparative Deep Dive (Few to One): Conduct rigorous head-to-head comparisons of shortlisted assets.
• Asset Diligence and Valuation: Support due diligence processes with AI-generated clinical evidence and risk assessments.
• Asset Out-licensing and Disposition: Inform decisions around licensing and asset disposition with simulation-backed insights.

Portfolio Management Use Cases

• Asset Prioritization: Rank pipeline assets based on simulated clinical and commercial potential.
• Asset Synergy and Overlap: Identify where assets within a portfolio complement or compete with one another.
• Gaps and Opportunities: Uncover unmet needs and strategic opportunities across the portfolio.

Prospective Validation and Platform Scale

• Validated across multiple high-profile trials, including IMVOKE010 (a randomized Phase III study of atezolizumab as adjuvant monotherapy in squamous cell carcinoma of the head and neck), TROPION-Breast01, and ELOQUENT1.
• Simulations are performed prospectively — predicting results before trial readout and without access to sponsor data.
• 85% accuracy on primary endpoint prediction across a validated trial set.
• Over 350 trials simulated spanning more than 45 disease areas.
• More than 10,000 data points per patient and over 100,000 drug and mechanism data points inform the underlying models.
• Platform insights have relevance to decisions affecting an estimated 350 million lives.

QuantHealth supports sponsors from early clinical development through to regulatory approval, providing a unified AI platform that connects clinical, business development, and portfolio management functions. Teams looking to explore the platform's capabilities can request a demo or book a meeting directly with the QuantHealth team.