Real-World Evidence (RWE) · PopSIM™ In Silico Population Simulation · Multimodal Biomarker Tensors
Real-World Evidence & PopSIM™.
Rescuing stalled clinical trials.
Over 80% of Phase II/III trials in oncology, neurology, and immunology stall due to sluggish recruitment, high screen-failure rates, and unacceptable placebo dropout. DeepSensi™ unites regulatory-grade Real-World Evidence (RWE) with PopSIM™ in silico trial simulation and cohort-scale MASAI Digital Twins, salvaging delayed pipelines and identifying curative responder sub-phenotypes.
Pipeline Protection
The Trial Rescue Engine: Why Promising Molecules Stall
Pediatric & Severe Dropout
In devastating disorders (Dravet, Lennox-Gastaut, refractory IBD, progressive neurodegeneration), caregivers and patients withdraw immediately if randomized to placebo. DeepSensi replaces or augments control cohorts with verified Synthetic Control Arms (SCA), retaining 100% of active participants.
Uncovering Responder Sub-Phenotypes
A breakthrough therapy frequently fails primary statistical endpoints because the trial cohort is biochemically heterogeneous. DeepSensi's multi-system tensor stratifies the population, demonstrating that while the drug scored borderline on the blended cohort, it achieved $p < 0.001$ efficacy in a specific metabolic/microbial sub-phenotype, turning a failed trial into an FDA-approvable targeted indication.
Narrow Eligibility Paralyzing Sites
Sponsors spend millions designing inclusion/exclusion criteria on theoretical assumptions, only to discover that 90% of real-world hospital patients fail screening. PopSIM™ stress-tests protocol parameters against longitudinal real-world cohorts before site activation, optimizing criteria to prevent recruitment collapse.
Pre-Clinical & Phase Optimization
PopSIM™: Running the Trial In Silico Before the First Human Dose
Competitive Pharmacokinetics
Simulating competitive cytochrome P450 inhibition, marrow clearance bottlenecks, and renal burden when the investigational candidate is added to standard-of-care polypharmacy.
Organ Toxicity Trajectory
Forecasting neutropenia nadirs, hepatic transaminase elevations, and mucosal barrier breakdown across diverse patient baselines under varying dose regimens.
NNT & Power Optimization
Computing the Number Needed to Treat (NNT) and statistical power under multiple endpoint definitions, enabling sponsors to right-size sample cohorts and reduce unnecessary burn.
Adaptive Physiology
MASAI Digital Twin: Cohort-Scale Precision Modeling
From Single-Cell to Organ Systems
The MASAI Digital Twin continuously updates each participant's physiological state as new lab results, e-diaries, and sensor streams arrive. It maps the dynamic feedback loops between the gut microbiome, metabolic cascades, cellular respiration, and clinical symptomatology.
FDA Real-World Evidence Program
DeepSensi RWE dossiers adhere to the FDA's Framework for FDA's Real-World Evidence Program and Guidance for Industry: Real-World Data (2023). Data provenance, algorithmic audit trails, and deterministic safety boundaries satisfy regulatory reviewers.
15x-30x CRO Efficiency
By eliminating site bureaucracy, manual monitoring travel, and multi-year recruitment bottlenecks, DeepSensi delivers verified trial datasets in months instead of years, saving sponsors between $15M and $35M per registrational trial.
