InSilicoTrials

InSilicoTrials is an end-to-end in silico platform purpose-built for science-backed drug development, operating at the intersection of scientific innovation and regulatory standards. The platform serves pharmaceutical and biotech organizations across preclinical, clinical, and post-approval stages, helping teams make earlier, safer decisions with reduced time, cost, and risk. InSilicoTrials integrates mechanistic models, AI, digital twins, synthetic data, and operations forecasting into a unified continuous optimization loop, and has co-authored guidance with the U.S. FDA — including contributions toward Good Simulation Practice frameworks — while maintaining compliance with FDA and EMA standards.

By decreasing reliance on in vivo studies and early human exposure, InSilicoTrials aligns with FDA initiatives encouraging alternatives to traditional animal testing. The platform has demonstrated substantial time and cost savings across a range of use cases, including preclinical mAb optimization (12–30 months; $15–30M saved), biosimilarity confirmation (1–2 years; $10–30M), Phase 3 ADC optimization (6–18 months; $20–50M), long-term MS strategy (3–5 years; $50–150M), rare disease trials (1–2 years; $10–40M), and in-licensing business development with RWE and synthetic trials (6–9 months; $5–20M in risk avoidance).

Core Platform Modules

• Scientific Platform: Enables clinical trial simulation including synthetic patient generation and scenario comparisons across dosing, sample size, inclusion/exclusion criteria, adaptive designs, and statistical methods. Includes a Model Library, Data Library, Data Integrator, Workflow Builder, Clinical Trial Simulator, and Output Dashboard. Supports safety, efficacy, biomarkers, disease progression, QSP, multi-omics, in vitro/in vivo, and AI/ML models.
• Operations Platform: Provides simulation capabilities for clinical trial operations, including synthetic patient generation and scenario comparisons for dosing, sample size, I/E criteria, adaptive designs, and statistical methods, supported by the same core toolset as the Scientific Platform.
• IRIS — Multi-Agentic Simulation Workflow Orchestration: An AI-powered orchestration layer built on a multi-agent architecture that connects internal tools, internal information, external information sources, and the simulation platform. IRIS searches external sources such as clinicaltrials.gov to suggest clinical trial designs, interprets data, makes recommendations, analyzes simulation results, and independently launches new simulations based on retrieved information and user preferences.

Flagship Use Cases

• In Silico Antibody Optimization (Preclinical mAb): Using AI-assisted Target-Mediated Drug Disposition (TMDD) modeling, simulation of clearance, affinity, and dosing frequency scenarios, and virtual patient simulations, InSilicoTrials identified an optimized antibody variant with improved affinity, reduced clearance, and stronger target suppression — accelerating preclinical optimization, reducing in vivo study reliance, and increasing confidence before first-in-human studies.
• ALS Synthetic Control Arm (Phase II, Rare Disease): Addressing the challenge of ultra-small patient populations in ALS trials, the platform applied ML-based disease progression modeling, synthetic control arm generation, and causal inference to augment the control arm with 60 synthetic patients. This increased statistical power, reduced the number of patients assigned to placebo, improved trial feasibility, and enabled faster go/no-go decisions — saving an estimated 1–2 years and $10–40M.
• Oncology Phase 3 ADC Digital Twin Optimization: For a large pharma organization optimizing dosing strategy for an antibody-drug conjugate, InSilicoTrials applied QSP digital twins, PK/PD modeling, tumor growth and safety modeling, and probability-of-success simulation to balance exposure, tumor control, and thrombocytopenia risk — delivering savings of 6–18 months and up to $50M.

Recognition and Awards

• ARPA-H CATALYST — CARDIOVERSE digital-twin program participant
• FDA GenAI Precision Challenge — Top 5 Winner
• EU Virtual Human Twin initiative participant
• London AI Summit Winner
• Grind AI Startup of the Year Winner

InSilicoTrials provides a unified data integration framework powering multi-modal data at global scale, making advanced simulation and AI-driven drug development accessible to organizations seeking to de-risk every stage from preclinical research through post-approval — democratizing the use of simulations across the healthcare and life sciences industry.