Accelerate Clinical Trials With In-Silico Virtual Cohorts
Silicon Arm empowers biopharmaceutical sponsors, CROs, and academic investigators to virtually design, simulate, and stress-test clinical trial protocols against Indian biology before dosing physical patients — cutting timelines by 40% and replacing up to 50% of physical control arms.
End-to-End In-Silico Trial Simulation Architecture
Select any clinical module to test real-time statistical powering, indication expansion, or virtual control arms.
Protocol Design & Statistical Power Optimizer
More than 80% of clinical trials experience enrollment delays or underpowered endpoints. Silicon Arm simulates patient enrollment, dropout kinetics, and primary efficacy endpoints to optimize trial powering.
Dynamic Power & Sample Sizing Engine
Adjust protocol parameters on the right to observe simulated statistical power, required physical cohort sizes, and projected clinical trial timelines calibrated against Indian clinical attrition rates.
- • Inclusion/Exclusion Sensitivity: Identifies overly restrictive criteria that choke enrollment without conferring safety advantages.
- • Interim Futility Boundaries: O'Brien-Fleming stopping boundaries evaluated over 10,000 in-silico trial runs.
- • Regulatory-Compliant Powering: Guarantees $\ge 90\%$ statistical power while saving months of patient recruitment.
Indication Selection & Multi-Disease Expansion Matrix
Expand pipeline value by evaluating candidate assets across multiple Indian disease populations in-silico before making physical Phase II capital commitments.
| Disease Indication | Clinical Deficit in India | In-Silico Simulation Solution | Program Status & Direct Subpage |
|---|---|---|---|
| NAFLD / NASH Metabolic Liver Disease | 38–40% national prevalence; silent progression to cirrhosis. | Cost-sensitive triage (θ*=0.40), biomarker attributions, 5-year survival. | Preliminary Results Live → |
| Tuberculosis (TB) Pulmonary & MDR-TB Regimens | 27% global burden; world's highest count of multi-drug resistant cases. | Bactericidal kill-curves, cavitary progression, synthetic control cohorts. | Explore TB Testing Arm → |
| Type 2 Diabetes Metabolic & Cardiorenal Axis | 101M diagnosed; thin-fat phenotype with premature beta-cell decay. | eGFR decay deceleration, liver-pancreas crosstalk, MACE reduction. | Explore Diabetes Axis → |
| Oncology & Immuno-Oncology Collaborative Pipeline | Distinct Indian genomic mutational profiles & delayed detection. | Tumor microenvironment kinetics & synthetic checkpoint response arms. | Partner to Co-Develop |
| Cardiovascular & Heart Failure Collaborative Pipeline | Early-onset coronary artery disease (CAD) 1–2 decades ahead of global baselines. | Hemodynamic in-silico simulation & HFpEF clinical endpoint modeling. | Partner to Co-Develop |
| Autoimmune & Rare Metabolic Collaborative Pipeline | Extremely sparse physical cohorts making traditional RCTs near impossible. | Microsimulation from scarce clinical priors with conformal uncertainty. | Partner to Co-Develop |
Target Product Profile (TPP) Modeling & Benchmark Clearances
Compare candidate molecules against current standard-of-care baselines across efficacy, safety, and pharmacokinetic clearance margins.
Mechanistic Clearance & Adverse Event Margins
By coupling ordinary differential equation (ODE) pharmacokinetics with semi-Markov disease hazard transitions, Silicon Arm benchmarks your candidate molecule against competitor assets across all key clinical endpoints.
- • Biomarker Clearance Velocity: Simulates relative drops in transaminases (ALT/AST), serum bilirubin, sputum conversion, or HbA1c.
- • Therapeutic Window Optimization: Evaluates therapeutic index across patient body surface area and renal function strata.
- • Target Product Profile Scorecard: Generates auditable comparative tables for investment committee reviews.
Probability of Technical Success (PTS) Bayesian Engine
Synthesize mechanistic target engagement, Phase II biomarker surrogate response, and 5-year progression hazard bounds to compute real technical success probabilities before capital allocation.
Bayesian Evidence Synthesis
Traditional PTS estimates rely on subjective survey heuristics. Silicon Arm computes objective Bayesian posterior success probabilities conditioned on simulated Indian population response variance.
Eliminates blind capital risk by identifying fatal protocol flaws or insufficient target engagement early in the preclinical-to-clinical transition.
Synthetic Virtual Control Arms & Ethical Trial Design
Assigning critically ill patients to failing physical placebos or standard-of-care controls causes severe ethical resistance and high loss-to-follow-up. Silicon Arm replaces up to 50% of physical control cohorts with population-calibrated virtual patients.
High Attrition & Ethical Dilemma
In a standard 600-patient trial, 300 vulnerable subjects receive inactive placebo or failing standard therapy for 18–24 months. Dropout rates reach 35%, delaying drug availability.
• Trial Duration: 36–48 Months
• Operational Budget: ₹32–₹45 Cr
Virtual Control Arm Replacement
Enrolling 300 active patients and only 100 physical control patients, augmented by 200 population-calibrated virtual controls with matching baseline covariates and Weibull hazard priors.
• Trial Duration: 21 Months (↓ 40% Faster)
• Operational Budget: ₹18–₹24 Cr (↓ ₹14+ Cr Saved)