Protocols fail late.
Roughly 9 in 10 drugs entering clinical trials never reach approval, and many of those failures trace back to design choices made before the first patient was dosed.
AI-Powered clinical simulation Run the trial before
Run the trial before
you run the trial.
Infiuss Health builds digital patient twins from your real-world and historical data, then simulates how your protocol performs across thousands of virtual patients. Design smarter, enroll fewer, and reach decisions with more confidence.
Explore the platform
Your data stays private. Your twin supports your health and future research.
Create your Digital Patient Twin 
Built for sponsors, CROs and biostatistics teams.
Trusted by trial teams at
The problem
Clinical trials are designed on assumptions and paid for in patients.
Most trials are powered using historical averages and expert judgment, then tested on real people at full cost. When those assumptions miss, the price is years of delay, hundreds of unnecessary enrollments, and promising therapies abandoned for reasons that had nothing to do with efficacy.
Recruitment stalls.
A large share of trials miss enrollment targets or timelines, and every month of delay carries direct cost and lost patent life.
Decisions wait on data.
Interim analyses, adaptive designs and go/no-go calls depend on evidence that arrives slowly, in small numbers, and often too late to change course.
You cannot afford to learn these lessons one trial at a time.
The solution Meet the digital
Meet the digital
patient twin.
A digital patient twin is a simulated patient built from real clinical data: demographics, biomarkers, disease progression, treatment response and dropout behavior. Infiuss Health builds populations of twins that mirror your target cohort with real patient inputs, then runs your protocol against them to show how the trial is likely to unfold before any real patient enrolls.
Twins are calibrated on historical trial data, registries and real-world evidence, not synthetic guesses. Every model is validated against held-out outcomes you can inspect.
Ready to see it in action?
Request a walkthrough
Outcomes
Smaller, faster, more decisive trials.
Up to 30%
Sample size reduction
Use simulation-informed sample sizing and synthetic control approaches to reduce unnecessary enrollment while maintaining confidence in the trial design.
10× faster
Faster design cycles
Evaluate multiple protocol scenarios in hours instead of weeks, helping teams identify stronger designs before moving into costly real-world testing.
4–6 Months
Time saved
Reach important go/no-go decisions earlier by using simulated outcomes to support feasibility, interim analysis, and trial planning.
1000 +
Scenarios per study
Compare different arms, endpoints, patient populations, and schedules before protocol lock to identify the most promising trial approach.
How it works
From your data to a simulated trial in four steps.
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// Step 01
Upload your protocol.
Share your draft protocol, inclusion and exclusion criteria, endpoints and target population. That is all we need to get started.
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// Step 02
We build the twin population.
Our models learn from real patients how they respond and drop out, then generate a calibrated population of digital twins that matches your inclusion and exclusion criteria.
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// Step 03
Simulate the protocol.
Run your design against thousands of twins. Compare arms, endpoints, sample sizes, visit schedules and adaptive rules, and see the distribution of likely outcomes rather than a single point estimate.
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// Step 04
Decide and iterate.
Export power calculations, scenario comparisons and audit trails your biostatistics team and regulators can review. Refine the design and simulate again in hours, then run the study on our in-house CTMS or export to the CTMS of your choice.
PROBE
One platform, every stage of the trial.
PROBE is modular. Start with the capability that solves your most pressing problem
and expand as your program grows.
Twin Builder
Builds calibrated digital patient populations from your data, with cohort filters that mirror your inclusion and exclusion criteria.
- Data science
- Biostatistics
Proof
Results from real programs.
Optimizing Phase II Trial Design
Simulated multiple dose arms and endpoints to identify a more efficient trial design before enrollment.
- 30% fewer patients
- 6 weeks saved
De-risking Phase III Before Investment
Compared trial scenarios and probability of success before committing to a larger Phase III program.
- 20% higher efficiency
- Faster go/no-go decision
Accelerating Rare Disease Trial Planning
Modeled patient populations and protocol variations to evaluate trial feasibility earlier.
- 4 months saved
- 1,000+ scenarios tested
Security and compliance 
Enterprise-grade security for regulated research.
Patient data never leaves your control without de-identification, encryption and an audit trail. Infiuss Health is built for the compliance requirements of sponsors, CROs and health systems from day one.
Encryption everywhere.
Data encrypted in transit (TLS 1.2+) and at rest (AES-256), with customer-managed keys available.
De-identification by default.
Identifiers removed or tokenized before data reaches the simulation layer.
Full audit trail.
Every dataset, model version, assumption and output is logged and reproducible for inspection.
Role-based access.
Granular permissions, SSO (SAML/OIDC) and MFA for every user.
Deployment flexibility.
Cloud, private cloud or on-premises installation to meet your data governance policies.
Validated models.
Documented model cards, performance monitoring and change control for every release.
See what the platform can do for your next trial.
Explore your protocol, test potential scenarios, and see what simulation could reveal before enrollment begins.
Role-based access.- No commitment
- No data needed initially
Patients
Create my twin Create your Digital Patient Twin.
Build a secure twin from your own health information and stay in control of how your data is used.
- Private by design
- You control your data
Frequently asked questions
A simulated patient built from real clinical data that reproduces how patients like yours progress, respond to treatment and leave studies. Populations of twins let you test a protocol thousands of times before enrolling anyone.
Simulation helps teams evaluate a protocol before enrollment. It supports trial planning and evidence generation alongside real patient data and clinical research.
Regulatory requirements depend on the study and the intended use of the simulation. Discuss your evidence requirements with your regulatory team. Model assumptions, scenario comparisons and audit trails can support that review.
Start with your draft protocol, inclusion and exclusion criteria, endpoints and target population. During a walkthrough, our team can discuss the historical trial data, registries or real-world evidence relevant to your study.
Twins are calibrated on historical trial data, registries and real-world evidence. Models are validated against held-out outcomes, with documented assumptions and performance information available for review.
The platform uses de-identification, encryption, role-based access and audit trails. Our team can walk through the deployment and data governance requirements for your organization.
The right approach depends on your target population, endpoints and available evidence. Share your protocol with our team to discuss whether a suitable model and dataset are available for your therapeutic area.
Timing depends on the protocol, data readiness and model validation required. Once a population is calibrated, teams can compare scenarios and refine the design. Book a walkthrough to discuss a timeline for your study.
You can run the study on our in-house CTMS or export to the CTMS of your choice. Discuss your existing systems and required export formats with our team during a walkthrough.
Contact our team to discuss your study, the capabilities you need and the scope of your program. A demo is available with no commitment and no data needed initially.