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DIGITAL TWINS FOR HEALTHCARE

Predict what patients will actually do.

Forecast dropout, non-adherence, and missed follow-up before they happen. The patient intelligence layer for clinical trials, commercial launch, and care.

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100% 50% 0% INDUSTRY AVG RISK CLIFF - V5 INTERA V1 V2 V3 V4 V5 V6 V7 V8 V9 V10 V11 V12

HARVARD · MIT · BROWN · ALAN TURING INSTITUTE · UNUSUAL VENTURES · CORRELATION VENTURES

Healthcare loses hundreds of billions of dollars annually because nobody can predict what patients will actually do. Intera is building the intelligence layer that answers that question. Before the trial begins, before the patient discontinues, before the readmission occurs.

97% PREDICTIVE ACCURACY · HOW IT WORKS

Patient intelligence, end to end.

1. Ingest
2. Simulate
Intera
3. Forecast
4. Calibrate

1. Ingest

Population-level demographic, clinical, psychosocial, and behavioral data structured across four conditioning layers to build synthetic patient populations calibrated to any target population or therapeutic context.

2. Simulate

Cohorts run through any program, protocol, or care pathway. Behavioral factors modeled at the patient segment level: visit burden, institutional trust, transportation barriers, side-effect tolerance, health literacy, and financial pressure.

3. Forecast

Risk-stratified predictions generated before resources are committed: engagement probability, dropout timing, adherence failure risk, and intervention response, across clinical trial design, commercial launch, and care delivery.

4. Calibrate

Predictions benchmarked against real-world outcomes. Discrepancies fed back into conditioning to improve model accuracy across therapeutic areas, patient populations, and program designs over time.

OUR PRODUCTS

Ensemble

Patient intelligence for clinical trials.

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Recruitment optimization. Identify patient segments most likely to adhere to your specific protocol before screening begins.

Dropout intelligence. Predict who drops out, when, and why. Modeled before protocol lock.

In-trial adherence. Real-time disengagement risk scoring with proactive intervention recommendations.

Placebo arm modeling. For CNS and behavior-dependent trials, identify placebo inflation risk before randomization.

Decentralized trials. All capabilities applied to remote and hybrid trial designs.

Chorus

Patient intelligence for commercial pharma.

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Brand perception simulation. Test how your target patient population will respond to positioning and messaging before launch.

Patient journey forecasting. Model how defined patient segments move through therapy initiation, titration, and persistence before the cohort experiences it.

Customer research. Test messaging variants and access program designs against calibrated patient cohorts. Faster than field research.

There is so much left to build.

Healthcare's most important decisions are still made without knowing what patients will actually do. We think that's fixable. Here's how we approach it.

Our methodology
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