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Decoding Biology

Simulating disease network dynamics to reduce translational risk.

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What we propose

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Bridging the Translational Gap

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The challenge

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Why Promising Drugs Still Fail

A lot of promising drugs fail in clinical trials, leaving patients waiting for treatments they desperately need.

  • High Failure Rates

    The overall success rate of a drug passing through all clinical trials is 8.4%. Depending on the therapeutic area the range is from 3.9% for infectious disease to 34.1% for blood borne diseases.

  • Lack of Efficacy

    Phase 2 trials that test if the drug is effective, have the lowest probability of success, ranging from 27.4% for respiratory diseases to 52.7% for ophthalmology.

  • Unclear MoA

    Lack of Efficacy results from poorly understood disease biology. How does the target to which the drug binds to modulate the disease (Mechanism of Action - MoA)?

"Target validation without clinical context and insufficient mechanistic understanding are the major reasons for high clinical attrition"
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How we do it

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We Tackle the Root Cause.

Causal simulation. Biomarker trajectory modeling. Mechanism-aware target evaluation.

Built for you, To decode biology.

  • From static snapshots to dynamic insights
  • From prediction patterns to prognostic simulation
  • Simulate relative system behavior under different target perturbations to compare mechanistic hypotheses