Simulating Disease Progression

Mu Sigma Simulates Disease Progression with Digital Twins for Faster Trial Readiness

Website casestudy 684x383 Simulating Disease Progression

Situation

A leading pharmaceutical company sought to reduce delays in its drug development cycle caused by prolonged cohort identification, protocol design, and feasibility analysis. The R&D team needed a more predictive, data-driven way to understand how diseases progress in real-world settings and how patients respond to various treatment strategies.

Challenge

Traditional methods for study design and feasibility testing were reactive, time-intensive, and disconnected from real-world patient progression. There was no scalable framework to simulate disease trajectories, anticipate treatment responses, or validate protocols before launching trials. This led to inefficiencies in trial setup, under-optimized inclusion criteria, and inflated control group sizes.

Approach

Mu Sigma partnered with the client to develop a digital simulation framework that modeled disease progression virtually, enabling hypothesis testing and protocol design before study execution.

  • Data Integration: Combined clinical trial data and real-world data across structured and unstructured sources.
  • Digital Twin Development: Created patient archetypes to simulate multiple disease trajectories based on historical treatment patterns and
    progression paths.
  • Interactive Dashboard: Built a dynamic simulation tool with visual views of patient states, survival curves, and treatment outcomes under
    different protocol assumptions.
  • Experimentation Platform: Enabled researchers to run virtual simulations on trial design options, optimizing key variables like
    inclusion/exclusion criteria and expected outcomes.

IMPACT

  • Reduced protocol design time by 40%, enabling faster trial readiness.
  • Allowed simulation of patient outcomes under various treatment pathways, improving confidence in study design.
  • Enabled more precise inclusion criteria and optimized control arm sizing, reducing recruitment burden.
  • Fostered cross-functional alignment between clinical, Health Economics and Outcomes Research (HEOR), and strategy teams by providing a common simulation platform.

Business Impact

  • 40%

    Lesser Protocol Design Time

  • More Precise Inclusion Data

“Mu Sigma’s simulation framework gave us a detailed look into how our patients evolve over time. We’re running virtual experiments before the first patient even walks in."

  • Chief Medical Officer

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