DIGITAL TWINS

Medical Avatars for Precision Medicine

Mavatar’s Medical Avatars transform molecular data into patient-specific digital twins—enabling in silico therapy simulations, smarter clinical decisions, and faster drug development.


MEDICAL AVATARS

Personalized Models for Smarter Decisions

At the core of Mavatar’s precision medicine approach is our Digital Twin technology, also known as Medical Avatars. These advanced, virtual models replicate the complex molecular and cellular features of both patients and diseases—providing a new layer of biological insight to support treatment selection and therapeutic innovation.

CORE PLATFORM

Powered by DINA

Built on our proprietary Deep Integrated Network Analysis (DINA) framework, Medical Avatars are created using vast amounts of single-cell RNA sequencing (scRNA-seq) and transcriptomic data. This allows our platform to simulate biological processes and treatment effects at a highly detailed level—purely through data, without the need for real-time tissue sampling.

Treatment Support for Clinicians

Medical Avatars are used to match individual patients to disease subgroups based on their biomarker profile, collected via a standard blood test. Once matched, the platform simulates how different therapies might interact with that patient’s unique molecular signature—helping clinicians make more personalized and informed treatment decisions.

Each avatar is pre-computed using data from hundreds of real cases, enabling rapid, scalable analysis. Physicians receive a ranked list of potential treatment options, based on how closely they align with the patient’s disease profile.

This capability is being integrated into Mavatar Precision, our upcoming clinical decision support platform, launching in 2026.

Additional disease models are in development and will continue to expand over time.

The first focus areas include:

CASE STUDY

Breast Cancer

CASE STUDY

Breast Cancer

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CASE STUDY

Lung Cancer

CASE STUDY

Lung Cancer

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CASE STUDY

Melanoma

CASE STUDY

Melanoma

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CASE STUDY

Lymphoma

CASE STUDY

Lymphoma

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How It Works

1. Data Collection

Blood-Based Biomarker Test

A standard blood test is used to measure key protein biomarkers that reflect the patient’s molecular profile.
2. Digital Twin Creation

Avatar Matching

The biomarker data is securely analyzed in the Mavatar platform and matched to a pre-computed avatar—based on molecular similarity to thousands of patients.
3. Therapy Simulation

In Silico Testing

Our platform runs simulations to virtually test therapies against the avatar. It ranks treatment options, supporting clinicians with personalized, data-driven insights.
RESEARCH & DRUG DISCOVERY

Accelerating Drug Development

Medical Avatars are not only useful in clinical decision support—they can also offer significant value to pharmaceutical R&D teams. By creating disease- and patient-specific digital twins, Mavatar helps:

All Cells. All Genes. All Diseases.

DINA maps the interactions of 22,000 genes across all known tissues and conditions—offering a systems-level understanding of disease biology.

Cross-Disease, Tissue-Specific Discovery

The framework learns from thousands of disease contexts simultaneously, identifying both shared and distinct molecular mechanisms within specific tissues.

Unbiased Insight Generation

DINA integrates data from humans, cell lines, animal models, and clinical trials—free from prior assumptions—allowing for novel insights into pathogenesis, drug response, and disease variability.
DISEASE AGNOSTIC

Accelerating Drug Development

Medical Avatars are not only useful in clinical decision support—they can also offer significant value to pharmaceutical R&D teams. By creating disease- and patient-specific digital twins, Mavatar helps:

  • Identify high-potential biomarkers and therapeutic targets
  • Predict drug efficacy through in silico modeling
  • Support drug repurposing opportunities
  • Improve trial design and patient subgroup selection


This technology helps reduce early development risks, enhance trial precision, and may improve timelines for bringing new therapies to market.

USING DIGITAL TWINS

Supporting Clinical Trials with AI-Powered Biomarkers

Mavatar also offers AI-based biomarker discovery—integrating transcriptomic and single-cell data to identify indicators predictive of therapeutic response. This allows pharma teams to:

  • Refine inclusion criteria
  • Define stronger endpoints
  • Select better-matched patient cohorts


This approach helps streamline trials, reduce costs, and improve outcome predictability across development stages.

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