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Rare Disease Research When Data Is Scarce

Accelerating discovery where data is scarce

Rare diseases affect millions globally, yet each condition impacts only a small number of patients. Small cohorts, limited samples, and fragmented datasets often make rare disease research slow, inconclusive, or impossible using traditional approaches. Mavatar Discovery enables data-driven exploration of rare disease biology, even when disease-specific molecular data is limited.

The Challenge

Why rare disease research is so difficult

- Very small patient cohorts

- Limited access to biological samples

- Fragmented, heterogeneous datasets

- Heavy reliance on prior knowledge

As a result, generating reproducible biological insight can take months, or may not be feasible at all.

A Data-Driven Alternative

What Is Mavatar Discovery?

Built on 20+ years of precision medicine and systems biology research, Mavatar Discovery integrates thousands of public transcriptomic datasets across diseases, tissues, and biological contexts.

Instead of relying on isolated datasets, researchers explore connected biological systems, revealing reproducible molecular patterns that remain hidden in traditional analyses.

By learning from related diseases with shared biological features, researchers can generate hypotheses and explore mechanisms, even when direct patient data is scarce.

Example Case: Mavatar Discovery is used in non-clinical research collaborations, including exploratory work with Sobi focused on IFNγ-related disease biology. 🔗 Read the press release

How Researchers Use Mavatar Discovery in Rare Disease Research

- Explore genetic factors by placing known disease genes into broader biological networks

- Investigate therapy mechanisms by analyzing pathways linked to existing treatments

- Study tissue-specific biology across relevant tissues and cell types

- Explore comorbidities by identifying shared molecular signatures across conditions

All analyses are exploratory, data-driven, and fully traceable to public transcriptomic sources.

Read our use case on Epidermolysis Bullosa

Value for Rare Disease Researchers

For Academic & Translational Research

- Faster hypothesis generation → quicker path to publications

- Stronger biological context → insights beyond single-gene findings

- Competitive pilot data → stronger grant applications

- Less time on pipelines and coding → more focus on science

For Pharma & Drug Development

- Earlier biological insight → shorter discovery timelines

- Better targets & biomarkers → reduced early-stage uncertainty

- Stronger go/no-go decisions → more confident R&D investment

- Scalable analysis → consistent insights across programs

Apply for a free licence

Rare Disease Discovery Award

To support researchers working in areas where data and resources are limited, Mavatar has launched the Rare Disease Discovery Awards.

The initiative provides selected researchers with year-long access to Mavatar Discovery, giving them a data-driven foundation to explore disease mechanisms, generate hypotheses, and support early-stage research without building custom analysis pipelines.

Selected researchers receive:

A one-year, full-access license to Mavatar Discovery

Scientific onboarding and support

Access to integrated transcriptomic datasets for exploratory research

Apply for a Free License here

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