Founded in Sweden and built on over two decades of scientific research, Mavatar is at the forefront of a new era in precision medicine. Its proprietary technology platform combines biological expertise, advanced machine learning, and high-resolution molecular data to create digital twins—virtual models of both patients and diseases that simulate treatment outcomes.
“Digital twins are not just a metaphor,” says Johan Juhlin, CEO of Mavatar. “They are real, data-driven models that allow us to simulate how a disease behaves in an individual person – and how different treatments might work, before they are given.”
At the core of Mavatar’s approach is DINA (Deep Integrated Network Analysis), a proprietary data framework that integrates large-scale transcriptomic and biomedical datasets. DINA analyzes the interactions between over 22,000 human genes and their behaviors across tissue types, enabling researchers to uncover complex disease mechanisms, therapeutic targets, and biomarker signatures with unprecedented precision.
Mavatar’s analytical engine is powered by a hybrid approach—leveraging both machine learning and traditional statistical models. This allows the platform not only to identify patterns in gene expression, but also to validate findings with rigorous scientific grounding. The result is an end-to-end system that produces biologically meaningful, clinically relevant insights in a fraction of the time required by traditional methods
This technology powers two core platforms:
- Mavatar Discovery is a cloud-based SaaS tool for pharmaceutical companies, biotech innovators, and academic researchers. It enables users to analyze disease biology at scale, identify novel targets, and explore cross-disease patterns – without writing a single line of code. Insights that once took months to generate can now be uncovered in minutes. The platform is on the market as per September 2025.
- Mavatar Precision, set to launch in 2026, is a clinical decision-support tool designed for physicians. By analyzing a simple blood sample, it creates a digital twin of the patient and models how they might respond to various treatment options- allowing doctors to personalize therapy from day one. The first focus areas are oncology.
Mavatar’s technology is already in use through collaborations with leading pharmaceutical companies. From drug repurposing to biomarker discovery and clinical trial optimization, the platform is helping partners uncover hidden connections in data, accelerate development pipelines, and unlock new value from existing compounds.
As Juhlin notes: “Our mission is to bring biology and technology together to solve real problems in healthcare. By using digital twins to make the invisible visible, we can help shift medicine away from generalizations and toward individualized care.”
With strong commercial momentum, a growing product ecosystem, and a platform designed for scale, Mavatar is poised to be a category-defining company in the next wave of data-driven, precision healthcare.
