SOPHiA GENETICS Launches AI-Powered Digital Twins to Enhance Intelligent Decision Making in Oncology

SOPHiA GENETICS Launches AI-Powered Digital Twins to Enhance Intelligent Decision Making in Oncology
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Boston, MA and Rolle, Switzerland – OCTOBER 16, 2025, — SOPHiA GENETICS (Nasdaq: SOPH), a leader in AI-driven precision medicine, today announced the launch of SOPHiA DDM™ Digital Twins, a breakthrough research technology that creates dynamic, virtual representations of individual patients to simulate potential outcomes and help oncologists make better treatment decisions.

SOPHiA DDM™ Digital Twins uses each patient’s unique clinical, biological, imaging, and genomic data to generate a computational replica of the patient and their individual disease. Oncologists can use the virtual replica of the patient, or Digital Twin, to simulate treatment responses, disease trajectories, and survival outcomes in real time, and to explore potential treatment strategies virtually before making decisions at the bedside.

“Digital twin technology enables integrative visualization of multimodal oncologic data, revealing latent correlations across modalities. By simulating disease trajectories and therapeutic responses within a virtual environment, Digital Twins offer a framework for in silico experimentation, supporting anticipatory and individualized clinical decision-making,” said Dr. Pierre Heudel, Medical Oncologist, Centre Léon Bérard.

Digital Twins leverages the collective intelligence of the SOPHiA GENETICS community and a robust, multimodal, longitudinal dataset to simulate potential therapy response. By breaking down institutional and geographic barriers, the tool equips clinicians with insights derived from a broad network of global patient cases.

Dr. Mariano Provencio Pulla, Head of Medical Oncology Department at Puerta de Hierro University Hospital, noted, “The Digital Twins concept developed by SOPHiA GENETICS is really a breakthrough in oncology. We absolutely need this approach to take full advantage of major progress that has been made in clinical care in recent years, especially in the context of pre-surgical immunotherapy for patients with non-small cell lung cancer eligible for surgery. I truly believe that it is the future of data-driven medicine.”

Powered by state-of-the-art artificial intelligence, SOPHiA DDM™ Digital Twins continuously evolves as new data becomes available, strengthening accuracy and research capabilities over time. The tool also generates synthetic data that reflects real-world disease patterns, enabling researchers to explore additional therapeutic paths and model potential outcomes before committing to a treatment strategy.

“Cancer is constantly evolving, and static snapshots are no longer enough,” said Jurgi Camblong, Ph.D., Co-Founder & CEO, SOPHiA GENETICS. “With SOPHiA DDM™ Digital Twins, we can create advanced AI models based on our broad patient network, accelerating research, sharpening clinical decisions, and turning today’s insights into tomorrow’s breakthroughs. This reflects our ambition to make data-driven medicine the global standard of care.”

SOPHiA DDM™ Digital Twins brings key features that could, in the future, reshape precision oncology:

• Personalized Treatment Insights: Help oncologists match patients to the most

effective treatment strategies based on simulated outcomes, including ability to

explore relevant clinical trials.

• Toxicity and Cost Avoidance: Provide insights to help physicians reduce patient

exposure to ineffective therapies that drive unnecessary side effects and expenses.

• Global Knowledge, Local Impact: Leverage one of the world’s most robust, de

identified multimodal cancer datasets to help oncologists make better decisions.

This launch marks a new era in precision oncology, one where technology empowers physicians to move beyond retrospective evidence and toward forward-looking, AI-powered decision support tailored to each patient. Digital Twins is launching on the SOPHiA DDMTM Platform for lung cancer, with more cancer types available in the coming months.

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