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TwinEdge Bioscience

Swiss techbio company building population-scale digital twins of patient tumours to guide oncology drug discovery and clinical development.

Last updated September 29, 2026

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Overview

TwinEdge Bioscience is a Swiss technology-biology ("techbio") company based in Lausanne that develops digital twins — computationally actionable representations of individual patients' tumours — for oncology drug discovery and development. The company describes its mission as delivering population-scale insight throughout the drug development process so that clients can make better decisions about which translational programmes advance into clinical trials and how those trials are designed and run. Its work combines computational biology, artificial intelligence and personalised medicine. The core of the TwinEdge offering is its proprietary methodology for turning datasets obtained from patient tumour samples into "avatars": digital representations of tumours that can be tested with candidate drugs in "in-avatar" trials. By integrating molecular and dose-response data into mechanistic simulations, TwinEdge aims to replicate real-world clinical diversity and to create what it describes as the world's largest population of digital twins. This is intended to enable large-scale clinical insight at translational and early clinical decision points, before expensive human trials are committed. TwinEdge markets its capabilities to the pharmaceutical and biotechnology industry. Its flagship asset, the TwinEdge Patient Avatar Collection, is described as an actionable and accessible collection of more than 10,000 patient avatars, each a unique digital representation of an individual patient tissue. The company positions the collection as a toolkit that can bring dormant data to life, test hypotheses, predict response, and allow sponsors to perform only the preclinical studies a programme actually needs — from early proof-of-concept through ongoing clinical trials. The company is led by a team with backgrounds in computational biology, translational bioinformatics and life-science business development. Its Chief Technology Officer has been a professor of computational biology at the Universities of Lausanne and Geneva and at CHUV, headed the Data Analysis for Health2030 Genome Centre, and formerly led Translational Bioinformatics at Merck Serono. Its Chief Business Officer was formerly Head of Corporate Development and Strategy at Crown Bioscience and has more than 15 years in life-science product and strategy roles. Its Chief Operating Officer was formerly Director of In silico Drug Development at JSR Life Sciences and has more than 20 years of experience in computational biology. Mike Prosser is identified as CEO. TwinEdge collaborates with oncology drug developers to interrogate preclinical data at greater depth. One announced collaboration is with Hanx Biotherapeutics, in which TwinEdge is developing individual digital twins of a collection of Diffuse large B-cell lymphoma (DLBCL) patient-derived xenograft (PDX) mouse models provided by Crown Bioscience, integrating molecular and dose-response data into mechanistic simulations to help elucidate the mechanism of action of the bispecific programme HX009, model potential clinical performance across lymphoma patients, and refine patient-selection hypotheses. The company is headquartered in Lausanne, Switzerland, and operates as a private company serving global pharmaceutical and biotechnology clients.

History

TwinEdge Bioscience is a privately held technology-biology company headquartered in Lausanne, Switzerland. It was established to apply computational biology, artificial intelligence and personalised medicine to oncology drug discovery and development, at a time when the pharmaceutical industry was seeking better ways to predict which translational programmes would succeed in clinical trials. The company's founding premise is that traditional preclinical readouts limit how deeply early efficacy and variability can be understood. TwinEdge therefore developed a proprietary methodology in which datasets obtained from patient tumour samples are combined with known mechanistic insights to produce "avatars" — digitally actionable representations of patients' tumours that can be tested with new drugs in "in-avatar" trials. By computationally testing across thousands of simulated patients, the approach is intended to explore heterogeneity across patient populations and biomarker-linked response patterns. A central element of the company's strategy has been scale. TwinEdge states that it is creating the world's largest population of digital twins, enabling large-scale clinical insight at translational and early clinical decision points. This culminated in the publicised TwinEdge Patient Avatar Collection, described as an actionable and accessible collection of over 10,000 patient avatars, each a unique digital representation of an individual patient tissue. The collection is marketed as a toolkit for the pharmaceutical and biotech industry, allowing sponsors to bring dormant data to life, test hypotheses, predict response, and perform only the preclinical studies a programme needs, from early proof-of-concept through ongoing clinical trials. TwinEdge has built a leadership team drawn from academic computational biology and the life-science industry. Its Chief Technology Officer has been a professor of computational biology at the Universities of Lausanne and Geneva and at CHUV, headed the Data Analysis for Health2030 Genome Centre, and formerly led Translational Bioinformatics at Merck Serono. Its Chief Business Officer was formerly Head of Corporate Development and Strategy at Crown Bioscience and has more than 15 years in life-science product and strategy roles. Its Chief Operating Officer was formerly Director of In silico Drug Development at JSR Life Sciences and has more than 20 years of experience in computational biology. Mike Prosser serves as CEO. The company has pursued collaborations with oncology drug developers to validate and apply its avatar engine. One announced collaboration is with Hanx Biotherapeutics. As part of that collaboration, TwinEdge is developing individual digital twins of a collection of Diffuse large B-cell lymphoma (DLBCL) patient-derived xenograft (PDX) mouse models provided by Crown Bioscience, integrating molecular and dose-response data into mechanistic simulations. The multi-phase goal is to further elucidate the mechanism of action of HX009, model potential clinical performance across lymphoma patients, and explore mechanism-of-action relevance beyond the initial DLBCL focus. The companies stated that the programme would explore heterogeneity across lymphoma patient populations and biomarker-linked response patterns, aiming to refine patient-selection hypotheses, strengthen early translational evidence for HX009, and help optimise clinical path planning. TwinEdge continues to operate as a private company based in Lausanne, serving pharmaceutical and biotechnology clients globally with digital-twin-based decision support for oncology development.

  • TwinEdge Bioscience is headquartered in Lausanne, Switzerland, as a techbio company focused on digital twins for oncology drug discovery and development.

  • TwinEdge announces the TwinEdge Patient Avatar Collection, an actionable and accessible collection of over 10,000 patient avatars.

  • TwinEdge announces a collaboration with Hanx Biotherapeutics to develop digital twins of DLBCL PDX mouse models provided by Crown Bioscience for the HX009 bispecific programme.

Products and positioning

Techbio provider of population-scale digital twins for oncology drug discovery and development, positioned as a decision-support toolkit for pharmaceutical and biotechnology sponsors.

  • TwinEdge Patient Avatar Collection

    An actionable and accessible collection of over 10,000 patient avatars, each a unique digital representation of an individual patient tissue, for pharmaceutical and biotech oncology development.

  • Digital avatar engine

    Proprietary methodology combining datasets from patient tumour samples with known mechanistic insights to create digitally actionable representations of tumours for in-avatar drug testing.

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