Transforming Radiaton Oncology Through Biological Intelligence

Dr. Javier F. Torres-Roca is a physician-scientist and entrepreneur recognized internationally for his work at the intersection of radiation oncology, genomics, and mathematical modeling. He is a Senior Member at Moffitt Cancer Center and Professor of Oncologic Sciences at the University of South Florida, where his research has helped define the field of precision radiation oncology.

Dr. Torres-Roca is the inventor and co-developer of the Radiosensitivity Index (RSI) and the Genomic Adjusted Radiation Dose (GARD) framework, foundational innovations that integrate tumor genomics with radiation dose optimization. These concepts underpin a new paradigm for biologically personalized radiation therapy and have been validated across multiple cancer types.

He is a co-founder of Cvergenx, where he leads the scientific vision behind the company’s Precision Genomic Radiation Therapy (pGRT™) platform. Dr. Torres-Roca is the inventor on multiple issued and pending patents supporting RSI, GARD, and RxRSI, translating academic discoveries into scalable clinical decision-support technologies.

His career reflects a commitment to bridging academic innovation and commercial execution to improve cancer treatment through data-driven, patient-specific approaches.

Dr. Jacob G. Scott is a physician-scientist and entrepreneur whose interdisciplinary work bridges radiation oncology, genomics, mathematics, and evolutionary modeling. He is a Professor and staff physician at the Cleveland Clinic in the Department of Translational Hematology & Oncology Research and Radiation Oncology, with academic affiliations spanning physics, data science, and medicine. 

Dr. Scott’s research focuses on understanding and overcoming treatment resistance through quantitative and evolutionary approaches, applying mathematical modeling to cancer therapy and integrating tumor biology with clinical outcomes. He is a co-inventor of the Genomic Adjusted Radiation Dose (GARD) framework—a genomics-driven method to personalize radiation dosing that represents a major advance in precision radiation oncology. 

In addition to his academic roles, Dr. Scott brings industry experience through consulting, advisory engagements, and equity interests in biotechnology and medical technology ventures, including Cvergenx and other innovative companies. At Cvergenx, he serves as Chief Scientific Officer, helping guide the scientific strategy that commercializes genomic and mathematical innovations for precision radiation therapy. 

Dr. Scott’s career reflects a commitment to translating foundational science into commercially viable technologies that empower clinicians and improve patient care through data-driven, individualized treatment paradigms.

Dr. Steven A. Eschrich is a computational biologist, entrepreneur, and co-founder of Cvergenx, where he serves as Chief Technology Officer. He is a Senior Member in the Department of Biostatistics and Bioinformatics at the H. Lee Moffitt Cancer Center & Research Institute and Associate Professor of Oncologic Sciences at the University of South Florida. In these roles, he leads the development of scalable machine-learning and bioinformatics platforms that translate complex genomic data into actionable insights for personalized cancer care. 

Dr. Eschrich’s research focuses on genomic biomarker discovery, systems biology, and computational modeling to quantify tumor radiosensitivity and predict treatment response. He is a co-inventor of the Radiation Sensitivity Index (RSI)—a gene expression–based model of intrinsic tumor radiosensitivity—and his work underpins the genomic frameworks now moving radiation therapy toward patient-specific optimization. 

As CTO of Cvergenx, Dr. Eschrich drives the company’s technology strategy, advancing the Precision Genomic Radiation Therapy (pGRT™) platform that integrates patented genomic and mathematical models into clinical decision support tools for radiation oncology. His leadership bridges cutting-edge computational science with translational impact, enabling data-driven personalization of radiation treatment.