Understanding disease before it becomes clinically apparent.
PreDiXome Bio is developing predictive oncology technologies designed to detect integrated biological state transitions associated with cancer before conventional diagnostic methods can identify disease.
Rather than measuring isolated biomarkers, our approach is designed to characterize functional disease biology—creating a new foundation for earlier clinical insight, precision diagnostics, and predictive oncology.
Beginning with ovarian cancer. Built for the future of cancer detection.
Cancer is not a single event—it is a progressive biological process.
Long before disease becomes clinically apparent, cells undergo coordinated functional changes that reflect the earliest stages of malignant transformation. These biological changes precede symptoms and the point at which conventional diagnostic methods can identify disease.
Today's diagnostic technologies have transformed cancer care, yet they are largely designed to recognize disease only after these biological changes have progressed to clinically detectable thresholds.
The challenge is therefore not simply improving the sensitivity of existing tests. It is identifying an earlier class of biological signals that emerge as disease begins to develop.
At PreDiXome, we believe these early biological state transitions represent an opportunity to fundamentally rethink how cancer is detected.
Cancer emerges through coordinated changes across interconnected biological systems—not a single biomarker.
As disease develops, changes in membrane organization, cellular metabolism, mitochondrial function, oxidative balance, and intercellular communication evolve together to create an integrated functional biological state.
This systems-level perspective forms the scientific foundation of PreDiXome's approach to predictive oncology.
Structural and electrochemical remodeling of cellular membranes reflects changes in cellular identity, signaling, and extracellular communication.
Altered oxidative balance and electron transfer reflect metabolic adaptation and changing cellular physiology during disease development.
Progressive mitochondrial dysfunction reshapes cellular energetics, signaling pathways, and functional biological behavior as disease evolves.
These biological systems do not operate independently. Together, they create integrated functional disease states that may provide a fundamentally new class of disease signals.
This observation forms the basis of our scientific thesis.
Functional Biological State Transitions May Provide a New Class of Disease Signals.
We hypothesize that coordinated biological changes converge to generate measurable functional disease-state signatures. If validated, these signatures may provide a new systems-level foundation for predictive oncology beyond conventional biomarker-based approaches.
Translating functional disease biology into clinically meaningful insight.
The Signara™ platform is being developed to identify and interpret functional disease-state signatures by integrating biological signal acquisition, advanced biosensing, computational analytics, and predictive modeling into a unified disease-state intelligence framework.
Its objective is not simply to detect biomarkers, but to characterize the evolving functional biology of disease and translate those measurements into clinically meaningful insight.
Signara™ is being developed as a predictive oncology platform designed to characterize functional disease biology across multiple malignancies.
Ovarian cancer is the first clinical application of the Signara™ platform. Designed as a scalable disease-state sensing framework, the platform is intended to expand across multiple cancer types.
Beginning with ovarian cancer, where the need for earlier detection remains one of oncology's greatest unmet clinical challenges.
Applying the same scientific framework to additional high-impact cancers through biological and clinical validation.
Building a scalable predictive oncology platform capable of generating disease-state intelligence across multiple cancers.
Signara™ is being developed through a phased validation strategy designed to establish scientific, biological, and clinical evidence while advancing the platform toward future clinical translation.
Establishing the foundational biological and analytical evidence required to characterize functional disease-state signatures and support future clinical validation.
Generate the biological and analytical evidence needed to establish disease-state signatures.
Advance biosensing technologies, computational methods, and platform integration.
Prepare for retrospective biospecimen validation, regulatory planning, and future clinical studies.
PreDiXome brings together physician-led clinical insight, disease biology, advanced biosensing, and strategic expertise to build a new approach to predictive oncology.
Physician-scientist with 13+ years of clinical experience in Obstetrics & Gynecology and women's health, with a background in gynecologic oncology, translational research, and precision oncology. She founded PreDiXome bio to translate a clinically driven understanding of cancer into new approaches to disease-state sensing and predictive diagnostics.
Associate Professor of Cardiology-Research, Internal Medicine, at The University of Texas MD Anderson Cancer Center. Dr. Kotla brings expertise in redox biology, oxidative stress, mitochondrial dysfunction, and cellular mechanisms underlying disease-state transitions.
His scientific guidance supports PreDiXome bio's efforts to characterize the biological mechanisms underlying its proposed disease-state signals.
Professor Emeritus of Obstetrics & Gynecology at the University of California, Irvine School of Medicine, and a recognized leader in gynecologic oncology.
Dr. Berman brings decades of clinical, surgical, research, and clinical-trial experience in ovarian and other gynecologic cancers, with particular expertise in disease management, early intervention, and translation of research into clinical practice.
As Chief Medical Advisor, he provides clinical guidance on disease biology, study design, clinical relevance, and the translation of PreDiXome bio's diagnostic approach into oncology practice.
Bhuvish is closely involved in PreDiXome bio's business strategy and commercialization efforts, helping translate the company's scientific platform into a scalable oncology enterprise.
His experience spans venture investing, healthcare strategy, commercialization, partnerships, and business development, supporting PreDiXome's fundraising strategy, strategic relationships, and path toward clinical adoption.
Extending PreDiXome bio's capabilities across computational intelligence and predictive oncology.
Strategic advisory role focused on artificial intelligence, computational biology, data architecture, and the development of predictive disease-state intelligence.
Co-Founder, President & CTO of Probius. Dr. Gupta is the inventor of the all-electronic molecular analyzer underlying Probius' technology and brings expertise spanning surface science, electrical engineering, quantum statistical physics, and molecular sensing.
He collaborates with PreDiXome bio on advanced biosensing and technology development supporting the Signara™ platform.
PreDiXome is developing a new approach to disease-state sensing for predictive oncology. We welcome collaborations with clinicians, scientists, technology innovators, strategic partners, and investors who share our vision of advancing earlier cancer detection.
Together, we are building the next generation of predictive oncology.