By Wolfgang Hackl M.D., Founder & CEO, OncoGenomX Inc., Switzerland

During my career as an oncologist and cancer drug developer, one question haunted me more than any other: Why do some patients respond to therapy — while others, with the same diagnosis, do not?

We have innovative treatments, biomarkers, advanced lab tests, and guidelines. But far too often, despite all that science, our treatment decisions come down to educated guesswork.

As medicine evolves, so do our data — but not always our ability to act on it with precision.

That enduring gap between what we know and what we can predict inspired me to found OncoGenomX, and to build PredictionStar™, a platform designed to redefine what precision oncology truly means.

From Biomarkers to Behavior: The Missing Link

Today, most molecular cancer tests focus on eligibility: they tell us whether a tumour expresses a particular target or carries a known mutation. This is useful, but it’s only half the story.

Eligibility does not equal efficacy.

Knowing that a patient’s tumour expresses the estrogen receptor (ER), or harbours a PIK3CA mutation, doesn’t mean it will respond to hormone therapy or PI3K inhibition. It simply means those drugs might work. And in oncology, “might” is not enough.

PredictionStar™ was built to close this precision gap — by answering not just which drugs can be used, but which will actually work.

We call this Precision Drug–Tumor Matching: the ability to segregate effective from ineffective treatments by connecting genomic and phenotypic insights into a coherent tumour profile predictive of therapeutic response.

Introducing PredictionStar™: Coherent Biomarker Intelligence

PredictionStar™ is a multidimensional tumour profiling and decision-support system powered by what we term Generative Clinical Intelligence™ — the synthesis of high-quality sequencing data and AI-driven interpretation into clear, actionable clinical guidance.

Traditional assays analyse biomarkers in isolation, treating each gene mutation or expression pattern as a separate clue.

PredictionStar™ instead identifies logically connected biomarker constellations — genomic enablers that reveal which response mechanisms are active, and phenotypic differentiators how likely the tumour will respond.

This networked approach replaces fragmented snapshots with an integrated, functional map of tumour behaviour.

It provides oncologists with something they rarely get from today’s tests: confidence. In clinical modelling, PredictionStar™ has the potential to reduce overtreatment fivefold and lower the cost of achieving one year of tumour growth control by 35 per cent.

But the numbers tell only part of the story. Behind them are patients spared from unnecessary toxicity — and doctors empowered to treat with precision instead of probability.

Built on the Technology of Giants

PredictionStar™ was designed for seamless integration into modern real-world workflows, harmonized and cross-validated to ensure reliability, and reproducibility.

The platform’s pre-sequencing tumor workup is fully standardised, minimizing inter-laboratory variability that can otherwise reach 70 per cent.

From tumour processing to data interpretation, PredictionStar™ enforces the same rigorous quality in every step, producing consistent and concordant results across labs.

As far as cloud architecture optimized for medical data privacy and global scalability we are privileged to work with world class-players of the health IOT industry
(F. Gaede, Oct 2025, Nordcloud).

A Femtech Focus: Personalising Breast Cancer Therapy

While PredictionStar™ has broad oncology applications, our first focus is hormone receptor-positive breast cancer, the most prevalent form among women.

It is here that the limits of current diagnostics are most evident — and the need for predictive and prescriptive clarity is greatest.

Even within hormone-dependent breast cancer, the most favorable form of the disease, patient outcomes vary widely. Some women respond beautifully to endocrine therapy for years, while others progress rapidly.

What makes the difference? The answers are buried in the tumour’s individual response profiles — but until now, we lacked the tools to decode them. PredictionStar™ offers that decoding ability.

Our non-interventional validation study, conducted in collaboration with clinical researchers from the Veterans Affairs Medical Centers in Cincinnati, Los Angeles, and Miami, involves data from over 4,300 patients with hormone receptor-positive disease.

By correlating predicted responses with actual treatment outcomes, we aim to establish a new clinical standard for predictive accuracy.

Our roadmap includes RUO and LDT certification in 2026, FDA-IDE clearance in Q2 2027, first RUO test sales as early as Q1 2027, and clinical study use from Q3 2027 onwards.

Redefining Precision Oncology

To understand why this matters, we need to reframe what “precision” means.

Most tests today are prognostic or eligibility-based. They classify risk or confirm target presence. PredictionStar™ adds a third, transformative dimension: functional prediction. It asks, “Which therapies will this specific tumour respond to — and how strongly?”

This evolution turns diagnostics into a true decision-support tool, enabling oncologists to design treatment compositions optimized for efficacy, rather than constrained by averages.

The distinction may seem subtle, but its impact for individuals living with breast cancer is enormous: Prognostic and eligibility tests describe. PredictionStar™ guides.

Innovation Through Unity

Our strength lies in collaboration.

I’ve often said that OncoGenomX stands “on the technology of giants, powered by the ambition to transform.” That is more than a slogan — it’s our reality. We built PredictionStar™ not as an isolated product, but as a platform for partnership.

Its architecture invites integration — with hospital systems, sequencing providers, AI developers, and pharmaceutical R&D pipelines.

In the coming years, we envision PredictionStar™ evolving into a broader family of tools: PredictionStar DX™ for predictive diagnostics, PredictionStar GCI™ for data integration and generation of actionable clinical intelligence, and PredictionStar IOT™ for real-time connectivity. Each module serves the same purpose: to transform complexity into clarity.

From Data to Decisions: A Personal Reflection

At its heart, PredictionStar™ was born from empathy.

As a clinician, I saw too many patients fall through the cracks — not because we lacked treatments, but because we lacked foresight.

Data without interpretation is noise. Our mission is to turn that noise into understanding.

When I speak with oncologists today, I sense both excitement and relief: “We will no longer be limited to maybes.” “We can begin to quantify response likelihood, combine therapies more rationally, and give patients something we cannot give today: certainty”.

Technology can be transformative, but only when anchored in purpose. For OncoGenomX, that purpose is simple — to give every patient the best possible chance at lasting response.

The Road Ahead

Our journey is just beginning. We are validating, scaling, and expanding across cancer types — from breast to prostate, lung, and beyond.

But our guiding principle remains unchanged: wherever there is cancer, there is a need for precision drug–tumour matching.

The convergence of genomics, phenomics, AI, and clinical data is redefining healthcare.

PredictionStar™ is part of that transformation — proving that predictive precision is not a futuristic concept, but an attainable standard.

We owe it to patients, to clinicians, and to science itself to make that standard universal.

In Closing

When I founded OncoGenomX, I imagined a world where no cancer patient has to live with uncertainty — where treatment is guided by prediction, not probability.

Today, that world feels within reach. PredictionStar™ is more than technology. It’s a promise:

That every patient deserves clarity. That every tumour can be understood.

And that, together, we can end the guesswork in cancer care.

Contact: Dr. Wolfgang Hackl | Founder & CEO, OncoGenomX | E-Mail | LinkedIn WH | Company Webpage | LinkedIn OGX