About

OnMune is a deep-tech precision medicine startup reimagining how we discover and match therapies to patients with cancer and immune‑mediated diseases. We combine advanced AI with systems immunology to build immune digital twins – computational replicas of a patient’s immune system that simulate how they will respond to existing and novel treatments. Our platform integrates multi‑omics, clinical and real‑world data to identify new indications for approved and late‑stage drugs, reducing development risk, timelines and cost. By focusing on drug repurposing and smarter trial design, OnMune enables faster translation from mechanism to the clinic, supporting more targeted, evidence‑based therapies for patients who currently exhaust standard of care. Founded in Greece and collaborating with leading clinicians and researchers, OnMune aims to position the Greek ecosystem at the forefront of AI‑driven immunology and precision oncology, while creating scalable technology that can be deployed globally.

Solution & Product

OnMune delivers an AI-native platform that builds immune digital twins to guide drug repurposing and personalized treatment decisions in oncology and immune‑mediated diseases. Our solution integrates multi‑omics, clinical and real‑world data into mechanistic and machine learning models of the patient’s immune system, enabling in silico simulation of response to different drugs, combinations and dosing strategies. The core product is a decision-support platform for clinicians, researchers and pharma teams. Users can upload curated patient or cohort data, run virtual response simulations across a library of approved and late‑stage therapies, and receive ranked, explainable treatment hypotheses and new indication signals. For hospital and CRO partners, OnMune supports smarter clinical trial design (enrichment, responder stratification, arm prioritization) and accelerates identification of repurposing candidates. Under the hood, the platform combines immune network models, longitudinal data assimilation and generative AI to continuously refine each digital twin as new data arrive (labs, imaging, omics, wearables). This allows dynamic monitoring of disease trajectory and treatment efficacy, turning static patient records into an evolving, actionable model. Our roadmap includes API access for integration with existing hospital IT and pharma pipelines, and modular disease‑specific twin “templates” that can be rapidly adapted across oncology and autoimmune indications.

Innovation & Scalability

OnMune’s innovation comes from combining systems immunology with AI-native modeling to build mechanistic, patient-specific immune digital twins, instead of relying on static biomarkers or black-box predictors. These twins simulate how a patient’s immune system responds over time to different therapies and combinations, enabling in silico experimentation on “virtual patients” and moving drug repurposing from trial-and-error to model-driven decisions. Our hybrid architecture fuses mechanistic immune network models with machine learning that learns from multi‑omics, clinical and real‑world data, keeping each twin interpretable and continuously updated as new data arrive. Shared, indication‑agnostic immune modules can be rapidly configured into disease‑specific templates, allowing fast expansion across oncology and autoimmune indications. Scalability is built into both technology and business model: a cloud‑native, modular platform supports running thousands of digital twins and virtual trials in parallel, while a SaaS and API‑first design allows integration with hospital IT systems, registries and pharma R&D pipelines. Each new partner and dataset strengthens the underlying models, creating a data network effect that improves performance, broadens indication coverage and makes the platform increasingly defensible and globally scalable.

Traction & achievements

OnMune has focused its early traction on building and validating a robust PoC and assembling the right clinical and technical network to scale it. We are developing a first PoC of our immune digital twin platform using high‑quality public multi‑omics and clinical datasets, demonstrating that we can reproduce known response patterns and generate biologically plausible repurposing hypotheses in oncology and immune‑mediated diseases. In parallel, we are advancing data access and collaboration agreements with Greek and EU partners (hospitals, research institutes and consortia) to integrate local and European real‑world data into the next versions of the platform and prepare prospective pilots. The team is led by a founder with a PhD‑level background in immuno-oncology and experience in AI‑driven clinical trial de-risking, complemented by a team of bioinformitician, ML and software engineer and Scientific Operations, also advisors in immunology, clinical oncology and computational modeling. This mix of data‑driven PoC work, European and Greek data collaborations, and a multidisciplinary team provides a clear path from prototype to clinically and commercially relevant deployments.

Team & Why Us

OnMune sits at the intersection of immunology, AI and clinical translation, and the team is built for that mission. The founder brings a PhD‑level background in immuno-oncology and experience in AI‑driven clinical trial de-risking, complemented by a team of bioinformitician, ML and software engineer and Scientific Operations, forming a strong scientific and technical backbone for the platform. A growing advisory network covers systems immunology, clinical oncology and computational modeling, ensuring that the immune digital twin approach and drug repurposing use cases are co‑designed with people who understand both biology and real‑world clinical workflows. Based in Greece but connected to European research and innovation ecosystems, the team is well placed to access high‑quality datasets and partners while building export‑oriented technology. Why us: we combine deep domain expertise, practical AI/ML experience and early access to Greek and EU clinical and multi‑omics data, all focused on a clear, capital‑efficient wedge — immune digital twins for drug repurposing and precision treatment in oncology and immune‑mediated diseases.

Funding Needs

OnMune is seeking early funding to complete the proof of concept, validate it with clinical partners, and prepare for scale. We aim to secure an initial pre-seed round (or equivalent non‑dilutive support) to cover 12-18 months of runway, focused on a few clear milestones. Key use of funds: Product and tech: Finalize the PoC of our immune digital twin platform on public and partner datasets, harden the cloud infrastructure, and build a usable MVP for clinicians and R&D teams. Data and pilots: Secure and operationalize Greek and EU data collaborations (hospitals, research institutes, consortia) and run 1–2 prospective pilots for drug repurposing and patient stratification in oncology/immune‑mediated diseases. Team: Hire a small core team (AI/ML engineer, software engineer, part‑time clinical/biostatistics support) and formalize the advisory board in immunology, oncology and computational modeling. Regulatory and business: Start the regulatory and data‑governance pathway (GDPR, medical device strategy) and validate business models with hospitals, CROs and pharma partners. This funding will de‑risk the core technology, demonstrate clinical and commercial relevance, and position OnMune for a larger follow‑on round with validated pilots, reference partners and a clearer go‑to‑market plan.