Redefining cancer treatment with AI and genomic data
AI trained on the clinical reasoning of a molecular tumor board, turning a genomic report into an evidence-based treatment path within minutes.
Precision- Trained on 2,500+ real patient records
- Evidence-based targeted recommendations
Interpreting complex genomic data clinically
Reading each tumor's genetic map to design individualized therapy requires continuously tracking a fast-growing literature and deep molecular oncology expertise.
Your digital decision support assistant: MDT Precision
A cloud-based system trained on the real-world genomic data of more than 2,500 patients and expert curation reports. When an oncologist uploads a test result, our AI scans the literature and offers targeted alternatives by predicting treatment response and resistance risk.
How do we train our AI?
We are not building an ordinary search engine. Our model is trained on three layers: the scientific literature, clinical guidelines, and real-world data from more than 2,500 patients built up over 10 years of experience. The platform is woven thread by thread with our expertise in bioinformatics, computational biology and precision oncology.
Real clinical data
The model is trained on the genomic variants, applied treatments and clinical responses of 2,500+ patients treated at our center.
Clinical reasoning
It learns the methodology our PhD-level molecular cancer biologists use to interpret data, identify active pathways and make decisions.
Smart literature review
A cloud-based infrastructure that analyzes scientific publications and clinical guidelines with advanced language models to offer clinicians evidence-based targeted treatment alternatives.
From report to treatment path, in three steps
Upload the genomic report
Tissue- or liquid biopsy-based comprehensive genomic profiling (CGP) results are uploaded to a secure cloud infrastructure.
AI analyzes
Variants are interpreted, active pathways are identified, relevant literature is scanned, and treatment response & resistance risk are predicted.
Board-quality report
Targeted treatment alternatives, generated with molecular tumor board logic and grounded in the literature, guidelines and real patient data, are presented.
Let's train the model together.
Would you like to be among the first physicians to use the platform? We invite selected oncology specialists to voluntarily try MDT Precision in their clinical practice and share feedback. Your feedback makes our model stronger and more accurate. At the start of this partnership, we offer the trial version free of charge.
Join the Beta Program- Free trial versionFull access to the platform throughout the pilot period.
- Direct product impactYour feedback shapes the roadmap and the model.
- Board-quality second opinionFast, evidence-based support on your cases.
At the intersection of science, medicine and technology
Behind the project stands a multidisciplinary, powerful brain trust.
Prof. Dr. Mutlu Demiray
Founder of Turkey's first personalized cancer treatment center. With over 30 years of oncology experience, he has evaluated the genomic profiling tests of more than 2,500 domestic and international patients, pioneering precision oncology.
Our core team & experts
Our multidisciplinary R&D team spans software engineering, bioinformatics, data science, cancer genetics and molecular cancer biology, with each member contributing equally to the project.
Becoming the global decision standard in genomics-based cancer treatment
Through our R&D within Teknopol İstanbul, our goal is to build an exportable, high-value healthcare technology platform.
Target audience & market
Private hospital chains, university hospitals, molecular diagnostics laboratories and independent oncologists who want to practice personalized oncology.
Business model
A hybrid model combining subscription-based B2B SaaS licensing for institutions with direct B2C access for individual users. A cloud-based platform that scales to institutions and individuals alike in a global market where comprehensive genomic profiling is becoming routine.
Sustainable competitive advantage
The biggest barrier in healthcare AI is the lack of validated clinical data. Our platform is trained on the CGP results of 2,500+ real patients, expert curation reports and validated treatment follow-ups, creating an advantage that is hard to imitate.
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R&D at Teknopol Technopark
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