Alex Graudenzi, PhD
Cancer evolution and computational biology.
Publication recordResearch & development
Turning cancer history into clinically useful foresight.
EvoClin develops time-aware AI models from longitudinal clinical and molecular data. Treatment response, relapse and molecular evolution, with traceable inputs, clinician oversight and validation built in.
Where we are going
A research program built around the next clinical decision.
Data infrastructure makes rigorous patient-level prediction possible.
- 01
Represent disease over time
A source-linked patient model across reports, therapies and sequencing.
- 02
Model what may happen next
Interpretable algorithms for response, relapse and future molecular states.
- 03
Validate before deployment
Retrospective benchmarking, site calibration and prospective evaluation.
Source-traceableClinician-in-the-loopValidation before deployment
Scientific foundation
World-class expertise in cancer evolution.
The 2026 NEJM Evidence paper is the latest result of an extensive, continuing body of peer-reviewed work. This foundation now feeds EvoClin's proprietary R&D pipeline.
NEJM EvidenceVolume 5, Issue 6 · 2026DOI 10.1056/EVIDoa2500124
Latest publication
Prognostic Score for Myelodysplastic Syndromes Based on Molecular Evolution.
Daniele Ramazzotti, PhD
Bioinformatics and cancer genomics.
Publication recordIvan Civettini, MD
Clinical hematology and translational research.
Publication recordResearch and validation