Interoperable Data Platform Standardizes Multi-Cancer Blood Test Results

Proteotype Diagnostics has introduced Alchemi, a proprietary data and clinical workflow platform being developed for Enlighten, the company’s investigational blood-based multi-cancer test. Unveiled on July 30, 2026, the platform is supported by approximately €499,000 from the European Innovation Council’s Pre-Accelerator. A 15-month development program beginning September 1, 2026, will focus on machine-learning optimization, multi-country data harmonization, clinician-interface development, interoperability, cloud security, and medical-device and software lifecycle, quality, and technical documentation.

Enlighten measures changes in the body’s response to tumor development using a laboratory kit. Alchemi is designed to standardize those measurements, orchestrate analytical and machine-learning workflows, and generate traceable, clinician-facing outputs. The platform supports interoperability with standards including Health Level Seven Fast Healthcare Interoperability Resources (HL7 FHIR) and SNOMED Clinical Terms (SNOMED CT), with the goal of reducing reliance on a single central testing facility and supporting integration into local care pathways.

Alchemi will securely harmonize pseudonymized data across countries and laboratory environments while enabling controlled development and validation of explainable machine-learning models. Planned features include interpretable outputs, uncertainty measures, and traceability of the data, model version, and processing steps used to produce each result. The modular architecture is designed for jurisdiction-appropriate cloud deployment with encryption, role-based access controls, and comprehensive audit trails, alongside a multilingual clinician portal for test ordering, results review, and workflow management.

Proteotype’s MODERNISED and INNOVATOR studies are expanding the clinical evidence base for Enlighten, and Alchemi is intended to serve as the shared digital infrastructure that governs and translates multi-country datasets into future clinical workflows.

“A diagnostic platform must do more than apply a machine-learning model. It must preserve the quality and traceability of every dataset, account for differences between populations and laboratory environments, and make clear how outputs are generated. Alchemi is being built to provide that controlled, explainable and reproducible foundation for Enlighten,” said Dr Emma Yates, Chief Scientific Officer and Co-Founder.

“Enlighten combines a distinctive biological signal with laboratory technology and machine learning. Alchemi brings those elements together as an integrated system, creating the infrastructure needed to translate scientific discovery into a clinically deployable and scalable diagnostic platform,” said Professor Gonçalo Bernardes, Co-Founder and Chair of Proteotype’s Scientific Advisory Board.

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