Tel Aviv, Israel, July 29, 2026 -- Quantum X Labs Inc. an advanced technologies company, today announced the successful demonstration of a complete quantum-enabled clinical data analysis use case.

The demonstration showcases the company's ability to process real clinical data through an integrated analytical workflow, preparation, quantum-enabled analysis, and generation of biologically and clinically interpretable insights. The workflow was executed using Quantum X's quantum simulation environment designed to emulate quantum computational processes relevant to the Company's analytical platform.

Quantum X’s proprietary algorithm platform, operated through its subsidiary, CliniQuantum and protected through the company's intellectual property portfolio and patent filings, is designed to enable quantum-enhanced sampling for continuous probability distributions relevant to advanced statistical analyses of clinical trial and biomedical datasets.

The completed End-to-End clinical data analysis demonstrates the platform's ability to take clinical grade data through the full lifecycle of its platform, from secure ingestion and preparation, through quantum based analytical processing, and back to domain relevant interpretability, within a single, integrated framework.

This milestone confirms that the platform can support a complete analytical workflow designed to handle complex, high dimensional biomedical data and apply quantum inspired and quantum enabled methods to uncover non obvious structure, while maintaining alignment with downstream scientific interpretation requirements.

“This milestone demonstrates that our platform is not conceptual, it is operational,” said Dr. Tidhar Turgeman, head of clinical trials data analysis at Quantum X. “We have shown that clinical data can be processed end to end within our system, enabling quantum enabled analytics while preserving the ability to interpret results in a meaningful scientific context.”

Building on this achievement, Quantum X plans to expand the scale of supported datasets, further optimize its quantum algorithms, and conduct performance studies aimed at quantifying the value of quantum computing technologies for clinical research, clinical trial analytics, and precision medicine applications.