Modelling and Implementation of a Precision-Oncology Data-Integration Platform for Real-Word Molecular Tumor Borad...

Area of Science:

• Oncology
• Bioinformatics
• Clinical Informatics

Background:

• Precision oncology (PO) utilizes next-generation sequencing (NGS) to match cancer therapies with tumor molecular profiles.
• Challenges exist in integrating NGS data into clinical workflows and Molecular Tumor Board (MTB) decision-making.

Purpose of the Study:

• To develop and evaluate an integrated platform supporting MTB decision-making.
• To consolidate heterogeneous clinical and molecular data for improved patient management.

Main Methods:

• An ETL (Extract, Transform, Load) process was used to integrate diverse data sources.
• The platform automated data loading, reducing manual data entry for clinicians.
• 69 variables including clinical, molecular, and MTB recommendations were integrated.

Main Results:

• The platform processed data from 1,119 patients and 1,221 NGS results between February 2024 and September 2025.
• 30% of cases received therapeutic recommendations through the platform.
• Automated data integration significantly reduced clinician time and provided a unified patient view.

Conclusions:

• The integrated platform enhances clinical care and data interoperability in PO.
• This approach supports real-world MTB workflows and facilitates data-driven treatment decisions.
• The system promotes efficient integration of genomic data for precision cancer therapy.