Unveiling the Digital Evolution of Molecular Tumor Boards

Area of Science:

• Oncology
• Bioinformatics
• Medical Informatics

Background:

• Molecular tumor boards (MTBs) are crucial for personalized cancer treatment, integrating diverse data for individualized therapy recommendations.
• The complexity of heterogeneous data (clinical, genomic) and external resources (databases, literature) presents significant challenges in MTB workflows.
• Manual data processing and analysis in MTBs are time-consuming and require substantial human effort.

Purpose of the Study:

• To conduct a comprehensive literature review on Molecular Tumor Boards (MTBs).
• To analyze the current processes, common knowledge bases, and supporting tools utilized in MTB decision-making.
• To identify trends towards automation and digitalization in MTB workflows.

Main Methods:

• Systematic literature search on Molecular Tumor Boards (MTBs).
• Analysis of existing MTB processes, data integration strategies, and knowledge management systems.
• Review of digital tools and automation solutions supporting MTB operations.

Main Results:

• MTBs integrate patient clinical data with molecular variants for tailored treatment plans.
• Heterogeneous data sources necessitate significant effort for homogenization and rapid analysis.
• Automation and digitalization are increasingly adopted to enhance efficiency and reduce manual workload in MTBs.
• Tools aid in data visualization, providing refined overviews for board members.

Conclusions:

• Automation and digitalization are key to optimizing MTB efficiency and reducing turnaround time for personalized treatment suggestions.
• Effective integration of diverse data sources and knowledge bases is critical for successful MTB operations.
• Continued development of supportive tools is essential for refining decision-making processes in molecular tumor boards.