Introducing the TOP framework: a novel phenotyping solution for collaborative phenotype algorithm development and...

Area of Science:

• Computational Biology
• Bioinformatics
• Medical Informatics

Background:

• Traditional phenotyping methods are manual, time-consuming, and limited in scope.
• The TOP Framework is introduced as a software suite to address these limitations.
• It offers tools for formal phenotype definition, ontological organization, and knowledge representation.

Purpose of the Study:

• To introduce the TOP Framework, a novel software suite for automated phenotyping.
• To demonstrate its capabilities using the Model for End-Stage Liver Disease (MELD) score as an example.
• To evaluate the user experience and suitability of the framework for researchers and clinicians.

Main Methods:

• The TOP Framework integrates modules for phenotype definition, ontological classification, and model creation.
• A dynamic phenotype algorithm facilitates automated data retrieval and analysis.
• A reasoner model derives complex phenotypes, and an automated testing module ensures reliability.

Main Results:

• The TOP Framework successfully implements a reasoner model and automated testing.
• Preliminary user experience evaluation (n=11) showed positive results.
• Mean scores for attractiveness (1.50), pragmatic quality (1.38), and hedonic quality (1.40) were favorable.

Conclusions:

• The TOP Framework provides a novel, automated approach to phenotyping.
• It has the potential to improve the efficiency, scalability, and reproducibility of phenotyping studies.
• This advancement supports deeper disease understanding and precision medicine.