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Targeted Next-generation Sequencing and Bioinformatics Pipeline to Evaluate Genetic Determinants of Constitutional Disease

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Comprehensive whole genome sequencing-based pharmacogenomics profiling using a personalized genome interpretation

Aikaterini Patrinou¹, Alexandros Kanterakis², Gerasimos Vonitsanos³

¹Department of Computer Science and Biomedical Informatics, University of Thessaly, Lamia, Greece.

Frontiers in Pharmacology

|July 15, 2026

Summary

We developed an open-source workflow to interpret patient genetic data for personalized medicine, enabling comprehensive pharmacogenomic assessments and facilitating clinical implementation of precision therapeutics.

Keywords:

biomarkers clinical decision support tool genome informatics open access pharmacogenes pharmacogenomics workflow

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Area of Science:

Genomics
Pharmacogenomics
Clinical Decision Support

Background:

Personalized medicine and precision therapeutics offer revolutionary potential in clinical practice by tailoring treatments to individual genetic profiles.
Clinical decision support tools are crucial for translating genomic information into actionable clinical insights for genome-guided therapies.
Implementing precision therapeutics requires efficient interpretation of a patient's genetic data into a clinically meaningful format.

Purpose of the Study:

To develop and present a personalized genome interpretation workflow utilizing open-source code.
To facilitate the practical application of precision therapeutics in clinical settings.
To enable comprehensive pharmacogenomic (PGx) assessments from next-generation sequencing data.

Main Methods:

Utilized two pharmacogene panels (12-gene PREPARE and 87-gene PyPGx) for comprehensive variant analysis.
Analyzed whole genome sequencing data from three members of a Greek family.
Developed a genome interpretation workflow based on open-source code.

Main Results:

Identified and reported clinically actionable, rare, and novel variants, primarily in pharmacogene introns and fringes.
Generated two types of pharmacogenomics (PGx) reports, including rare and novel variants for hypothesis generation.
Demonstrated the workflow's capability for targeted and comprehensive clinical PGx assessment.

Conclusions:

The developed genome interpretation workflow enables targeted, comprehensive clinical PGx assessment.
The workflow facilitates the integration of pharmacogenomics into routine clinical practice using next-generation sequencing data.
This approach holds promise for advancing personalized medicine and optimizing drug efficacy while minimizing toxicity.