The introduction and incorporation of Pharmacogenomic (PGx) tests in daily clinical practice is increasing in recent years. In several cases currently, adverse drug reactions (ADRs) and treatment of severe side effects could be predicted and prevented based on clinical PGx tests, especially if a pre-emptive genotyping approach is used. The utilization of high throughput DNA sequencing technologies for PGx tests paved the way for precision medicine implementation as well. Both common and rare genetic variants could be revealed while applying sequencing as the gold standard method for identification of such changes. However, two main barriers may restrict the fast integration of advanced sequencing results into clinical reports: a) huge obtained data needs more automated approaches for primary and secondary analysis, and b) novel variants with unknown clinical significance mostly appeared through sequencing technologies, mainly next generation sequencing (NGS) platforms. Bioinformatics will play an essential role in dealing with such challenges. However, drug-related genes are less conserved during evolution and behave not like other genes in diseases. They actually need more attention for employing the appropriate tools for variant calling in both well-known pharmacogenes and less-studied drug-related genes. The utilization of multiple tools at once for particular tests also proved to be promising. Knowing all the available PGx dedicated bioinformatic tools and their main features while selecting the best of them for special needs in haplotype/diplotype calling through PGx genes is one of the major challenges in the field. Moreover, using common bioinformatics algorithms as well as SIFT, Polyphen2, FATHMM, CAD, etc. may need a pre-filtration of variants for choosing the specific markers. However, such tools mostly ignore "increased or decreased function" variants, which result in ultra-rapid and intermediate metabolizer phenotypes respectively.
The aim of this "Research Topic" is to highlight the real-world clinical cases which may benefit from computational Pharmacogenomic analysis for patients’ primary care. Displaying the direct translation of in-silico approaches results into routine clinical settings will bring a better understanding of the associated challenges and needs, which is a fundamental step towards the acceptance of the methodology by healthcare worldwide. Submissions should discuss and address the clear advantages of bioinformatics tools and algorithms for running clinical PGx tests. Additionally, they must present challenges and future needs of applying such approaches through performing PGx testing as a primary test in any kind of clinical context.
We welcome submissions of Original Research, Review, Mini-review, and Systematic Review and Meta-analyses articles dealing with the following themes, including but not limited to:
• Role of computational genomics in Pharmacogenetics and Pharmacogenomics
• Advantages of bioinformatics tools and algorithms for running clinical Pharmacogenomic tests
• Second and third generation sequencing platforms and Pharmacogenomic data analysis
• Genomic data management and optimization for Pharmacogenomic testing performed in clinical centers
• Direct translation of computational analysis of Pharmacogenomic test result into routine clinical practice
• Challenges and future needs in utilization of bioinformatics tools for clinical Pharmacogenomic tests
• Validation and functional prediction of novel variants in pharmacogenes
The introduction and incorporation of Pharmacogenomic (PGx) tests in daily clinical practice is increasing in recent years. In several cases currently, adverse drug reactions (ADRs) and treatment of severe side effects could be predicted and prevented based on clinical PGx tests, especially if a pre-emptive genotyping approach is used. The utilization of high throughput DNA sequencing technologies for PGx tests paved the way for precision medicine implementation as well. Both common and rare genetic variants could be revealed while applying sequencing as the gold standard method for identification of such changes. However, two main barriers may restrict the fast integration of advanced sequencing results into clinical reports: a) huge obtained data needs more automated approaches for primary and secondary analysis, and b) novel variants with unknown clinical significance mostly appeared through sequencing technologies, mainly next generation sequencing (NGS) platforms. Bioinformatics will play an essential role in dealing with such challenges. However, drug-related genes are less conserved during evolution and behave not like other genes in diseases. They actually need more attention for employing the appropriate tools for variant calling in both well-known pharmacogenes and less-studied drug-related genes. The utilization of multiple tools at once for particular tests also proved to be promising. Knowing all the available PGx dedicated bioinformatic tools and their main features while selecting the best of them for special needs in haplotype/diplotype calling through PGx genes is one of the major challenges in the field. Moreover, using common bioinformatics algorithms as well as SIFT, Polyphen2, FATHMM, CAD, etc. may need a pre-filtration of variants for choosing the specific markers. However, such tools mostly ignore "increased or decreased function" variants, which result in ultra-rapid and intermediate metabolizer phenotypes respectively.
The aim of this "Research Topic" is to highlight the real-world clinical cases which may benefit from computational Pharmacogenomic analysis for patients’ primary care. Displaying the direct translation of in-silico approaches results into routine clinical settings will bring a better understanding of the associated challenges and needs, which is a fundamental step towards the acceptance of the methodology by healthcare worldwide. Submissions should discuss and address the clear advantages of bioinformatics tools and algorithms for running clinical PGx tests. Additionally, they must present challenges and future needs of applying such approaches through performing PGx testing as a primary test in any kind of clinical context.
We welcome submissions of Original Research, Review, Mini-review, and Systematic Review and Meta-analyses articles dealing with the following themes, including but not limited to:
• Role of computational genomics in Pharmacogenetics and Pharmacogenomics
• Advantages of bioinformatics tools and algorithms for running clinical Pharmacogenomic tests
• Second and third generation sequencing platforms and Pharmacogenomic data analysis
• Genomic data management and optimization for Pharmacogenomic testing performed in clinical centers
• Direct translation of computational analysis of Pharmacogenomic test result into routine clinical practice
• Challenges and future needs in utilization of bioinformatics tools for clinical Pharmacogenomic tests
• Validation and functional prediction of novel variants in pharmacogenes