PharmCAT Version 2.0 Released

Version 2.0 of the Pharmacogenomics Clinical Annotation Tool (PharmCAT) has been released October 20, 2022. PharmCAT is a software tool that takes the genetic data (VCF file) of an individual as input, interprets the pharmacogene alleles, diplotypes, and phenotypes, and generates a report with genotype-based drug prescribing recommendations. 

In version 2.0, we have made substantial improvements and changes to the tool based in part on user feedback. Below we outline these features and provide links to read more about each one. We have also slightly reorganized and expanded the documentation found on the PharmCAT website to better support users. 

We hope you will take a look and send any comments, questions or feedback to pharmcat@pharmgkb.org. 

Major PharmCAT v2.0 features:

• PharmCAT now includes available DPWG prescribing guidance (as annotated in the PharmGKB DB) in addition to CPIC recommendations. Read more about the genes and drugs included from DPWG and how they are sourced 
• PharmCAT report has been redesigned for multiple recommendation sources 
• Added functionality for research use only 
• CYP2D6 diplotype calling based on SNPs and INDELs from a VCF file (does not include structural variants/CNVs). Warning: Because structural variation and haplotype can’t be determined from VCF, this functionality shouldn’t be used for clinical purposes. 
• Partial and combination calls for novel combinations of PGx positions included in the PharmCAT allele definitions. This functionality helps users determine if a sample potentially contains a novel allele. 
• Added support for the DPYD genotype based on the lowest activity score as described in CPIC’s fluoropyrimidine guideline (PMID: 29152729) for samples with more than two DPYD variants.
• Extended support of external genotype/phenotype input (see input and output examples and outside call format). This functionality allows users to include genetic test results from other sources in PharmCAT’s report. 
• Reworked PharmCAT command line tool/arguments. These changes are not backwards compatible with previous PharmCAT versions. 
• VCF Preprocessor updates 
• Harmonized the VCF preprocessor command line arguments and flags with PharmCAT
• Unified the output file name patterns of the VCF preprocessor with what PharmCAT uses
• Added a few amenities, e.g., bcftools and bgzip version check, switch to .bgz file suffix for clarity 

 The latest PharmCAT version and extensive documentation is available on PharmCAT.org

There is no ontology term for Phenoconversion in BioPortal

There are two papers ahead of print in Pharmacogenomics both discussing how important phenoconversion is to consider in the implementation of PGx in clinical practice. Phenoconversion in the PGx context is a drug-drug interaction that impacts a drug metabolizing phenotype such that it mimics the effects of a metabolizer genotype. Yet there was no match for phenoconversion in a search of BioPortal (on 10/3/2022) which has over a thousand biomedical ontologies including MeSH, MedDRA, RxNorm and other ones we use for PGx. PharmGKB does collect drug-drug interaction information from drug labels and publications that can potentially be used in the future to help account for phenoconversion. However, while phenoconversion is a well-known phenomenon, the specifics of how phenoconversion affects patient phenotype, especially on top of genotype, has not been quantified (to our knowledge). This makes it difficult to apply drug-drug interaction information to predict how patient genotype-to-phenotype mapping should be altered by information about concomitant drugs the patient takes when using prescribing guidance from CPIC, DPWG or FDA.

Paper 1: Pharmacogenomics in psychiatry - the challenge of cytochrome P450 enzyme phenoconversion and solutions to assist precision dosing. Mostafa S, Polasek TM, Bousman CA, Müeller DJ, Sheffield LJ, Rembach J, Kirkpatrick CM.Pharmacogenomics. 2022 Sep 28:0. doi: 10.2217/pgs-2022-0104. Online ahead of print. [PMID: 36169629]

This review proposes a model for improved clinical decision support that integrates genomics, co-prescribing information, lifestyle and disease factors into precision dosing. Excerpt from the paper: “In psychiatry, the proposed CDSS (Clinical decision support system) powered by MIPD (model-informed precision dosing) would apply precision dosing of psychotropics by accounting for the influence of genetic variations in CYPs; the presence of CYP phenoconversion; and coexisting lifestyle (smoking), pregnancy or disease (cancer) factors…. In this study, clozapine concentrations were better predicted by MIPD accounting for the CYP1A2 inducing effect in smokers homozygous for the CYP1A2*1F allele. This is an example of where environmental (smoking) and PGx (CYP1A2 genotype) factors were used to optimize the MIPD model, resulting in improved predictions of clozapine plasma concentrations. In principle, this approach can be applied across other psychotropics, especially those with a high risk of toxicity in overdose (e.g., tricyclic antidepressants).”

Paper 2: The importance of phenoconversion when using the CYP2D6 genotype in clinical practice. Cicali EJ, Wiisanen K.Pharmacogenomics. 2022 Sep;23(14):749-752. doi: 10.2217/pgs-2022-0087. Epub 2022 Sep 14. [PMID: 36102178]

This is an editorial with a case study describing a patient with chronic pain taking tramadol (among other medications). The patient is then started on an antidepressant and the pain is no longer relieved even at higher doses. Even though the patient tests as a CYP2D6 normal metabolizer the antidepressant fluoxetine has resulted in phenoconversion and clinically the patient now responds as a CYP2D6 poor metabolizer with respect to tramadol. They discuss options to change the antidepressant or the pain therapies. The authors caution that “CYP2D6 genetic test results should be continually evaluated in the light of concomitant medications throughout a patient’s lifetime.”

Searching PubMed to see the impact of phenoconversion is complicated as this word is also used to describe change or evolution of disease phenotypes, but the results by year tracker shows exponentially increased use. A phenoconversion tag specific for drug interaction related phenoconversion, would help people in PGx research identify the relevant papers.

Maybe phenoconversion could be added as a child term to MedDRA under Drug-drug pharmacokinetic interaction?