Pharmacogenomics annotation tools are computerized tools which parse inputted genomic data to output previously issued clinical prescribing recommendations tailored to the inputted genotypes. Examples of pharmacogenomics annotation tools are PharmCAT^[1], PAnno^[2], and PharmVIP^[3]. For those three tools, genomic data is inputted as a Variant Call Format (VCF) file, and the output is the corresponding prescribing recommendations.

Pharmacogenomics is a field of study combining pharmacology with genomics. It seeks to tailor drug prescribing to individual patients using, in part, genotyping data from those patients.^[4] Individuals may possess genetic variants (differences in their DNA) that may alter the pharmacokinetics (PK; the way that drugs are absorbed, distributed to tissues, metabolized, and excreted) or pharmacodynamics (PD; how the drug interacts with it’s receptor) of specific drugs. Alterations in pharmacokinetics or pharmacodynamics can impact the effectiveness of pharmacological interventions, even in non-pharmacogenomic contexts.^[5]

Through research into these variants, both clinicians and researchers have found that modifying the doses of drugs can be effective for treating patients carrying variants affecting their PK and PD.^[6] Prescribing recommendations already exist for certain variants that have been identified through prior research into genetic predictors of drug effectiveness and side effects. ^[7]

Clinically actionable haplotypes are referred to in the literature as star (*) alleles. Haplotypes are groups of variants that are inherited together, due to being physically close on the same chromosome, reducing the chance of crossover during meiosis. Star alleles are of particular interest in pharmacogenomics due to their clinical utility. Pharmacogene diplotypes are generated from the maternal and paternal star alleles.^[8]

Genomic data is inputted as a VCF File.^[1][2] VCF Files are one type of file format used in bioinformatics. They can be generated from genomic data through separate bioinformatics software.

Bioinformatics refers to the computational analysis of biological data, such as genomic sequences. Bioinformatic methods are used in a pharmacogenomics annotation workflow.

Pharmacogenomics annotation also relies on genes and variants being annotated. Annotation in the genetics context means matching DNA sequences to a corresponding gene, protein, or variant.

The workflows for pharmacogenomics annotation tools consist of two steps:

1. Processing and allele determination
2. Matching pharmacogenomic phenotypes to diplotypes

The first phase consists of a preprocessing step and an allele determination step. This preprocessing step removes extraneous information and downloads the corresponding human reference genome sequence. It then formats the file to the standardized format.^[9] The allele determination step matches inputted genotypes to named alleles. If the inputted data is phased, the step can match diplotypes without extra computation steps. If the data is unphased, the software will go through additional steps to attempt to correctly match alleles. ^[10][2]

The second phase also has two steps: matching phenotypes and report generation. The phenotype matching step matches the diplotypes generated in the first phase to known pharmacogenomic phenotypes (like metabolizer status, discussed below). The report generation step compiles all of the information generated in that previous step into a comprehensive report. ^[11]

Pharmacogenomics Annotation tools such as PharmCAT, PAnno, and PharmVIP are used to analyze and annotate pharmacogenes by helping to predict drug metabolism, efficacy and potential adverse effects. The annotation tools are used in:

1. Variant identification by detecting structural changes in genome sequence such as SNPs and indels.^[12]
2. Converting raw genomic data into functional phenotype by stratifying the genotype-to-phenotype characteristics into low, medium, or high function, or for metabolism-related genes, into poor, intermediate or rapid metabolizers.^[2]
3. Analyzing the interaction between drugs and genes.
4. Assisting in clinical interpretation by recommending drug dosage, assessing impact of drug metabolism for medications such as warfarin or codeine.^[13][2]

Pharmacogene annotations have several advantages. They allow physicians to select the right drug and recommend the right dosage amount to reduce adverse reactions. This can reduce toxicity, improve drug efficacy and eliminate trial and error prescriptions.^[14]