Will pharmacogenomic testing become a routine part of clinical care?
Some medications are administered as prodrugs that need to be metabolized in the active form by the body. An example of such a drug is codeine. It undergoes biotransformation into morphine by CYP2D6. Patients who transform codeine faster who are referred to as ultrarapid metabolizers, transform codeine into morphine so fast that they can develop opioid toxicity. On the other hand, poor metabolizers would not be able to produce enough active moiety, thereby making the drug ineffective. One such example is clopidogrel, a drug activated by CYP2C19. Poor metabolizers will have difficulty reaching the therapeutic threshold, so the drug will likely be ineffective.
The blood thinner warfarin is the most widely studied example of the pharmacodynamic gene VKORC1 which serves as a marker of stable dose requirements. Both VKORC1 and CYP2C9 need to be tested to determine doses required to achieve stable therapeutic anticoagulation. Genotyping is used in combination with INR monitoring. It is most beneficial at the beginning of the treatment. Correct dosage balances the effect of warfarin between the two extremes represented by thromboembolic events and bleeding.
Abacavir-related hypersensitivity was discovered in clinical trials. About 5-8% of Caucasian HIV patients develop fever, rash, and gastrointestinal complaints. Genome-wide association studies discovered that a specific allele of the HLA-B gene (HLA-B*5701) was associated with abacavir hypersensitivity syndrome.
The importance of pharmacogenomic testing is that these biomarkers have a large effect on the risk of developing adverse drug events. Very few cases are required to find a reliable association. Clinical relevance of pharmacogenomic biomarkers depends on their sensitivity, specificity, and predictive value. The ability to conduct genetic association studies for rare adverse drug events will be significantly enhanced if the infrastructure exists to capture incidents and collect genetic samples at the same time. Another critical issue is the ability to validate pharmacogenomic associations and replicate them.
Currently, Clinical Pharmacogenomic Implementation Consortium (CPIC) lists 417 drug-gene pairs, of which 121 already have a dosing guideline. The evidence in support of pharmacogenomic testing in clinical practice is accumulating rapidly. While ex-post testing can help researchers establish causal relationships between specific genes and adverse drug reactions, it is pre-emptive testing that will ultimately make a difference in clinical practice.