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  • Oral antipsychotics are substrates of CYP enzymes which are


    Oral antipsychotics are substrates of CYP450 enzymes, which are crucial to their metabolism and elimination (Fig. 1). The efficacy and toxicity of antipsychotic agents is affected by factors that induce or inhibit CYP450 expression and function, such as drug–drug interactions. Additionally, the multiallelic nature of CYP450 enzyme genetics can result in various phenotypes. These polymorphisms reflect gene insertions and deletions, gene duplications, copy number variations, and single nucleotide polymorphisms (SNPs), which can lead to decreased or elevated metabolism. The resulting phenotypes associated with these genetic variants are usually classified as one of four groups: poor metabolizers (PM), intermediate metabolizers (IM), extensive metabolizers (EM) or normal, and ultra-rapid metabolizers (UM) (Fig. 2) (van der Weide et al., 2005). The clinical consequences of variations in metabolism depend on whether the drug taken is pharmacologically active or is a prodrug that needs to be converted to an active metabolite. If the antipsychotic is pharmacologically active, the PM phenotype will result in increased plasma concentration. Many antipsychotics have a narrow therapeutic window and reduced metabolism can result in concentration-dependent adverse effects, as illustrated in Fig. 2 (van der Weide et al., 2005). Patients with the IM phenotype are also likely to have increased exposure to drugs compared with EMs. However, the degree to which plasma levels are elevated and their clinical significance is often unclear. The UM phenotype can result in subtherapeutic drug levels when conventional doses are administered as the antipsychotic will be metabolized before it has a pharmacologic effect. The PM is most extensively studied for antipsychotics, particularly in those agents with a narrow therapeutic index. UM phenotype is clinically significant because of its wide distribution (Sistonen et al., 2009). In AEG 3482 to pharmacologically active agents, a prodrug must be metabolized to an active form. For some antipsychotics, the parent drug and its metabolite will both have activity, and variations in metabolism can have complex outcomes.
    Clinical outcomes studies
    Is CYP pharmacogenetics ready for clinical practice? Several laboratories offer Clinical Laboratory Improvement Amendments (CLIA)-approved CYP450 genotyping to identify known polymorphisms and these test results are currently being used in treatment decision making. In its Critical Path Initiative 2010, the US FDA emphasized the need to include pharmacogenetics language on product labeling where appropriate, and specific CYP450 pharmacogenetic recommendations can now be found on numerous package inserts (US Food and Drug Administration, 2012); however, the issue of whether to use pharmacogenetic testing to enhance outcomes in patients receiving antipsychotics is complex. There is a plausible biologic rationale, accumulating evidence linking genetic variation with drug response, and availability of reliable laboratory tests (Mrazek and Lerman, 2011). Conversely, the lack of large, high-quality studies has hindered consensus and widespread evidence-based recommendations. The major question is whether there is sufficient evidence that pharmacogenetic testing improves efficacy or safety in specific settings, such as the use of antipsychotics in adult patients with schizophrenia. Given the urgency of implementation and the plethora of potentially confounding factors involved in drug metabolism, it is unlikely that randomized controlled trials will be conducted for every clinical application of pharmacogenetic testing desirable. Therefore, the level of evidence needed for clinical implementation is currently being debated. The Clinical Pharmacogenetics Implementation Consortium (CPIC) of the Pharmacogenomics Research Network has argued that, given biologic plausibility and evidence of a gene–drug association, noninferiority when compared with current standards of prescribing is an acceptable threshold (Altman, 2011).