IntroductionDifficulties in non-vitamin K anticoagulant (NOAC) administration in acute stroke can be associated with changes in pharmacokinetic parameters of NOAC such as biotransformation, distribution, and excretion. Therefore, obtaining data on pharmacokinetics of NOAC and factors that affect it may help develop algorithms for personalized use of this drug class in patients with acute cardioembolic stroke.Patients and methodsPharmacokinetics of apixaban in patients with acute stroke was studied earlier by Kryukov et al. The present study enrolled 17 patients with cardioembolic stroke, who received 5 mg of apixaban. In order to evaluate the pharmacokinetic parameters of apixaban, venous blood samples were collected before taking 5 mg of apixaban (point 0) and 1, 2, 3, 4, 10, and 12 hours after drug intake. Blood samples were centrifuged at 3000 rpm for 15 minutes. Separate plasma was aliquoted in Eppendorf tubes and frozen at −70°C until analysis. High-performance liquid chromatography mass spectrometry analysis was used to determine apixaban plasma concentration. Genotyping was performed by real-time polymerase chain reaction. CYP3A isoenzyme group activity was evaluated by determining urinary concentration of endogenous substrate of the enzyme and its metabolite (6-β-hydroxycortisol to cortisol ratio). Statistical analysis was performed using SPSS Statistics version 20.0. The protocol of this study was reviewed and approved by the ethics committee; patients or their representatives signed an informed consent.ResultsABCB1 (rs1045642 and rs4148738) gene polymorphisms do not affect the pharmacokinetics of apixaban as well as CYP3A5 (rs776746) gene polymorphisms. Apixaban pharmacokinetics in groups with different genotypes did not differ statistically significantly. Correlation analysis showed no statistically significant relationship between pharmacokinetic parameters of apixaban and the metabolic activity of CYP3A.ConclusionQuestions such as depending on genotyping results for apixaban dosing and implementation of express genotyping in clinical practice remain open for NOACs. Large population studies are required to clarify the clinical significance of genotyping for this drug class.
ObjectivesAlthough pharmacogenetic tests provide the information on a genotype and the predicted phenotype, these tests do not themselves provide the interpretation of data for a physician. Currently, there are approximately two dozen pharmacogenomic clinical decision support systems (CDSSs) used in psychiatry. Implementation of the CDSSs forming the recommendations on drug and dose selection according to the results of pharmacogenetic testing is an urgent task. Fulfillment of this task will allow increasing the efficacy of therapy and decreasing the risk of undesirable side effects.MethodsThe study included 118 male patients (48 in the main group and 70 in the control group) with affective disorders and comorbid alcohol use disorder. To evaluate the efficacy and safety of therapy, several international psychometric scales and rating scales to measure side effects were used. Genotyping was performed using the real-time polymerase chain reaction with allele-specific hybridization. Pharmacogenetic testing results were interpreted using free software PGX2 (LLE Medicine, Russian Federation, Biomedical Cluster of Skolkovo, Moscow Innovative Cluster; www.pgx2.com).ResultsThe statistically significant differences across the scores on psychometric scales were revealed. For instance, the total score on the Hamilton Rating Scale for Depression by day 9 was 9.0 [8.0; 10.0] for the main group and 11.0 [10.0; 12.0] (p<0.001) for the control group and by day 16 it was 4.0 [2.0; 6.0] for the main group and 14.0 [13.0; 14.0] (p<0.001) for the control group. The UKU Side-Effect Rating Scale (UKU) also revealed a statistically significant difference. The total score on the UKU scale by day 9 was 4.0 [4.0; 5.0] for the main group and 5.0 [5.0; 6.0] (p<0.001) for the control group and by day 16 this difference grew significantly: 3.0 [0.0; 4.2] for the main group and 9.0 [7.0; 11.0] (p<0.001) for the control group.ConclusionsPharmacogenetic-guided personalization of the drug dose in patients with affective disorders and comorbid alcohol use disorder can reduce the risk of undesirable side effects and pharmacoresistance. It allows recommending the use of pharmacogenetic CDSSs for optimizing drug dosage.
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