View clinical trials related to Pharmacogenomics.
Filter by:Individual differences in drug efficacy and adverse reactions are common in the clinical application of drugs. Individual differences are caused by many factors, among which genetic factors account for more than 20%. Novel oral anticoagulant drugs (NOACs, including rivaroxaban, apixaban, edoxaban, dabigatran, etc.) and novel antiplatelet drug ticagrelor have the advantages of convenient use and no need for monitoring. But novel oral antithrombotic drugs also increase the risk of bleeding, and there is currently a lack of effective antagonists when antithrombosis is excessive or emergency surgery is required. At present, there are few studies on the causes of individual differences in novel antithrombotic drugs, and there is a lack of predictable biomarkers or drug genotypes, especially in China. Therefore, on the basis of previous studies on NOACs and ticagrelor individualized medication cohorts, this study plans to establish a validation cohort for novel antithrombotic drugs bleeding related biomarkers, conduct multi-omics testing and long-term follow-up, and explore markers related to pharmacodynamics of antithrombotic drugs, adverse bleeding reactions and clinical outcomes.
Based on pharmacogenomics analysis technology, this topic explored its impact on individualized precise treatment of patients with depression through randomized controlled trials. The study subjects were depression patients from the mental health research center affiliated to Tongji University. The sample size was estimated by PASS 21.0.3 software. The sample size of the intervention group and the control group was 60 cases each, and SPSS 25.0 software was used for random sampling. The intervention group completed the pharmacogenomic analysis of antidepressants before using them, and selected appropriate antidepressants according to the characteristics of pharmacokinetics and pharmacodynamics of individual patients, while the control group was administered according to routine treatment. 17 items Hamilton Compression Scale (HAMD-17), Hamilton Anxiety Scale (HAMA), Dimensional Anhedonia Rating Scale (DARS), Pittsburgh sleep quality index (PSQI), Antidepressant Side Effect Checklist (ASEC), Short form 36 item health survey questionnaire (SF-36) (PDQ) assessment. R Project 4.1.1 software was used for statistical analysis of data, PLink v1.07 and Haploview software were used for association analysis of whole genome and drug efficacy and adverse reactions. To explore the difference between the reduction rate of drug efficacy and adverse reactions in patients with depression after pharmacogenomics intervention and conventional treatment. At the same time, we verified and found the gene loci related to the efficacy and adverse reactions of antidepressants in the East Asian population.
The aim of this works is to investigate the effect of genetic variation of UGT2B7 on human response to treatment with indapamide and its correlation with pharmacokinetic parameters in Egyptian subjects.