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Clinical Pharmacology and Therapeutics Jun 2021Proton pump inhibitors (PPIs) are widely used for acid suppression in the treatment and prevention of many conditions, including gastroesophageal reflux disease, gastric...
Proton pump inhibitors (PPIs) are widely used for acid suppression in the treatment and prevention of many conditions, including gastroesophageal reflux disease, gastric and duodenal ulcers, erosive esophagitis, Helicobacter pylori infection, and pathological hypersecretory conditions. Most PPIs are metabolized primarily by cytochrome P450 2C19 (CYP2C19) into inactive metabolites, and CYP2C19 genotype has been linked to PPI exposure, efficacy, and adverse effects. We summarize the evidence from the literature and provide therapeutic recommendations for PPI prescribing based on CYP2C19 genotype (updates at www.cpicpgx.org). The potential benefits of using CYP2C19 genotype data to guide PPI therapy include (i) identifying patients with genotypes predictive of lower plasma exposure and prescribing them a higher dose that will increase the likelihood of efficacy, and (ii) identifying patients on chronic therapy with genotypes predictive of higher plasma exposure and prescribing them a decreased dose to minimize the risk of toxicity that is associated with long-term PPI use, particularly at higher plasma concentrations.
Topics: Cytochrome P-450 CYP2C19; Gastroesophageal Reflux; Genotype; Humans; Pharmacogenetics; Proton Pump Inhibitors
PubMed: 32770672
DOI: 10.1002/cpt.2015 -
British Journal of Clinical Pharmacology May 2021Hypophosphataemia is an increasingly recognized side-effect of ferric carboxymaltose (FCM) and possibly iron isomaltoside/ferric derisomaltose (IIM), which are used to... (Meta-Analysis)
Meta-Analysis Review
AIMS
Hypophosphataemia is an increasingly recognized side-effect of ferric carboxymaltose (FCM) and possibly iron isomaltoside/ferric derisomaltose (IIM), which are used to treat iron deficiency. The aim of this study was to determine frequency, severity, duration and risk factors of incident hypophosphataemia after treatment with FCM and IIM.
METHODS
A systematic literature search for articles indexed in EMBASE, PubMed and Web of Science in years 2005-2020 was carried out using the search terms 'ferric carboxymaltose' OR 'iron isomaltoside'. Prospective clinical trials reporting outcomes on hypophosphataemia rate, mean nadir serum phosphate and/or change in mean serum phosphate from baseline were selected. Hypophosphataemia rate and severity were compared for studies on IIM vs. FCM after stratification for chronic kidney disease. Meta-regression analysis was used to investigate risk factors for hypophosphataemia.
RESULTS
Across the 42 clinical trials included in the meta-analysis, FCM induced a significantly higher incidence of hypophosphataemia than IIM (47%, 95% CI 36-58% vs. 4%, 95% CI 2-5%), and significantly greater mean decreases in serum phosphate (0.40 vs. 0.06 mmol/L). Hypophosphataemia persisted at the end of the study periods (maximum 3 months) in up to 45% of patients treated with FCM. Meta-regression analysis identified low baseline serum ferritin and transferrin saturation, and normal kidney function as significant predictors of hypophosphataemia.
CONCLUSION
FCM is associated with a high risk of hypophosphataemia, which does not resolve for at least 3 months in a large proportion of affected patients. More severe iron deficiency and normal kidney function are risk factors for hypophosphataemia.
Topics: Administration, Intravenous; Anemia, Iron-Deficiency; Disaccharides; Ferric Compounds; Fibroblast Growth Factor-23; Humans; Hypophosphatemia; Maltose; Prospective Studies
PubMed: 33188534
DOI: 10.1111/bcp.14643 -
Clinical Pharmacology and Therapeutics Aug 2020Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most commonly used analgesics due to their lack of addictive potential. However, NSAIDs have the potential to... (Meta-Analysis)
Meta-Analysis
Nonsteroidal anti-inflammatory drugs (NSAIDs) are among the most commonly used analgesics due to their lack of addictive potential. However, NSAIDs have the potential to cause serious gastrointestinal, renal, and cardiovascular adverse events. CYP2C9 polymorphisms influence metabolism and clearance of several drugs in this class, thereby affecting drug exposure and potentially safety. We summarize evidence from the published literature supporting these associations and provide therapeutic recommendations for NSAIDs based on CYP2C9 genotype (updates at www.cpicpgx.org).
Topics: Anti-Inflammatory Agents, Non-Steroidal; Clinical Decision-Making; Consensus; Cytochrome P-450 CYP2C9; Drug Interactions; Drug-Related Side Effects and Adverse Reactions; Genotype; Humans; Pharmacogenetics; Pharmacogenomic Testing; Pharmacogenomic Variants; Phenotype; Predictive Value of Tests; Risk Assessment; Risk Factors
PubMed: 32189324
DOI: 10.1002/cpt.1830 -
European Journal of Human Genetics :... Mar 2024The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to...
The Dutch Pharmacogenetics Working Group (DPWG) aims to facilitate pharmacogenetics implementation in clinical practice by developing evidence-based guidelines to optimize pharmacotherapy. A guideline describing the gene-drug interaction between the genes CYP2D6, CYP3A4 and CYP1A2 and antipsychotics is presented here. The DPWG identified gene-drug interactions that require therapy adjustments when respective genotype is known for CYP2D6 with aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol, and for CYP3A4 with quetiapine. Evidence-based dose recommendations were obtained based on a systematic review of published literature. Reduction of the normal dose is recommended for aripiprazole, brexpiprazole, haloperidol, pimozide, risperidone and zuclopenthixol for CYP2D6-predicted PMs, and for pimozide and zuclopenthixol also for CYP2D6 IMs. For CYP2D6 UMs, a dose increase or an alternative drug is recommended for haloperidol and an alternative drug or titration of the dose for risperidone. In addition, in case of no or limited clinical effect, a dose increase is recommended for zuclopenthixol for CYP2D6 UMs. Even though evidence is limited, the DPWG recommends choosing an alternative drug to treat symptoms of depression or a dose reduction for other indications for quetiapine and CYP3A4 PMs. No therapy adjustments are recommended for the other CYP2D6 and CYP3A4 predicted phenotypes. In addition, no action is required for the gene-drug combinations CYP2D6 and clozapine, flupentixol, olanzapine or quetiapine and also not for CYP1A2 and clozapine or olanzapine. For identified gene-drug interactions requiring therapy adjustments, genotyping of CYP2D6 or CYP3A4 prior to treatment should not be considered for all patients, but on an individual patient basis only.
Topics: Humans; Antipsychotic Agents; Aripiprazole; Clopenthixol; Clozapine; Cytochrome P-450 CYP1A2; Cytochrome P-450 CYP2D6; Cytochrome P-450 CYP3A; Drug Interactions; Haloperidol; Olanzapine; Pharmacogenetics; Pimozide; Quetiapine Fumarate; Quinolones; Risperidone; Thiophenes
PubMed: 37002327
DOI: 10.1038/s41431-023-01347-3 -
Clinical Pharmacology and Therapeutics Feb 2018The purpose of this guideline is to provide information for the interpretation of clinical dihydropyrimidine dehydrogenase (DPYD) genotype tests so that the results can...
The purpose of this guideline is to provide information for the interpretation of clinical dihydropyrimidine dehydrogenase (DPYD) genotype tests so that the results can be used to guide dosing of fluoropyrimidines (5-fluorouracil and capecitabine). Detailed guidelines for the use of fluoropyrimidines, their clinical pharmacology, as well as analyses of cost-effectiveness are beyond the scope of this document. The Clinical Pharmacogenetics Implementation Consortium (CPIC ) guidelines consider the situation of patients for which genotype data are already available (updates available at https://cpicpgx.org/guidelines/guideline-for-fluoropyrimidines-and-dpyd/).
Topics: Antimetabolites, Antineoplastic; Capecitabine; Clinical Decision-Making; Dihydrouracil Dehydrogenase (NADP); Drug Dosage Calculations; Fluorouracil; Genotype; Humans; Patient Selection; Pharmacogenetics; Pharmacogenomic Testing; Pharmacogenomic Variants; Phenotype; Precision Medicine; Predictive Value of Tests
PubMed: 29152729
DOI: 10.1002/cpt.911 -
Current Neuropharmacology 2023Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML)...
Traditional medicine and biomedical sciences are reaching a turning point because of the constantly growing impact and volume of Big Data. Machine Learning (ML) techniques and related algorithms play a central role as diagnostic, prognostic, and decision-making tools in this field. Another promising area becoming part of everyday clinical practice is personalized therapy and pharmacogenomics. Applying ML to pharmacogenomics opens new frontiers to tailored therapeutical strategies to help clinicians choose drugs with the best response and fewer side effects, operating with genetic information and combining it with the clinical profile. This systematic review aims to draw up the state-of-the-art ML applied to pharmacogenomics in psychiatry. Our research yielded fourteen papers; most were published in the last three years. The sample comprises 9,180 patients diagnosed with mood disorders, psychoses, or autism spectrum disorders. Prediction of drug response and prediction of side effects are the most frequently considered domains with the supervised ML technique, which first requires training and then testing. The random forest is the most used algorithm; it comprises several decision trees, reduces the training set's overfitting, and makes precise predictions. ML proved effective and reliable, especially when genetic and biodemographic information were integrated into the algorithm. Even though ML and pharmacogenomics are not part of everyday clinical practice yet, they will gain a unique role in the next future in improving personalized treatments in psychiatry.
Topics: Humans; Pharmacogenetics; Precision Medicine; Machine Learning; Mental Disorders; Psychiatry
PubMed: 37559539
DOI: 10.2174/1570159X21666230808170123 -
Journal of Psychiatric Research Nov 2021Ketamine is a dissociative anesthetic used worldwide for anesthesia, pain management, treatment resistant depression (TRD) and suicidality. Predictors of antidepressant... (Review)
Review
Ketamine is a dissociative anesthetic used worldwide for anesthesia, pain management, treatment resistant depression (TRD) and suicidality. Predictors of antidepressant response and adverse effects to ketamine remain poorly understood due to contradictory results. The objective of the systematic review herein is to identify and evaluate the extant literature assessing pharmacogenomic predictors of ketamine clinical benefits and adverse effects. Electronic databases were searched from inception to July 2021 to identify relevant articles. Twelve articles involving 1,219 participants with TRD, 75 who underwent elective surgeries and received ketamine as an anesthetic, 49 with pain, and 68 healthy participants met the inclusion criteria and enrolled to this review. While identified articles reported mixed results, three predictors emerged: 1) Val66Met (rs6265) brain derived neurotrophic factor (BDNF; Met allele) was associated with reduced antidepressant and anti-suicidal effects, 2) CYP2B6*6 (e.g., CYB2B6 metabolizer) was associated with more severe dissociative effects and 3) NET allelic (rs28386840) variant were associated with greater cardiovascular complications (e.g., moderate to severe treatment emergent hypertension). Several important limitations were identified, most notably the small sample sizes and heterogeneity of study design and results. Taken together, preliminary evidence suggests the potential for pharmacogenomic testing to inform clinical practices; however, further research is needed to better determine genetic variants of greatest importance and the clinical validity of pharmacogenomics to help guide ketamine treatment planning.
PubMed: 34844049
DOI: 10.1016/j.jpsychires.2021.11.036 -
British Journal of Clinical Pharmacology Apr 2021Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the... (Review)
Review
AIMS
Numerous algorithms have been developed to guide warfarin dosing and improve clinical outcomes. We reviewed the algorithms available for various populations and the covariates, performances and risk of bias of these algorithms.
METHODS
We systematically searched MEDLINE up to 20 May 2020 and selected studies describing the development, external validation or clinical utility of a multivariable warfarin dosing algorithm. Two investigators conducted data extraction and quality assessment.
RESULTS
Of 10 035 screened records, 266 articles were included in the review, describing the development of 433 dosing algorithms, 481 external validations and 52 clinical utility assessments. Most developed algorithms were for dose initiation (86%), developed by multiple linear regression (65%) and mostly applicable to Asians (49%) or Whites (43%). The most common demographic/clinical/environmental covariates were age (included in 401 algorithms), concomitant medications (270 algorithms) and weight (229 algorithms) while CYP2C9 (329 algorithms), VKORC1 (319 algorithms) and CYP4F2 (92 algorithms) variants were the most common genetic covariates. Only 26% and 7% algorithms were externally validated and evaluated for clinical utility, respectively, with <2% of algorithm developments and external validations being rated as having a low risk of bias.
CONCLUSION
Most warfarin dosing algorithms have been developed in Asians and Whites and may not be applicable to under-served populations. Few algorithms have been externally validated, assessed for clinical utility, and/or have a low risk of bias which makes them unreliable for clinical use. Algorithm development and assessment should follow current methodological recommendations to improve reliability and applicability, and under-represented populations should be prioritized.
Topics: Algorithms; Anticoagulants; Cytochrome P-450 CYP2C9; Dose-Response Relationship, Drug; Genotype; Humans; Pharmacogenetics; Reproducibility of Results; Vitamin K Epoxide Reductases; Warfarin
PubMed: 33080066
DOI: 10.1111/bcp.14608 -
Clinical Pharmacokinetics Aug 2015Tramadol hydrochloride is used worldwide as an analgesic drug with a unique dual function. The metabolic enzymes cytochrome P450 (CYP) 3A4, CYP2B6, and CYP2D6 and the... (Review)
Review
BACKGROUND AND OBJECTIVE
Tramadol hydrochloride is used worldwide as an analgesic drug with a unique dual function. The metabolic enzymes cytochrome P450 (CYP) 3A4, CYP2B6, and CYP2D6 and the various transporters [adenosine triphosphate-binding cassette B1/multidrug resistance 1/P-glycoprotein, organic cation transporter 1, serotonin transporter (SERT), norepinephrine transporter (NET)] and receptor genes (opioid receptor μ 1 gene) give possible genetic differences that might affect the pharmacokinetics and/or pharmacodynamics of tramadol. Therefore, the aim of this review is to present a systematic walkthrough of all possible genetic factors involved in the pharmacology of tramadol.
METHOD
A systematic literature search was conducted in PubMed and EMBASE involving all metabolic enzymes, drug transporters and receptors, as well as SERT and NET that are involved in the pharmacokinetics and pharmacodynamics of tramadol. An additional search on population pharmacokinetics with genetic factors as covariates was performed separately.
RESULTS
A total of 56 studies (45 cohort and case-control studies, three case reports, six in vitro studies, and two animal studies) were included.
CONCLUSION
In this systematic review, the current knowledge on all possible genetic factors that might influence the metabolism or clinical efficacy of tramadol has been collected and summarized. Only the effect of CYP2D6 polymorphisms on the metabolism of tramadol and the consequent effect on pain relief has been thoroughly studied and sufficiently established as clinically relevant.
Topics: Analgesics, Opioid; Animals; Biological Availability; Case-Control Studies; Clinical Studies as Topic; Cohort Studies; Cytochrome P-450 CYP2D6; Humans; Pain; Pharmacogenetics; Tramadol
PubMed: 25910878
DOI: 10.1007/s40262-015-0268-0 -
Journal of Personalized Medicine Jun 2022Pharmacogenetics research on leukotriene modifiers (LTMs) for asthma has been developing rapidly, although pharmacogenetic testing for LTMs is not yet used in clinical...
Pharmacogenetics research on leukotriene modifiers (LTMs) for asthma has been developing rapidly, although pharmacogenetic testing for LTMs is not yet used in clinical practice. We performed a systematic review and meta-analysis on the impact of pharmacogenomics on LTMs response. Studies published until May 2022 were searched using PubMed, EMBASE, and Cochrane databases. Pharmacogenomics/genetics studies of patients with asthma using LTMs with or without other anti-asthmatic drugs were included. Statistical tests of the meta-analysis were performed with Review Manager (Revman, version 5.4, The Cochrane Collaboration, Copenhagen, Denmark) and R language and environment for statistical computing (version 4.1.0 for Windows, R Core Team, Vienna, Austria) software. In total, 31 studies with 8084 participants were included in the systematic review and five studies were also used to perform the meta-analysis. Two included studies were genome-wide association studies (GWAS), which showed different results. Furthermore, none of the SNPs investigated in candidate gene studies were identified in GWAS. In candidate gene studies, the most widely studied SNPs were ALOX5 (tandem repeats of the Sp1-binding domain and rs2115819), LTC4S-444A/C (rs730012), and SLCO2B1 (rs12422149), with relatively inconsistent conclusions. LTC4S-444A/C polymorphism did not show a significant effect in our meta-analysis (AA vs. AC (or AC + CC): −0.06, 95%CI: −0.16 to 0.05, p = 0.31). AA homozygotes had smaller improvements in parameters pertaining to lung functions (−0.14, 95%CI: −0.23 to −0.05, p = 0.002) in a subgroup of patients with non-selective CysLT receptor antagonists and patients without inhaled corticosteroids (ICS) (−0.11, 95%CI: −0.14 to −0.08, p < 0.00001), but not in other subgroups. Variability exists in the pharmacogenomics of LTMs treatment response. Our meta-analysis and systematic review found that LTC4S-444A/C may influence the treatment response of patients taking non-selective CysLT receptor antagonists for asthma, and patients taking LTMs not in combination with ICS for asthma. Future studies are needed to validate the pharmacogenomic influence on LTMs response.
PubMed: 35887565
DOI: 10.3390/jpm12071068