The Influence of Pharmacogenetics on the Clinical Relevance of Pharmacokinetic Drug–Drug Interactions: Drug–Gene, Drug–Gene–Gene and Drug–Drug–Gene Interactions

Hahn, Martina; Roll, Sibylle C.

doi:10.3390/ph14050487

Cited by 33 publications

(44 citation statements)

References 42 publications

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“…None of the cases reported in this article presented significant pharmacological interactions allowing to explain either the reported clinical phenotype or the CDKis plasma levels detected. An integrated clinical pharmacology approach should always be considered in association with pharmacogenetic profiling to better define potential phenoconversion, and avoid conflicting results often observed in DGIs association studies ( Shah and Smith, 2015 ; Hahn and Roll, 2021 ). Evaluation of DDIs that can compromise optimal drug exposure is part of clinical practice, although not systematically applied ( Dürr et al, 2021 ; Leenhardt et al, 2021 ).…”

Section: Discussionmentioning

confidence: 99%

An Integrated Pharmacological Counselling Approach to Guide Decision-Making in the Treatment with CDK4/6 Inhibitors for Metastatic Breast Cancer

et al. 2022

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A wide inter-individual variability in the therapeutic response to cyclin-dependent kinases 4 and 6 inhibitors (CDKis) has been reported. We herein present a case series of five patients treated with either palbociclib or ribociclib referred to our clinical pharmacological counselling, including therapeutic drug monitoring (TDM), pharmacogenetics, and drug–drug interaction analysis to support clinicians in the management of CDKis treatment for metastatic breast cancer. Patients’ plasma samples for TDM analysis were collected at steady state and analyzed by an LC-MS/MS method for minimum plasma concentration (Cmin) evaluation. Under and overexposure to the drug were defined based on the mean Cmin values observed in population pharmacokinetic studies. Polymorphisms in selected genes encoding for proteins involved in drug absorption, distribution, metabolism, and elimination were analyzed (CYP3A4, CYP3A5, ABCB1, SLCO1B1, and ABCG2). Three of the five reported cases presented a CDKi plasma level above the population mean value and were referred for toxicity. One of them presented a low function ABCB1 haplotype (ABCB1-rs1128503, rs1045642, and rs2032582), possibly causative of both increased drug oral absorption and plasmatic concentration. Two patients showed underexposure to CDKis, and one of them was referred for early progression. In one patient, a CYP3A5*1/*3 genotype was found to be potentially responsible for more efficient drug metabolism and lower drug plasma concentration. This intensified pharmacological approach in clinical practice has been shown to be potentially effective in supporting prescribing oncologists with dose and drug selection and could be ultimately useful for increasing both the safety and efficacy profiles of CDKi treatment.

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Section: Discussionmentioning

confidence: 99%

An Integrated Pharmacological Counselling Approach to Guide Decision-Making in the Treatment with CDK4/6 Inhibitors for Metastatic Breast Cancer

et al. 2022

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“…This potential confounder involving drug-drug interactions can ultimately influence the prevalence of DGIs and treatment response. For example, concomitant administration of medications such as bupropion, fluoxetine and paroxetine which are CYP2D6 inhibitors could result in an adjusted CYP2D6 phenotype that is different to genotype-based prediction of drug metabolism ( Owen et al, 2009 ; Cicali et al, 2021 ; Hahn and Roll, 2021 ). Another limitation in our sub-analysis includes the small number of patients restricting additional data analyses related to RAR and race/ethnicity ( Ruaño et al, 2020 ).…”

Section: Discussionmentioning

confidence: 99%

Sub-Analysis of CYP-GUIDES Data: Assessing the Prevalence and Impact of Drug-Gene Interactions in an Ethnically Diverse Cohort of Depressed Individuals

Crutchley

Keuler

2022

Front. Pharmacol.

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Introduction: Minority groups are underrepresented in pharmacogenomics (PGx) research. Recent sub-analysis of CYP-GUIDES showed reduced length of stay (LOS) in depressed patients with CYP2D6 sub-functional status. Our primary objective was to determine whether PGx guided (G) versus standard treatment (S) influenced LOS among different race/ethnic groups. Secondary objectives included prevalence of drug-gene interactions (DGIs) and readmission rates (RAR).Methods: Retrospective sub-analysis of CYP-GUIDES data comprising CYP2D6 phenotypes was reclassified using standardized CYP2D6 genotype to phenotype recommendations from the Clinical Pharmacogenetics Implementation Consortium (CPIC) and Dutch Pharmacogenetics Working Group (DPWG). The Mann-Whitney test was used to determine differences in LOS between groups G and S and Kruskal Wallis test to compare LOS among different race/ethnic groups. Logistic regression was used to determine covariates associated with RAR.Results: This study included 1,459 patients with 67.3% in G group (n = 982). The majority of patients were White (57.5%), followed by Latinos (25.6%) and Blacks (12.3%). Although there were no differences in LOS between G and S groups, Latinos had significant shorter LOS than Whites (p = 0.002). LOS was significantly reduced by 5.6 days in poor metabolizers in group G compared to S (p = 0.002). The proportion of supra functional and ultra-rapid metabolizers (UMs) were 6 and 20.3% using CYP-GUIDES and CPIC/DPWG definitions, respectively. Prevalence of DGIs was 40% with significantly fewer DGIs in Blacks (p < 0.001). Race/ethnicity was significantly associated with RAR (aOR 1.30; p = 0.003).Conclusion: A greater number of patients were classified as CYP2D6 UMs using CPIC/DPWG definitions as compared to CYP-GUIDES definitions. This finding may have clinical implications for using psychotropics metabolized by CYP2D6.

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“…The clinical relevance of drug–drug interactions also depends on the patient’s genetic profile. Drug–drug–gene and drug–gene–gene interactions affect the therapeutic properties of drugs ( Hahn and Roll, 2021 ). A method for calculating drug similarity using drug–gene associations was proposed by Groza et al (2021) .…”

Section: Methodsmentioning

confidence: 99%

Drug Repositioning with GraphSAGE and Clustering Constraints Based on Drug and Disease Networks

et al. 2022

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The understanding of therapeutic properties is important in drug repositioning and drug discovery. However, chemical or clinical trials are expensive and inefficient to characterize the therapeutic properties of drugs. Recently, artificial intelligence (AI)-assisted algorithms have received extensive attention for discovering the potential therapeutic properties of drugs and speeding up drug development. In this study, we propose a new method based on GraphSAGE and clustering constraints (DRGCC) to investigate the potential therapeutic properties of drugs for drug repositioning. First, the drug structure features and disease symptom features are extracted. Second, the drug–drug interaction network and disease similarity network are constructed according to the drug–gene and disease–gene relationships. Matrix factorization is adopted to extract the clustering features of networks. Then, all the features are fed to the GraphSAGE to predict new associations between existing drugs and diseases. Benchmark comparisons on two different datasets show that our method has reliable predictive performance and outperforms other six competing. We have also conducted case studies on existing drugs and diseases and aimed to predict drugs that may be effective for the novel coronavirus disease 2019 (COVID-19). Among the predicted anti-COVID-19 drug candidates, some drugs are being clinically studied by pharmacologists, and their binding sites to COVID-19-related protein receptors have been found via the molecular docking technology.

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The Influence of Pharmacogenetics on the Clinical Relevance of Pharmacokinetic Drug–Drug Interactions: Drug–Gene, Drug–Gene–Gene and Drug–Drug–Gene Interactions

Cited by 33 publications

References 42 publications

An Integrated Pharmacological Counselling Approach to Guide Decision-Making in the Treatment with CDK4/6 Inhibitors for Metastatic Breast Cancer

An Integrated Pharmacological Counselling Approach to Guide Decision-Making in the Treatment with CDK4/6 Inhibitors for Metastatic Breast Cancer

Sub-Analysis of CYP-GUIDES Data: Assessing the Prevalence and Impact of Drug-Gene Interactions in an Ethnically Diverse Cohort of Depressed Individuals

Drug Repositioning with GraphSAGE and Clustering Constraints Based on Drug and Disease Networks

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