15 research outputs found
Physiologically Based Pharmacokinetic Modeling to Describe the CYP2D6 Activity Score-Dependent Metabolism of Paroxetine, Atomoxetine and Risperidone
The cytochrome P450 2D6 (CYP2D6) genotype is the single most important determinant of
CYP2D6 activity as well as interindividual and interpopulation variability in CYP2D6 activity. Here,
the CYP2D6 activity score provides an established tool to categorize the large number of CYP2D6
alleles by activity and facilitates the process of genotype-to-phenotype translation. Compared to
the broad traditional phenotype categories, the CYP2D6 activity score additionally serves as a
superior scale of CYP2D6 activity due to its finer graduation. Physiologically based pharmacokinetic
(PBPK) models have been successfully used to describe and predict the activity score-dependent
metabolism of CYP2D6 substrates. This study aimed to describe CYP2D6 drug–gene interactions
(DGIs) of important CYP2D6 substrates paroxetine, atomoxetine and risperidone by developing a
substrate-independent approach to model their activity score-dependent metabolism. The models
were developed in PK-Sim®, using a total of 57 plasma concentration–time profiles, and showed
good performance, especially in DGI scenarios where 10/12, 5/5 and 7/7 of DGI AUClast ratios and
9/12, 5/5 and 7/7 of DGI Cmax ratios were within the prediction success limits. Finally, the models
were used to predict their compound’s exposure for different CYP2D6 activity scores during steady
state. Here, predicted DGI AUCss ratios were 3.4, 13.6 and 2.0 (poor metabolizers; activity score = 0)
and 0.2, 0.5 and 0.95 (ultrarapid metabolizers; activity score = 3) for paroxetine, atomoxetine and
risperidone active moiety (risperidone + 9-hydroxyrisperidone), respectively
Prediction of Drug–Drug–Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling
Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the
treatment of anovulation for more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its
metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be
affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene
therapy may be susceptible to drug–gene interactions (DGIs), drug–drug interactions (DDIs) and
drug–drug–gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a
tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK
model of (E)-Clom including three important metabolites to describe and predict DGI and DD(G)I
effects. Model performance was evaluated both graphically and by calculating quantitative measures.
Here, 90% of predicted Cmax and 80% of AUClast values were within two-fold of the corresponding
observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed
quantitative contributions of different CYP enzymes to the involved metabolic pathways of (E)-Clom
and its metabolites. The developed PBPK model can be employed to assess the exposure of (E)-Clom
and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies
Study of the association between beta1-adrenoceptor polymorphisms and postoperative atrial fibrillation in patients after cardiac surgery
Vorhofflimmern (AFib), gehören zu den häufigsten unerwünschten Ereignissen im postoperativen Verlauf nach kardiochirurgischen Eingriffen.
Der vorliegenden Arbeit lag die Hypothese eines Zusammenhangs zwischen den Allelhäufigkeiten bestimmter Beta1-Adrenozeptor-Polymorphismen und dem Auftreten von postoperativem AFib zugrunde.
Eingeschlossen wurden 226 konsekutive Patienten, die sich einer Herzoperation mit extrakorporaler Zirkulation unterzogen, die präoperativ einen Sinusrhythmus aufwiesen und keine relevanten Rhythmusstörungen in der Vorgeschichte hatten.
Genomische DNA wurde aus peripheren Leukozyten (präoperative Blutabnahme ca. 9ml) isoliert und die Genotypisierung erfolgte für die Polymorphismen Ser49Gly und Arg389Gly mittels PCR-RFLP.
Postoperatives AFib trat bei 93 Patienten (41%) (AFib-Gruppe) auf und bei 133 Patienten (59%) nicht (non-AFib-Gruppe).
In der Subgruppe der ACB-Patienten (n=142) zeigte sich ein signifikanter Unterschied für den Ser49Gly Polymorphismus. Das Wildtyp-Allel (A145) kommt in der non-AFib-Gruppe (172) signifikant häufiger als in der AFib-Gruppe (74) vor (odds ratio 2,6; 95%-KI 1,29 bis 5,16; p=0,0089). Entsprechend ergab sich eine signifikant größere Häufigkeit des Wildtyp-Genotyps (Ser/Ser) in der non-AFib- (79) als in der AFib-Gruppe (29) (odds ratio 3,1; 95%-KI 1,38 bis 6,80; p=0,007). Für den Arg389Gly-Polymorphismus wurde keine Assoziation mit AFib gefunden.
Zusammenfassend haben Träger des Gly49 Allels des Beta1-Adrenozeptors ein statistisch signifikant höheres Risiko, nach einer ACB-Operation postoperatives AFib zu entwickeln.Atria fibrillation (Afib) is one of the most frequent complications of cardiac surgery. We hypothesized that allele frequencies of certain beta1-adrenoceptor polymorphisms are associated with the risk of postoperative Afib.
Patients (226) in sinus rhythm undergoing elective coronary artery bypass grafting and/or valve replacement but with no relevant Afib were examined. Genomic DNA was extracted from peripheral leukocytes and the genotyping for the Ser49Gly and Arg398Gly loci of beta1-adrenoceptor was performed using PCR-RFLP.
To check for Afib, electrocardiograms were taken daily until day 6 after surgery. Beta-blocker medication was permitted.
93 (41%) patients developed pstoperative Afib and 133 (59%) patients did not.
In the group of patients after coronary artery bypass grafting there was a significant difference in the allele frequency of Ser49Gly polymorphism between Afib- and non-Afib- patients. The wildtype allele A145 was significantly more frequent (odds ratio 2.6; 95%-Cl 1.29 to 5.16; P=0.0089) in non-Afib patients than in Afib patients. Accordingly, carriers of the wildtype genotype (Ser/Ser) were significantly more frequent (odds ratio 3.1; 95%-CI 1.38 to 6.80; P=0.007) among non-Afib than in Afib patients. No association of the Arg389GIy polymorphism with Afib development was observed.
We conclude that the carriers of the Gly49 allele of the beta1-adrenoceptor have statistlically significantly higher risk of developing a postoperative Afib after cardiac surgery
Personalising drug safety-results from the multi-centre prospective observational study on Adverse Drug Reactions in Emergency Departments (ADRED)
Prevalence of a first-degree relative with colorectal cancer and uptake of screening among persons 40 to 54 years old
Impact of NUDT15 genetics on severe thiopurine-related hematotoxicity in patients with European ancestry
Stereoselective quantification of phase 1 and 2 metabolites of clomiphene in human plasma and urine
Prediction of Drug-Drug-Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling
Study protocol of the RaPS study: novel risk adapted prevention strategies for people with a family history of colorectal cancer
Abstract Background People aged 40–60 years with a family history (FH) of colorectal cancer (CRC) in 1st degree relatives (FDRs) have a 2- to 4-fold increased risk of CRC compared to the average risk population. Therefore, experts recommend starting CRC screening earlier for this high-risk group. However, information on prevalence of relevant colonoscopic findings in this group is sparse, and no risk adapted screening offers are implemented in the German health care system. For example, screening colonoscopy is uniformly offered from age 55 on, regardless of family history. Thus, we initiated a multicenter epidemiological study - the RaPS study (Risk adapted prevention strategies for colorectal cancer) – with the following aims: to determine the prevalence of having a FH of CRC in FDR in the German population aged 40–54 years; to investigate the prevalence of colorectal neoplasms among people with a FDR; and to develop risk-adapted prevention strategies for this high-risk group based on the collected information. Methods/Design A random sample of 160.000 persons from the general population aged 40–54 years from the catchment areas of three study centers in Germany (Dresden, Munich and Stuttgart) are contacted to assess FH of CRC by an online-questionnaire. Those with a FH of CRC in FDRs are invited to the study centers for individual consultation regarding CRC prevention. Participants are asked to donate blood and stool samples and medical records of colonoscopies will be obtained. Prevalence of CRC and its precursors will be evaluated. Furthermore, genetic, epigenetic and proteomic biomarkers in blood and microbiomic biomarkers in stool will be investigated. Risk markers and their eligibility for risk adapted screening offers will be examined. Discussion This study will provide data on the prevalence of colorectal neoplasms among persons with a FH of CRC in the age group 40–54 years, which will enable us to derive evidence based screening strategies for this high-risk group. Trial registration This trial was registered retrospectively in the German Clinical Trials Register (DRKS) on 29th of December 2016: German Clinical Trials Register DRKS-ID: DRKS00007842
Prediction of Drug–Drug–Gene Interaction Scenarios of (E)-Clomiphene and Its Metabolites Using Physiologically Based Pharmacokinetic Modeling
Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation for more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 and CYP3A4, exposure can be affected by CYP2D6 polymorphisms and concomitant use with CYP inhibitors. Thus, clomiphene therapy may be susceptible to drug–gene interactions (DGIs), drug–drug interactions (DDIs) and drug–drug–gene interactions (DDGIs). Physiologically based pharmacokinetic (PBPK) modeling is a tool to quantify such DGI and DD(G)I scenarios. This study aimed to develop a whole-body PBPK model of (E)-Clom including three important metabolites to describe and predict DGI and DD(G)I effects. Model performance was evaluated both graphically and by calculating quantitative measures. Here, 90% of predicted Cmax and 80% of AUClast values were within two-fold of the corresponding observed value for DGIs and DD(G)Is with clarithromycin and paroxetine. The model also revealed quantitative contributions of different CYP enzymes to the involved metabolic pathways of (E)-Clom and its metabolites. The developed PBPK model can be employed to assess the exposure of (E)-Clom and its active metabolites in as-yet unexplored DD(G)I scenarios in future studies