A5066134767- Pharmacogenetics and Drug Metabolism
- Analytical Chemistry and Chromatography
- Analytical Methods in Pharmaceuticals
- Computational Drug Discovery Methods
- PI3K/AKT/mTOR signaling in cancer
- Chronic Myeloid Leukemia Treatments
- Blood groups and transfusion
- Pharmacological Effects and Toxicity Studies
- Lung Cancer Treatments and Mutations
- Hormonal Regulation and Hypertension
- Renal Transplantation Outcomes and Treatments
- Statistical Methods in Clinical Trials
- HIV/AIDS drug development and treatment
- Hematopoietic Stem Cell Transplantation
- Estrogen and related hormone effects
- Platelet Disorders and Treatments
- Chronic Lymphocytic Leukemia Research
Dr. Margarete Fischer-Bosch-Institute of Clinical Pharmacology
2020-2025
Saarland University
2020-2024
University of Tübingen
2022
Abstract This study provides a whole‐body physiologically‐based pharmacokinetic (PBPK) model of dextromethorphan and its metabolites dextrorphan O ‐glucuronide for predicting the effects cytochrome P450 2D6 (CYP2D6) drug‐gene interactions (DGIs) on pharmacokinetics (PK). Moreover, effect interindividual variability (IIV) within CYP2D6 activity score groups PK was investigated. A parent‐metabolite‐metabolite PBPK dextromethorphan, dextrorphan, developed in PK‐Sim MoBi. Drug‐dependent...
Abstract The immunosuppressant and narrow therapeutic index drug tacrolimus is metabolized mainly via cytochrome P450 (CYP) 3A4 CYP3A5. For its pharmacokinetics (PK), high inter‐ intra‐individual variability can be observed. Underlying causes include the effect of food intake on absorption as well genetic polymorphism in CYP3A5 gene. Furthermore, highly susceptible to drug–drug interactions, acting a victim when coadministered with CYP3A perpetrators. This work describes development...
The antiarrhythmic agent quinidine is a potent inhibitor of cytochrome P450 (CYP) 2D6 and P-glycoprotein (P-gp) therefore recommended for use in clinical drug-drug interaction (DDI) studies. However, as also substrate CYP3A4 P-gp, it susceptible to DDIs involving these proteins. Physiologically-based pharmacokinetic (PBPK) modeling can help mechanistically assess the absorption, distribution, metabolism, excretion processes drug has proven its usefulness predicting even complex scenarios....
Dasatinib, a second-generation tyrosine kinase inhibitor, is approved for treating chronic myeloid and acute lymphoblastic leukemia. As sensitive cytochrome P450 (CYP) 3A4 substrate weak base with strong pH-sensitive solubility, dasatinib susceptible to enzyme-mediated drug-drug interactions (DDIs) CYP3A4 perpetrators pH-dependent DDIs acid-reducing agents. This work aimed develop whole-body physiologically-based pharmacokinetic (PBPK) model of describe predict DDIs, evaluate the impact...
Platelet reconstitution after allogeneic hematopoietic cell transplantation (allo‐HCT) is heterogeneous and influenced by various patient‐ transplantation‐related factors, associated with poor prognoses for graft function (PGF) isolated thrombocytopenia. Tailored interventions could improve the outcome of patients PGF post‐HCT To provide individual predictions 180‐day platelet counts from early phase data, we developed a model long‐term allo‐HCT. A large cohort ( n = 1949) adult undergoing...
Conducting clinical studies on drug–drug‐gene interactions (DDGIs) and extrapolating the findings into dose recommendations is challenging due to high complexity of these interactions. Here, physiologically‐based pharmacokinetic (PBPK) modeling networks present a new avenue for exploring such complex scenarios, potentially informing guidelines handling patient‐specific DDGIs at bedside. Moreover, they provide an established framework drug–drug interaction (DDI) submissions regulatory...
The beta-blocker metoprolol (the sixth most commonly prescribed drug in the USA 2017) is subject to considerable drug–gene interaction (DGI) effects caused by genetic variations of CYP2D6 gene. poor metabolizers (5.7% US population) show approximately five-fold higher exposure compared normal metabolizers. This study aimed develop a whole-body physiologically based pharmacokinetic (PBPK) model predict DGIs with metoprolol. (R)- and (S)-enantiomers as well active metabolite...
The first-generation tyrosine kinase inhibitor imatinib has revolutionized the development of targeted cancer therapy and remains among frontline treatments, for example, against chronic myeloid leukemia. As a substrate cytochrome P450 (CYP) 2C8, CYP3A4, various transporters, is highly susceptible to drug-drug interactions (DDIs) when co-administered with corresponding perpetrator drugs. Additionally, its main metabolite N-desmethyl (NDMI) act as inhibitors CYP2C8, CYP2D6, CYP3A4 affecting...
Adverse drug reactions (ADRs) are among the leading causes of death, and frequently associated with drug-gene interactions (DGIs). In addition to pharmacogenomic programs for implementation genetic preemptive testing into clinical practice, mathematical modeling can help understand, quantify predict effects DGIs in vivo. Moreover, contribute optimize prospective trial activities reduce DGI-related ADRs.Approaches challenges mechanistical DGI model parameterization discussed population...
The cytochrome P450 2D6 (CYP2D6) genotype is the single most important determinant of CYP2D6 activity as well interindividual and interpopulation variability in activity. Here, score provides an established tool to categorize large number alleles by facilitates process genotype-to-phenotype translation. Compared broad traditional phenotype categories, additionally serves a superior scale due its finer graduation. Physiologically based pharmacokinetic (PBPK) models have been successfully used...
Clomiphene, a selective estrogen receptor modulator (SERM), has been used for the treatment of anovulation more than 50 years. However, since (E)-clomiphene ((E)-Clom) and its metabolites are eliminated primarily via Cytochrome P450 (CYP) 2D6 CYP3A4, exposure can be affected by CYP2D6 polymorphisms concomitant use with CYP inhibitors. Thus, clomiphene therapy may susceptible to drug–gene interactions (DGIs), drug–drug (DDIs) drug–drug–gene (DDGIs). Physiologically based pharmacokinetic...