Clinical Pharmacokinetics最新文献

Stable iron isotope techniques are critical for developing strategies to combat iron deficiency anemia, a leading cause of global disability. There are four primary stable iron isotope methods to assess ferrokinetics in humans. (i) The fecal recovery method applies the principles of a metabolic balance study but offers enhanced accuracy because the amount of iron isotope present in feces can be directly traced back to the labeled dose, distinguishing it from endogenous iron lost in stool from shed intestinal cells. (ii) In the plasma isotope appearance method, plasma samples are collected for several hours after oral dosing to evaluate the rate, quantity, and pattern of iron absorption. Key metrics include the time of peak isotope concentration and the area under the curve. (iii) The erythrocyte iron incorporation method measures iron bioavailability (absorption and erythrocyte iron utilization) from a whole blood sample collected 2 weeks after oral dosing. Simultaneous administration of oral and intravenous tracers allows for separate measurements of iron absorption and iron utilization. These three methods determine iron absorption by measuring tracer concentrations in feces, serum, or erythrocytes after administration of a tracer. In contrast, (iv) in iron isotope dilution, an innovative new approach, iron of natural composition acts as the tracer, diluting an ad hoc modified isotopic signature obtained via prior isotope administration and equilibration with body iron. This technique enables highly accurate long-term studies of iron absorption, loss, and gain. This review discusses the application of these kinetic methods and their potential to address important questions in hematology and iron biology.

Antibody-drug conjugates (ADCs) have become a pivotal area in the research and development of antitumor drugs. They provide innovative possibilities for tumor therapy by integrating the tumor-targeting capabilities of monoclonal antibodies with the cytotoxic effect of small molecule drugs. Pharmacometrics, an important discipline, facilitates comprehensive understanding of the pharmacokinetic characteristics of ADCs by integrating clinical trial data through modeling and simulation. However, due to the complex structure of ADCs, their modeling approaches are still unclear. In this review, we analyzed published population pharmacokinetic models for ADCs and classified them into single-analyte, two-analyte, and three-analyte models. We also described the benefits, limitations, and recommendations for each model. Furthermore, we suggested that the development of population pharmacokinetic models for ADCs should be rigorously considered and established based on four key aspects: (1) research objectives; (2) available in vitro and animal data; (3) accessible clinical information; and (4) the capability of bioanalytical methods. This review offered insights to guide the application of pharmacometrics in the clinical research of ADCs, thereby contributing to more effective therapeutic development.

Background and objective: When utilizing population pharmacokinetic (popPK) models for a priori dosage individualization, selecting the best model is crucial to obtain adequate doses. We developed and evaluated several model-selection and ensembling methods, using external evaluation on the basis of therapeutic drug monitoring (TDM) samples to identify the best (set of) models per patient for a priori dosage individualization.

Methods: PK data and models describing both hospitalized patients (n = 134) receiving continuous vancomycin (26 models) and patients (n = 92) receiving imatinib in an outpatient setting (12 models) are included. Target attainment of four model-selection methods was compared with standard dosing: the best model based on external validation, uninformed model ensembling, model ensembling using a weighting scheme on the basis of covariate-stratified external evaluation, and model selection using covariates in decision trees that were subsequently ensembled.

Results: Overall, the use of PK models improved the proportion of patients exposed to concentrations within the therapeutic window for both cohorts. Relative improvement of proportion on target for best model, unweighted, weighted, and decision trees were - 7.0%, 2.3%, 11.4%, and 37.0% (vancomycin method-development); 23.2%, 7.9%, 15.6%, and, 77.2% (vancomycin validation); 40.7%, 50.0%, 59.5%, and 59.5% (imatinib method-development); and 19.0%, 28.5%, 38.0%, and 23.8% (imatinib validation), respectively.

Conclusions: The best (set of) models per patient for a priori dosage individualization can be identified using a relatively small set of TDM samples as external evaluation. Adequately performing popPK models were identified while also excluding poor-performing models. Dose recommendations resulted in more patients within the therapeutic range for both vancomycin and imatinib. Prospective validation is necessary before clinical implementation.

Background and objectives: Recently a number of antibody-drug conjugate (ADC) pharmacometric models have been reported in the literature, describing one or two ADC-related analytes. The objective of this analysis was to build a population pharmacokinetic (popPK) three-analyte ADC model to describe efficacy and safety of zilovertamab vedotin, an ROR1-targeting ADC conjugated to monomethyl auristatin E (MMAE).

Methods: Data from a phase 1 study of zilovertamab vedotin in subjects with hematologic malignancies was used in a stepwise ADC modeling strategy based on the simplified ADC popPK model proposed by Gibiansky. This choice provided opportunity to model three analytes: conjugated monomethyl auristatin E (acMMAE), total monoclonal antibody (total mAb), and free MMAE. The model was extrapolated to the pediatric population using a clearance maturation function and accounting for weight dependent pharmacokinetic (PK) changes.

Results: The simplified model provided a good structure to fit the adult acMMAE, total mAb, and free MMAE data. Analysis showed that MMAE was released through deconjugation of the payload and full proteolytic degradation of the acMMAE. Deconjugation was associated with an immediate release of MMAE, proteolytic clearance introduced a delay in the release of MMAE. Simulation of the model extrapolated to the pediatric population was the basis for pediatric dosing strategies for zilovertamab vedotin that were approved in the United States and European Union.

Conclusions: The total mAb, acMMAE, and free MMAE model showed a good fit to the data. The pediatric population can match the acMMAE adult exposure at the same weight-based dose regimen without concerns that the toxic MMAE concentration will reach higher levels than found in adults.

Background: Cetagliptin is a novel dipeptidyl peptidase-4 (DPP-4) inhibitor developed for the treatment of patients with type 2 diabetes (T2D). Several phase 1 studies have been conducted in China. Modelling and simulation were used to obtain cetagliptin dose for phase 3 trials in T2D patients.

Methods: A pharmacokinetic (PK)/pharmacodynamic (PD) model and model-based analysis of the relationship between hemoglobin A1c (HbA1c) and dosage was explored to guide dose selection of cetagliptin for phase 3 trials. The PK/PD data were derived from four phase 1 clinical studies, and sitagliptin 100 mg was employed as a positive control in studies 1, 3, and 4.

Results: The PK profiles of cetagliptin were well described by a two-compartment model with first-order absorption, saturated efflux, and first-order elimination. The final PD model was a sigmoid maximum inhibitory efficacy (E_max) model with the Hill coefficient. The final model accurately captured cetagliptin PK/PD, demonstrated by goodness-of-fit plots. Based on weighted average inhibition (WAI), the relationship between HbA1c and dose was well displayed. Cetagliptin 50 mg once daily or above as monotherapy or as add-on therapy appeared more effective in HbA1c reduction than sitagliptin 100 mg. Cetagliptin 50 mg or 100 mg once daily was selected as the dose for phase 3 trials of cetagliptin in T2D patients.

Conclusions: The PK/PD model supports dose selection of cetagliptin for phase 3 trials. A model‑informed approach can be used to replace a dose-finding trial and accelerate cetagliptin's development.

Background and objective: Tacrolimus is an immunosuppressant commonly administered after solid organ transplantation. It is characterized by a narrow therapeutic window and high variability in exposure, demanding personalized dosing. In recent years, population pharmacokinetic models have been suggested to guide model-informed precision dosing of tacrolimus. We aimed to provide a comprehensive overview of population pharmacokinetic models and model-informed precision dosing software modules of tacrolimus in all solid organ transplant settings, including a simulation-based investigation of the impact of covariates on exposure and target attainment.

Methods: We performed a systematic literature search to identify population pharmacokinetic models of tacrolimus in solid organ transplant recipients. We integrated selected population pharmacokinetic models into an interactive software tool that allows dosing simulations, Bayesian forecasting, and investigation of the impact of covariates on exposure and target attainment. We conducted a web survey amongst model-informed precision dosing software tool providers and benchmarked publicly available tools in terms of models, target populations, and clinical integration.

Results: We identified 80 population pharmacokinetic models, including 44 one-compartment and 36 two-compartment models. The most frequently retained covariates on clearance and distribution parameters were cytochrome P450 3A5 polymorphisms and body weight, respectively. Our simulation tool, hosted at https://lpmx.shinyapps.io/tacrolimus/ , allows thorough investigation of the impact of covariates on exposure and target attainment. We identified 15 model-informed precision dosing software tool providers, of which ten offer a tacrolimus solution and nine completed the survey.

Conclusions: Our work provides a comprehensive overview of the landscape of available tacrolimus population pharmacokinetic models and model-informed precision dosing software modules. Our simulation tool allows an interactive thorough exploration of covariates on exposure and target attainment.

Background: Cariprazine is metabolised mainly by CYP3A4 and to a lesser extent by CYP2D6.

Aim: This study aimed to evaluate the effects of erythromycin, a moderate cytochrome P450 (CYP)3A4 inhibitor, on the pharmacokinetics of cariprazine in male patients with schizophrenia, and to assess the influence of CYP2D6 phenotypes on cariprazine metabolism.

Methods: Forty-two patients received oral doses of 1.5 mg cariprazine alone for 28 days (to reach steady state), followed by a co-administration of cariprazine 1.5 mg daily with erythromycin 500 mg twice daily (BID) and Enterol 250 mg BID for 21 days, followed by a 14-day post-treatment period. Blood samples were collected at predefined time points and analysed for cariprazine, its two active metabolites: desmethyl cariprazine (DCAR) and didesmethyl cariprazine (DDCAR), and erythromycin using validated high performance liquid chromatography-tandem mass spectrometry methods. CYP2D6 phenotypes were determined by genotyping. The pharmacokinetic parameters were calculated using non-compartmental analysis.

Results: Erythromycin increased the area under the curve (AUC_τ) and peak concentration (C_max) of Total cariprazine (cariprazine + DCAR + DDCAR) by about 40-50% but did not affect the time to peak concentration (T_max). The CYP2D6 phenotypes had no substantial effect on the pharmacokinetics of cariprazine and its metabolites, either alone or in combination with erythromycin. Cariprazine was well tolerated and safe.

Conclusion: The findings suggest that co-administration of cariprazine with moderate CYP3A4 inhibitors may require dose adjustment or monitoring; however, pharmacogenetic testing for CYP2D6 is not necessary for optimising cariprazine therapy.

Trial registration: Trial registration number (EudraCT Number): 2018-003721-28. Date of registration: 21-SEP-2018.

Background and Objective

Firsocostat is an oral, liver-targeted inhibitor of acetyl-CoA carboxylase in clinical development for the treatment of metabolic dysfunction-associated steatohepatitis. This work evaluated the potential drug–drug interactions (DDIs) of firsocostat as a victim and as a perpetrator, to inform concomitant medication use.

Methods

In this phase I study, healthy participants (n = 13–30 in each of four cohorts) received firsocostat alone or in combination with either victims or perpetrators of cytochrome P450 (CYP) enzymes and drug transporters to evaluate firsocostat as both a victim and perpetrator of DDIs, respectively.

Results

Overall, 80 participants completed the study. As a victim of DDI, firsocostat plasma exposure (area under the plasma concentration-time curve [AUC] from 0 to infinity [AUC_∝]) was 19-fold, 22-fold, 63%, and 38% higher when administered with single-dose rifampin 600 mg (organic anion transporting polypeptide [OATP] 1B1/B3 inhibitor), single-dose cyclosporine A 600 mg (OATP/P-glycoprotein/CYP3A inhibitor), multiple-dose probenecid 500 mg twice daily (evaluated as a uridine diphosphate glucuronosyltransferase [UGT] inhibitor), and multiple-dose voriconazole 200 mg twice daily (CYP3A inhibitor), respectively, compared with the administration of firsocostat alone. As a perpetrator of DDI, multiple-dose administration of firsocostat did not affect the exposure of midazolam 2 mg (CYP3A substrate) or drospirenone/ethinylestradiol 3 mg/0.02 mg (combined oral contraceptive). Study treatments were well-tolerated and all adverse events were mild.

Conclusions

Firsocostat can be administered with CYP3A and UGT inhibitors without dose adjustment. However, firsocostat should not be coadministered with strong OATP1B/3 inhibitors, such as rifampin and cyclosporine A. Firsocostat can be administered with CYP3A substrates or combined oral contraceptives without dose modification.

Background and Objective

Systemic corticosteroids have a long history of use in the treatment of autoimmune and inflammatory diseases. Both efficacy and safety show large interindividual variability (IIV), suggesting that corticosteroids may have the potential for individualised dosing strategies to optimise therapy. This systematic review aims to provide an overview of current evidence on the pharmacokinetic (PK) and pharmacodynamic (PD) relationships of systemic corticosteroids in patients with autoimmune and inflammatory diseases.

Methods

A systematic literature search was conducted in PubMed and Embase for PK/PD studies of systemic corticosteroids in autoimmune and inflammatory diseases in humans published until December 2023. Studies were scored from 1 to 5 according to criteria for the levels of evidence, as inspired by the Oxford Centre for Evidence-Based Medicine.

Results

Twelve studies (1981–2016) were included. The majority of these studies had a small sample size. The corticosteroids involved were prednisone, prednisolone, methylprednisolone and budesonide. Substantial IIV of corticosteroid PK was described in all studies. Evidence for a relationship between the PK of corticosteroids and efficacy was inconclusive and limited. However, there was some evidence for a relationship between the PK of prednisolone and the severity of Cushingoid features.

Conclusion

There is insufficient evidence to draw firm conclusions on the potential associations between PK and clinical outcome of systemic corticosteroid treatment in autoimmune and inflammatory diseases. This is remarkable given the many decades that steroid drugs have been used in clinical care. Prospective research is recommended with robust and well-defined cohorts to fully quantify the PK/PD associations of corticosteroids.