Clinical Pharmacokinetics最新文献

Polypharmacy is commonly employed in clinical settings. The potential risks of drug-drug interactions (DDIs) can compromise efficacy and pose serious health hazards. Integrating pharmacokinetics (PK) and pharmacodynamics (PD) models into DDIs research provides a reliable method for evaluating and optimizing drug regimens. With advancements in our comprehension of both individual drug mechanisms and DDIs, conventional models have begun to evolve towards more detailed and precise directions, especially in terms of the simulation and analysis of physiological mechanisms. Selecting appropriate models is crucial for an accurate assessment of DDIs. This review details the theoretical frameworks and quantitative benchmarks of PK and PD modeling in DDI evaluation, highlighting the establishment of PK/PD modeling against a backdrop of complex DDIs and physiological conditions, and further showcases the potential of quantitative systems pharmacology (QSP) in this field. Furthermore, it explores the current advancements and challenges in DDI evaluation based on models, emphasizing the role of emerging in vitro detection systems, high-throughput screening technologies, and advanced computational resources in improving prediction accuracy.

Introduction: Cabozantinib is one of the preferred treatment options in the latest metastatic renal cell carcinoma (mRCC) guidelines. Cabozantinib is also associated with high drug expenses irrespective of the used dose, because a flat-prizing model has been implemented. In addition, concomitant intake with a high-fat meal increases its bioavailability on average by 57%. Combined with the long terminal half-life of cabozantinib (99 h), this creates possibilities to extend the dosing interval to reduce drug expenses whilst maintaining equivalent exposure.

Objectives: The primary objective was to evaluate the population pharmacokinetic (POPPK) model of cabozantinib developed for its registration using real-world patients' therapeutic drug monitoring (TDM) data. The secondary objective was to design, simulate, and evaluate alternative dose regimens with the aim to reduce drug expenses whilst maintaining comparable exposure.

Methods: Retrospective TDM data from mRCC patients treated with cabozantinib were obtained. The data were evaluated using the published Food and Drug Administration (FDA) cabozantinib POPPK model, a two-compartment disposition model with a dual (fast and slow) lagged first-order absorption process derived from FDA registration documents, as a basis. Subsequently, simulations of alternative drug expenses saving regimens were evaluated.

Results: Twenty-seven mRCC patients with 75 pharmacokinetic observations were included. Patients were treated for a median of 75 days with a median dose of 40 mg. Model evaluation results showed that the cabozantinib TDM concentrations were adequately predicted by the published FDA cabozantinib POPPK model, except for a slightly higher clearance (CL) of 3.11 L/h compared to the reported value (2.23 L/h). The simulation study indicated that an alternative dose regimen that consists of taking 60 mg of cabozantinib for 2 days and then skipping 1 day results in comparable average exposure when compared with a 40 mg daily dose, both without food interaction, while saving 33.3% of the total drug expenses per month. The food effect of a high-fat meal was also taken into account when simulating other alternative dose regimens; 40 mg every 72 h combined with a high-fat meal resulted in comparable exposure when compared with a 20 mg daily dose fasted, while saving 66.7% in drug expenses.

Conclusions: In this study, the optimized cabozantinib POPPK model resulted in adequate prediction of real-world cabozantinib pharmacokinetic data. Alternative dosing regimens with and without using known food interactions were proposed that resulted in potential strategies to significantly reduce cabozantinib drug expenses.

Introduction: The activity changes of cytochrome P450 (CYP450) enzymes, along with the complicated medication scenarios in diabetes mellitus (DM) patients, result in the unanticipated pharmacokinetics (PK), pharmacodynamics (PD), and drug-drug interactions (DDIs). Physiologically based pharmacokinetic (PBPK) modeling has been a useful tool for assessing the influence of disease status on CYP enzymes and the resulting DDIs. This work aims to develop a novel diabetic PBPK population model to facilitate the prediction of PK and DDI in DM patients.

Methods: First, mathematical functions were constructed to describe the demographic and non-CYP physiological characteristics specific to DM, which were then incorporated into the PBPK model to quantify the net changes in CYP enzyme activities by comparing the PK of CYP probe drugs in DM versus non-DM subjects.

Results: The results show that the enzyme activity is reduced by 32.3% for CYP3A4/5, 39.1% for CYP2C19, and 27% for CYP2B6, while CYP2C9 activity is enhanced by 38% under DM condition. Finally, the diabetic PBPK model was developed through integrating the DM-specific CYP activities and other parameters and was further used to perform PK simulations under 12 drug combination scenarios, among which 3 combinations were predicted to result in significant PK changes in DM, which may cause DDI risks in DM patients.

Conclusions: The PBPK modeling applied herein provides a quantitative tool to assess the impact of disease factors on relevant enzyme pathways and potential disease-drug-drug-interactions (DDDIs), which may be useful for dosing regimen optimization and minimizing the DDI risks associated with the treatment of DM.

Background and objective: Spinal anesthesia remains the preferred mode of anesthesia for preeclamptic patients during cesarean delivery. We investigated the incidence of maternal hypotension under spinal anesthesia during cesarean delivery, by comparing different prophylactic infusion rates of norepinephrine with normal saline.

Methods: We randomly allocated 180 preeclamptic patients (45 in each groups) aged 18-45 scheduled for cesarean delivery to receive one of four prophylactic norepinephrine infusions at doses of 0 (normal saline group), 0.025 (0.025 group), 0.05 (0.05 group), or 0.075 (0.075 group) µg/kg/min following spinal anesthesia. The primary endpoint was the incidence of maternal hypotension (systolic blood pressure < 80% of baseline).

Results: The incidence of maternal hypotension was reduced with different prophylactic infusion rates of norepinephrine (26.7%, 15.6%, and 6.7%) compared with normal saline (37.8%) with a significant decreasing trend (p = 0.002). As the infusion doses of norepinephrine increased, there is a significant decreasing trend in deviation of systolic blood pressure control (median performance error; median absolute performance error) from baseline (p < 0.001; p < 0.001) and need for rescue norepinephrine boluses (p = 0.020). The effective dose 50 and effective dose 90 of prophylactic norepinephrine infusion were - 0.018 (95% confidence interval - 0.074, 0.002) µg/kg/min and 0.065 (95% confidence interval 0.048, 0.108) µg/kg/min, respectively.

Conclusions: Prophylactic infusion of norepinephrine, as compared to no preventive measures, can effectively reduce the incidence of maternal hypotension in preeclamptic patients under spinal anesthesia during cesarean delivery, without increasing other adverse events for either the mother or neonate.

Registration: Clinical trials.gov identifier number NCT04556370.

Background: Pharmacogenetic profiling and therapeutic drug monitoring (TDM) have both been proposed to manage inter-individual variability (IIV) in drug exposure. However, determining the most effective approach for estimating exposure for a particular drug remains a challenge. This study aimed to quantitatively assess the circumstances in which pharmacogenetic profiling may outperform TDM in estimating drug exposure, under three sources of variability (IIV, inter-occasion variability [IOV], and residual unexplained variability [RUV]).

Methods: Pharmacokinetic models were selected from the literature corresponding to drugs for which pharmacogenetic profiling and TDM are both clinically considered approaches for dose individualization. The models were used to simulate relevant drug exposures (trough concentration or area under the curve [AUC]) under varying degrees of IIV, IOV, and RUV.

Results: Six drug cases were selected from the literature. Model-based simulations demonstrated that the percentage of patients for whom pharmacogenetic exposure prediction is superior to TDM differs for each drug case: tacrolimus (11.0%), tamoxifen (12.7%), efavirenz (49.2%), vincristine (49.6%), risperidone (48.1%), and 5-fluorouracil (5-FU) (100%). Generally, in the presence of higher unexplained IIV in combination with lower RUV and IOV, exposure was best estimated by TDM, whereas, under lower unexplained IIV in combination with higher IOV or RUV, pharmacogenetic profiling was preferred.

Conclusions: For the drugs with relatively low RUV and IOV (e.g., tamoxifen and tacrolimus), TDM estimated true exposure the best. Conversely, for drugs with similar or lower unexplained IIV (e.g., efavirenz or 5-FU, respectively) combined with relatively high RUV, pharmacogenetic profiling provided the most accurate estimate for most patients. However, genotype prevalence and the relative influence of genotypes on the PK, as well as the ability of TDM to accurately estimate AUC with a limited number of samples, had an impact. The results could be used to support clinical decision making when considering other factors, such as the probability for severe side effects.

Background and objective: Icodec is a once-weekly insulin being developed to provide basal insulin coverage in diabetes mellitus. This study evaluated the effects of renal or hepatic impairment on icodec pharmacokinetics.

Methods: Two open-label, parallel-group, single-dose (1.5 U/kg subcutaneously) trials were conducted. In a renal impairment trial, 58 individuals were allocated to normal renal function (measured glomerular filtration rate ≥ 90 mL/min), mild (60 to < 90 mL/min), moderate (30 to < 60 mL/min) or severe (< 30 mL/min) renal impairment or end-stage renal disease. In a hepatic impairment trial, 25 individuals were allocated to normal hepatic function or mild (Child-Pugh Classification grade A), moderate (grade B) or severe (grade C) hepatic impairment. Blood was sampled frequently for a pharmacokinetic analysis until 35 days post-dose.

Results: The shape of the icodec pharmacokinetic profile was not affected by renal or hepatic impairment. Total icodec exposure was greater for mild (estimated ratio [95% confidence interval]: 1.12 [1.01; 1.24]), moderate (1.24 [1.12; 1.37]) and severe (1.28 [1.16; 1.42]) renal impairment, and for end-stage renal disease (1.14 [1.03; 1.28]), compared with normal renal function. It was also greater for mild (1.13 [1.00; 1.28]) and moderate (1.15 [1.02; 1.29]) hepatic impairment versus normal hepatic function. There was no statistically significant difference between severe hepatic impairment and normal hepatic function. Serum albumin levels (range 2.7-5.1 g/dL) did not statistically significantly influence icodec exposure.

Conclusions: The clinical relevance of the slightly higher icodec exposure with renal or hepatic impairment is limited as icodec should be dosed according to individual need. No specific icodec dose adjustment is required in renal or hepatic impairment.

Clinical trial registration: ClinicalTrials.gov identifiers: NCT03723785 and NCT04597697.

Background: Levetiracetam is an antiseizure medication used for several seizure types in adults and children aged 1 month and older; however, due to a lack of data, pharmacokinetic (PK) variability of levetiracetam is not adequately characterized in certain populations, particularly neonates, children younger than 2 years of age, and children older than 2 years of age with obesity.

Objective: This study aimed to address the gap by leveraging PK data from two prospective standard-of-care pediatric trials (n = 88) covering an age range from 1 month to 19 years, including those with obesity (64%), and applying a physiologically based PK (PBPK) modeling framework.

Methods: A published PBPK model of levetiracetam for children aged 2 years and older was extended to pediatric patients younger than 2 years of age and patients older than 2 years of age with obesity by accounting for the obesity and age-related changes in PK using PK-Sim^® software. The prospective pediatric data, along with the literature data for neonates and children younger than 2 years of age, were used to evaluate the extended PBPK models.

Results: Overall, 82.4% of data fell within the 90% interval of model-predicted concentrations, with an average fold error within twofold of the accepted criteria. PBPK modeling revealed that children with obesity had lower weight-normalized clearances (0.053 L/h/kg) on average than children without obesity (0.063 L/h/kg). The effect of maturation was well-characterized, resulting in comparable PBPK-simulated, weight-normalized clearances for neonates and children younger than 2 years of age reported from the literature.

Conclusions: PBPK modeling simulations revealed that the current US FDA-labeled pediatric dosing regimen listed in the prescribing information can produce the required exposure of levetiracetam in these target populations with dose adjustments for children with obesity aged 4 years to younger than 16 years.