Unraveling the Effects of Acute Inflammation on Pharmacokinetics: A Model-Based Analysis Focusing on Renal Glomerular Filtration Rate and Cytochrome P450 3A4-Mediated Metabolism

Background and Objectives Acute inflammation caused by infections or sepsis can impact pharmacokinetics. We used a model-based analysis to evaluate the effect of acute inflammation as represented by interleukin-6 (IL-6) levels on drug clearance, focusing on renal glomerular filtration rate (GFR) and cytochrome P450 3A4 (CYP3A4)-mediated metabolism. Methods A physiologically based model incorporating renal and hepatic drug clearance was implemented. Functions correlating IL-6 levels with GFR and in vitro CYP3A4 activity were derived and incorporated into the modeling framework. We then simulated treatment scenarios for hypothetical drugs by varying the IL-6 levels, the contribution of renal and hepatic drug clearance, and protein binding. The relative change in observed area under the concentration-time curve (AUC) was computed for these scenarios. Results Inflammation showed opposite effects on drug exposure for drugs eliminated via the liver and kidney, with the effect of inflammation being inversely proportional to the extraction ratio (ER). For renally cleared drugs, the relative decrease in AUC was close to 30% during severe inflammation. For CYP3A4 substrates, the relative increase in AUC could exceed 50% for low-ER drugs. Finally, the impact of inflammation-induced changes in drug clearance is smaller for drugs with a larger unbound fraction. Conclusion This analysis demonstrates differences in the impact of inflammation on drug clearance for different drug types. The effects of inflammation status on pharmacokinetics may explain the inter-individual variability in pharmacokinetics in critically ill patients. The proposed model-based analysis may be used to further evaluate the effect of inflammation, i.e., by incorporating the effect of inflammation on other drug-metabolizing enzymes or physiological processes

Le Web du Goupil.

National audienc

Semiphysiological versus Empirical Modelling of the Population Pharmacokinetics of Free and Total Cefazolin during Pregnancy

This work describes a first population pharmacokinetic (PK) model for free and total cefazolin during pregnancy, which can be used for dose regimen optimization. Secondly, analysis of PK studies in pregnant patients is challenging due to study design limitations. We therefore developed a semiphysiological modeling approach, which leveraged gestation-induced changes in creatinine clearance (CrCL) into a population PK model. This model was then compared to the conventional empirical covariate model. First, a base two-compartmental PK model with a linear protein binding was developed. The empirical covariate model for gestational changes consisted of a linear relationship between CL and gestational age. The semiphysiological model was based on the base population PK model and a separately developed mixed-effect model for gestation-induced change in CrCL. Estimates for baseline clearance (CL) were 0.119 L/min (RSE 58%) and 0.142 L/min (RSE 44%) for the empirical and semiphysiological models, respectively. Both models described the available PK data comparably well. However, as the semiphysiological model was based on prior knowledge of gestation-induced changes in renal function, this model may have improved predictive performance. This work demonstrates how a hybrid semiphysiological population PK approach may be of relevance in order to derive more informative inferences

Clinical Pharmacokinetics and Pharmacodynamics of Immune Checkpoint Inhibitors

Immune checkpoint inhibitors (ICIs) have demonstrated signifcant clinical impact in improving overall survival of several malignancies associated with poor outcomes; however, only 20–40% of patients will show long-lasting survival. Further clarifcation of factors related to treatment response can support improvements in clinical outcome and guide the development of novel immune checkpoint therapies. In this article, we have provided an overview of the pharmacokinetic (PK) aspects related to current ICIs, which include target-mediated drug disposition and time-varying drug clearance. In response to the variation in treatment exposure of ICIs and the signifcant healthcare costs associated with these agents, arguments for both dose individualization and generalization are provided. We address important issues related to the efcacy and safety, the pharmacodynamics (PD), of ICIs, including exposure–response relationships related to clinical outcome. The unique PK and PD aspects of ICIs give rise to issues of confounding and suboptimal surrogate endpoints that complicate interpretation of exposure–response analysis. Biomarkers to identify patients benefting from treatment with ICIs have been brought forward. However, validated biomarkers to monitor treatment response are currently lacking

Design of informative renal impairment studies : evaluation of the impact of design stratification on bias, precision and dose adjustment error

PURPOSE: Renal impairment (RI) studies are conducted to estimate the impact of RI on pharmacokinetics (PK). In some disease areas, these studies can be difficult to conduct, for instance due to the limited number of eligible patients. The objective of this analysis was to evaluate bias and precision of population PK parameters, and the dose adjustment error (DAE) for RI studies i) with different levels of study design imbalance in the stratification of subjects across RI categories, and ii) that include additional patients in the control arm of RI studies, that may be available from previously conducted PK studies. METHODS: Study designs were simulated and re-estimated using a hypothetical 2-compartmental PK model with varying magnitude of the fraction of renal elimination (FR) and magnitude of between-subject variability (BSV). The DAE was computed based on the difference between the theoretical necessary dose adjustment versus the empirical estimated dose adjustment to reach a similar exposure as controls. RESULTS: Although some design imbalance may still lead to DAEs of acceptable magnitude (DAE < -11.05-14.44 inter-quartile range, IQR), at least some patients are necessary in the more severe RI groups. When 100 additional patients with normal renal function were included in a sub-informative design, the DAE changed from < -7.63-16.64 IQR to < -8.89-8.69 IQR. CONCLUSIONS: We quantified the impact of study design imbalance on bias and precision of PK parameters and DAE, as may occur for RI studies in some indications. Adding additional data from earlier studies to the analysis dataset improves the bias and precision of PK parameters

Semiphysiological versus empirical modelling of the population pharmacokinetics of free and total cefazolin during pregnancy

This work describes a first population pharmacokinetic (PK) model for free and total cefazolin during pregnancy, which can be used for dose regimen optimization. Secondly, analysis of PK studies in pregnant patients is challenging due to study design limitations. We therefore developed a semiphysiological modeling approach, which leveraged gestation-induced changes in creatinine clearance (CrCL) into a population PK model. This model was then compared to the conventional empirical covariate model. First, a base two-compartmental PK model with a linear protein binding was developed. The empirical covariate model for gestational changes consisted of a linear relationship between CL and gestational age. The semiphysiological model was based on the base population PK model and a separately developed mixed-effect model for gestation-induced change in CrCL. Estimates for baseline clearance (CL) were 0.119 L/min (RSE 58%) and 0.142 L/min (RSE 44%) for the empirical and semiphysiological models, respectively. Both models described the available PK data comparably well. However, as the semiphysiological model was based on prior knowledge of gestation-induced changes in renal function, this model may have improved predictive performance. This work demonstrates how a hybrid semiphysiological population PK approach may be of relevance in order to derive more informative inferences

Semiphysiological versus empirical modelling of the population pharmacokinetics of free and total cefazolin during pregnancy

This work describes a first population pharmacokinetic (PK) model for free and total cefazolin during pregnancy, which can be used for dose regimen optimization. Secondly, analysis of PK studies in pregnant patients is challenging due to study design limitations. We therefore developed a semiphysiological modeling approach, which leveraged gestation-induced changes in creatinine clearance (CrCL) into a population PK model. This model was then compared to the conventional empirical covariate model. First, a base two-compartmental PK model with a linear protein binding was developed. The empirical covariate model for gestational changes consisted of a linear relationship between CL and gestational age. The semiphysiological model was based on the base population PK model and a separately developed mixed-effect model for gestation-induced change in CrCL. Estimates for baseline clearance (CL) were 0.119 L/min (RSE 58%) and 0.142 L/min (RSE 44%) for the empirical and semiphysiological models, respectively. Both models described the available PK data comparably well. However, as the semiphysiological model was based on prior knowledge of gestation-induced changes in renal function, this model may have improved predictive performance. This work demonstrates how a hybrid semiphysiological population PK approach may be of relevance in order to derive more informative inferences