Investigating the Critical Variables of Azithromycin Oral Absorption Using In Vitro Tests and PBPK Modeling

Mechanistic Modeling of In Vitro Biopharmaceutic Data for a Weak Acid Drug: A Pathway Towards Deriving Fundamental Parameters for Physiologically Based Biopharmaceutic Modeling

Mechanistic modeling of in vitro experiments using metabolic enzyme systems enables the extrapolation of metabolic clearance for in vitro-in vivo predictions. This is particularly important for successful clearance predictions using physiologically based pharmacokinetic (PBPK) modeling. The concept of mechanistic modeling can also be extended to biopharmaceutics, where in vitro data is used to predict the in vivo pharmacokinetic profile of the drug. This approach further allows for the identification of parameters that are critical for oral drug absorption in vivo. However, the routine use of this analysis approach has been hindered by the lack of an integrated analysis workflow. The objective of this tutorial is to (1) review processes and parameters contributing to oral drug absorption in increasing levels of complexity, (2) outline a general physiologically based biopharmaceutic modeling workflow for weak acids, and (3) illustrate the outlined concepts via an ibuprofen (i.e., a weak, poorly soluble acid) case example in order to provide practical guidance on how to integrate biopharmaceutic and physiological data to better understand oral drug absorption. In the future, we plan to explore the usefulness of this tutorial/roadmap to inform the development of PBPK models for BCS 2 weak bases, by expanding the stepwise modeling approach to accommodate more intricate scenarios, including the presence of diprotic basic compounds and acidifying agents within the formulation.

Develop adult extrapolation to pediatrics and pediatric dose optimization based on the physiological pharmacokinetic model of azithromycin

Physiologically-based pharmacokinetic (PBPK) models are more frequently used for supporting pediatric dose selection in small-molecule drugs. Through literature research, drug parameters of azithromycin and clinical data from different studies were obtained. Through parameter optimization of the absorption and dissolution process, the adult intravenous model was extended to the adult oral model. The adult intravenous and oral PBPK models are precise to meet the AAFE<2 standard, and the pharmacokinetic parameters of the predicted values of the model are all within the mean standard deviation of the clinical observations. The values of plasma protein unbound fraction, renal clearance, and gastric juice pH between adults and pediatrics were changed by using the age-dependent pediatric organ maturity formula, and the adult model was extrapolated to the pediatric model. The final developed pediatric PBPK model was used to evaluate optimal dosing for children of different developmental ages. The relationship between the frist dose and age was as follows: 8.8 mg/kg/day from 0.5 to 2 years old, 9.2 mg/kg/day from 3 to 6 years old, 9.4 mg/kg/day from 7 to 12 years old, and 8.2 mg/kg/day from 13 to 18 years old, taken in half for 2-5 days. Simultaneously, the simulated exposures achieved with the dosing regimen proposed were comparable to adult plasma exposures for treatment of community-acquired pneumonia. A reasonable azithromycin pharmacokinetic-pharmacodynamic model for adults and pediatrics has been established, which can be demonstrated by the use of literature pediatric data to develop pediatric PBPK models, expanding the scope of this powerful modeling tool.

Physiologically based pharmacokinetic modeling of daptomycin dose optimization in pediatric patients with renal impairment

Background and Objective: Daptomycin is used to treat Gram-positive infections in adults and children and its dosing varies among different age groups. We focused on the pharmacokinetics of daptomycin in children with renal impairment, which has not been evaluated.

Methods: A physiologically based pharmacokinetic (PBPK) model of daptomycin was established and validated to simulate its disposition in healthy populations and adults with renal impairment, along with a daptomycin exposure simulated in pediatric patients with renal impairment.

Results: The simulated PBPK modeling results for various regimens of intravenously administered daptomycin were consistent with observed data according to the fold error below the threshold of 2. The Cmax and AUC of daptomycin did not differ significantly between children with mild-to-moderate renal impairment and healthy children. The AUC increased by an average of 1.55-fold and 1.85-fold in severe renal impairment and end-stage renal disease, respectively. The changes were more significant in younger children and could reach a more than 2-fold change. This scenario necessitates further daptomycin dose adjustments.

Conclusion: Dose adjustments take into account the efficacy and safety of the drug; however, the steady-state Cmin of daptomycin may be above 24.3 mg/L in a few instances. We recommend monitoring creatine phosphokinase more than once a week when using daptomycin in children with renal impairment.