Development of a physiologically based pharmacokinetic model of actinomycin D in children with cancer.

AIMS: Use of the anti-tumour antibiotic actinomycin D is associated with development of hepatotoxicity, particularly in young children. A paucity of actinomycin D pharmacokinetic data make it challenging to develop a sound rationale for defining dosing regimens in younger patients. The study aim was to develop a physiologically based pharmacokinetic (PBPK) model using a combination of data from the literature and generated from experimental analyses. METHODS: Assays to determine actinomycin D Log P, blood:plasma partition ratio and ABCB1 kinetics were conducted. These data were combined with physiochemical properties sourced from the literature to generate a compound file for use within the modelling-simulation software Simcyp (version 14 release 1). For simulation, information was taken from two datasets, one from 117 patients under the age of 21 and one from 20 patients aged 16-48. RESULTS: The final model incorporated clinical renal and biliary clearance data and an additional systemic clearance value. The mean AUC0-26h of simulated subjects was within 1.25-fold of the observed AUC0-26h (84 ng h ml(-1) simulated vs. 93 ng h ml(-1) observed). For the younger age ranges, AUC predictions were within two-fold of observed values, with simulated data from six of the eight age/dose ranges falling within 15% of observed data. Simulated values for actinomycin D AUC0-26h and clearance in infants aged 0-12 months ranged from 104 to 115 ng h ml(-1) and 3.5-3.8 l h(-1) , respectively. CONCLUSIONS: The model has potential utility for prediction of actinomycin D exposure in younger patients and may help guide future dosing. However, additional independent data from neonates and infants is needed for further validation. Physiological differences between paediatric cancer patients and healthy children also need to be further characterized and incorporated into PBPK models.

Does age affect gastric emptying time? A model-based meta-analysis of data from premature neonates through to adults.

PURPOSE: Gastric emptying (GE) is often reported to be slower and more irregular in premature neonates than in older children and adults. The aim of this study was to investigate the impact of age and other covariates on the rate of GE. METHODS: The effect of age on the mean gastric residence times (MGRT) of liquid and solid food was assessed by analysing 49 published studies of 1457 individuals, aged from 28 weeks gestation to adults. The data were modelled using the nonlinear mixed-effects approach within NONMEM version 7.2 (ICON, Dublin, Ireland), with evaluation of postnatal age, gestational age and meal type as covariates. A double Weibull function was selected as a suitable model since it could account for the typical biphasic nature of GE. RESULTS: Age was not a significant covariate for GE but meal type was. Aqueous solutions were associated with the fastest emptying time (mean simulated gastric residence time of 45 min) and solid food was associated with the slowest (98 min). CONCLUSIONS: These findings challenge the assertion that GE is different in neonates, as compared with older children and adults due to age, and they reinforce the significance of food type in modulating GE.

PBPK-led assessment of antimalarial drugs as candidates for Covid-19: Simulating concentrations at the site of action to inform repurposing strategies.

The urgent need for safe, efficacious, and accessible drug treatments to treat coronavirus disease 2019 (COVID-19) prompted a global effort to evaluate drug repurposing opportunities. Pyronaridine and amodiaquine are both components of approved antimalarials with in vitro activity against severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). In vitro activity does not always translate to clinical efficacy across a therapeutic dose range. This study applied available, verified, physiologically based pharmacokinetic (PBPK) models for pyronaridine, amodiaquine, and its active metabolite N-desethylamodiaquine (DEAQ) to predict drug concentrations in lung tissue relative to plasma or blood in the default healthy virtual population. Lung exposures were compared to published data across the reported range of in vitro EC50 values against SARS-CoV-2. In the multicompartment permeability-limited PBPK model, the predicted total Cmax in lung mass for pyronaridine was 34.2 µM on Day 3, 30.5-fold greater than in blood (1.12 µM) and for amodiaquine was 0.530 µM, 8.83-fold greater than in plasma (0.060 µM). In the perfusion-limited PBPK model, the DEAQ predicted total Cmax on Day 3 in lung mass (30.2 µM) was 21.4-fold greater than for plasma (1.41 µM). Based on the available in vitro data, predicted drug concentrations in lung tissue for pyronaridine and DEAQ, but not amodiaquine, appeared sufficient to inhibit SARS-CoV-2 replication. Simulations indicated standard dosing regimens of pyronaridine-artesunate and artesunate-amodiaquine have potential to treat COVID-19. These findings informed repurposing strategies to select the most relevant compounds for clinical investigation in COVID-19. Clinical data for model verification may become available from ongoing clinical studies.

Development and application of a PBPK modeling strategy to support antimalarial drug development.

As part of a collaboration between Medicines for Malaria Venture (MMV), Certara UK and Monash University, physiologically-based pharmacokinetic (PBPK) models were developed for 20 antimalarials, using data obtained from standardized in vitro assays and clinical studies within the literature. The models have been applied within antimalarial drug development at MMV for more than 5 years. During this time, a strategy for their impactful use has evolved. All models are described in the supplementary material and are available to researchers. Case studies are also presented, demonstrating real-world development and clinical applications, including the assessment of the drug-drug interaction liability between combination partners or with co-administered drugs. This work emphasizes the benefit of PBPK modeling for antimalarial drug development and decision making, and presents a strategy to integrate it into the research and development process. It also provides a repository of shared information to benefit the global health research community.

Development and verification of an endogenous PBPK model to inform hydrocortisone replacement dosing in children and adults with cortisol deficiency.

The goal of hormone replacement is to mirror physiology. Hydrocortisone granules and modified release formulations are being developed to optimise cortisol replacement in the rare disease of adrenal insufficiency. To facilitate clinical development, we built and verified a physiologically based pharmacokinetic (PBPK) model for the endogenous hormone cortisol (hydrocortisone) in healthy adults, and children and adults with adrenal insufficiency. The model predicted immediate-release hydrocortisone pharmacokinetics in adults across the dose range 0.5 to 20 mg, with predicted/observed AUCs within 0.8 to 1.25-fold.  The model also tightly predicted pharmacokinetic parameters for modified-release formulations, with AUCs within 0.8 to 1.25-fold after single and multiple dosing.  Predicted modified-release formulation pharmacokinetics (PK) in 12 to 18-year olds showed PK to be similar to adults. This hydrocortisone PBPK model is a useful tool to predict adult and paediatric pharmacokinetics of both immediate- and modified-release hydrocortisone formulations, and develop clinical dosing regimens.