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

Bonner, Jennifer J.; Burt, Howard; Johnson, Trevor N.; Whitaker, Martin J.; Porter, John B.; Ross, Richard

doi:10.1016/j.ejps.2021.105913

Cited by 12 publications

(14 citation statements)

References 41 publications

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“…As this analysis is based on data from patients aged from 0 to 6 years, the applicability of the PK model to children older than 6 years can be investigated in future with respective available data. The PK in adolescents aged 12 to 18 years can be assumed to be similar to adult HC PK and binding kinetics as it was found in published pharmacokinetic analyses ( Bonner et al, 2021 ).…”

Section: Discussionmentioning

confidence: 87%

Exploring Dried Blood Spot Cortisol Concentrations as an Alternative for Monitoring Pediatric Adrenal Insufficiency Patients: A Model-Based Analysis

et al. 2022

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Congenital adrenal hyperplasia (CAH) is the most common form of adrenal insufficiency in childhood; it requires cortisol replacement therapy with hydrocortisone (HC, synthetic cortisol) from birth and therapy monitoring for successful treatment. In children, the less invasive dried blood spot (DBS) sampling with whole blood including red blood cells (RBCs) provides an advantageous alternative to plasma sampling. Potential differences in binding/association processes between plasma and DBS however need to be considered to correctly interpret DBS measurements for therapy monitoring. While capillary DBS samples would be used in clinical practice, venous cortisol DBS samples from children with adrenal insufficiency were analyzed due to data availability and to directly compare and thus understand potential differences between venous DBS and plasma. A previously published HC plasma pharmacokinetic (PK) model was extended by leveraging these DBS concentrations. In addition to previously characterized binding of cortisol to albumin (linear process) and corticosteroid-binding globulin (CBG; saturable process), DBS data enabled the characterization of a linear cortisol association with RBCs, and thereby providing a quantitative link between DBS and plasma cortisol concentrations. The ratio between the observed cortisol plasma and DBS concentrations varies highly from 2 to 8. Deterministic simulations of the different cortisol binding/association fractions demonstrated that with higher blood cortisol concentrations, saturation of cortisol binding to CBG was observed, leading to an increase in all other cortisol binding fractions. In conclusion, a mathematical PK model was developed which links DBS measurements to plasma exposure and thus allows for quantitative interpretation of measurements of DBS samples.

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Section: Discussionmentioning

confidence: 87%

Exploring Dried Blood Spot Cortisol Concentrations as an Alternative for Monitoring Pediatric Adrenal Insufficiency Patients: A Model-Based Analysis

et al. 2022

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“…In addition, in 2021, in the Bonner et al work, the hydrocortisone P‐PBPK model developed in Simcyp (version 16.1) investigated the clinical dosing regimens. The model is a valuable tool to predict adult and pediatric PK of both immediate‐ and modified‐release hydrocortisone formulations 55 . Additionally, Jie Zhou et al 56 used GastroPlus (version 9.7) simulation and found that their P‐PBPK model was adequate to support ceftazidime dosing recommendations in pediatric patients with different degrees of renal impairment.…”

Section: Resultsmentioning

confidence: 99%

“…The model is a valuable tool to predict adult and pediatric PK of both immediateand modified-release hydrocortisone formulations. 55 Additionally, Jie Zhou et al 56 used GastroPlus (version 9.7) simulation and found that their P-PBPK model was…”

Section: Renal Impairmentmentioning

confidence: 99%

Predicting the correct dose in children: Role of computational Pediatric Physiological‐based pharmacokinetics modeling tools

Zhang

Dun

Chen

et al. 2022

CPT Pharmacom & Syst Pharma

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The pharmacokinetics (PKs) and safety of medications in particular groups can be predicted using the physiologically-based pharmacokinetic (PBPK) model. Using the PBPK model may enable safe pediatric clinical trials and speed up the process of new drug research and development, especially for children, a population in which it is relatively difficult to conduct clinical trials. This review summarizes the role of pediatric PBPK (P-PBPK) modeling software in dose prediction over the past 6 years and briefly introduces the process of general P-PBPK modeling.We summarized the theories and applications of this software and discussed the application trends and future perspectives in the area. The modeling software's extensive use will undoubtedly make it easier to predict dose prediction for young patients.

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“…Based on our data, P‐PBPK made up around 31% (32/102) of such publications for that year in contrast to 2009 where it was approximately 4%. The growth in the use of P‐PBPK modeling is not surprising given its recognized potential, for instance, to replace clinical studies, 24 support clinical questions, 25 and inform dose projection in neonates, infants, and children. 26 The latter application is increasingly being used by the pharmaceutical industry as a more mechanistic means of dose extrapolation for pediatric clinical trials defined in a PIP or PSP.…”

Section: Conclusion/discussionmentioning

confidence: 99%

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations

Johnson

Small

Yeo

2022

CPT Pharmacom & Syst Pharma

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There has been a significant increase in the use of physiologically based pharmacokinetic (PBPK) models during the past 20 years, especially for pediatrics.The aim of this study was to give a detailed overview of the growth and areas of application of pediatric PBPK (P-PBPK) models. A total of 181 publications and publicly available regulatory reviews were identified and categorized according to year, author affiliation, platform, and primary application of the P-PBPK model (in clinical settings, drug development or to advance pediatric model development in general). Secondary application areas, including dose selection, biologics, and drug interactions, were also assessed. The growth rate for P-PBPK modeling increased 33-fold between 2005 and 2020; this was mainly attributed to growth in clinical and drug development applications. For primary applications, 50% of articles were classified under clinical, 18% under drug development, and 33% under model development. The most common secondary applications were dose selection (75% drug development), pharmacokinetic prediction and covariate identification (47% clinical), and model parameter identification (68% model development), respectively. Although population PK modeling remains the mainstay of approaches supporting pediatric drug development, the data presented here demonstrate the widespread application of P-PBPK models in both drug development and clinical settings. Although applications for pharmacokinetic and drug-drug interaction predictions in pediatrics is advocated, this approach remains underused in areas such as assessment of pediatric formulations, toxicology, and trial design. The increasing number of publications supporting the development and refinement of the pediatric model parameters can only serve to enhance optimal use of P-PBPK models.

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

Cited by 12 publications

References 41 publications

Exploring Dried Blood Spot Cortisol Concentrations as an Alternative for Monitoring Pediatric Adrenal Insufficiency Patients: A Model-Based Analysis

Exploring Dried Blood Spot Cortisol Concentrations as an Alternative for Monitoring Pediatric Adrenal Insufficiency Patients: A Model-Based Analysis

Predicting the correct dose in children: Role of computational Pediatric Physiological‐based pharmacokinetics modeling tools

Increasing application of pediatric physiologically based pharmacokinetic models across academic and industry organizations

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