Modelling Hydrocortisone Pharmacokinetics on a Subcutaneous Pulsatile Infusion Replacement Strategy in Patients with Adrenocortical Insufficiency

Ioannis G Violaris, Konstantinos Kalafatakis*, Eder Zavala, Ioannis G Tsoulos, Theodoros Lampros, Stafford L Lightman, Markos G Tsipouras, Nikolaos Giannakeas, Alexandros Tzallas, Georgina M Russell

*Corresponding author for this work

Research output: Contribution to journalArticle (Academic Journal)peer-review

Abstract

In the context of glucocorticoid (GC) therapeutics, recent studies have utilised a subcutaneous hydrocortisone (HC) infusion pump programmed to deliver multiple HC pulses throughout the day, with the purpose of restoring normal circadian and ultradian GC rhythmicity. A key challenge for the advancement of novel HC replacement therapies is the calibration of infusion pumps against cortisol levels measured in blood. However, repeated blood sampling sessions are enormously labour-intensive for both examiners and examinees. These sessions also have a cost, are time consuming and are occasionally unfeasible. To address this, we developed a pharmacokinetic model approximating the values of plasma cortisol levels at any point of the day from a limited number of plasma cortisol measurements. The model was validated using the plasma cortisol profiles of 9 subjects with disrupted endogenous GC synthetic capacity. The model accurately predicted plasma cortisol levels (mean absolute percentage error of 14%) when only four plasma cortisol measurements were provided. Although our model did not predict GC dynamics when HC was administered in a way other than subcutaneously or in individuals whose endogenous capacity to produce GCs is intact, it was found to successfully be used to support clinical trials (or practice) involving subcutaneous HC delivery in patients with reduced endogenous capacity to synthesize GCs.

Original languageEnglish
Article number769
Pages (from-to)769
Journalpharmaceutics
Volume13
Issue number6
DOIs
Publication statusPublished - 21 May 2021

Bibliographical note

Funding Information:
Funding: This work has been supported by the European Union and Greek national funds through the Operational Program Competitiveness, Entrepreneurship, and Innovation, under the call RESEARCH-CREATE-INNOVATE, Project: “INSPECT” (T2E∆K-03717). The authors would like to express their gratitude to Bodossaki Foundation (https://www.bodossaki.gr/en/, accessed on 20 May 2021) for supporting the research on modelling biological and biomedical data with a postdoctoral fellowship to Dr K. Kalafatakis. This work was also partly funded by the Medical Research Council fellowship MR/P014747/1 to Dr E. Zavala. Finally, the authors would like to gratefully acknowledge earlier funding from the Medical Research Council (DCS Grant Number MR/J0125481/1), which supported the preceding clinical trials.

Publisher Copyright:
© 2021 by the authors. Licensee MDPI, Basel, Switzerland.

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