Elevated acute phase proteins affect pharmacokinetics in COVID‐19 trials: Lessons from the CounterCOVID ‐ imatinib study

Abstract

This study aimed to determine whether published pharmacokinetic (PK) models can adequately predict the PK profile of imatinib in a new indication, such as coronavirus disease 2019 (COVID‐19). Total (bound + unbound) and unbound imatinib plasma concentrations obtained from 134 patients with COVID‐19 participating in the CounterCovid study and from an historical dataset of 20 patients with gastrointestinal stromal tumor (GIST) and 85 patients with chronic myeloid leukemia (CML) were compared. Total imatinib area under the concentration time curve (AUC), maximum concentration (C max ) and trough concentration (C trough ) were 2.32‐fold (95% confidence interval [CI] 1.34–3.29), 2.31‐fold (95% CI 1.33–3.29), and 2.32‐fold (95% CI 1.11–3.53) lower, respectivelwy, for patients with CML/GIST compared with patients with COVID‐19, whereas unbound concentrations were comparable among groups. Inclusion of alpha1‐acid glycoprotein (AAG) concentrations measured in patients with COVID‐19 into a previously published model developed to predict free imatinib concentrations in patients with GIST using total imatinib and plasma AAG concentration measurements (AAG‐PK‐Model) gave an estimated mean (SD) prediction error (PE) of −20% (31%) for total and −7.0% (56%) for unbound concentrations. Further covariate modeling with this combined dataset showed that in addition to AAG; age, bodyweight, albumin, CRP, and intensive care unit admission were predictive of total imatinib oral clearance. In conclusion, high total and unaltered unbound concentrations of imatinib in COVID‐19 compared to CML/GIST were a result of variability in acute phase proteins. This is a textbook example of how failure to take into account differences in plasma protein binding and the unbound fraction when interpreting PK of highly protein bound drugs, such as imatinib, could lead to selection of a dose with suboptimal efficacy in patients with COVID‐19.

Physiologically Based Pharmacokinetic Modeling Approaches for Patients With SARS‐CoV‐2 Infection: A Case Study With Imatinib

“…The mean plasma concentrations of AAG were modified from the Simcyp default value in healthy adult males of 0.79 g/L (coefficient of variation [CV] 23%) to 0.90 g/L (CV 30%) for the gastrointestinal stromal tumor (GIST) cohort 8 and 1.93 g/L (CV 30%) for the SARS‐CoV‐2 patient cohort. 7 The default female‐to‐male ratio in AAG concentrations of 0.9 was maintained throughout the simulations. An accurate representation of plasma AAG concentrations is critical for PBPK model predictions of imatinib concentrations due to its extensive binding to this protein.…”

“…Previously published clinical pharmacokinetic data of imatinib in patients with reverse transcription polymerase chain reaction test‐confirmed SARS‐CoV‐2 infection 7 , 17 was retrieved from the original publication using the WebPlotDigitizer version 4.2 ( www.automeris.io/WebPlotDigitizer ). Reported unbound imatinib concentration in the patient population with SARS‐CoV‐2 that were below half of the lowest limit of quantitation (50 µg/L) 7 were excluded (2 sampling points). Since most of the patients in this cohort (≈70%) also received dexamethasone, 17 PBPK simulations were performed with and without coadministration of dexamethasone (6 mg daily orally).…”

“… c Two different clinically reported values each correspond to the subsets of patient cohort used for development and verification of the population pharmacokinetic model of imatinib, respectively. 7 d Reported as median values with the corresponding IQR. e For comparison with the PBPK simulations, all the samples were assumed to be collected at day 4 after initiation of treatment.…”

“… c Two different clinically reported values each correspond to the subsets of patient cohort used for development and verification of the population pharmacokinetic model of imatinib, respectively. 7 …”

“… 6 Total plasma concentrations of imatinib, a kinase inhibitor that binds extensively to plasma α 1 ‐acid‐glycoprotein (AAG), were considerably higher in patients with severe SARS‐CoV‐2 infection than those reported in patients with cancer. 7 Understanding (patho)physiological changes in patients with SARS‐CoV‐2 infection is of clinical importance to help guide optimal dosing regimens of drugs for individual patients.…”