1. Elevated acute phase proteins affect pharmacokinetics in COVID-19 trials
- Author
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Ivo P E Tielbeek, Richard Honeywell, Bram Grob, Pierre M Bet, Harm Jan Bogaard, Monia Guidi, Erik Duijvelaar, Imke H Bartelink, Eleonora L Swart, Nicolas Widmer, Laurent A. Decosterd, Jurjan Aman, Amanda Evelo, Sue D Snape, Henrike Hamer, Clinical pharmacology and pharmacy, APH - Mental Health, APH - Personalized Medicine, Amsterdam Neuroscience - Mood, Anxiety, Psychosis, Stress & Sleep, Pulmonary medicine, Laboratory Medicine, ACS - Pulmonary hypertension & thrombosis, and ACS - Microcirculation
- Subjects
Male ,medicine.medical_specialty ,Cmax ,Orosomucoid ,RM1-950 ,030226 pharmacology & pharmacy ,Gastroenterology ,Article ,03 medical and health sciences ,0302 clinical medicine ,Pharmacokinetics ,Internal medicine ,hemic and lymphatic diseases ,medicine ,Humans ,Pharmacology (medical) ,Protein Kinase Inhibitors ,neoplasms ,Aged ,Aged, 80 and over ,GiST ,biology ,Acute-Phase Proteins/metabolism ,COVID-19/blood ,COVID-19/drug therapy ,Female ,Imatinib Mesylate/blood ,Imatinib Mesylate/therapeutic use ,Middle Aged ,Protein Binding/drug effects ,Protein Binding/physiology ,Protein Kinase Inhibitors/blood ,Protein Kinase Inhibitors/therapeutic use ,business.industry ,Research ,Albumin ,Acute-phase protein ,COVID-19 ,Imatinib ,Confidence interval ,3. Good health ,COVID-19 Drug Treatment ,030220 oncology & carcinogenesis ,Modeling and Simulation ,biology.protein ,Imatinib Mesylate ,Therapeutics. Pharmacology ,business ,medicine.drug ,Acute-Phase Proteins ,Protein Binding - 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, respectively, 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.
- Published
- 2021