Elevated acute phase proteins affect pharmacokinetics in COVID-19 trials: lessons from the CounterCovid - imatinib - study.

Bartelink, Imke H; Bet, Pierre M; Widmer, Nicolas; Guidi, Monia; Duijvelaar, Erik; Grob, Bram; Honeywell, Richard; Evelo, Amanda; Tielbeek, Ivo P E; Snape, Sue D; Hamer, Henrike; Decosterd, Laurent A; Bogaard, Harm Jan; Aman, Jurjan; Swart, Eleonora L

This study aimed to determine whether published PK-models can adequately predict the PK profile of imatinib in a new indication such as COVID-19. Total (bound + unbound) and unbound imatinib plasma concentrations obtained from 134 COVID-19 patients participating in the CounterCovid study and from an historical dataset of 20 patients with gastrointestinal stromal tumor (GIST) and 85 chronic myeloid leukemia (CML) were compared. Total imatinib area under the concentration time curve (AUC), maximum concentration (Cmax ) and trough concentration (Ctrough ) were 2.32- (CI95% 1.34-3.29), 2.31- (1.33-3.29) and 2.32-fold (1.11-3.53) lower, respectively, for CML/GIST patients compared with COVID-19 patients, while unbound concentrations were comparable among groups. Inclusion of AAG concentrations measured in COVID-19 patients into a previously published model developed to predict free imatinib concentrations in GIST patients using total imatinib and plasma alpha1-acid glycoprotein (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 ICU 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 sub-optimal efficacy in patients with COVID-19.