Pharmacokinetics and pharmacodynamics of imatinib for optimal drug repurposing from cancer to COVID-19
Bibliographic record
Abstract
In the randomized double-blind placebo-controlled CounterCOVID study, oral imatinib treatment conferred a positive clinical outcome and a signal for reduced mortality in COVID-19 patients. High concentrations of alpha-1 acid glycoprotein (AAG) were observed in these patients and were associated with increased total imatinib concentrations. This post-hoc study aimed to compare the difference in exposure following oral imatinib administration in COVID-19 patients to cancer patients and assess assocations between pharmacokinetic (PK) parameters and pharmacodynamic (PD) outcomes of imatinib in COVID-19 patients. We hypothesize that a relatively higher drug exposure of imatinib in severe COVID-19 patients leads to improved pharmacodynamic outcome parameters. 648 total concentration plasma samples obtained from 168 COVID-19 patients were compared to 475 samples of 105 cancer patients, using an AAG-binding model. Total trough concentration at steady state (Cttrough) and total average area under the concentration-time curve (AUCtave) were associated with ratio between partial oxygen pressure and fraction of inspired oxygen (P/F), WHO ordinal scale (WHO-score) and liberation of oxygen supplementation (O2lib). Linear regression, linear mixed effects models and time-to-event analysis were adjusted for possible confounders. AUCtave and Cttrough were respectively 2.21-fold (95%CI 2.07–2.37) and 1.53-fold (95%CI 1.44–1.63) lower for cancer compared to COVID-19 patients. Cttrough, not AUCtave, associated significantly with P/F (β=-19,64; p-value=0.014) and O2lib (HR 0.78; p-value= 0.032), after adjusting for sex, age, neutrophil-lymphocyte ratio, dexamethasone concomitant treatment, AAG and baseline P/F-and WHO-score. Cttrough, but not AUCtave associated significantly with WHO-score. These results suggest an inverse relationship between PK-parameters, Cttrough and AUCtave, and PD outcomes. COVID-19 patients exhibit higher total imatinib exposure compared to cancer patients, attributed to differences in plasma protein concentrations. Higher imatinib exposure in COVID-19 patients did not associate with improved clinical outcomes. Cttrough and AUCtave inversely associated with some PD-outcomes, which may be biased by disease course, variability in metabolic rate and protein binding. Therefore, additional PKPD analyses into unbound imatinib and its main metabolite may better explain exposure-response.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".