ArticleCancer chemotherapy and pharmacology2022
Assessment of cytochrome P450 3A4-mediated drug-drug interactions for ipatasertib using a fit-for-purpose physiologically based pharmacokinetic model.
Article in Cancer chemotherapy and pharmacology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
1 citing paper in PubMed, 4 citations in OpenAlex.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
purposeIpatasertib, a potent and highly selective small-molecule inhibitor of AKT, is currently under investigation for treatment of cancer. Ipatasertib is a substrate and a time-dependent inhibitor of CYP3A4. It exhibits non-linear pharmacokinetics at subclinical doses in the clinical dose escalation study. To assess the DDI risk of ipatasertib at the intended clinical dose of 400 mg with CYP3A4 inhibitors, inducers, and substrates, a fit-for-purpose physiologically based pharmacokinetic (PBPK) model of ipatasertib was developed.
methodsThe PBPK model was constructed in Simcyp using in silico, in vitro, and clinical data and was optimized and verified using clinical data.
resultsThe PBPK model described non-linear pharmacokinetics of ipatasertib and captured the magnitude of the observed clinical DDIs. Following repeated doses of 400 mg ipatasertib once daily (QD), the PBPK model predicted a 3.3-fold increase of ipatasertib exposure with itraconazole; a 2-2.5-fold increase with moderate CYP3A4 inhibitors, erythromycin and diltiazem; and no change with a weak CYP3A4 inhibitor, fluvoxamine. Additionally, in the presence of strong or moderate CYP3A4 inducers, rifampicin and efavirenz, ipatasertib exposures were predicted to decrease by 86% and 74%, respectively. As a perpetrator, the model predicted that ipatasertib (400 mg) caused a 1.7-fold increase in midazolam exposure.
conclusionThis study demonstrates the value of using a fit-for-purpose PBPK model to assess the clinical DDIs for ipatasertib and to provide dosing strategies for the concurrent use of other CYP3A4 perpetrators or victims.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.