Evidence map›Paper›PMID 35428895›Full record

ArticleCancer chemotherapy and pharmacology2022

Assessment of cytochrome P450 3A4-mediated drug-drug interactions for ipatasertib using a fit-for-purpose physiologically based pharmacokinetic model.

Jing Jing, Yuan Chen, Luna Musib, Jin Y Jin, Kit Wun Kathy Cheung, Kenta Yoshida, Rucha Sane

Open access · hybridAbstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
0.7field-weighted citation impact, top 33% of its field
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 4 citations in OpenAlex.

  1. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 1 institution in 1 country.

Jing JingClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA.ORCID http://orcid.org/0000-0003-0916-4901
Yuan ChenClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA.
Luna MusibClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA.
Jin Y JinClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA.
Kit Wun Kathy CheungClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA.
Kenta YoshidaClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA. yoshida.kenta@gene.com.
Rucha SaneClinical Pharmacology, Genentech, Inc., South San Francisco, CA, USA. saner@gene.com.
Gene Therapy Laboratory · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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

Cytochrome P-450 CYP3ACytochrome P-450 CYP3A InhibitorsComputer SimulationCytochrome P-450 CYP3A InducersDrug InteractionsHumansModels, BiologicalPiperazinesPyrimidinesCytochrome P-450 CYP3ACytochrome P-450 CYP3A InducersCytochrome P-450 CYP3A InhibitorsipatasertibPiperazinesPyrimidinesCYP3A4Drug–drug interactionIpatasertibPBPK

Identifiers

PMID35428895
PMCPMC9054915
OpenAlexW4224031477

What OpenQuestion holds

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LicenceCC BY
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Registered trials

None linked

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.