Characterization of exposure-response relationships of ipatasertib in patients with metastatic castration-resistant prostate cancer in the IPATential150 study.

AKT inhibitor Exposure–response IPATential150 Ipatasertib Metastatic castration-resistant prostate cancer

Journal

Cancer chemotherapy and pharmacology
ISSN: 1432-0843
Titre abrégé: Cancer Chemother Pharmacol
Pays: Germany
ID NLM: 7806519

Informations de publication

Date de publication:
Dec 2022
Historique:
received: 14 07 2022
accepted: 19 10 2022
pubmed: 29 10 2022
medline: 9 11 2022
entrez: 28 10 2022
Statut: ppublish

Résumé

The exposure-response relationships for efficacy and safety of ipatasertib, a selective AKT kinase inhibitor, were characterized using data collected from 1101 patients with metastatic castration-resistant prostate cancer in the IPATential150 study (NCT03072238). External validation of a previously developed population pharmacokinetic model was performed using the observed pharmacokinetic data from the IPATential150 study. Exposure metrics of ipatasertib for subjects who received ipatasertib 400 mg once-daily orally in this study were generated as model-predicted area under the concentration-time curve at steady state (AUC A statistically significant correlation between ipatasertib AUC The exposure-efficacy results indicated that patients receiving ipatasertib may continue benefiting from this treatment at the administered dose, despite some variability in exposures, while the exposure-safety results suggested increased risks of AEs with ipatasertib treatment and/or increased ipatasertib exposures.

Identifiants

pubmed: 36305957
doi: 10.1007/s00280-022-04488-2
pii: 10.1007/s00280-022-04488-2
pmc: PMC9637074
doi:

Substances chimiques

ipatasertib 524Y3IB4HQ
Piperazines 0
Pyrimidines 0

Banques de données

ClinicalTrials.gov
['NCT03072238']

Types de publication

Clinical Study Journal Article Research Support, Non-U.S. Gov't

Langues

eng

Sous-ensembles de citation

IM

Pagination

511-521

Informations de copyright

© 2022. The Author(s).

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Auteurs

Naoki Kotani (N)

Genentech, Inc., South San Francisco, CA, USA. kotani.naoki47@chugai-pharm.co.jp.
Pharmaceutical Science Department, Chugai Pharmaceutical Co., Ltd., 1-1 Nihonbashi-Muromachi 2-Chome, Chuo-ku, Tokyo, 103-8324, Japan. kotani.naoki47@chugai-pharm.co.jp.

Justin J Wilkins (JJ)

Occams Coöperatie UA, Amstelveen, The Netherlands.

Janet R Wade (JR)

Occams Coöperatie UA, Amstelveen, The Netherlands.

Steve Dang (S)

Genentech, Inc., South San Francisco, CA, USA.

Dhruvitkumar S Sutaria (DS)

Genentech, Inc., South San Francisco, CA, USA.

Kenta Yoshida (K)

Genentech, Inc., South San Francisco, CA, USA.

Sameer Sundrani (S)

Genentech, Inc., South San Francisco, CA, USA.
Department of Bioengineering/Biomedical Computation, Stanford University, Stanford, CA, USA.

Hao Ding (H)

Genentech, Inc., South San Francisco, CA, USA.

Josep Garcia (J)

F. Hoffmann-La Roche AG, Basel, Switzerland.

Heather Hinton (H)

F. Hoffmann-La Roche AG, Basel, Switzerland.

Rucha Sane (R)

Genentech, Inc., South San Francisco, CA, USA.

Pascal Chanu (P)

Department of Clinical Pharmacology, Genentech/Roche, Lyon, France.

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Classifications MeSH