Model-based dose selection to inform translational clinical oncology development of WNT974, a first-in-class Porcupine inhibitor.


Journal

Clinical and translational science
ISSN: 1752-8062
Titre abrégé: Clin Transl Sci
Pays: United States
ID NLM: 101474067

Informations de publication

Date de publication:
07 2022
Historique:
revised: 01 04 2022
received: 16 02 2022
accepted: 07 04 2022
pubmed: 28 5 2022
medline: 19 7 2022
entrez: 27 5 2022
Statut: ppublish

Résumé

WNT974 is a potent, selective, and orally bioavailable first-in-class inhibitor of Porcupine, a membrane-bound O-acyltransferase required for Wnt secretion, currently under clinical development in oncology. A phase I clinical trial is being conducted in patients with advanced solid tumors. During the dose-escalation part, various dosing regimens, including once or twice daily continuous and intermittent dosing at a dose range of 5-45 mg WNT974 were studied, however, the protocol-defined maximum tolerated dose (MTD) was not established based on dose-limiting toxicity. To assist in the selection of the recommended dose for expansion (RDE), a model-based approach was utilized. It integrated population pharmacokinetic (PK) modeling and exposure-response analyses of a target-inhibition biomarker, skin AXIN2 mRNA expression, and the occurrence of the adverse event, dysgeusia. The target exposure range of WNT974 that would provide a balance between target inhibition and tolerability was estimated based on exposure-response analyses. The dose that was predicted to yield an exposure within the target exposure range was selected as RDE. This model-based approach integrated PK, biomarker, and safety data to determine the RDE and represented an alternative as opposed to the conventional MTD approach for selecting an optimal biological dose. The strategy can be broadly applied to select doses in early oncology trials and inform translational clinical oncology drug development.

Identifiants

pubmed: 35620969
doi: 10.1111/cts.13287
pmc: PMC9283749
doi:

Substances chimiques

Antineoplastic Agents 0
Pyrazines 0
Pyridines 0
LGK974 U27F40013Q

Types de publication

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

Langues

eng

Sous-ensembles de citation

IM

Pagination

1713-1722

Informations de copyright

© 2022 Novartis. Clinical and Translational Science published by Wiley Periodicals LLC On behalf of American Society for Clinical Pharmacology and Therapeutics.

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Auteurs

Yan Ji (Y)

Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA.

Pai-Hsi Huang (PH)

Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA.

Steve Woolfenden (S)

Novartis Institutes for Biomedical Research, Cambridge, Massachusetts, USA.

Andrea Myers (A)

Novartis Pharmaceuticals Corporation, East Hanover, New Jersey, USA.

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Classifications MeSH