Optimizing chemotherapy dose and schedule by Norton-Simon mathematical modeling.

Abstract

BACKGROUND:

to hasten and improve anticancer drug development, we created a novel approach to generating and analyzing preclinical dose-scheduling data so as to optimize benefit-to-toxicity ratios.

METHODS:

we applied mathematical methods based upon Norton-Simon growth kinetic modeling to tumor-volume data from breast cancer xenografts treated with capecitabine (Xeloda®, Roche) at the conventional schedule of 14 days of treatment followed by a 7-day rest (14-7).

RESULTS:

the model predicted that 7 days of treatment followed by a 7-day rest (7-7) would be superior. Subsequent preclinical studies demonstrated that this biweekly capecitabine schedule allowed for safe delivery of higher daily doses, improved tumor response, and prolonged animal survival.

CONCLUSIONS:

we demonstrated that the application of Norton-Simon modeling to the design and analysis of preclinical data predicts an improved capecitabine dosing schedule in xenograft models. This method warrants further investigation and application in clinical drug development.

• Authors: Tiffany A Traina, Ute Dugan, Brian Higgins, Kenneth Kolinsky, Maria Theodoulou, Clifford A Hudis, Larry Norton
• Journal: Breast disease (Breast Dis) Vol. 31 Issue 1 Pg. 7-18 ( 2010) ISSN: 1558-1551 [Electronic] Netherlands
• PMID: 20519801 (Publication Type: Journal Article)

Chemical References

• Antimetabolites, Antineoplastic
• Deoxycytidine
• Capecitabine
• Fluorouracil

Topics

• Animals
• Antimetabolites, Antineoplastic (administration & dosage)
• Breast Neoplasms (drug therapy, pathology)
• Capecitabine
• Deoxycytidine (administration & dosage, analogs & derivatives)
• Dose-Response Relationship, Drug
• Drug Administration Schedule
• Female
• Fluorouracil (administration & dosage, analogs & derivatives)
• Mice
• Models, Theoretical
• Tumor Burden
• Xenograft Model Antitumor Assays