Traina Tiffany A, Dugan Ute, Higgins Brian, Kolinsky Kenneth, Theodoulou Maria, Hudis Clifford A, Norton Larry
Department of Medicine, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA.
Breast Dis. 2010;31(1):7-18. doi: 10.3233/BD-2009-0290.
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.
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).
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.
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.
为加速和改进抗癌药物研发，我们创建了一种新方法来生成和分析临床前剂量安排数据，以优化效益与毒性比。
我们将基于诺顿 - 西蒙生长动力学模型的数学方法应用于用卡培他滨（希罗达®，罗氏公司）按照常规方案治疗的乳腺癌异种移植瘤的肿瘤体积数据，该常规方案为治疗14天，随后休息7天（14 - 7）。
该模型预测治疗7天随后休息7天（7 - 7）的方案会更优。随后的临床前研究表明，这种每两周一次的卡培他滨给药方案能够安全地给予更高的每日剂量，改善肿瘤反应，并延长动物生存期。
我们证明将诺顿 - 西蒙模型应用于临床前数据的设计和分析可预测异种移植模型中卡培他滨给药方案的改进。该方法值得在临床药物研发中进一步研究和应用。
