A stochastic population pharmacodynamic model of QAP14 in the treatment of lung metastases of 4T1 breast cancer

doi:10.5246/jcps.2021.10.067

Abstract

Abstract:

Cancer metastasis is a process with multi-step complexity and apparent randomness. In this study, we aimed to establish a stochastic mathematical model to describe the random process of cancer metastasis and predict the drug effect of QAP14 on metastasis in a mouse model. The data of lung metastases on the 22^nd day after cancer cell implantation with or without the treatment of QAP14, a new chemical compound, were collected in 4T1 breast cancer BALB/c mice. Based on the exponential growth of the primary tumor and metastatic loci, a joint distribution model of metastasis size and number was developed. Disease progression of metastasis and preclinical efficacy of QAP14 were modeled. Parameters M and m representing maximum and minimum of metastasis volume were 3.24 and 0.0184 mm³, respectively. The metastasis growth rate γ and metastasis promotion time ρ were estimated and fixed to be 0.0216 d^–1 and 7.8 d, respectively. The efficacy of QAP14 acted on metastasis promotion time and metastasis growth rate constant in an exponential term, and the effect parameter Effect_ρ and Effect_γ were 16.6 and 0.327 g/mg, respectively. In the present study, we comprehensively characterized the random process of lung metastasis and efficacy of QAP14 in 4T1 breast cancer mice, which might provide a useful reference for the establishment of a clinical population model of cancer metastasis.

Key words: Stochastic population model, PD model, 4T1, Lung metastasis, Breast cancer

Supporting:

Supplement Figure 1. Individual fit plots of instantaneous seeding model on the 22^nd day. Abscissa is metastasis volume and ordinate is cumulative density function value (cdf). The dotted lines, dashed and solid lines represent observed values, population predicted values and individual population predicted values, respectively.

Supplement Figure 2.Individual fit plots of two types of models in reference article. Abscissa is metastasis volume and ordinate is cumulative density function value (cdf). The dotted lines and dashed lines represent observed values and population predicted values respectively.a. The individual fit plot of instantaneous seeding model;b. The individual fit plot of homogeneous model.

Supplementary Table 1. Metastasis volume-cdf data of ID 1 on the 22^nd day.

Mengyi Han, Ling Yong, Yuchen Guo, Xiaoxue Yan, Guoshu Chen, Daming Kong, Tianyan Zhou. A stochastic population pharmacodynamic model of QAP14 in the treatment of lung metastases of 4T1 breast cancer[J]. Journal of Chinese Pharmaceutical Sciences, 2021, 30(10): 794-805.

Figures/Tables 6

References 29

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