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Machine-learning and mechanistic modeling of metastatic breast cancer after neoadjuvant treatment

Fig 2

Calibration and validation of a kinetics-pharmacodynamics (K-PD) mathematical model for neoadjuvant sunitinib treatment effect on pre- and post-surgical tumor growth.

Pre- and postsurgical growth of LM2-4LUC+ human metastatic breast carcinomas were measured in multiple groups involving different neoadjuvant treatment modalities (doses and durations). The mathematical model was fitted to the experimental data using a mixed-effects population approach (n = 104 animals in total). (A) Comparison of the simulated model population distribution (visual predictive check) for vehicle and neoadjuvant sunitinib treatment (60mg/kg/day) 14 days before surgery. (B) Examples of individual dynamics. Tx, treatment; PT, primary tumor; MB, metastatic burden.

Fig 2

doi: https://doi.org/10.1371/journal.pcbi.1012088.g002