  Neoadjuvant chemotherapy has been used for breast cancer aiming at
downgrading before surgery. In this article we propose a new quantitative
analysis of the effects of the neoadjuvant therapy to obtain numerical,
personalized, predictions on the shrinkage of the tumor size after the drug
doses, by data assimilation of the individual patient. The algorithm has been
validated by a sample of 37 patients with histological diagnosis of locally
advanced primary breast carcinoma. The biopsy specimen, the initial tumor size
and its reduction after each treatment were known for all patients. We find
that: a) the measure of tumor size at the diagnosis and after the first dose
permits to predict the size reduction for the follow up; b) the results are in
agreement with our data sample, within 10-20 %, for about 90% of the patients.
The quantitative indications suggest the best time for surgery. The analysis is
patient oriented, weakly model dependent and can be applied to other cancer
phenotypes.
