A research team at the University of Tokyo has developed a mathematical model for early prediction of the therapeutic effects of nilotinib, a drug for treating chronic myeloid leukemia (CML), on a patient-by-patient basis.
Nilotinib is a BCR-ABL1 tyrosine kinase inhibitor (TKI) that has the effect of inhibiting the proliferation of CML cells and is a therapeutic drug that improves the prognosis of many CML patients.On the other hand, it is also known that there are individual differences in the effects of TKIs, and if the effects of TKIs during administration are poor, switching to another TKI (in addition to nilotinib, there are options for imatinib, dasatinib, and bosutinib). Therefore, a method for early prediction of the effect of TKI for each patient has been sought.
Based on the International Scale (IS) values at the start of nilotinib administration and at 3 and 6 months after the start of nilotinib administration and the amount of total white blood cells in the peripheral blood, the present investigators determined that CML within 2 years after the start of nilotinib administration. We have developed a method to estimate whether a patient will achieve a "deep response". The IS value is a value corresponding to the ratio of the amount of CML cells to the amount of total white blood cells in peripheral blood, and can be measured by a general blood test, and a deep response is also defined by the IS value.
Based on the IS value and the total white blood cell mass in the peripheral blood, we developed an ordinary differential equation model that can simulate the time changes in the normal white blood cell and CML cell mass in the peripheral blood. Based on the time-series data of the "-road study", we sought the boundaries of parameter values that classify patients who achieved a deep response within 2 years and those who did not.Using this mathematical model, when the parameter values estimated from the data from the start of treatment to the 6th month of treatment for the target patient were plotted on the classification boundary, it was possible to predict whether or not a deep response would be achieved with a high accuracy rate of about 94%. .
By using only general blood test data, the possibility of predicting the treatment effect of nilotinib (whether a deep response can be achieved within 6 years) for each patient in a short period of 2 months has been opened up. It is hoped that this will lead to the realization of personalized medicine for CML, which optimizes treatment for each patient.
Paper information:[npj Systems Biology and Applications] Early Dynamics of Chronic Myeloid Leukemia on Nilotinib Predicts Deep Molecular Response
