Method and system for prediction of medical treatment effect

A computerized system for use in planning a medical treatment for an individual having a specific cancer disease, the system comprising:

• a data input utility configured for receiving input data comprising first and second input data, the first input data comprising medical data of a specific individual, and the second input data comprising one or more predetermined endpoints defined by a physician as a treatment target with respect to the specific individual, the one or more predetermined endpoints comprising at least one of a time to disease progression or tumor size over time with respect to the cancer disease;
• a database including one or more standard disease progression models and training data sets of medical data of a group of individuals that had the specific cancer disease, each of the standard disease progression models including a set of differential equations forming a population model representing a uniform general mechanistic model applicable for all patients;
• a data processor comprising a modifier module, a predictor module and a simulator module,
• the modifier module being configured to apply machine learning to the one or more standard disease models by utilizing the medical data of a group of individuals that had the specific cancer disease and generate respective one or more modified disease progression models, each modified disease progression model comprising modifications of the standard disease models based on the medical data of the group of individuals and functions describing relations between the medical data of the group of individuals and variations of one or more coefficients of the differential equations in the standard disease progression models, each modified disease progression model defining relationships between tumor size, vascular system, and mechanism of action of one or more drugs included in one or more treatment plans comprising one or more predetermined treatment protocols for treating said specific cancer disease, thereby describing dynamics of the cancer disease, in time, under treatment by the one or more treatment plans;
• the predictor module being configured for processing the one or more modified disease progression models by utilizing said first input data and generating respective one or more personalized disease progression models adapted to the individual,
• the simulator module being configured for processing said one or more personalized disease progression models with respect to said one or more endpoints, and generating output data indicative of personal treatment effect with respect to said one or more treatment plans and each of said one or more endpoints, the output data comprising recommendation data as to whether use said one or more treatment plans in treating the individual;
• and
• a data presentation utility configured for presenting said output data to the physician, thereby enabling evaluation of said one or more treatment plans with respect to each of said one or more endpoints.