Method and apparatus for predicting therapeutic outcomes

A method for producing a statistical model of a likely response to a treatment regimen for treating a disease in a mammal, the method comprising the steps of:

• a) obtaining at least one sample population of individuals representative of said disease, said sample population being treated for said disease using said treatment regimen for treating said disease;
• b) determining from said sample population a set of data for at least one variable relating to said population, said disease, or said regimen, said variable having a putative correlation with said regimen for treating said disease;
• c) deriving from said set of data said statistical model of said likely response to said regimen for treating said disease, wherein said step of deriving includes the sub-steps of:
• i) standardizing said data;
• ii) developing a discriminant function which is effective for classifying the response of individuals afflicted with said disease to said treatment regimen, said discriminant function being based at least in part on clinical profiles of individual patients who have been treated for said disease using said treatment regimen, said clinical profiles of individual patients including said diagnostic variable;
• and
• iii) performing a logistic regression using said discriminant function to assign thereby a probability of treatment outcome for said individuals.

A computer system for producing a statistical model of a regimen for treating a disease in a mammal using a set of data derived from at least one sample population of individuals representative of said disease, said sample population being treated for said disease using a treatment regimen for treating said disease, the system comprising:

• a) a pre-processing mechanism for standardizing said set of data to produce a set of normalized data;
• and
• b) a processing mechanism for processing said standardized data, said processing mechanism configured to
• i) develop a discriminant function which is effective for classifying the response of individuals afflicted with said disease to said treatment regimen, said discriminant function being based at least in part on clinical profiles of individual patients who have been treated for said disease using said treatment regimen, said clinical profiles of individual patients including said diagnostic variable;
• and
• ii) perform a logistic regression using said discriminant function to assign thereby a probability of treatment outcome for said individuals.

A computer program product including a computer-readable medium having computer-readable program code devices embodied therein for producing a statistical model of a regimen for treating a disease in a mammal using data obtained from at least one sample population of individuals representative of said disease, said sample population being treated for said disease using said treatment regimen, said program code devices being configured to cause a computer to perform the steps of:

• a) standardizing said data to produce standardized data;
• b) processing said standardized data to develop a discriminant function which is effective for classifying the response of said individuals to said treatment regimen, said discriminant function being based at least in part on clinical profiles of individual patients who have been treated for said disease using said treatment regimen, said clinical profiles of individual patients including said diagnostic variable;
• and
• c) performing a logistic regression using said discriminant function to assign thereby a probability of treatment outcome for said individuals.