A method, comprising: obtaining, with a computer system, test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient, a first subset of the plurality of cardiovascular dimensions being independent cardiovascular dimensions and a second subset of the plurality of dimensions being dependent cardiovascular dimensions; determining, with the computer system, a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions, the plurality of normalized differences quantifying different aspects of hypertension of the patient; determining, with the computer system, predicted-effect vectors of each of a plurality of different classes of pharmaceuticals having hypertension as an indication, wherein: the predicted-effect vectors each correspond to a different respective class of pharmaceuticals among the different classes of pharmaceuticals, the predicted-effect vectors each have a plurality of values quantifying respective effects of the corresponding class of pharmaceuticals on corresponding dimensions among a third set of the cardiovascular dimensions of the patient, the values are each based on both the corresponding normalized differences of the corresponding dimension among the third set and a respective strength of effect of the corresponding class of pharmaceuticals on the corresponding dimension, the respective strength effects are determined based on respective multi-dimensional models of the corresponding class of pharmaceuticals, and the third set at least overlaps with the first subset and the second subset; determining, with the computer system, an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors of the corresponding class of pharmaceuticals; ranking, with the computer system, the different classes of pharmaceuticals based on the aggregate scores to form a ranked list of the different classes of pharmaceuticals; and outputting, with the computer system, based on the ranking, a recommended sequence of the classes of pharmaceuticals to administer to the patient. obtaining, with a computer system, test data that quantifies a patient's cardiovascular status, the test data specifying patient attributes in a plurality of cardiovascular dimensions of the patient, a first subset of the plurality of cardiovascular dimensions being independent cardiovascular dimensions and a second subset of the plurality of dimensions being dependent cardiovascular dimensions; determining, with the computer system, a plurality of normalized differences between the test data and target criteria in each of the cardiovascular dimensions, the plurality of normalized differences quantifying different aspects of hypertension of the patient; determining, with the computer system, predicted-effect vectors of each of a plurality of different classes of pharmaceuticals having hypertension as an indication, wherein: the predicted-effect vectors each correspond to a different respective class of pharmaceuticals among the different classes of pharmaceuticals, the predicted-effect vectors each have a plurality of values quantifying respective effects of the corresponding class of pharmaceuticals on corresponding dimensions among a third set of the cardiovascular dimensions of the patient, the values are each based on both the corresponding normalized differences of the corresponding dimension among the third set and a respective strength of effect of the corresponding class of pharmaceuticals on the corresponding dimension, the respective strength effects are determined based on respective multi-dimensional models of the corresponding class of pharmaceuticals, and the third set at least overlaps with the first subset and the second subset; the predicted-effect vectors each correspond to a different respective class of pharmaceuticals among the different classes of pharmaceuticals, the predicted-effect vectors each have a plurality of values quantifying respective effects of the corresponding class of pharmaceuticals on corresponding dimensions among a third set of the cardiovascular dimensions of the patient, the values are each based on both the corresponding normalized differences of the corresponding dimension among the third set and a respective strength of effect of the corresponding class of pharmaceuticals on the corresponding dimension, the respective strength effects are determined based on respective multi-dimensional models of the corresponding class of pharmaceuticals, and the third set at least overlaps with the first subset and the second subset; determining, with the computer system, an aggregate score for each respective class of pharmaceuticals among the different classes of pharmaceuticals based on values of the corresponding predicted-effect vectors of the corresponding class of pharmaceuticals; ranking, with the computer system, the different classes of pharmaceuticals based on the aggregate scores to form a ranked list of the different classes of pharmaceuticals; and outputting, with the computer system, based on the ranking, a recommended sequence of the classes of pharmaceuticals to administer to the patient.