The
system described herein enables clinicians and researchers to use aggregated genetic and phenotypic data from clinical trials and medical records to make the safest, most
effective treatment decisions for each patient. This involves (i) the creation of a standardized ontology for genetic, phenotypic, clinical, pharmacokinetic, pharmacodynamic and other data sets, (ii) the creation of a translation engine to integrate heterogeneous data sets into a
database using the standardized ontology, and (iii) the development of statistical methods to perform
data validation and
outcome prediction with the integrated data. The
system is designed to interface with patient electronic medical records (EMRs) in hospitals and laboratories to extract a particular patient's relevant data. The
system may also be used in the context of generating phenotypic predictions and enhanced
medical laboratory reports for treating clinicians. The system may also be used in the context of leveraging the huge amount of data created in medical and pharmaceutical clinical trials. The ontology and validation rules are designed to be flexible so as to accommodate a disparate set of clients. The system is also designed to be flexible so that it can change to accommodate scientific progress and remain optimally configured.