|Decades of biomedical research in acute stroke has led to the discovery of genetic, molecular, neuroimaging and epidemiological disease markers that may profoundly improve the treatment of stroke patients - and the targeting and speedy testing of new therapies. The quantity and complexity of these data, however, currently prohibit the integration of this wealth of information into individualized patient management - and cost-effective drug development. I-Know is a knowledge discovery IT-based tool to aid early stroke diagnosis, stroke treatment, drug development and identification of risk factors as targets in disease prevention. In patient management, the I-Know system will use computerized stroke disease progression models (DPMs) (generated in this proposal) to provide an accurate diagnosis in individual patients (based on patient history and genetic profile, biochemical, clinical and neuroimaging findings).Interacting with the physician, I-Know will produce images, predicting the course of the disease given available therepeutic options and their specific actions recorded in other patients (DPMs from clinical trials). This allows physicians to diagnose and treat the patient on the basis of a wealth of information otherwise impossible to integrate by the human mind. In drug development, the pharmaceutical industry will use the I-Know stroke DPMs in classifying data in patients treated with new drug candidates, comparing it with DPMs from untreated patients. The statistical power of I-Know, we claim, far superceeds standard estimators of drug action (neurological outcome, infarct size), allowing demonstration of drug efficacy by a fraction of the patients, resources and time used today. The resulting, drug-specific DPM - accounting in unparalleled detail for drug action as well as adverse effects - is then supplied to the physician's I-Know system, allowing detailed prediction of a patient's individual response to the new drug.