Physical activity is a powerful lifestyle factor that on average reduces risk for development of diabetes and cardiovascular disease. Nevertheless, we have demonstrated that following supervised endurance exercise training, 20% of subjects show no change in fitness and 30% demonstrate no improvement in insulin sensitivity or worse-still an adverse response. Our concept is that by using molecular profiling of blood/muscle samples we will develop personalised lifestyle intervention tools. Further, revealing the biological basis for a variable metabolic or cardiovascular response to exercise will enable us to propose new targets and biomarkers for drug discovery efforts directly in humans. Using our established OMICS approaches (RNA, DNA and Metabo-) we will generate classifiers that predict the responses to exercise-therapy (fitness and insulin sensitivity). Classifier generation is a statistical strategy for diagnosis or prognosis. Critically, we have a large human tissue biobank, including subjects with insulin-resistance; young to elderly males and females, as well as twins. Our SME partners have significant intellectual property and capacity in the field of bio-prediction, with a proven track-record of collaboration with the team and product development. We will add to the diversity of our biobank by carrying-out an exercise intervention study using a novel time-efficient strategy that we have recently proven to be effective in reducing insulin resistance in sedentary young people and in middle aged obese subjects. A time-efficient protocol is a critical as lack-of-time is a key reason for not maintaining physical activity levels. Finally, we have a novel out-bred rodent model that replicates high and low exercise training responses and we will establish its suitability for future drug screening purposes. Because of these substantial pre-existing resources we believe that our project has a very high probability of delivering on its goals of improving the healthcare of European citizens