Slides for my invited talk at UPCP'2013, the second Up Close and Personalized Congress.
Paris 25-28 July 2013, Paris, France
Big Data refers to the new technical ability to digitally record, transmit and process massive amounts of digital data. Data mining technologies offer the possibility to extract meaningful knowledge from this data, through the analysis of statistical correlations.
Medicine has recently entered the realms of Personalization and Prediction: treatments become personalized to fit the patient's profile, and Prediction allows forecasting the likeliness of future health condition. Personalization and Prediction are based on patients and statistical medical data, coming from various sources: Electronic Health Records, Historical records of healthcare reimbursement, Genomics, Social media, Sensors and biosensors
Research and Industry are fueling a constant flow of innovation in this last field: Connected Health devices (including monitoring of Activities of Daily Life), smart clothing, implanted or ingestible sensors are increasingly being used to gather information about the patient’s health status or life habits. This innovation provides new sources of data essential to Personalized Medicine. In particular, this offers a brand new opportunity to correlate information gathered by these new sensors with the clinical information that is commonly gathered in clinical trials. For instance it is quite realistic to imagine a clinical trial performed at the patient’s home, where drug taking is precisely monitored by sensors in ingestible pills, while the drug’s clinical effects are correlated with constant monitoring of medical indicators such as blood pressure or heart rate, as well as with the performance of daily life activities such as eating, exercising, resting, sleeping, toilet use... This opens a new realm of opportunities in the design and analysis of clinical trials.