Automatic Selection of Clinical Trials Based on A Semantic Web Approach.

Recruitment of patients in clinical trials is nowadays preoccupying, as the inclusion rate is particularly low. The main identified factors are the multiplicity of open clinical trials, the high number and complexity of eligibility criteria, and the additional workload that a systematic search of the clinical trials a patient could be enrolled in for a physician. The principal objective of the ASTEC project is to automate the prescreening phase during multidisciplinary meetings (MDM).

Improving the pre-screening of eligible patients in order to increase enrollment in cancer clinical trials.

Background: The performance of randomized controlled trials (RCTs) is often hindered by recruitment difficulties. This study aims to explore the pre-screening phase of four prostate cancer RCTs to identify the impact of a systematic pre-selection of eligible patients for RCT recruitment.

Methods: The pre-screening of four RCTs opened at the Comprehensive Cancer Center in Rennes was analyzed retrospectively (French Genitourinary Tumor Group (GETUG) 14, 15, 16, and 17).

OWL model of clinical trial eligibility criteria compatible with partially-known information.

Background: Clinical trials are important for patients, for researchers and for companies. One of the major bottlenecks is patient recruitment. This task requires the matching of a large volume of information about the patient with numerous eligibility criteria, in a logically-complex combination.