[Development of an artificial intelligence system to improve cancer clinical trial eligibility screening]

INTRODUCTION

The recruitment step of all clinical trials is time consuming, harsh and generate extra costs. Artificial intelligence tools could improve recruitment in order to shorten inclusion phase. The objective was to assess the performance of an artificial intelligence driven tool (text mining, machine learning, classification…) for the screening and detection of patients, potentially eligible for recruitment in one of the clinical trials open at the "Institut de Cancérologie de Lorraine".

METHODS

Computerized clinical data during the first medical consultation among patients managed in an anticancer center over the 2019-2023 period were used to study the performances of an artificial intelligence tool (SAS® Viya). Recall, precision and F1-score were used to determine the artificial intelligence algorithm effectiveness. Time saved on screening was determined by the difference between the time taken using the artificial intelligence-assisted method and that taken using the standard method in clinical trial participant screening.

RESULTS

Out of 9876 patients included in the study, the artificial intelligence algorithm obtained the following scores: precision of 96 %, recall of 94 % and a 0.95 F1-score to detect patients with breast cancer (n=2039) and potentially eligible for inclusion in a clinical trial. The screening of 258 potentially eligible patient's files took 20s per file vs. 5min and 6s with standard method.

DISCUSSION

This study suggests that artificial intelligence could yield sizable improvements over standard practices in several aspects of the patient screening process, as well as in approaches to feasibility, site selection, and trial selection.

Optimisation of a large WWTP thanks to mathematical modelling

Better controlling and optimising the plant's processes has become a priority for WWTP (Wastewater Treatment Plant) managers. The main objective of this project is to develop a simplified mathematical tool able to reproduce and anticipate the behaviour of the Tougas WWTP (Nantes, France). This tool is aimed to be used directly by the managers of the site. The mathematical WWTP model was created using the software WEST. This paper describes the studied site and the modelling results obtained during the stage of the model calibration and validation. The good simulation results have allowed to show that despite a first very simple description of the WWTP, the model was able to correctly predict the nitrogen composition (ammonia and nitrate) of the effluent and the daily sludge extraction. Then, a second more detailed configuration of the WWTP was implemented. It has allowed to independently study the behaviour of each of four biological trains. Once this first stage will be completely achieved, the remainder of the study will focus on the operational use of a simplified simulator with the purpose of optimising the Tougas WWTP operation.