Mendel Health, Inc.

The goal of this prospective study is to assess the performance of AI (artificial intelligence) augmentation (compared against historical controls) to identify oncology patients who meet inclusion criteria for a clinical trial. The study staff will leverage a natural language processing (NLP)-based AI algorithm that rank-orders patients most likely to meet inclusion criteria for a trial. We hypothesize that this collaborative Human+AI workflow can improve the efficiency, accuracy, and diversity of trial prescreening.

Identifying eligible patients is a key process in the clinical trial enterprise. Currently, this process relies on time-intensive manual chart review, creating a rate-limiting step for trial participation. The integration of AI technology into the trial screening process has potential to improve participation rates. This study aims to assess the performance (accuracy, efficiency) of AI-augmented patient identification and inform optimal integration into clinical research screening processes.

This is a double blinded two-arm randomized case-only interventional trial. A total of 60 patients who are to receive Paclitaxel to be included and allocated in two groups. The protocol is to be reviewed by the Research Ethics Committee of Faculty of Medicine Cairo University.
All procedure will be done in Kasr El-Einy Center of Radiation Oncology and Nuclear Medicine.
The first arm (Venlafaxine group) will receive Venlafaxine extended release (37.5 mg) tablets (Zimmerman et al., 2016).
The second arm (Memantine group) will receive memantine 10 mg once daily (Morel et al., 2016)