Programmed Cell Death Ligand 1 Pathologist Training in the Time of COVID-19: Our Experience using a Digital Solution.

Abstract

The COVID-19 pandemic presented numerous challenges to the continuity of programmed cell death ligand 1 (PD-L1) assay training events conducted by our organization. Under typical conditions, these training events are face-to-face affairs, where participants are trained to assay algorithms on glass slides during multi-headed scope sessions. Social distancing measures undertaken to slow pandemic spread necessitated the adaptation of our training methods to facilitate assay training and subsequent continuation of clinical trials. The present report details the creation and use of the Roche pathology training portal (PTP) that allowed for remote training to diagnostic assay algorithms. The PTP is a web-based system comprised of a learning management system (LMS) coupled to an image management system (IMS). Whole slide images (WSIs) were produced using a DP200 instrument (Roche, Pleasanton, CA) and these scan files were then uploaded to an IMS. Courses were created on the LMS using annotated WSIs that were shared with enrolled pathologists worldwide during assay training events. These courses culminated in assay certification examinations, where pathologists evaluated test-case WSIs and evaluated these cases within the LMS. Trainee submissions were analyzed for pass/fail status by comparing user data entries with consensus scores on these test-case WSIs. To date, 47 pathologist trainings have occurred and of these, 44 have successfully passed the associated assay certification exam on the first attempt (93% 1st-try pass rate). The PTP allowed roche to continue training sites during the COVID-19 pandemic, and these early results demonstrate the capability of this digital solution regarding PD-L1 diagnostic assay training events.

• Authors: Dorothy Hayden, Joseph M Herndon, James C Campion, Janine D Feng, Fangru Lian, Jessica L Baumann, Bryan K Roland, Ehab A ElGabry
• Journal: Journal of pathology informatics (J Pathol Inform) Vol. 12 Pg. 47 ( 2021) ISSN: 2229-5089 [Print] United States
• PMID: 34934522 (Publication Type: Journal Article)
• Copyright: Copyright: © 2021 Journal of Pathology Informatics.