Brown, Alan, Drew, Philip, Knight, Brian, Marc, Philippe, Troth, Sean, Wuersch, Kuno and Zandee, Joyce (2016) Graphical display of histopathology data from toxicology studies for drug discovery and development: an industry perspective. Regulatory toxicology and pharmacology, 82. pp. 167-172.

Abstract

Histopathology data comprise a critical component of toxicology studies conducted on experimental drugs and are typically presented as finding incidence counts and severity scores per organ, tabulated in study reports. These data are oftentimes presented on multiple pages of a report which can be challenging for review and aggregation of results. However, the SEND (Standard for Exchange of Nonclinical Data; a subpart of CDISC-SDTM) standard provides a means for electronically collecting and managing histopathology data in a uniform fashion which can allow informatics systems to archive, display and analyse data in novel ways. Various software applications have become available to convert histopathology data into graphical displays as well as outputs for visual analyses. A subgroup of the FDA-PhUSE Nonclinical Working Group conducted intra-industry surveys regarding the use of graphical displays of histopathology data. Visual cues, use-cases, the value of cross-domain (e.g. histopathology versus organ weight data) and cross-study visualizations, and limitations were topics for discussion in the context of the surveys. The subgroup came to the following conclusions. Graphical displays appear advantageous as a communication tool to both pathologists and non-pathologists, and provide an efficient means for communicating pathology findings to project teams involved in drug discovery and development. Graphical displays can support hypothesis-generation which could include cross-domain interactive visualizations and/-or aggregating large datasets from multiple studies to observe and/or display patterns and trends. Incorporation of the SEND standard will provide a platform by which visualization tools will be able to aggregate, select and display information from complex and disparate datasets.

Item Type:	Article
Keywords:	SEND, informatics, histopathology, toxicology, graphics, IND, FDA, NDA
Date Deposited:	24 Jan 2017 00:45
Last Modified:	24 Jan 2017 00:45
URI:	https://oak.novartis.com/id/eprint/30778