From Chaos to Order: Mapping Extracted Data from Systematic Literature Reviews for Application to the AOP Framework

Abstract

Introduction:

Systematic reviews (SR) collect and integrate data corpuses into consistent, computable, and comparable datasets. The adverse outcome pathway (AOP) framework facilitates the linking of data describing molecular initiating events, through one or more key events (KEs), to adverse biological outcomes. To explore the potential application of data from SRs to the AOP framework, a case study was conducted to explore mapping SR to existing AOP KEs.

Methods:

SR data consisted of in vitro and in vivo androgen receptor (AR) toxicity information from nonmammalian vertebrate species collected as described by the authors, limiting data comparability. Data were standardized and mapped to terms for Level of Biological Organization, Object, Process, and Action using existing KEs in the AOP-Wiki as a source for endpoint terms.

Results:

In vitro SR data had 131 of 264 records that mapped to AR transactivation, while in vivo data had 226 of 1891 records directly mappable to 31 different KEs (e.g., increased vitellogenin messenger RNA). When no appropriate terms existed in the AOP-Wiki, standardized terms were proposed for future use. For unstructured data, mapping and standardization required additional interpretation.

Conclusions:

This study highlights the difficulties in aligning heterogeneously extracted SR data with a structured framework. This work highlights the need for language standardization and the adoption of clear data collection guidance prior to, and during, the SR to enhance data comparability and computability. The adoption of such efforts can advance the ability of resulting data to be reused and applied to frameworks such as AOPs. Lessons learned in this case study are applicable to similar efforts examining the use of automation in data extraction and evaluation.