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OPERA models supporting regulatory needs (SOT 2023)
Citation:
Mansouri, K., T. Martin, X. Chang, D. Allen, A. Williams, AND N. Kleinstreuer. OPERA models supporting regulatory needs (SOT 2023). SOT, Nashville, TN, March 19 - 23, 2022. https://doi.org/10.23645/epacomptox.22551853
Impact/Purpose:
N/A
Description:
OPERA is a freely accessible standalone application based on the open-source/open-data concept providing a suite of over twenty QSAR models for toxicity endpoints and physicochemical, environmental fate, and ADME properties. OPERA follows the five OECD principles for QSAR modeling to provide scientifically valid, high accuracy models with minimal complexity that support mechanistic interpretation, when possible. Experimental data is thoroughly curated, and chemical structures standardized, prior to modeling. Recent additions to OPERA include models for ADME related parameters of high importance to in vitro-to-in vivo extrapolations such as fraction unbound to plasma protein (Fu), intrinsic hepatic clearance (Clint), and Caco2 permeability (logPapp). Previously, three consensus models developed through international collaborative projects were added to the suite to support regulatory assessment processes involving estrogen and androgen pathway activity (CERAPP and CoMPARA), as well as cute oral systemic toxicity (CATMoS). In the latest version, 3.0, most OPERA models including physicochemical properties (logKow, water solubility, Henry’s law constant, vapor pressure, melting point and boiling point) and ADME parameters (Fu, Clint and Caco2) were updated with the latest publicly available datasets to improve their predictivity and applicability domain coverage and to account for highly investigated groups of chemicals such as polyfluorinated substances (PFAS). The largest datasets included in the knowledge base reached over 20,000 experimental entries for logKow and melting point. OPERA can generate predictions for single chemicals or in batch mode, and the chemical structure inputs can be processed using its internal QSAR-ready standardization workflow or provided via structure identifiers (CASRN, DTXSID, InChI Key) that are used to query its internal database of over 1M curated chemical structures from EPA’s DSSTox. The models’ yielded predictions associated with accuracy estimates, applicability domain assessments, confidence ranges, and experimental values when available. Technical and performance details are described in OECD-compliant QSAR model reporting format (QMRF) reports. OPERA predictions are available through EPA’s CompTox Chemicals Dashboard (https://comptox.epa.gov/dashboard), the National Toxicology Program’s Integrated Chemical Environment (https://ice.ntp.niehs.nih.gov/) and recently through FDA’s Precision Platform (https://precision.fda.gov/). In addition to the standalone command-line and graphical user interface for Windows and Linux operating systems that can be downloaded from the NIEHS GitHub repository (https://github.com/NIEHS/OPERA), the OPERA application can now be run as a plugin within the OECD’s QSAR Toolbox (https://repository.qsartoolbox.org/). It is also provided as Python, C/C++ and Java libraries that can be embedded in other applications. This project was funded with federal funds from the NIEHS, NIH under Contract No. HHSN273201500010C. The views expressedin this presentation are those of the authors and do not necessarily reflect the views or policies of any federal agency. *Presenting author (will attend and present the abstract at the conference)
URLs/Downloads:
DOI: OPERA models supporting regulatory needs (SOT 2023)
OPERA MANSOURI SOT23_NCK_KM.PDF (PDF, NA pp, 3979.573 KB, about PDF)