Integrating in silico models to enhance predictivity for developmental toxicity.
Application of in silico models to predict developmental toxicity has demonstrated limited success particularly when employed as a single source of information. It is acknowledged that modelling the complex outcomes related to this endpoint is a challenge; however, such models have been developed and reported in the literature. The current study explored the possibility of integrating the selected public domain models (CAESAR, SARpy and P&G model) with the selected commercial modelling suites (Multicase, Leadscope and Derek Nexus) to assess if there is an increase in overall predictive performance. The results varied according to the data sets used to assess performance which improved upon model integration relative to individual models. Moreover, because different models are based on different specific developmental toxicity effects, integration of these models increased the applicable chemical and biological spaces. It is suggested that this approach reduces uncertainty associated with in silico predictions by achieving a consensus among a battery of models. The use of tools to assess the applicability domain also improves the interpretation of the predictions. This has been verified in the case of the software VEGA, which makes freely available QSAR models with a measurement of the applicability domain.
Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy. Electronic address: marco.marzo@marionegri.it.
Marco
M
Marzo
Existing Substances Risk Assessment Bureau, Health Canada, Ottawa, Ontario, Canada.
Sunil
S
Kulkarni
Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
Alberto
A
Manganaro
Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
Alessandra
A
Roncaglioni
The Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, OH 45040, USA.
Shengde
S
Wu
Existing Substances Risk Assessment Bureau, Health Canada, Ottawa, Ontario, Canada.
Tara S
TS
Barton-Maclaren
The Procter & Gamble Company, 8700 Mason-Montgomery Rd, Mason, OH 45040, USA.
Cathy
C
Lester
Laboratory of Environmental Chemistry and Toxicology, Department of Environmental Health Sciences, IRCCS-Istituto di Ricerche Farmacologiche Mario Negri, Via La Masa 19, 20156 Milano, Italy.
Emilio
E
Benfenati
D000818:Animals; D016208:Databases, Factual; D023381:Endpoint Determination; D047109:Fetal Development / Q000187:drug effects; D006801:Humans; D016015:Logistic Models; D008962:Models, Theoretical; D012680:Sensitivity and Specificity; D018675:Toxicity Tests / Q000379:methods*
Developmental toxicity; In silico; In vitro and alternatives; QSAR; VEGA