consultancy in computational toxicology
Computational / in silico toxicology is a rapidly developing discipline. If you are looking to incorporate data generated in silico into your safety, hazard or risk assessment, you can choose one of our options.
25 years of experience with in silico modelling
Multiple relevant models are used to increase confidence in the derived toxicity estimates
Expert selection of tools and methods in agreement with the official guidelines
In silico results complementary to in vitro results
COST EFFECTIVE & FLEXIBLE
Free feasibility study
In silico methods - lower cost compared to in vitro methods
Rapid access to several free and commercial tools
Service tailored to your needs (e.g. internal decision making or safety evaluation)
DELIVERY & CUSTOMER SUPPORT
Feasibility study typically delivered in two days
Study report typically delivered within two weeks
24 hour reactivity to client questions
Expert advice service for in silico toxicology
Computational toxicology is a rapidly developing discipline increasingly being adopted and encouraged by regulators. It offers lower cost and time compared to in vitro and in vivo methods
Keeping up to date is resources and time consuming ...
In silico assessment of mutagenicity for E&L and medical devices
Computational toxicology is applied to predict skin sensitisation and bacterial
in vitro reverse mutagenicity (Ames test) using a combination of rules-based SAR, statistical QSAR and an expert judgement.
(Q)SAR and read-across service
ToxNavigation is specialised in the application of QSAR and read-across for internal and regulatory purposes. Choosing the best analogues, assessing uncertainty, building a case using weight of evidence, applying the best QSAR models and assembling a report with justifications are all part of this comprehensive service.
Non-testing methods for Dietary Risk Assessment of Plant Protection Products and their Residues
The Guidance on the establishment of the residue definition for dietary risk assessment adopted by EFSA in 2016 describes a stepwise approach based on toxicological, metabolism and non-testing data ((Q)SAR, read-across and TTC ) ...
In silico assessment of mutagenicity for drug impurities under ICH M7
Computational toxicology is applied to predict bacterial in vitro reverse mutagenicity (Ames test) under the ICH M7 regulations using a combination of rules-based SAR, statistical QSAR and an expert judgement.
Endocrine disruption screening service
Screening for endocrine disruptors early in your development cycle can save you considerable costs. The service provides a cost effective QSAR screen applying 153 different models covering 18 receptors to your compound, mixture or UVCB. An expert analysis is provided along with a detailed report.
Alternatives to testing on animals for the REACH Regulation
(Q)SAR, grouping and read-acros
ECHA says “… We want to encourage registrants to use alternative methods in the best possible way ... The registrants should consider their registration dossiers as “living documents” and regularly update them ” ...