Expert knowledge-based toxicity prediction software from Lhasa Limited.
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Expert knowledge-based toxicity prediction software from Lhasa Limited.
Index
This brochure is an interactive PDF and
P3 Introduction to Derek Nexus
Created by Lhasa’s scientific experts, Derek Nexus provides
an early indication of the toxicity of a query compound.
contains ‘hotlinks’. Please use the navigation
panel on the top left or click on the relevant
headings on the right to navigate to the subject
of your choice. Alternatively you can ‘scroll’
P4-5 Features and benefits
Including features such as ICH M7 prediction functionality,
through the document. negative predictions and transparency, Derek is designed to
facilitate your workflow.
P6 Our products
Lhasa develops software for toxicity, metabolic fate,
purge factor calculation and chemical degradation.
P7 Why choose Lhasa?
Lhasa has been creating scientifically robust expert software
to improve efficiency and aid regulatory submission for over
35 years.Introduction
to Derek Nexus
Derek Nexus is the preferred expert rule-based system for They use their expertise to analyse complex, sometimes
the prediction of toxicity (Dobo et al. 2012, Sutter et al. 2013). conflicting data and provide expert reasoning rules to give
you an indication of the likelihood for toxicity.
Using structure activity relationships (SAR) created by
Lhasa’s scientific experts, Derek provides you with an early Derek is used across a wide range of industry
indication of the potential toxicity of your query compound. sectors, including:
Predictions given by Derek are supported by a graphical Cosmetics, Pharmaceuticals, Chemicals, Regulators,
explanation of the SAR, mechanistic rationale, toxicity data Government Agencies and Academia.
of known compounds within the SAR and key references.
Generating transparent and scientifically robust predictions,
Derek can be used to fill gaps within your in-house data.
Drawing on over 35 years of experience, Lhasa scientists
continually work on the Derek knowledge base, updating it
regularly with current toxicological knowledge.Features and benefits
Expert ICH M7 Auto
Support Classification
Derek predictions are accepted by regulators under the A user editable ICH M7 classification is derived from the
ICH M7 Guideline. The M7 prediction functionality allows predictions provided by Derek and Sarah and any relevant
for simultaneous compound processing in Derek and Sarah experimental information (from the Carcinogenicity Potency
against the mutagenicity in vitro endpoint fulfilling both the Database and Lhasa certified Ames data).
expert rule-based and statistical-based predictions required
under ICH M7.
Negative Predictions
Extensive Coverage of Provided
Chemical Space Rather than an “out of domain”, Derek provides negative
predictions for the bacterial in vitro mutagenicity and skin
Derek alerts are built on public, proprietary and regulatory sensitisation endpoints when no associated alerts are fired
data (including data from the FDA). More than 35% of the (Williams et al. 2016).
mutagenicity alerts have been developed using proprietary
data. Users can also incorporate their own data into Derek
thereby generating predictions relevant to their chemical
space, safe in the knowledge that regulators are using the
same approach.
Skin Sensitisation
Potency Predictions
A Nearest Neighbour model is used to predict EC3 values
for compounds that fire a skin sensitisation alert, allowing
you to assess their skin sensitisation risk (Macmillan et al.
2016).Features and benefits
Transparent Customisable
Predictions Reports
Predictions are clearly represented and contain supporting Derek incorporates a reporting framework that allows (.doc
evidence and patterns associated with the alerts for your .pdf .xlsx and .sdf) file export. Report templates are fully
compound. Expert commentary, including a review of data, customisable by the end user ensuring that you can provide
validation comments, mechanistic rationale and explanation the right information at the right time.
of the structure activity relationship are also included,
making the expert review easier (Barber et al. 2015).
A Derek Alert is a
Reducing Risk Lhasa Alert
in R&D All alerts are developed in-house by a dedicated team
of expert scientists. Lhasa’s investment in research
Save time and money by identifying potentially toxic ensures that alerts are regularly updated based on current
chemicals, thereby reducing risk in research and toxicological knowledge.
development. Derek can swiftly provide single or batch
predictions for the toxicity of compounds from Lhasa
knowledge and your own knowledge.
Rapid Toxicity
Assessment
One Interface,
Multiple Predictions Derek can swiftly provide single or batch predictions for the
toxicity of query compounds.
Using Derek within the Nexus platform can give you direct
access to other Lhasa in silico tools, including Meteor Nexus,
Sarah Nexus and Vitic, improving workflow efficiency.Our Products
What software do we produce?
Through regular scientific and software updates, Lhasa continues to deliver
accurate, transparent knowledge to its solutions, to make them more
comprehensive, as well as easier and faster to use.
Lhasa offers some of its products on the Lhasa Cloud. This means new
features can be delivered even faster, giving members immediate access to
cutting-edge science. Find out more about our products at:
https://www.lhasalimited.org/products
An expert rule-based system A chemical database and
for the prediction of toxicology. information management system.
A statistical-based system for An expert rule-based system for
the prediction of mutagenicity. the prediction of metabolic fate.
A project-centric database for A secondary pharmacology model suite
storage of toxicity knowledge. leveraging value from federated learning.
A tool for assessing the relative A tool to support risk assessment in the
purging of mutagenic impurities. context of adverse outcome pathways.
An expert rule-based system for the
prediction of degradation pathways.References
• Barber et al. (2015) ‘Establishing
best practice in the application of
expert review of mutagenicity under
ICH M7’, Regulatory Toxicology and
Pharmacology, vol 73, no. 1, pp.
Working together
for a better future
367-377.
http://dx.doi.org/10.1016/j.
yrtph.2015.07.018
• Dobo et al. (2012) ‘In silico
methods combined with expert
knowledge rule out mutagenic
potential of pharmaceutical
impurities: An industry survey’, When asked why people choose to work with
Regulatory Toxicology and
Pharmacology, vol. 62, no. 3, April,
pp. 449-455.
Lhasa Limited, the common responses are:
http://dx.doi.org/10.1016/j.
yrtph.2012.01.007
• Macmillan et al. (2016) ‘Predicting
All science is developed in-house, providing
skin sensitisation using a decision
tree integrated testing strategy with Software is easy to use and well supported. the opportunity to discuss directly with
an in silico model and in chemico/in Lhasa expert scientists.
vitro assays’, Regulatory Toxicology
and Pharmacology, vol. 76, April,
pp. 30-38.
http://dx.doi.org/10.1016/j. Lhasa collaborates with the wider scientific
yrtph.2016.01.009 Transparency of Lhasa systems allows trust
community to advance the understanding
and confidence in the science presented.
and performance of in silico technology.
• Sutter et al. (2013) ‘Use of in silico
systems and expert knowledge
for structure-based assessment of
potentially mutagenic impurities’,
Regulatory Toxicology and Over 35 years of experience in developing Feedback from members is encouraged
Pharmacology, vol. 67, no. 1, state-of-the-art in silico prediction and and listened to, and drives the future
October, pp. 39-52. database systems. development of Lhasa products.
http://dx.doi.org/10.1016/j.
yrtph.2013.05.001
• Williams et al. (2016) ‘It’s difficult,
but important, to make negative
predictions’, Regulatory Toxicology shared knowledge shared progress
and Pharmacology, vol. 76, April,
pp. 79-86.
http://dx.doi.org/10.1016/j.
yrtph.2016.01.008
www.lhasalimited.org
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