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Zeneth

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Zeneth is an expert, knowledge-based software that gives you accurate forced degradation predictions quickly. Zeneth is the perfect cost-effective solution for scientists who need to understand the forced degradation pathways of organic compounds.

Zeneth is your trusted degradation expert system. It is based on data implemented by scientists at Lhasa Limited, who continually work on the transformation knowledge base with current transformation knowledge.

Benefits

How Zeneth Can Benefit You

Whether your industry is cosmetics, pharmaceuticals, chemicals, or you are in academia, Zeneth can help you because it:

  • Provides information for decision-making when there is little or no experimental data available, supporting regulatory submissions and informing early stages of development.
  • Shows predicted transformation and degradant information graphically.
  • Assists in the selection of appropriate excipients and highlighting potentially problematic ones.
  • Acts as a training or learning tool by using the extensive expert knowledge in the Lhasa knowledge base. Working with Zeneth helps you to develop more in-depth knowledge about forced degradation.
  • Prevents the overlooking of possible pathways through an unbiased application of transformations.

The Zeneth knowledge base is created and supplied by Lhasa Limited containing data from published sources and data donated by our member organisations. This data is collated, checked and verified by Lhasa scientists before being used to develop new knowledge rules and relationships. These rules and relationships are based on empirical observations that are supported by an understanding of the transformation mechanism or by rigorous vetting.

“The benefit of predictive programs for forced degradation is even greater when you consider that information on stress testing is not readily available. As a matter of fact, forced degradation studies are expensive and time consuming, and are mainly performed on compounds that have a good chance of reaching the market. Furthermore, these studies are often conducted on highly confidential material (i.e. APIs that are already in an advanced stage of development) and may not even be published. For this reason, the field of degradation chemistry is relatively immature and generates a limited amount of publicly available data.” (Parenty et al, 2013)

 

Parenty et al. (2013) An Expert System To Predict the Forced Degradation of Organic Molecules, Molecular Pharmaceutics, 10 (8), pp. 2962-2974. http://pubs.acs.org/doi/abs/10.1021/mp400083h

 

 

Approach

How Zeneth Works

Following submission of your structures to Zeneth, the structures are compared to the Lhasa knowledge base, or your own knowledge base that you have created using the Zeneth Knowledge Editor. 

Zeneth then predicts the first generation degradants by considering:

  • the presence or absence of conditions (light, water, oxygen, radical initiator, peroxide, metal) as well as temperature and pH
  • the presence or absence of structural features
  • the relative likelihood of competing transformations

Each degradant is analysed to predict further degradation and its level of likelihood is shown. The results are displayed in an interactive tree graphic along with supporting data, such as reasoning behind each prediction, transformation details and degradation path. The prediction is generated by applying expert knowledge rules in degradation to the data returned from the knowledge base.

Zeneth Knowledge Editor

The integrated Zeneth Knowledge Editor enables you to create your own knowledge base that is based on the same schema used in the Lhasa-supplied Zeneth knowledge base.

This means that you can effectively capture your organisation’s knowledge from past research and make it useful and easily accessible to your current research programs. Using Zeneth Knowledge Editor, you can create and add knowledge, such as:

  • transformations and structure-activity relationships (SARs)
  • knowledge rules
  • literature references

Features of Zeneth

Zeneth has the following key features:

  • Select transformations - You can select the transformations to be used in processing, meaning the results output are those of most interest to your project.
  • Process against excipients - Easily select from a pre-defined list of excipients and add further excipients to this list for processing against your compounds. This assists you in selection of the most appropriate excipients to use and can highlight potential problems.
  • Result filtering - After a prediction, you can easily filter your results to focus on the degradants that you are interested in.
  • Duplicate handling - Duplicate degradant structures are identified by Zeneth. You can select to view only one instance of each duplicate and find other duplicates.
  • Reasoning details - There is richly-detailed information for each prediction to help you understand the basis of a prediction. There is also an easily accessible explanation of the impact that both the absolute and relative reasoning have had on the prediction results.
  • Report customisation - You can customise the information that is included in the reports. Customised settings will be retained between sessions.

How is Zeneth Used?

Zeneth is used across a range of industry sectors but most notably within pharmaceutical departments. The following provide an indication of how some of our members are using Zeneth as part of their workflow.

Genotoxic impurities:

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

A use of Zeneth in conjunction with experimental forced degradation studies:


Zeneth can be used to help determine the chemical structures of degradants detected by a mass spectrometer or other detection methods and to deduce the likely degradation pathways. Following processing of the parent compound through Zeneth, a range of filters can be applied to provide a results tree that is consistent with experimental findings.


Early warning system:


Zeneth has been used within exploratory formulations departments to understand and account for any potential degradation problems within the API at an early stage. This advanced understanding of the possible degradants informs future decisions around experiment and excipient selection, as well as identifying any testing requirements.

 

Contact Us

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