Optimising Drug Discovery
Optimising Drug Discovery
Optibrium and NextMove Software recently announced a technology collaboration which will help to guide compound optimisation in drug discovery.
To find out more about Optibrium and the collaboration, we spoke to Matt Segall, Co-founder and CEO, Optibrium.
Can you tell us a little about Optibrium?
At Optibrium we develop software that helps to quickly target high quality leads and candidate drugs, to improve the efficiency and productivity of the drug discovery process. As we know, the success rate of candidate drugs entering clinical trials is extremely low. One of the major reasons for this low success rate and the large associated cost, is the challenge of identifying compounds with an optimal balance of the many, conflicting, factors that are required in a successful candidate, such as potency, ADME and safety. Our software platforms address these challenges by providing unique solutions for small molecule design, optimisation and data analysis in interactive and easy-to-use software.
We are headquartered in Cambridge, UK and work closely with a broad range of customers and collaborators world-wide that include leading global pharma companies, biotech and academic groups. However, Optibrium’s software products are not exclusively used in drug discovery and have wide application in other industries including agrochemical, flavourings, cosmetics and fragrances.
Optibrium’s primary software platform is StarDrop. Can you describe some of its features?
StarDrop is a unique platform for multi-parameter optimisation, guiding the identification of effective leads and their transformation into candidate drugs with a high probability of success downstream. StarDrop is a highly visual and interactive environment that makes it easy for all members of a project team to quickly and confidently make decisions on compound selection and design. The suite is complemented by a range of optional, plug-in modules, developed by Optibrium and our partners with world-leading computational methods, including predictive modelling and de novo design.
We are especially excited about StarDrop's latest innovation, Card View™, as it offers a ground-breaking way to work with compound data in the context of a drug discovery project. Chemical structures and associated data are presented on virtual cards that can be moved and organised with complete freedom, creating ‘links’ and ‘stacks’ to capture relationships and groupings. This lets researchers explore data in a ﬂexible and interactive way to organise compounds the way that they are thinking about them.
We have put StarDrop at the very heart of the drug discovery process, making sure it provides an intuitive environment to integrate data from experimental databases or predictive models. The result is a comprehensive platform that spans the drug discovery process from selection of compounds in early hit-to-lead through design of improved molecules in lead optimization to identification of high quality candidates.
Optibrium has recently announced a collaboration with NextMove Software, to integrate NextMove Software’s Matsy technology with the StarDrop software suite. How did this collaboration come about?
We have an on-going commitment to provide access to the best computational methods through our user-friendly StarDrop environment. This is primarily through our own in-house research and development but also with partner organisations who share this ethos. We initially learned about Matsy through mutual clients and scientific presentations given by NextMove at conferences. Both Optibrium and NextMove realised that Matsy was highly complementary to the compound design tools of StarDrop and would bring additional benefits to our users.
What benefits will this collaboration bring to Optibrium’s customers?
The combination of NextMove Software’s Matsy technology with Optibrium’s StarDrop will help guide scientists to quickly identify novel, active compounds based on matched molecular series analysis.
The Matsy algorithm generates and searches databases of matched molecular series to identify chemical substitutions that are most likely to improve target activity (J. Med. Chem.,2014, 57(6), pp 2704–2713). This goes beyond conventional ‘matched molecular pair analysis’ by using data from longer series of matched compounds (and not just pairs) to make more relevant predictions for a particular chemical series of interest. As part of the collaboration with Optibrium, Matsy will be applied in StarDrop’s Nova module, which automatically generates new compound structures to stimulate the search for optimisation strategies related to initial hit or lead compounds. StarDrop’s unique capabilities for multi-parameter optimisation and predictive modelling will enable the resulting ideas to be efficiently prioritised and identify high quality compounds with the best chance of success.
For more information, please visit www.optibrium.com.
Matt Segall was speaking to Anna-Marie MacDonald, Editor for Technology Networks.