Pharma R&D Today
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The Power of Two in Lead Optimization
Posted on July 3rd, 2017 by Prima Sung in Chemistry
The rise of in silico approaches has revolutionized early drug discovery, making it possible to model the potential in vivo behaviors of large numbers of compounds, delve deep into their bioactive and chemical properties, and make predictions about their interactions with other drugs. Efficient and successful pharmaceutical R&D is dependent on high-quality data and the right modeling tools to work with it.
A major goal for Elsevier is to ensure that our research solutions give the best support for data-driven drug discovery. We focus on delivering high-quality data through solutions that are easily integrated into an IT environment designed for insightful in silico workflows.
Two of those research solutions, Reaxys and Reaxys Medicinal Chemistry are each designed to be an important part of early drug discovery.
Reaxys focuses on physicochemical substance properties, reactions and synthesis methods. It helps researchers to make decisions about the possible effects of structural changes on properties, assess the best means to synthesize their compound (or indeed, the best place to purchase it), and get a clear picture of a compound’s reactivity.
Reaxys Medicinal Chemistry focuses on the bioactivity of chemical substances. It helps researchers to get a clear picture of a compound’s affinities for targets and its toxicity, safety, efficacy and pharmacokinetics. It also enables clear comparison of substances in terms of their affinity for targets.
What makes them such a powerful tool for early drug discovery is that they are available as an integrated research solution through a single user interface. They provide all the information needed for decisions in lead optimization.
Identifying the right lead compound is critical for successful drug development. The more that the researchers can determine about a substance’s drug-like properties at an early stage, the more efficient the whole development process. Time and resources are not wasted pursuing a “dead-end lead” and the developers gain a deeper understanding of the market potential that helps inform business decisions.
The previous versions of Reaxys and Reaxys Medicinal Chemistry were already available in this integrated form that enabled expert users to perform lead optimization workflows. However, it was noticed that relatively few users were getting the most out of the connection between the two.
This year, New Reaxys and New Reaxys Medicinal Chemistry have been launched. Both have been significantly re-designed to make those workflows easier and more efficient, with researchers able to thoroughly investigate the potential of a compound in a single session. Users can retrieve precise results by performing a keyword- and/or structure-based query through Quick Search or constructing a detailed search using Query Builder, which includes 19 dedicated query forms for medicinal chemistry workflows.
Navigation between results tabs for physicochemical properties, bioactivity, reactions, literature and related experimental procedures has also been streamlined to ensure that users can more easily move through a complete research workflow for lead optimization, even comparing the affinity of multiple substances for multiple targets.
Crucially, both solutions support application programming interfaces and allow the exporting of results in formats that are suitable for common in silico modeling software. This means that the combined lead optimization solution can integrate into an end user’s existing IT environment, supporting broader research.
Integrating related solutions, such as has been done with the combined New Reaxys and New Reaxys Medicinal Chemistry, is an essential step in creating platforms that properly support modern, data-driven pharmaceutical development. Opportunities to make connections between separate databases and in silico modeling tools must be taken to keep pushing the evolution of drug discovery.
All opinions shared in this post are the author’s own.
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Sr. Product Marketing Manager at Elsevier
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