Certara said this week that it will be the exclusive provider of Barcelona, Spain-based Chemotargets' software for predicting the off-target effects of small drug molecules.
Financial arrangements related to the distribution deal were not disclosed.
Chemotargets' software is an open system that uses a ligand-based approach to predict the affinity profiles of real or virtual small molecules across a list of thousands of protein targets from public, commercial, and proprietary sources.
These predicted profiles can then be used to suggest possible unintended impacts of these drugs.
The company, founded in 2006, is a spinoff from Jordi Mestres's chemogenomics laboratory in the Hospital del Mar, a research center associated with the University Pompeu Fabra in Barcelona.
Mestres said in a statement that "drug selectivity has been historically biased by the limited amount of pharmacological data available" to drug developers.
"Having a computational tool that allows for extending the currently known target affinities with additional predicted off-target affinities is a means to having a more realistic picture of how drugs may actually exert their action," he said.
Mestres further noted that because drugs with similar side effects "tend to bind to common targets," being able to spot similarities in "target profiles" between these therapies and new small molecules could help drug developers anticipate unintended outcomes.
James Hayden, Certara's senior vice president of sales and marketing, added that the "ability to augment public ligand-based target models" with other kinds of commercial and proprietary pharmacological data "offers a significant competitive advantage to our customers."
Hayden added that the firms plan to offer additional modules that will address other aspects of systems drug discovery and development.
Chemotargets peddles its software solution to groups in the systems drug discovery market including pharmaceutical and chemical firms.
Chemotargets' target profiling program processes small molecules against ligand-based models of 4,819 protein targets, including 2,790 enzymes, 217 G-protein-coupled receptors, 401 transporters and ion channels, and 40 nuclear receptors.