TORONTO–(BUSINESS WIRE)–lt;a href="https://twitter.com/hashtag/artificialintelligence?src=hash" target="_blank"gt;#artificialintelligencelt;/agt;–Cyclica, a leading biotechnology company that leverages artificial
intelligence and computational biophysics to enable the discovery of new
medicines, has announced the addition of a machine learning predictive
engine called POEM to its Ligand Express® platform. POEM has
been applied to the prediction of ADMET
(Absorption, Distribution, Metabolism, Excretion and Toxicity) properties,
which provides critical insight into a molecule’s expected behavior in
the body. Unlike conventional quantitative structure activity
relationship (QSAR) models that have existed in pharma for decades, POEM
is parameter-free, based on multiple fingerprints, and does not require
time-consuming model training.
Ligand Express, is a cloud-based platform that uncovers the
polypharmacological profiles of small molecules, and allows scientists
to gain insights into structural pharmacogenomics by incorporating
systems biology databases including single nucleotide variant data. With
the integration of POEM, Ligand Express now offers insights into the
pharmacokinetic properties of small molecules, providing a better
understanding of the predicted behaviour of potential drug molecules.
This integration will further augment workflows within pharma, providing
scientists with a deeper understanding of a small molecule’s
polypharmacology and its key pharmacokinetic properties.
“Enabling more effective drug discovery through an integrated
computational platform is a central tenant at Cyclica,” said Naheed
Kurji, President & CEO of Cyclica. “With the integration of POEM in
Ligand Express, our users can readily access predictive ADMET properties
of their small molecules in an elegantly designed user interface,
enabling them to make effective decisions and bring better medicines to
the market faster. We will continue to enhance Ligand Express with new
features as we believe an end-to-end enabling platform will be essential
to transform drug discovery.”
“We recognize that drug discovery is a process, and part of that process
requires the evaluation of many possibilities. It is impossible to
pursue every possibility, so choosing the best starting point is
essential, but it’s not always easy,” said Vijay Shahani, Head of Design
of Cyclica. “We designed the user interface of POEM in Ligand Express to
facilitate comparisons between multiple small molecules, making it
easier to identify better starting points. We are actively developing
new features to allow greater molecular exploration and enable the
selection of top candidates.”
Cyclica is committed to building out a platform that will facilitate
effective drug discovery, and do more with artificial intelligence to
design medicines for patients. The integration of POEM into Ligand
Express® further demonstrates Cyclica’s commitment to
accelerating pharma R&D, and making drug discovery faster, cheaper, and
safer.
On May 22nd at the Collision Conference in Toronto, Cyclica will
announce its novel, first-in-class, multi-objective, drug design
technology, which also incorporates POEM. For more information, visit www.cyclicarx.com.
Cyclica is a Toronto-based, globally recognized biotechnology company
that leverages artificial intelligence and computational biophysics to
reshape the drug discovery process. Cyclica provides the pharmaceutical
industry with an integrated, holistic, and end-to-end enabling platform
focused on polypharmacology that enhances how scientists design, screen,
and personalize medicines for patients while minimizing off-target side
effects. By doing more with artificial intelligence, Cyclica aims to
revolutionize a system troubled with attrition and costly failures,
accelerate the drug discovery process, and develop medicines with
greater precision.
Contacts
Naheed Kurji
President & CEO
naheed.kurji@cyclicarx.com