This revolutionary platform empowers scientists in the pharmaceutical industry to generate novel drug-like compounds by combining powerful methods for molecule generation, ADMET prediction, and high-throughput ligand-protein interaction prediction.
Classical computational drug design approaches, like virtual screening, focus on a single protein target. These approaches do not holistically consider a drug’s polypharmacology, the phenomenon of one drug acting on multiple proteins in the body, or a drug’s pharmacokinetic properties, which describes how a drug is absorbed and processed by the body. Unlike single target approaches, Ligand Design focuses on a drug’s polypharmacology and explores synthetically accessible chemical space to de novo design small molecules against a collection of targets and anti-targets, while simultaneously selecting for physicochemical and ADMET properties. Ligand Design has the ability to transform research and discovery processes, and augment the capabilities of scientists to rapidly design drugs with greater precision and efficacy. The platform has been used by leading pharmaceutical companies, biotech companies, and academia globally, and is showing promising results in drug discovery. To date, several novel agents have been synthesized and tested successfully for activity in multiple disease areas.
“I believe that the Cyclica team is on the forefront of innovation in drug discovery. Together with Ligand Express, their new Ligand Design technology will reshape and enhance how scientists conduct their research faster and with higher quality,” said John Conway, Adviser at Cyclica, and Global Head, Data Science and AI IT at AstraZeneca. “At the end of the day, it’s all about making faster and more informed decisions, and their drug discovery platform allows scientists to do just that.”
“Our vision is to reduce the time of drug discovery from 7 years to 2 years, and to get the best molecules in the hands of patients faster. We believe this can be accomplished by empowering experimental scientists in pharma with a holistic and integrated in silico workflow that combines computational biophysics and machine learning,” said Naheed Kurji, President and CEO at Cyclica. “Together, with Ligand Design and Ligand Express we will move away from the classical computational approaches, and accelerate drug discovery by designing drugs for patients, not proteins.”
Source: Company Press Release