Certara, the leading provider of decision support technology and consulting services for optimizing drug development and improving health outcomes, has announced that the Standards Council of Canada (SCC) has awarded Good Laboratory Practices (GLP) certification to its Certara Strategic Consulting (CSC) Montreal facility. CSC Montreal has passed the requisite inspection and study audits and is now recognized as a GLP compliant Toxicokinetic Test Site by SCC.

“To derive the greatest value from modeling and simulation (M&S), sponsors need to incorporate these quantitative methods into their drug discovery and development process as early as possible,” said Dr. Martin Beliveau, director of CSC. “By attaining GLP accreditation, we underscore the high quality of our toxicology analysis services, demonstrate the SCC compliance of our processes and procedures, and underscore to sponsor companies the many benefits of incorporating M&S into their pre-clinical programmes.”

CSC Montreal performs toxicokinetic analyses to support the pivotal toxicology programs required for new drug regulatory submissions. Drug concentrations observed in animals and the appearance of toxic adverse effects are routinely incorporated into M&S workflows to derive safer initial and escalation doses for first-in-human trials. These M&S workflows can also provide insight into the minimum anticipated biological effect level (MABEL) of a drug and efficacious outcomes.

Formed from the merger of Pharsight Consulting Services, Quantitative Solutions, and d3 Medicine, CSC is the largest global pharmacometrics consultancy. CSC is comprised of more than 100 scientists, most with PhDs, using a wide range of M&S methods and technologies to support global sponsors in bringing new therapies to patients. Regulatory agencies are increasingly promoting the use of M&S in drug programs to inform key decisions. M&S has been highlighted in more than a dozen regulatory guidance documents over the past few years and is used by those agencies to review drug submittals.