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Using PopPK Modeling to Optimize Dosing in Patients with Organ Impairment

On-Demand Webinar

The FDA-approved drug label is the official description of a drug product and includes what the drug is used for, who should take it, side effects, instructions for use, and safety information for clinicians and patients. For drug companies, the label is the culmination of years of work and millions, if not billions of dollars. Every element, word, and comma in the label will impact the potential patient population that can benefit from that new drug, while detailing any associated risks, including staying “silent” when information is not available. In other words, what is included or excluded from the label will affect the overall profit potential of the drug.

Are you positioned to optimize the labels for the drugs in your pipeline? How can you determine dosing recommendations that ensure safety and efficacy for your targeted patient population, including subpopulations for whom conducting extensive clinical trials may not be ethical or practical? In this webinar, Colin Chang presented a case study showing how Certara scientists used pop PK modeling to optimize dosing and inform the label for a combination drug to treat obesity.

About Our Speaker

Colin Chang, Scientist, Pharmacometrics, Certara. Colin Chang, M.Sc., is a Scientist in the Pharmacometrics group at Certara Consulting Services. Mr. Chang has been involved in PK/PD analyses and reporting across Phases 1 and 2 of drug development for industry sponsors. His experience involves using noncompartmental as well as population PK/PD modeling and simulation methods in support of drug development programs.

The FDA-approved drug label is the official description of a drug product and includes what the drug is used for, who should take it, side effects, instructions for use, and safety information for clinicians and patients. For drug companies, the label is the culmination of years of work and millions, if not billions of dollars. Every element, word, and comma in the label will impact the potential patient population that can benefit from that new drug, while detailing any associated risks, including staying “silent” when information is not available. In other words, what is included or excluded from the label will affect the overall profit potential of the drug.

Are you positioned to optimize the labels for the drugs in your pipeline? How can you determine dosing recommendations that ensure safety and efficacy for your targeted patient population, including subpopulations for whom conducting extensive clinical trials may not be ethical or practical? In this webinar, Colin Chang presented a case study showing how Certara scientists used pop PK modeling to optimize dosing and inform the label for a combination drug to treat obesity.