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Multiple Model Dosage Design Roger Jelliffe, M.D. USC Lab of Applied Pharmacokinetics 5/23/2017 USC LAPK 1 Conventional Design of Drug Dosage Regimens • • • • • Use Population Model Select single target goal Develop the dosage regimen to “hit target” But will it? How precisely? How to evaluate the expected precision? 5/23/2017 USC LAPK 2 5/23/2017 USC LAPK 3 Optimal Drug Dosage • Consider the effects of the pop outliers. • Do a clinical simulation to validate each regimen. • Standard Doses: no feedback. Optimize them to hit desired targets. • Cancer Rx, Veterinary Rx. • Individualized Doses: Optimize them also. • Targets are desired Conc, AUC, etc • AIDS, Transplants, Cancer, Antibiotics, Cardiovascular, etc. 5/23/2017 USC LAPK 4 What is the BEST Pop Model? • The correct structural PK/PD Model. • The collection of each subject’s exactly known parameter values for that model. 5/23/2017 USC LAPK 5 An NPML Population Joint Density, as made by Mallet 5/23/2017 USC LAPK 6 “Multiple Model” Dosage Design • Start with multiple models in pop model • Best starting tool = NPAG joint density. • Compute regimen having least weighted squared error in target goal achievement. 5/23/2017 USC LAPK 7 5/23/2017 8 Continuous IV Vanco. Predictions when regimen 5/23/2017 9 based on means is given to all subjects Vanco, continuous IV. Predictions from 5/23/2017 10 MM regimen MM Optimal Dosage Regimens: • • • • • • Consider the quantitative effect of outliers. A built-in simulated clinical trial each time. Achieve target goals with max precision. Get the best overall “standard dose”. Best for Vet use, without feedback. Best for Patient use, with or without feedback - cancer, AIDS, inf. Disease, CV disease. • Best optimally coordinated combination regimens in future. 5/23/2017 USC LAPK 11 Clinical Illustrations • Planning the initial regimen • Adjusting it based on TDM data 5/23/2017 USC LAPK 12