Multiple Model Dosage Design

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Presentation transcript:

Multiple Model Dosage Design Roger Jelliffe, M.D. USC Lab of Applied Pharmacokinetics 11/7/2018 USC LAPK

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? 11/7/2018 USC LAPK

11/7/2018 USC LAPK

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. 11/7/2018 USC LAPK

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. 11/7/2018 USC LAPK

An NPML Population Joint Density, as made by Mallet 11/7/2018 USC LAPK

“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. 11/7/2018 USC LAPK

11/7/2018

Continuous IV Vanco. Predictions when regimen based on means is given to all subjects 11/7/2018

Vanco, continuous IV. Predictions from MM regimen 11/7/2018

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. 11/7/2018 USC LAPK

Clinical Illustrations Planning the initial regimen Adjusting it based on TDM data 11/7/2018 USC LAPK