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

2. 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

3. 11/7/2018
USC LAPK

4. 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

5. 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

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

7. “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

8. 11/7/2018

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

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

11. 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

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