Therapeutic Drug Monitoring for Model-Based, Goal-Oriented Optimal Individualized Drug Therapy: Relationship to Parametric and Nonparametric Population PK/PD Modelling and to Multiple Model Dosage Design
This course is intended for physicians, pharmacists, clinical toxicologists and biomedical scientists with an interest in population pharmacokinetic and pharmacodynamic modelling and in therapeutic drug monitoring and optimal individualization of drug therapy for patient care. Prior experience in clinical pharmacokinetics will be an advantage. Participants will be introduced to the USC*PACK and NONMEM software programs which can be used both for therapeutic drug monitoring as well as for parametric and nonparametric population PK/PD and physiological modelling.
Objectives and Expectations:
After this conference, the participant should:
Faculty:Dr. Nils Hoem, University of Oslo, Norway Dr. Roger Jelliffe, USC Laboratory of Applied Pharmacokinetics, Los Angeles, CA Dr. Robert Leary, San Diego Supercomputer Center, San Diego, CA Dr. Alison Thomson, University of Glasgow, UK Dr. Sander Vinks, University of Cincinnati, Ohio. Day 1 - Introduction and Review of Basic Pharmacokinetics, related responses, and Clinical Applications 8:30 AM - Registration 9:00 AM - Welcome - Dr. Vinks 9:15 AM - Introduction to basic concepts in pharmacokinetics, including Review of Basic Pharmacokinetic behavior. Elimination and Renal Function - Dr. Jelliffe 9:30 AM - Evaluating Renal Function - Dr. Jelliffe 9:45 AM - Bayes’ Theorem and the MAP Bayesian scenario of planning, monitoring, and adjusting drug dosage regimens for patients. - Dr. Jelliffe 10:00 AM - Introduction to the USC*PACK MAP Bayesian Clinical Program - Using PK software to optimize drug dosage - Dr. Jelliffe Demo - A one compartment model Planning the Initial regimen Gentamicin: CCr = 100, 50, 5. Also, entering past doses and levels, analyzing the data. 10:30 AM BREAK 10:45 AM – Optimal Times to get Serum concentrations - Dr. Vinks 11:05 AM - Cost Effectiveness of Goal-Oriented, Model-Based Drug Regimens - Dr. Vinks. 11:30 AM - Demo - Vancomycin - Setting the initial goals, planning the initial regimen - Dr. Jelliffe 11:45 AM - Demo 2 compartment model - Digoxin - Dr. Jelliffe Setting the initial goals, planning the initial regimen A simple patient with atrial fibrillation Another interesting patient with atrial fib 12:15 PM - Lunch 1:30 PM - Introduction to Population Modelling - Dr. Jelliffe Why model? For description? For action? For what purpose? Types of PK models Linear regression, NLLS 1:45 PM - Determining the Assay Error Polynomial - Dr. Jelliffe 2:00 PM - Parametric Population Models - Dr. Jelliffe Iterative 2 stage Bayesian 2:30 PM - Introduction to NONMEM - Dr. Thomson 3:15 PM Break 3:30 PM - Nonparametric Population models - Dr. Jelliffe NPEM, NPML 3:45 PM – Adaptive Grid Nonparametric Population Modeling – Dr. Leary 4:00 PM - Optimal procedures for Population Modelling - Dr. Jelliffe First, determine the assay error pattern polynomial, to weight each data point properly Second, use a parametric population model, get gamma, ranges Third, use an NP population model, use gamma, ranges, get the entire parameter distribution. Why? 4:30 PM Multiple Model Dosage Design for maximally precise goal - oriented, model - based drug dosage regimens. - Dr. Jelliffe 5:00 PM - Adjourn Day 2 - Intermediate and Advanced Population Modeling 8:30 AM – Modeling diffusion into endocardial vegetations, and the postantibiotic effect - Dr. Jelliffe 8:45 AM - Modeling bacterial growth and kill - Dr. Jelliffe. An interesting patient on Tobramycin. 9:00 AM – General Guidelines for making, validating, and comparing population PK/PD Models - Dr. Jelliffe Weighting the data appropriately. Fitting the data - comparing methods. Validating models - what does this involve? Comparing patient populations - how to do this. 9:20 AM - Demonstration - The NONMEM Parametric Population Modeling Program - Dr. Thomson 10:00 AM - Break 10:15 AM - Demonstration The IT2B Parametric Population Modeling Program. - Dr. Jelliffe Modeling Amikacin. A typical patient data file Running the program. Getting gamma, ranges, evaluating the results 10:30 AM - Demonstration - Nonparametric Population Modeling Software - Dr. Jelliffe The new NPAG: NPEM with an Adaptive Grid Modelling Amikacin further. Using gamma, ranges. Evaluating the results: the log-likelihood function, and descriptors of dispersion : The DF50 and DF95 The 2 and 3-D plots of the marginal and joint marginal PDF’s Linking Nonparametric Models to Multiple Model Adaptive Control Deriving individual Bayesian posterior patient parameter joint densities Relationships between parameters and covariates 11:00 AM - Converting Parametric Models to Nonparametric ones: The Maximum Entropy Approach. Dr. Jelliffe 12:00 Noon Lunch 1:15 PM - Making Large and Nonlinear Population Models - Dr. Jelliffe 1:30 PM - Demo The IT2B program. - Dr. Hoem Demo - Using BOXES making a Michaelis-Menten model of Cyclosporine 2:15 PM - Demo NONMEM and large models - Dr. Thomson 3:00 PM - Break 3:15 PM - Demo Big NPEM: Modelling Cyclosporine - Dr. Hoem Using gamma, ranges Setting up the model, the data, the instructions, sending it over the web, analyzing it, evaluating the results - Dr. Hoem 4:00 PM - Clinical Application: Multiple Model Dosage Design - Dr. Jelliffe 4:30 PM - Group discussion session - all participants 5:00 PM - Adjourn