The USC Laboratory of Applied Pharmacokinetics and the Schools of Medicine and Pharmacy are pleased to announce a Three-Day, Hands-on workshop on

Principles of Pharmacokinetics - Parametric and Nonparametric Population PK and PD Modeling: Applications to Therapeutic Drug Monitoring and to Optimal individualization of Drug Therapy

Thursday - Saturday, February 21-23, 2002.
Location: 3rd Floor Computer Classroom, USC School of Pharmacy
USC Medical Campus, 1985 Zonal Avenue, Los Angeles, California.

Online registration is available.

Course material (Course_material.zip 5,535 kB).

This course is intended for physicians, pharmacists and biomedical scientists with an interest in population pharmacokinetic / pharmacodynamic modeling, and also for those interested in therapeutic drug monitoring and optimally precise individualization of drug therapy for patient care.

Prior experience in clinical pharmacokinetics will be an advantage. Participants will be introduced to the USC*PACK software, which can be used both for therapeutic drug monitoring and optimal individualization of drug dosage regimens, as well as for parametric and nonparametric population PK/PD and physiological modeling.

This course will also introduce the new Win*USC*PACK software for "Multiple Model" design of dosage regimens that hit target goals with maximal precision. This method is based first on nonparametric population models. It also obtains a patient's Bayesian posterior nonparametric individual model, and, if needed, to detect and quantify the interoccasional variability in each patient's individual model, thus permitting detection of unsuspected changes in parameter values such as take place with the volume of distribution (and other parameters), in aminoglycoside antibiotics, for example, with changes in the patient's status. This sequential Bayesian "Interacting Multiple Model" Bayesian approach to interoccasional intra-individual variability comes from the aerospace community, where it is used to track evasive targets. It is new, to our knowledge, in the pharmacokinetic community. It is designed to track the behavior of drugs, especially in unstable patients, with maximum precision, to detect unsuspected changes in a patient's parameter values during the period of the data analysis, and to permit achievement of target therapeutic goals with maximum precision.

In addition, new work on stochastic analysis of patient data in the Surgical Intensive Care Unit will be presented, with new methods of analyzing such data, predicting outcome, and suggesting optimal therapy will be presented.

Faculty:

Roger W. Jelliffe, M.D., Professor of Medicine, USC, Course coordinator.
David Bayard, Ph.D., Guidance and Control Section, Jet Propulsion 
Laboratory, Pasadena, CA
Paul Beringer, Pharm. D., Associate Professor of Clinical Pharmacy, USC 
School of Pharmacy.
Andreas Botnen, M.S., USC Laboratory of Applied Pharmacokinetics
Aida Bustad, B.A., USC Laboratory of Applied Pharmacokinetics
David D'Argenio, Ph.D., Chief, Department of Biomedical Engineering, 
USC.
George Drusano, M.D., Chief, Clinical Pharmacology, Albany Medical 
College, Albany NY.
Robert Leary, Ph. D., Senior Scientist, San Diego Supercomputer Center, 
San Diego CA.
Stan Louie, Pharm.D., Associate Professor of Clinical Pharmacy, USC 
School of Pharmacy.
Mark Milman, Ph.D., Guidance and Control Section, Jet Propulsion 
Laboratory, Pasadena, CA
Darryl Murry, Pharm. D., Purdue University School of Pharmacy, 
Indianapolis, IN
William Shoemaker, M.D., Professor of Clinical Surgery, USC School of 
Medicine.
Alan Schumitzky, Ph.D., Professor of Mathematics, USC.
Michael Van Guilder, Ph.D., Associate Professor of Mathematics, Cal-
State Fullerton, USC Laboratory of Applied Pharmacokinetics.
Xin Wang, Ph.D., Department of Computer Science, USC.
Walter Wolf, Ph.D., Distinguished Professor of Pharmaceutical Sciences, 
USC School of Pharmacy.


Preliminary Program:

************************************************************
Thursday February 21, 2002 - Basic Pharmacokinetics, 
Introduction to Population Modeling, and Clinical Applications
************************************************************
8:30 AM - Registration
9:00 AM - Welcome - Dr. Jelliffe
9:15 AM - Introduction to basic concepts in pharmacokinetics, including
          Review of Basic Pharmacokinetic Behavior.
	  Drug 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 for patients - Dr. Jelliffe
10:00 AM - Introduction to Population Modeling - Dr. Jelliffe
	   Why model? For description? For action? 
	   Types of PK models
	   Linear regression, NLLS, MAP Bayesian

10:30 AM - BREAK

10:45 AM - Parametric Population Models - Dr. Schumitzky
           Iterative 2 stage Bayesian, NONMEM
11:15 AM - Nonparametric Population models - Dr. Schumitzky
           NPEM, NPML
11:45 AM - Nonparametric Adaptive Grid (NPAG) Modeling - Dr. Leary

12:15 PM - LUNCH

1:15 PM - Comparing Parametric and Nonparametric Approaches - IT2B, 
	  NPEM, and NPAG - Ms. Aida Bustad.
1:45 PM - Multiple Model (MM) Dosage Design for maximum precision 
	  regimens - Dr. Bayard
2:15 PM - Getting MM Bayesian Posterior Individual Parameter Distributions. 
	  The Interacting MM (IMM) Approach - Dr. Bayard.
2:45 PM - Introduction to the new Windows USC*PACK MM and IMM Clinical Program 
	  to Achieve Target Goals with Maximum Precision - Dr. Jelliffe 
	  Demo - 1 compartment model Planning the Initial regimen - 
	  Gentamicin: CCr = 100, 50, 5.

3:00 PM - BREAK

3:15 PM - Entering past doses and levels, analysing the data.
	  A patient on Gentamicin
	  An interesting patient on Tobramycin.
3:45 PM - Hands-on session - Dr. Jelliffe
	  The patient on Gentamicin
	  The interesting patient on Tobramycin.
4:15 PM - 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
4:45 PM - Hands-on session - Setting the initial goals, planning the 
	  initial regimen.
	  The simpler patient with atrial fib
5:15 PM - Demo Vancomycin - Setting the initial goals, planning the 
	  initial regimen. - Dr. Jelliffe
5:30 PM - Hands-on session - Setting the initial goals, planning the 
	  initial regimen.

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An evening get-together at the USC Medical Campus Faculty Center. 

6:30 PM - No-host cocktails
7:00 PM - Dinner
7:45 PM - Dinner Seminar: PK/PD Approaches in Antiviral Therapy - Dr. Drusano
----------------------------------------------------------------

************************************************************
Friday February 22, 2002 - Intermediate Population Modeling
************************************************************
8:30 AM - Vancomycin Therapy Today - Dr. Beringer
9:00 AM - Pharmacokinetic Approaches to Imaging and Cancer Chemotherapy - 
	  Dr. Wolf
9:30 AM - Optimal procedures for population modeling - 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.
10:00 AM - Demo - getting the assay error polynomial - Dr. Jelliffe
10:15 AM - Hands-on session - getting the assay error polynomial

10:30 AM - BREAK

10:45 AM - Demo - The IT2B program. Modelling Amikacin - Dr. Jelliffe
	   A typical patient data file
	   Running the program. Getting gamma, ranges, evaluating the results
11:15 AM - Hands-on session Modeling Amikacin
	   Running the program. Getting gamma, ranges, evaluating the results

12:00 Noon - LUNCH

1:00 PM - Demo NPEM: Modeling Amikacin further. Using gamma, ranges results - 
	  Dr. Jelliffe
          Evaluating the results - The log-likelihood function
	  Descriptors of dispersion : The DF50 and DF95
	  The 2 and 3-D plots of the marginal and joint marginal PDF's
1:45 PM - Hands-on session - NPEM: Amikacin. Using gamma, ranges - Dr. Jelliffe
	  Linking Nonparametric Models to the Multiple Model Adaptive
	  Control Software
	  Deriving individual Bayesian posterior patient parameter joint densities
	  Evaluating relationships between parameters and covariates

2:30 PM - BREAK

2:45 PM - Optimal Times to Sample Serum Concentrations and other 
          Responses - Dr. D'Argenio.
3:15 PM - Individualizing Cancer Chemotherapy in the Genomic Era - 
	  Dr. Murry
3:45 PM - Getting Discrete "Nonparametric" Population Models from 
	  Literature Data - Dr. Milman.
4:15 PM - Antiviral Therapy Update - Dr. Louie
4:45 PM - Antifungal Therapy Update - Dr. Neely

************************************************************
Saturday February 23, 2002 - Advanced Population Modeling - 
Large and Nonlinear Models
************************************************************
8:30 AM - Population PK/PD Modeling over the web - Mr. Botnen
9:00 AM - Making large and nonlinear population models - Dr. Jelliffe
	  Demo - Using BOXES making a Michaelis-Menten model of Piperacillin
10:00 AM - Hands-on session - Using BOXES making a Michaelis-Menten model 
	   of Piperacillin - Dr. Jelliffe

10:30 AM - BREAK

10:45 AM - Demo: Setting up Big IT2B Modelling Piperacillin - Dr. Jelliffe
           A typical subject data file
	   Setting up the model, the data, the instructions, sending it, 
	   analysing it. 
	   Evaluating the results

11:15 AM - Hands-on session - setting up big IT2B Modelling Piperacillin.
	   Setting up the model, the data, sending it, analysing it, 
	   Evaluating the results

12:30 PM - LUNCH

1:30 PM - Demo Big NPEM Modelling Piperacillin - Dr. Jelliffe
	  Setting up the model, the data, sending it, analysing it, 
	  Evaluating the results
2:00 PM - Hands-on session - Big NPEM Modelling Piperacillin
	  Setting up the model, the data, sending it, analysing it, 
	  Evaluating the results

3:00 PM - BREAK

3:15 PM - New Approaches to Critical Care Therapy - 
	  Noninvasive Hemodynamic Monitoring - Dr. Shoemaker 
3:45 PM - New Approaches to Critical Care Therapy - 
	  Stochastic Analysis of Patient Data and Outcome Prediction - 
	  Dr. Bayard
4:30 PM - Group Discussion and Certificate Presentation.