The Laboratory of Applied Pharmacokinetics of the University of Southern California School of Medicine and The Institute for Physical and Chemical Medicine, Moscow, Russia, are pleased to announce a four-day 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

Monday through Friday, April 8-12, 2002.
Location: The Institute for Physical and Chemical Medicine, 4/6-b-101 Kuusinena Street, Moscow, 123 308, Russia

A registration form is available.

For more information, please contact

Irina Bondareva, Ph.D.
Laboratory of Mathematical Modelling
Research Institute of Physical and Chemical Medicine
4/6-b-101 Kuusinena Street
Moscow, 123 308, Russia
Phone: 7-(095)-195-3878
Fax: 7-(095)-314-1053
Email: ibondareva@mtu-net.ru

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.

Faculty:

Roger W. Jelliffe, M.D., USC School of Medicine, Los Angeles, USA
Irina Bondareva, Ph.D., Research Institute of Physical and Chemical 
Medicine, Moscow


Preliminary Program:

************************************************************
Day 1 - Basic Pharmacokinetic Review
************************************************************

9:00 AM - Welcome Dr. Belousov
9:15 AM - Introduction to basic concepts in pharmacokinetics, including
          Review of Basic Pharmacokinetic Behavior.
	  Drug Elimination and Renal Function - Dr. Jelliffe
10:00 AM - Evaluating Renal Function  Dr. Jelliffe

10:30 BREAK

1045 AM - Bayes' Theorem and the MAP Bayesian Scenario of Planning, 
          Monitoring, and Adjusting Drug Dosage for patients -
          Dr. Jelliffe
11:15 AM - Introduction to Population Modeling - Dr. Jelliffe
           Why model? For description? For action? 
           Types of PK models
           Linear regression, NLLS, Bayesian
11:45 AM - 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.

12:30 ADJOURN

************************************************************
Day 2 -Introduction to using the WinUSC*PACK clinical software, 
Clinical Applications, and Population Modeling
************************************************************
8:30 AM - Entering a patient's past doses and levels, analysing the data.
          A patient on Gentamicin
	  An interesting patient on Tobramycin.
9:15 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
10:00 -   Demo  Vancomycin - Setting the initial goals, planning the 
          initial regimen. - Dr. Jelliffe

10:30 BREAK

10:45 AM - Parametric Population Models - Dr. Jelliffe
        		 Iterative 2 stage Bayesian, NONMEM
11:15 AM - Nonparametric Population models - Dr. Jelliffe
         		NPEM, NPML
11:45 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.

12:30 PM ADJOURN

***********************************************************
Day 3 - Advanced Population Pharmacokinetic Modeling
***********************************************************
8:30 AM - Demo - getting the assay error polynomial - Dr. Jelliffe
9:00 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 - 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
Linking Nonparametric Models to the Multiple Model Adaptive Control Software
Deriving individual Bayesian posterior patient parameter joint densities
Evaluating relationships between parameters and covariates
11:45 AM - Optimal Times to Sample Serum Concentrations and other 
Responses - Dr. Jelliffe.

12:30 PM - ADJOURN


************************************************************
Day 4 - Advanced Population Modeling -Nonlinear and Large Models
************************************************************
8:30 AM - Modeling of Antiepileptic Drugs - Dr. Bondareva
9:00 AM - Population PK/PD Modeling over the web - Dr. Jelliffe
9:30 AM - Making large and nonlinear population models - Dr. Bondareva
10:00 AM - Demo - Using BOXES - making a Michaelis-Menten model of Phenytoin

10:30 AM - BREAK

10:45 AM - Demo  setting up Big IT2B  Modeling Phenytoin - Dr. Bondareva
           A typical subject data file
           Setting up the model, the data, the instructions, sending it,
           analysing it. 
           Evaluating the results
11:15 AM - Demo Big NPEM  Modelling Phenytoin - Dr. Bondareva
	   Setting up the model, the data, sending it, analysing it, 
	   Evaluating the results

12:00 ADJOURN

************************************************************
Day 5 - Modeling Drug Diffusion and Antibiotic Effects
************************************************************
8:30 AM - Modeling Diffusion into Endocardial Vegetations
9:00 AM - Modeling Organism Growth and Kill, and Postantibiotic Effect

10:00 AM - BREAK

10:15 AM - Optimizing Therapeutic Precision - a Synthesis - Dr. Jelliffe
	   Summarizing Nonparametric Population Modeling
           Summarizing Multiple Model Dosage Design
11:00 AM - Getting MM Bayesian Posterior Individual Parameter Distributions. 
           The Interacting MM (IMM) Approach - Dr. Jelliffe.
11:30 AM - Summarizing Clinical Applications
           Aminoglycosides
           Vancomycin
           Digoxin
	   Antiepileptic Drugs - Dr. Bondareva

12:30 PM - ADJOURN