December 1, 1995
Dear Colleague:

        The Laboratory of Applied Pharmacokinetics of the USC School of
Medicine is pleased to announce its new Version 10.7 of the USC*PACK
programs for population pharmacokinetic modeling, modeling larger
nonlinear systems, and for planning, monitoring, and optimal
individualization of goal-oriented drug dosage regimens for patient
care.

WHAT'S NEW IN THE SETUP!  CLIENT - SERVER MODES!

        The programs now run in 3 modes. The first is the usual mode
on a single machine. The second is on a network, in a classroom mode.
Each classroom machine accesses the programs from the network, but
keeps its patient data files in its own disk or directory. The
third is a true client-server mode. Here, all programs and patient
data files are kept on the central hospital server, for example, but
are accessed and run from the satellite (client) machines.

WHAT'S NEW WITH AMINOGLYCOSIDES!

        These programs have several new population PK models, for general
medical patients, ICU patients, young previously healthy patients, and for
gentamicin in patients with spinal cord injuries and for newborn infants.
As before, the GENTamicin, TOBramycin, NETilmicin, and AMIKacin programs
compute D-optimal times for monitoring serum levels. Diffusion into
vegetations and dynamics of bacterial growth vs killing effect at a stated
MIC can also be evaluated as described just below.

WHAT'S NEW WITH GENERAL MODELING, BAYESIAN FITTING!

        The General Modeling, Bayesian fitting program has an option for
entry of a chronic steady-state dosage regimen, followed by subsequent
changes in dosage or renal function. Other related programs compute the
dynamics of diffusion into a spherical simulated endocardial vegetation,
abscess, or a bacterium, nonlinear saturable pharmacological effects, and
the dynamics of bacterial growth and kill, and the post-antibiotic
effect (PAE). These help to evaluate the  efficacy of antibiotic regimens
with respect to their ability to kill adequately under various circumstances,
for various values of an organism's MIC. Models for simulating a PAE of 6
hours, and for growth and kill of Pseudomonas by gentamicin, tobramycin, and
ticarcillin are now provided. You can also make and store your own models.

WHAT'S NEW WITH THE NPEM2 POPULATION MODELING PROGRAM!

        The NPEM2 program has been very much overhauled and upgraded. It now
automatically helps you select an appropriate number of grid points to support
your population joint density. It has algorithms to make each computational
cycle go progressively faster. The 2D plots of the marginal and the 3D plots
of the joint marginal densities are enhanced. Scatterplots and regression
relationships are now available for predicted versus measured serum levels
in both the Iterative 2 Stage Bayesian (IT2B) front population modeler, from
mean or median population parameter values. Each patient's own Bayesian
posterior parameter values can also be used to predict the measured levels.
For the NPEM2 part, one similarly can predict measured serum levels from
population mean, median, or mode values, and can also further compute each
patient's parameter joint density as a "population" of one, and can see the
predicted versus measured serum levels based now on each patient's own mean,
median, or mode parameter values.

THE OVERALL USC*PACK COLLECTION NOW INCLUDES:

1.      The USC*PACK CLINICAL programs. These enhance precise goal-oriented
dosage design and therapeutic drug monitoring by Bayesian individualization
of drug dosage regimens. {*filter*} include aminoglycosides, vancomycin, digoxin,
digoxin with quinidine, digitoxin, lidocaine, procainamide, theophylline,
quinidine, gentamicin in newborns, and TMP-SMX for PCP pneumonia. CCr is
computed between a single stable or pairs of unstable serum creatinine
levels. It can change from dose to dose, as can body weight. Models of
diffusion and bacterial growth and killing are especially useful to evaluate
adequacy of a regimen to kill under stated conditions of growth rate, max
kill rate, and MIC.

2.      The USC*PACK NPEM2 POPULATION pharmacokinetic modeling
program employs a nonparametric expectation maximization (NPEM) algorithm.
It computes the entire joint probability density for a 2 compartment
absorptive model, even with mixed {*filter*}and intravenous input, and thus can
obtain both Vd and bioavailability together. It makes no parametric
assumptions such as mean, standard deviation, etc., but also gets them. It
can thus discover unrecognized subpopulations. It reads routine patient
data files from the clinical programs. Parameter values found can be entered
and stored for use with the clinical programs.

3.      The USC*PACK BOXES program makes customized PK/PD models by placing
boxes on the screen and connecting them with arrows. Equations are
automatically written for the Model part of the ADAPT I PC programs. Effect
models (Hill or Keo) are easily made.

        The programs run on the IBM PC and compatible machines. A math
coprocessor is required. They need at least DOS 5.0, and 2.0 MB of memory
(4 is better, and for NPEM2, the more there is, the faster it runs). The
programs come on three 3.5 inch disks.

        Since July 1995, we must ask for an increased donation to offset our
increasing costs. This applies even if you already have a previous USC*PACK
program. However, upgrading from version 10.6 is free. These requested
donations are:
                                        Hospital or          Commercial
                                   Academic Institution      or Industry
        First donation:                   $395.00              $695.00
        Upgrades thereafter:              $295.00              $495.00

         Please print out, sign, and mail the enclosed license agreement back
to us, with a check, made out to the University of Southern California. We
will send the programs as soon as possible. If you have questions, write to
us at 2250 Alcazar St., Los Angeles CA 90033, call us at 213/342-1300, fax

World Wide Web at   http://www.***.com/ ; It has announcements of
new events.

                                                Sincerely,

                                                Roger Jelliffe, M.D.
                                                Professor of Medicine