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$design.html
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<HTML><HEAD> <TITLE> $design.ctl</TITLE><HEAD>
<BODY BGCOLOR="#FFFFFF">
<PRE>
+--------------------------------------------------------------------+
| |
| $DESIGN (NM75) |
| |
+--------------------------------------------------------------------+
MEANING: Instructions for Clinical Trial Design Evaluation and Opti-
mization
CONTEXT: NM-TRAN Control Record
DISCUSSION:
The optimal design process can help you in designing or evaluating a
clinical trial. It may be desired to evaluate specified time points,
or find the optimal time points, dose levels, and number of time
points appropriate for a particular sub-design, etc. The design algo-
rithms have been modeled after POPED by Hooker et al., and PFIM by
Mentre et al. (see references [22-27]) in Introduction to NONMEM 7.
USAGE:
$DESIGN Record Options
[APPROX=[FO|FOI|FOCE|LAPLACE|LAPLACEI]]
[OFVTYPE=[0|1|2|3|4|5|6|7|8]]
[GROUPSIZE=n]
[FIMTYPE=[0|1|2|3]]
[FIMDIAG=[0|1|2|3]]
[VARCROSS=[0|1]]
[EOPTD=1]
[SEED=n]
[CLOCKSEED=[0|1]]
[MODE=[0|1|2|3]]
[DATASIM=[0|1]]
Additional Control Options for $DESIGN
[SIGL=n]
[SIGLO=n]
[ABORT|NOABORT|NOHABORT]
[MAXEVALS=n]
[PRINT=n]
[NUMERICAL|NONUMERICAL]
[LIKELIHOOD|-2LOGLIKELIHOOD|-2LL]
[SLOW|NOSLOW|FAST]
[POSTHOC|NOPOSTHOC]
[NOPRIOR=[0|1]]
[FILE=filename]
[FORMAT|DELIM=s3]
[FNLETA=n]
Options for Setting up Types of Optimal Design
[NELDER]
[FEDOROV]
[RS]
[STGR]
[DISCRETE]
[DISCRETE_RS]
[DISCRETE_SG]
[DESEL=label]
[DESELSTRAT=label]
[DESELMIN=label]
[DESELMAX=label]
[NMIN=label]
[NMAX=label]
[STRAT=label]
[STRATF=label]
SAMPLE:
$DESIGN APPROX=FOCEI MODE=1 NELDER FIMDIAG=0
DATASIM=1 GROUPSIZE=32 OFVTYPE=0
will produce the most empirical, "clinical trial simulation" (CTS)
style covariances, complete with simulated etas and eps, and standard
FIM is assessed. If FIMDIAG>0, then a y-expectation covariance will
be evaluated, but mode will be evaluated with the simulated data.
DISCUSSION:
The record name can be shortened to $DESI. Another name for the
record is $OPTDESIGN, which can be shortened to $OPT.
The following is a brief summary of the options. See Introduction to
NONMEM 7 "Clinical Trial Design Evaluation and Optimization" for more
detail and more examples. The options are described in the following
sections:
(1) $DESIGN Record Options
(2) Additional Control Options for $DESIGN
(3) Options for Setting up Types of Optimal Design
(1) $DESIGN Record Options
APPROX=FO (default)
The nlme approximation method is specified here. First order
(no interaction) is the default, and the appropriate type of
covariance matrix is evaluated or used in optimization of
the design. Other options are:
FOI First order interaction with interaction"
FOCE first order conditional estimation
FOCEI
first order conditional estimation with interaction
LAPLACE
Laplace conditional estimation
LAPLACEI
Laplace conditional estimation with interaction
OFVTYPE=1 (default)
The objective function types are comparable to those of
PopED:
0,1,3,4,5: design type: d-optimality, -log(det(FIM)), where FIM=Fisher
Information Matrix (inverse of variance-covariance).
2: design type: a-optimality, -1/tr(1/FIM)
6: design type: ds-optimality, -log(det(FIM))+log(det(FIMunintersting))
To identify parameters as uninteresting, place UNINT at the parameter
in the same manner you would place FIX.
7: design type: r-optimality (relative standard error),-1/tr(sqrt(1/FIM)/Paramer))
8: optimal design type: Individual Bayesian FIM, -log(det(Bayes
FIM)), as described in the PFIM 4.0 manual [26].
9: Same as option 2, and using the UNINT filter.
10: Same as option 7, and using the UNINT filter.
GROUPSIZE=1 (default)
The GROUPSIZE is comparable to that of POPED, in which the
FIM is multiplied by this number to provide the subject num-
ber size of the dataset template. For a template of one
subject, GROUPSIZE would then offer the variance-covariance
expected from GROUPSIZE number of subjects.
FIMTYPE or FIMDIAG=0
FIMTYPE or FIMDIAG may be set to the following, and corre-
sponds to fimcalc.type in POPED:
0 (default): Full information matrix
Uses finite difference assessment for Theta, Omega, and
Sigma variances and covariances.
1 Create a block diagonal information matrix of the esti-
mates
2 Create a block information matrix
3 Create a full information matrix
VARCROSS=0 (default)
Standard NONMEM residual variance modeling.
VARCROSS=1
Residual Standard Deviation Modeling
VARCROSS=1 means to treat the residual variance model in the
manner of PFIM 4.0, as described in the manual.
FIMTYPE=1 VARCROSS=1 is equivalent to fim.calc.type=4 in
POPED, and diagonal option in PFIM.
EOPTD=1
For each iteration, this creates a random sample of thetas,
omegas, or sigmas, using the prior information. $PRIOR
NWPRI prior information is required, and PLEV=0.999 must be
specified. Best used with STGR. See example optdesign16.
SEED=223345
Set the starting seed for any random samples to be created,
whether for EOPTD=1, or for FOCE type FIM in creating random
etas (see below).
CLOCKSEED=0 (default)
As of nm75, the actual starting seed will be 10000*(seconds
after midnight)+SEED (SEED may be set to 0 for this pur-
pose), if CLOCKSEED=1. This allows a control stream to pro-
duce different stochastic results for automated replica-
tions, without the need to modify the seed value in the con-
trol stream file in each replication.
MODE=0 (default), 1, 2, or 3
Used for specifying data and prediction value type when
specifying APPROX=FOCEI. In NONMEM report:
0 EVALUATE AT F(ETAsim) DURING CONDITIONAL DESIGN ASSESSMENT
1 EVALUATE AT THE MODE F(ETAhat) DURING CONDITIONAL DESIGN ASSESSMENT
2 EVALUATE AT F(ETAsim)-G*ETAsim DURING CONDITIONAL DESIGN ASSESSMENT
3 EVALUATE AT F(0) DURING CONDITIONAL DESIGN ASSESSMENT
In other words,
MODE=0 means FOCEI with data at F(ETAsim), and predicted
function evalauted at f(ETAsim), is to be used. This method
works well.
MODE=1 means FOCEI with data at F(ETAsim), and predicted
function evaluated at the mode, f(ETAhat), is to be used.
The results are not satisfactory.
MODE=2 means linearized FOCEI, with data at
F(ETAsim)-G*ETAsim, and predicted function at F(ETAsim).
Works well.
DATASIM=0 (default)
Normally, y-expectation evaluation of the FIM is performed.
To actually simulate data, set DATASIM=1, and along with
APPROX=FOCEI, this will produce simulated etas as well.
(2) Additional Control Options for $DESIGN
The following options may be set within the $DESIGN record, and
they operate exactly as their equivalents in the $EST record.
Thus, the following are equivalent:
$DESIGN FIMDIAG=1 OFVTYPE=6 APPROX=FO
MAXEVAL=9999 NOHABORT PRINT=20 SIGL=10 POSTHOC
$DESIGN FIMDIAG=1 OFVTYPE=6 APPROX=FO
$EST MAXEVAL=9999 NOHABORT PRINT=20 SIGL=10 POSTHOC
The options are as follows.
SIGL
SIGLO
SIGL
SIGLO
ABORT/NOABORT/NOHABORT
MAXEVAL
MAXEVAL=0 indicates design evaluation (the default)
MAXEVAL>0 indicates design optimization
PRINT control iteration printing during optimal design
NUMERICAL/NONUMERICAL
-2LL/LIKELIHOOD/LLIKELIHOOD
SLOW/NOSLOW/FAST
POSTHOC
NOPRIOR
FORMAT
FILE
FNLETA
(3) Options for Setting up Types of Optimal Design
The additional options for $DESIGN listed below are for optimiz-
ing parts of the design components. For example, the DESEL,
DESELSTRAT, DESELMIN, DESELMAX can be specified for all the vari-
ous design elements that you want optimized. It might be TIME
for time samples, AMT for dose, or some type of covariate spe-
cific for the problem. Certainly, any combination of covariates
can be requested to be optimized.
NELDER
Use Nelder method to search for optimal continuous parame-
ters
FEDOROV
Use to find ideal set of discrete time points from a larger
set of possible time points.
RS Random Search method to find optimal continuous parameters
STGR Stochastic Gradient method to find optimal continuous param-
eters
DISCRETE
Find optimal number of time points for each sub-design (sub-
ject template), and use NELDER method to find optimal con-
tinuous parameters.
DISCRETE_RS
Find optimal number of time points for each sub-design (sub-
ject template), and use RS method to find optimal continuous
parameters.
DISCRETE_SG
Find optimal number of time points for each sub-design (sub-
ject template), and use STGR method to find optimal continu-
ous parameters.
Specific parameters must be specified to be optimized.
This is done using the following options:
DESEL=label
The data item (column) that contains the design element
(DESEL) values that are to be modified and optimized. For
example, TIME column would indicate that you want times to
be estimated.
DESELSTRAT=label
The data item (column) indicating stratification. The
DESELSTRAT data item should contain integer indices to indi-
cate what values are to be shared, and estimated together.
If a record contains a value of 0 in the DESELSTRAT column,
then this record is not included in the estimation process,
and its value (say its time value in DESEL=TIME column) will
not be changed. If the record contains a value >0 in DESEL-
STRAT, let us suppose a 1, then all records with the value
of 1 in DESELSTRAT will share the same time value (or what-
ever DESEL selected), extimated together. Those records
with value 2 will be another set of records which will share
a time value, etc. Thus, within a subject, there may be a
PK record and a PD record which should share the same time
value. Also, a group of subjects may share the same time
values. Within a subject, times will be automatically
sorted as they are changed, so that NONMEM's time ordering
policy is not violated.
DESELMIN=label
The data item (column) containing the minimal value
DESELMAX=label
The data item (column) containing the maximal value
You must impose boundaries on the values that are being
optimized. That is done with these two data items. Only
those records with a stratification value >0 in DESELSTRAT
column will require a min and max value, and only those
records that define that stratification value for the first
time.
All four DESEL items must be specified: DESEL,DESEL-
STRAT,DESELMIN,DESELMAX. They may be repeated for as many
design elements are to be optimized.
For example for times and amounts:
DESEL=TIME DESELMMIN=TMIN DESELMAX=TMAX DESELSTRAT=TSTRAT
DESEL=AMT DESELMIN=AMTMIN DESELMAX=AMTMAX DESELSTRAT=AMTSTRAT
NMIN=label
The name of the data item (column) containing minimal number
of time points to the subject.
NMAX=label
The name of the data item (column) containing maximal number
of time points to the subject.
If NMIN<0 or NMAX<0, then most previous non-negative value
is used. The NMIN and NMAX column are only used for the
DISCRETE* analyses, to bound the number of time points that
may be permitted for a given subject. With DISCRETE*, the
total N of time points among all subjects is determined by
the total number of time points whose MDV=0 in the starting
data set.
STRAT=label
The data item (column) containing grouping or stratification
number pertaining to that subject.
STRATF=label
The data item (column) containing starting fraction repre-
sentation for the stratification value in column STRAT.
If STRAT and STRATF are specified, and there is at least one
STRAT value >0, then the SRATF values are optimized, and
represent the weight to the contribution of that subject to
the Information matrix. For STRAT<=0, then their STRATF
values are not optimized, and remain fixed at their initial
values, but are still used as weights to the information
matrix. It is up to the user to ensure that the sum of
STRATF values among unique STRAT values sum to 1. If value
of STRATF<0.0, then that subject is not included in the
assessment.
Additional $COVARIANCE Control Options for $DESIGN
In addition, $DESIGN sets up the covariance step as $COV MATRIX=R
UNCONDITIONAL without the user requiring this record entered in the
control stream. If you wish to specify additional control for the
covariance, you can add these in a $COV record, such as:
$DESIGN FIMDIAG=1 OFVTYPE=6 APPROX=FO MAXEVAL=9999 NOHABORT PRINT=20 SIGL=10 POSTHOC
$COV PRINT=E
RECORD ORDER:
Same as $ESTIMATION or $SIMULATION
REFERENCES: Guide <a href="intro7/index.html">Introduction_7<a/>
<pre>Go to <A HREF=index.html>main index</A>.</pre>
<pre>
<hr ALIGN=LEFT WIDTH="450"></pre>
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