Mahesh
This is the interpolation code for use in the $DES block, assuming that
you have values of a covariate at all observation records. If not, you
need to control the code by appropriate IF-statements or interpolate
(for observation times) at the time of data set creation:
IF(NEWIND.NE.2) THEN ; SET UP FOR NEW INDIVIDUAL
LCP=0
LTM=TIME
ENDIF
INT = LCP ; INTERCEPT = LAST covariate value
TINT = LTM ; TIME SCALE ORIGIN = LAST TIME
DEN = TIME-TINT
SLOP = 0
IF(DEN.NE.0) SLOP = (CONC-INT)/DEN
; CONC is the value of the covariate in your case
LCP=CONC ; RECORD CURRENT TIME & conc
LTM=TIME ; FOR NEXT CALL
$DES
NPUT=INT+SLOP*(T-TINT)
....
;INPUT IS INTERPOLATED covariate, can be used even in $DES block
Interpolation is better than imputation if you use differential
equations (and need values at any time, not only at observation times).
For example, with Nonmem interpolation, you can use interpolated PK and
effect compartment model (to integrate, you need values at all times)
Initialization can be done either using a unit dose to the biomarker
compartment and assigning bioavailability (Nonmem V and VI) or (with
Nonmem VI) using A_0(1)= etc. statements
Leonid
--------------------------------------
Leonid Gibiansky, Ph.D.
President, QuantPharm LLC
web: www.quantpharm.com
e-mail: LGibiansky at quantpharm.com
tel: (301) 767 5566
Samtani, Mahesh [PRDUS] wrote:
Dear NMusers,
I wish to model a biomarker that is controlled by a time-varying
variable. The temporal pattern of this time-varying variable is
irregular which makes a parametric description of its profile somewhat
difficult. I am hoping to use a “connect the dots” approach for this
exercise i.e. linear interpolation for the time-varying variable in
between the observation. I believe there are suggestions on the users
net to modify the dataset to complete slopes and intercepts for each
time interval. I was wondering if there is a simpler way to compute the
linear interpolation on the fly within the control stream. Finally, the
complicating issue is that the biomarker of interest needs an
initialization of it’s compartment since it doesn’t start at zero.
I would greatly appreciate if someone has a code and example dataset for
such an exercise.
Thanking the group in advance…Mahesh
