news/changelog

July 12th 2010

Version PFIM 3.2.1 (change of the file libFED.dll + bug correction in the call of the Fedorov-Wynn algorithm + bug correction in the PD libraries)

In the previous versions, the length of the character string "directory", which is defined in the file PFIM3.2.r, was limited to 109 characters when using the Federov-Wynn algorithm. Previously, when the length of "directory" was greater than 109 characters, there was the following error message in the R command: "Error in 1:np.f : argument of length 0" or the R software would abnormally terminate. The implementation in the dynamically loaded library of the Federov-Wynn algorithm (libFED.dll) has been modified; the length limitation is no longer present in the version of PFIM 3.2.1.

A bug in the call of the Fedorov-Wynn algorithm has also been corrected. The bug concerned the generation of the list of possible elementary designs in the initial step of design optimisation, when the user constrained PFIM to choose one sampling time from a sampling window composed of this sampling time only. The implementation in the file algofedorov3.2.r has been modified to take into account this error.

Furthermore, a bug in the previous version of PFIM 3.2 concerning the implementation of the Imax models has been fixed. The bug concerns the three library files LibraryPD_PDdesign.r, LibraryPD_PKPDdesign.r and CreateModel_PKPDdesign.r.

January 23th 2010

Version PFIM 3.2

PFIM 3.2 is an extension of the version PFIM 3.0. This version incorporates new features in terms of model specification and expression of the Fisher information matrix. Regarding model specification, the library of standard pharmacokinetic (PK) models has been completed by the three compartment models with linear elimination and models with Michaelis-Menten elimination (one, two and three compartment models). Furthermore, a library of pharmacodynamic (PD) models is now available. Concerning the expression of the Fisher information matrix, PFIM 3.2 can handle either a block diagonal Fisher information matrix or the complete one. It is now also possible in PFIM 3.2 to use models including inter-occasion variability (IOV) with replicated designs at each occasion. Last, a new feature of PFIM 3.2 is the computation of the Fisher information matrix for models including fixed effects for the influence of discrete covariates on the parameters. It can be specified if covariates change or not through the different occasions. The computation of the predicted power of the Wald test for comparison or equivalence test for a given distribution of a discrete covariate as well as the number of subjects needed to achieve a given power can be computed.

May 20th 2008

Update of version PFIM Interface 2.1 (bug correction)

A bug in the previous version of the Fedorov-Wynn algorithm has been corrected.
The bug concerns the computation of the number of subjects in the optimised designs using the Fedorov-Wynn algorithm (designs optimised with the Simplex algorithm are unaffected by the bug).
The only results affected are population designs combining elementary designs with unequal number of sampling times. eg :

if the final design is for instance ((1,2,3),(1,3,5)) with frequencies (alpha1, alpha2) it is unaffected by the bug
if the final design is for instance ((1,2,3),(1,3)) with frequencies (alpha1, alpha2), it is affected by the bug, and the frequencies will not be correct. In this case the correct frequencies should be respectively (alpha1/3)/sum and (alpha2/2)/sum where sum=(alpha1/3)+(alpha2/2) to normalise the sum of the frequencies to 1. ("frequencies" refer to the frequencies reported by the bugged version of the algorithm)

Because of this bug, the final criterion and estimates of SE for the parameters in the model, being computed with the wrong frequencies, is also incorrect, but differences should be small and unlikely to be clinically significant. The new version of the Fedorov-Wynn outputs the correct frequencies and we encourage users to update PFIM interface 2.1 with the new version.

April 24th 2008

Version PFIM 3.0

PFIM 3.0 is an extension of PFIM for multiple response models. It is based on extensions of R functions PFIM1.2 and PFIMOPT1.0 for evaluation and optimisation respectively. Conversely to the previous version, only one function is proposed allowing both evaluation and optimisation of population designs. Options have been added for model specification and optimisation, compared to PFIM 1.2 and PFIMOPT 1.0. The model can be written using an analytical form or using a differential equation system. Moreover, with these new versions a library of pharmacokinetics models is available. Regarding optimisation step, the Federov-Wynn algorithm has been added as an alternative to the Simplex algorithm. It allows to optimise design with fixed sampling times in opposite to the Simplex. Moreover, it considers only pre-specified sampling times, avoiding, clinically unfeasible sampling times.

January 29th 2008

1. Version PFIM Interface 2.1 (corrected version of PFIM Interface 2.0)
PFIM Interface 2.1 allows both evaluation and optimisation and it is was programmed as a graphical user interface package using the R software. It is based on the previous functions PFIM1.2 and PFIMOPT1.0. Documentation on this graphical user interface version is available in the relevant section and includes detailed explanations and examples as to how to use PFIM Interface 2.1. Options have been added for model specification and optimisation, compared to PFIM 1.2 and PFIMOPT 1.0. The model can be written using an analytical form or using a differential equation system. Moreover, with these new versions a library of pharmacokinetics models is available. Regarding optimisation step, the Federov-Wynn algorithm has been added as an alternative to the Simplex algorithm. It allows to optimise design with fixed sampling times in opposite to the Simplex. Moreover, it considers only pre-specified sampling times, avoiding, clinically unfeasible sampling times.