Bioequivalence and Bioavailability Forum

Dear all,

package replicateBE is on CRAN. Background information in its Vignette.

Data can be imported from CSV- or XLS(X)-files. Following ten designs are covered:

• Four period full replicates
  • TRTR | RTRT
    
  • TRRT | RTTR
    
  • TTRR | RRTT
    
  • TRTR | RTRT | TRRT | RTTR
    
  • TRRT | RTTR | TTRR | RRTT
• Two period full replicate
  • TR | RT | TT | RR ¹
• Three period full replicates
  • TRT | RTR
    
  • TRR | RTT
• Three period partial replicates
  • TRR | RTR | RRT
    
  • TRR | RTR ²

Implemented:

• Estimation of CV_wR (and CV_wT in full replicates)
  A linear model of log-transformed PK responses and effects
     sequence, subject(sequence), period
  of the reference (and test, if possible) treatment – where all effects are fixed (i.e., ANOVA).
  Estimated via function lm() of library stats.
  In full replicate designs assessment of \(s_{wT}/s_{wR}\) and the upper confidence limit of \(\sigma_{wT}/\sigma_{wR}\) for the WHO’s reference-scaling of AUC.
  
  
• Method A
  A linear model of log-transformed PK responses and effects
     sequence, subject(sequence), period, treatment
  – where all effects are fixed (i.e., ANOVA).
  Estimated via function lm() of library stats.
  
  
• Method B
  A linear mixed model of log-transformed PK responses and effects
     sequence, subject(sequence), period, treatment
  – where subject(sequence) is a random effect and all others are fixed.
  Three options
  1. Estimated via function lme() of library nlme. Uses degrees of freedom equivalent to SAS’ DDFM=CONTAIN and Phoenix/WinNonlin’s DF Residual. Implicitly preferred according to the EMA’s Q&A document and hence, the default.
     
  2. Estimated via function lmer() of library lmerTest. Uses Satterthwaite’s degrees of freedom equivalent to SAS’ DDFM=SATTERTHWAITE and Phoenix/WinNonlin’s DF Satterthwaite. This is the only option available in SPSS.
     Potentially better for highly incomplete data.
     
  3. Estimated via function lmer() of library lmerTest. Uses the Kenward-Roger approximation equivalent to SAS’ DDFM=KENWARDROGER. This is the only option available in JMP.
     Potentially better for highly incomplete data.

• ABE
  Conventional Average Bioequivalence. Optionally with tighter (EMA: NTIDs) or wider limits (GCC: C_max).

Assessment of potential outliers in the ABEL-methods is done by box plots of studentized model residuals.

Installation/Update of the latest release from CRAN with

install.packages("replicateBE", repos = "https://cloud.r-project.org/")

Installation of the development version from GitHub:

devtools::install_github("Helmut01/replicateBE")

Enjoy!

Bug reports to GitHub or the maintainer.

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1. Balaam’s design (not recommended due to poor power characteristics).
   
2. Extra-reference design; biased in the presence of period effects (design not recommended).