expirest (version 0.1.5)

print.expirest_osle: Print a summary of the shelf life estimation (osle)

Description

This is a method for the function print() for objects of class ‘expirest_osle’.

Usage

# S3 method for expirest_osle
print(x, ...)

Value

The ‘expirest_osle’ object passed to the x

parameter is returned invisibly.

Arguments

x

An object of class ‘expirest_osle’ returned by the expirest_osle() function.

...

Further arguments passed to or from other methods or arguments that can be passed down to the formatC() function.

Details

The function expirest_osle() estimates the shelf life, or retest period, following the ICH Q1E guideline. By default, batch poolability is checked as recommended by the guideline at a significance level of 0.25. Other levels can be used, although not recommended, by changing the default of the alpha_pool parameter. Three possible models may be appropriate, i.e.

• a common intercept / common slope model (cics),

• a different intercept / common slope model (dics) or

• a different intercept / different slope model (dids).

The worst case intercept is the intercept of the batch whose confidence limit is the first crossing the acceptance limit. As in case of the cics model type all batches have a common intercept and a common confidence interval, all batches can be regarded as equally worst case. In case of the dids model type, shelf life estimation is done using the models obtained from fitting the data of each batch individually.

See Also

expirest_osle, expirest_wisle, formatC, methods.

Examples

# Potency stability data (in % of label claim (LC)) of five batches of a drug
# product obtained over a 24 months period:
str(exp1)

# 'data.frame':	53 obs. of  3 variables:
# $ Batch  : Factor w/ 6 levels "b2","b3","b4",..: 1 1 1 1 1 1 1 1 1 1 ...
# $ Month  : num  0 1 3 3 6 6 12 12 24 24 ...
# $ Potency: num  101 101.3 99.8 99.2 99.5 ...

# Fit models of different type
res1 <-
  expirest_osle(data = exp1[exp1$Batch %in% c("b2", "b5", "b7"), ],
                response_vbl = "Potency", time_vbl = "Month",
                batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500))
res2 <-
  expirest_osle(data = exp1[exp1$Batch %in% c("b3", "b4", "b5"), ],
                response_vbl = "Potency", time_vbl = "Month",
                batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500))
res3 <-
  expirest_osle(data = exp1[exp1$Batch %in% c("b4", "b5", "b8"), ],
                response_vbl = "Potency", time_vbl = "Month",
                batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500))

res1
# Expected output of print(res1)
# Summary of shelf life estimation following the ICH Q1E guideline
#
# The best model accepted at a significance level of 0.25 has
# Common intercepts and Common slopes (acronym: cics).
#
# Worst case intercept: 100.5669
# Worst case batch: NA
#
# Estimated shelf life for cics model:  26.2241

res2
# Expected output of print(res2)
# Summary of shelf life estimation following the ICH Q1E guideline
#
# The best model accepted at a significance level of 0.25 has
# Different intercepts and Common slopes (acronym: dics).
#
# Worst case intercept:   100.82
# Worst case batch: b5
#
# Estimated shelf life for dics model: 23.60194

res3
# Expected output of print(res3)
# Summary of shelf life estimation following the ICH Q1E guideline
#
# The best model accepted at a significance level of 0.25 has
# Different intercepts and Different slopes (acronym: dids).
#
# Worst case intercept: 101.2594
# Worst case batch: b8
#
# Estimated shelf life for dids model: 15.96453