Half-life is calculated by fitting the natural logarithm of concentration by time. The default calculation method is curve stripping (described in more detail below). Manual half-life points with no automated half-life selection can be performed, or specific points can be excluded while still performing curve stripping.

When automatic point selection is performed for curve stripping, the algorithm described below is used.

All sets of points that are applicable according to the current options are selected.

- Drop all BLQ values, then
- Choose all sets of points that start from the \(T_{last}\) and step back:
- at least 3 points (customizable with
`PKNCA.options("min.hl.points")`

) - Not including \(T_{max}\)
(customizable with
`PKNCA.options("allow.tmax.in.half.life")`

)

- at least 3 points (customizable with

As a specific example, if measurements were at 0, 1, 2, 3, 4, 6, 8, 12, and 24 hours; if \(T_{last}\) is 12 hours; and if \(T_{max}\) is 1 hour then the default point sets that would be fit are:

- 6, 8, and 12 hours;
- 4, 6, 8, and 12 hours;
- 3, 4, 6, 8, and 12 hours; and
- 2, 3, 4, 6, 8, and 12 hours.

If `PKNCA.options("min.hl.points")`

were set to
`4`

, then the 6, 8, and 12 hour set would not be fit. If
`PKNCA.options("allow.tmax.in.half.life")`

were set to
`TRUE`

, then 1, 2, 3, 4, 6, 8, and 12 hours would be fit.

After fitting all points, the best fit among the set of possible fit is selected by the following rules:

- \(\lambda_z > 0\) and at the
same time the maximum r-squared must be within an adjusted \(r^2\) factor of the best.
- The adjusted \(r^2\) factor is
controlled by
`PKNCA.options("adj.r.squared.factor")`

and it defaults to 10^{-4}. - These rules must be met simultaneously, so if the maximum adjusted \(r^2\) is for a line with \(\lambda_z \leq 0\), the half-life may end up being unreportable.

- The adjusted \(r^2\) factor is
controlled by
- If fitting the log-linear concentration-time line fails, then it is not the best line.
- If more than one fit still meets the criteria above, then choose the fit with the most points included.

```
# Perform calculations for subject 1, only
<- as.data.frame(datasets::Theoph)[datasets::Theoph$Subject == 1, ]
data_conc
# Keep all points
<-
conc_obj PKNCAconc(
data_conc,~Time|Subject
conc
)
# Only calculate half-life and parameters required for half-life
<- data.frame(start=0, end=Inf, half.life=TRUE)
current_intervals <- PKNCAdata(conc_obj, intervals=current_intervals)
data_obj <- pk.nca(data_obj) result_obj
```

`## No dose information provided, calculations requiring dose will return NA.`

```
# Extract the results for subject 1
as.data.frame(result_obj)
```

```
## # A tibble: 10 × 6
## Subject start end PPTESTCD PPORRES exclude
## <ord> <dbl> <dbl> <chr> <dbl> <chr>
## 1 1 0 Inf tmax 1.12 <NA>
## 2 1 0 Inf tlast 24.4 <NA>
## 3 1 0 Inf lambda.z 0.0485 <NA>
## 4 1 0 Inf r.squared 1.00 <NA>
## 5 1 0 Inf adj.r.squared 1.00 <NA>
## 6 1 0 Inf lambda.z.time.first 9.05 <NA>
## 7 1 0 Inf lambda.z.n.points 3 <NA>
## 8 1 0 Inf clast.pred 3.28 <NA>
## 9 1 0 Inf half.life 14.3 <NA>
## 10 1 0 Inf span.ratio 1.07 <NA>
```

In some cases, specific points will be known outliers, or there may be another reason to exclude specific points. And, with those points excluded, the half-life should be calculated using the normal curve stripping methods described above.

To exclude specific points but otherwise use curve stripping, use the
`exclude_half.life`

option as the column name in the
concentration dataset for `PKNCAconc()`

as illustrated
below.

```
$exclude_hl <- data_conc$Time == 12.12
data_conc# Confirm that we will be excluding exactly one point
stopifnot(sum(data_conc$exclude_hl) == 1)
# Drop one point
<-
conc_obj_exclude1 PKNCAconc(
data_conc,~Time|Subject,
concexclude_half.life="exclude_hl"
)
<- PKNCAdata(conc_obj_exclude1, intervals=current_intervals)
data_obj_exclude1
# Perform the calculations
<- pk.nca(data_obj_exclude1) result_obj_exclude1
```

`## No dose information provided, calculations requiring dose will return NA.`

```
# Results differ when excluding the 12-hour point for subject 1 (compare to
# example in the previous section)
as.data.frame(result_obj_exclude1)
```

```
## # A tibble: 10 × 6
## Subject start end PPTESTCD PPORRES exclude
## <ord> <dbl> <dbl> <chr> <dbl> <chr>
## 1 1 0 Inf tmax 1.12 <NA>
## 2 1 0 Inf tlast 24.4 <NA>
## 3 1 0 Inf lambda.z 0.0482 <NA>
## 4 1 0 Inf r.squared 1.00 <NA>
## 5 1 0 Inf adj.r.squared 0.999 <NA>
## 6 1 0 Inf lambda.z.time.first 5.1 <NA>
## 7 1 0 Inf lambda.z.n.points 4 <NA>
## 8 1 0 Inf clast.pred 3.28 <NA>
## 9 1 0 Inf half.life 14.4 <NA>
## 10 1 0 Inf span.ratio 1.34 <NA>
```

In other cases, the exact points to use for half-life calculation are known, and automatic point selection with curve stripping should not be performed.

To exclude specific points but otherwise use curve stripping, use the
`include_half.life`

option as the column name in the
concentration dataset for `PKNCAconc()`

as illustrated
below.

```
$include_hl <- data_conc$Time > 3
data_conc# Confirm that we will be excluding exactly one point
stopifnot(sum(data_conc$include_hl) == 6)
# Drop one point
<-
conc_obj_include6 PKNCAconc(
data_conc,~Time|Subject,
concinclude_half.life="include_hl"
)
<- PKNCAdata(conc_obj_include6, intervals=current_intervals)
data_obj_include6
# Perform the calculations
<- pk.nca(data_obj_include6) result_obj_include6
```

`## No dose information provided, calculations requiring dose will return NA.`

```
# Results differ when including 6 points (compare to example in the previous
# section)
as.data.frame(result_obj_include6)
```

```
## # A tibble: 10 × 6
## Subject start end PPTESTCD PPORRES exclude
## <ord> <dbl> <dbl> <chr> <dbl> <chr>
## 1 1 0 Inf tmax 1.12 <NA>
## 2 1 0 Inf tlast 24.4 <NA>
## 3 1 0 Inf lambda.z 0.0475 <NA>
## 4 1 0 Inf r.squared 0.999 <NA>
## 5 1 0 Inf adj.r.squared 0.998 <NA>
## 6 1 0 Inf lambda.z.time.first 3.82 <NA>
## 7 1 0 Inf lambda.z.n.points 6 <NA>
## 8 1 0 Inf clast.pred 3.30 <NA>
## 9 1 0 Inf half.life 14.6 <NA>
## 10 1 0 Inf span.ratio 1.41 <NA>
```