df = data.frame(group = c(rep('A',4), rep('B',3)),
            response = c(1,4,2,1,1,2,3),
            treatment = c("control","100mg","200mg","50mg","control","100mg","200mg"))

> df
    group response treatment
       A     1   control
       A     4     100mg
       A     2     200mg
       A     1      50mg
       B     1   control
       B     2     100mg
       B     3     200mg

# function for % change
pct <- function(x) {(x/lag(x)-1)*100}

library(dplyr)
# group data and apply function
percChange <- df %>%
  group_by(group) %>%
  mutate_at(vars(response), funs(pct))

# the output (perChange) is:

#   group response treatment
# 1 A        NA   control
# 2 A       300   100mg
# 3 A       -50   200mg
# 4 A       -50   50mg
# 5 B        NA   control
# 6 B       100   100mg
# 7 B        50   200mg

# group  response  treatment
# 1 A        NA   control
# 2 A       300   100mg
# 3 A       100   200mg
# 4 A       0     50mg
# 5 B       NA    control
# 6 B       100   100mg
# 7 B       200   200mg