R dplyr: how to filter a column within a grep() when its name is stored in a vector?

Filtering a column of a data frame data using dplyr when its name is stored within an "external" vector col_name can be achieved using !!. However, this no longer appears to work if trying to apply the same logic within a filter and a grepl().

How one should do that in plyr in a single line?

data <- read.table(text="Sol_name    geo_pos     loc_pos     dol_pos    pol_pos   kol_pos
A            1            1          0          0         1
B            0            1          1          0         0
C            1            0          1          1         1
D            0            1          0          0         1",h=T)

kw <- "B|D"
data %>% 
  filter(grepl(toupper(kw), toupper(Sol_name))) # works

  Sol_name geo_pos loc_pos dol_pos pol_pos kol_pos
1        B       0       1       1       0       0
2        D       0       1       0       0       1

col_name <- "Sol_name"
data %>% 
  filter(grepl(toupper(kw), toupper(!!col_name))) # does not

[1] Sol_name geo_pos  loc_pos  dol_pos  pol_pos  kol_pos 
<0 lignes> (ou 'row.names' de longueur nulle)

You can use [[ with . or .data:

col_name <- "Sol_name"
kw <- "B|D"
data %>% 
  filter(grepl(kw, .data[[col_name]]))

#   Sol_name geo_pos loc_pos dol_pos pol_pos kol_pos
# 1        B       0       1       1       0       0
# 2        D       0       1       0       0       1

From ?.data

> .data versus the magrittr pronoun .
> In a magrittr pipeline, .data is not necessarily interchangeable with the magrittr pronoun .. With grouped data frames in particular, .data represents the current group
> slice whereas the pronoun . represents the whole data frame. Always
> prefer using .data in data-masked context.