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Use this function to determine the antibiotic drug code of one or more antibiotics. The data set antibiotics will be searched for abbreviations, official names and synonyms (brand names).


as.ab(x, flag_multiple_results = TRUE, info = interactive(), ...)




a character vector to determine to antibiotic ID


a logical to indicate whether a note should be printed to the console that probably more than one antibiotic drug code or name can be retrieved from a single input value.


a logical to indicate whether a progress bar should be printed, defaults to TRUE only in interactive mode


arguments passed on to internal functions


A character

vector with additional class ab


All entries in the antibiotics data set have three different identifiers: a human readable EARS-Net code (column ab, used by ECDC and WHONET), an ATC code (column atc, used by WHO), and a CID code (column cid, Compound ID, used by PubChem). The data set contains more than 5,000 official brand names from many different countries, as found in PubChem. Not that some drugs contain multiple ATC codes.

All these properties will be searched for the user input. The as.ab() can correct for different forms of misspelling:

  • Wrong spelling of drug names (such as "tobramicin" or "gentamycin"), which corrects for most audible similarities such as f/ph, x/ks, c/z/s, t/th, etc.

  • Too few or too many vowels or consonants

  • Switching two characters (such as "mreopenem", often the case in clinical data, when doctors typed too fast)

  • Digitalised paper records, leaving artefacts like 0/o/O (zero and O's), B/8, n/r, etc.

Use the ab_* functions to get properties based on the returned antibiotic ID, see Examples.

Note: the as.ab() and ab_* functions may use very long regular expression to match brand names of antimicrobial drugs. This may fail on some systems.

You can add your own manual codes to be considered by as.ab() and all ab_* functions, see add_custom_antimicrobials().


World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology:



This package contains all ~550 antibiotic, antimycotic and antiviral drugs and their Anatomical Therapeutic Chemical (ATC) codes, ATC groups and Defined Daily Dose (DDD) from the World Health Organization Collaborating Centre for Drug Statistics Methodology (WHOCC, and the Pharmaceuticals Community Register of the European Commission (

These have become the gold standard for international drug utilisation monitoring and research.

The WHOCC is located in Oslo at the Norwegian Institute of Public Health and funded by the Norwegian government. The European Commission is the executive of the European Union and promotes its general interest.

NOTE: The WHOCC copyright does not allow use for commercial purposes, unlike any other info from this package. See

Reference Data Publicly Available

All data sets in this AMR package (about microorganisms, antibiotics, R/SI interpretation, EUCAST rules, etc.) are publicly and freely available for download in the following formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, SAS, and Stata. We also provide tab-separated plain text files that are machine-readable and suitable for input in any software program, such as laboratory information systems. Please visit our website for the download links. The actual files are of course available on our GitHub repository.

See also

  • antibiotics for the data.frame that is being used to determine ATCs

  • ab_from_text() for a function to retrieve antimicrobial drugs from clinical text (from health care records)


# these examples all return "ERY", the ID of erythromycin:
#> Class 'ab'
#> [1] ERY
as.ab("J 01 FA 01")
#> Class 'ab'
#> [1] ERY
#> Class 'ab'
#> [1] ERY
#> Class 'ab'
#> [1] ERY
as.ab("   eryt 123")
#> Class 'ab'
#> [1] ERY
#> Class 'ab'
#> [1] ERY
#> Class 'ab'
#> [1] ERY
as.ab("eritromicine") # spelled wrong, yet works
#> Class 'ab'
#> [1] ERY
as.ab("Erythrocin") # trade name
#> Class 'ab'
#> [1] ERY
as.ab("Romycin") # trade name
#> Class 'ab'
#> [1] ERY

# spelling from different languages and dyslexia are no problem
#> [1] "J01DD04"
ab_atc("cephtriaxone") # small spelling error
#> [1] "J01DD04"
ab_atc("cephthriaxone") # or a bit more severe
#> [1] "J01DD04"
ab_atc("seephthriaaksone") # and even this works
#> [1] "J01DD04"

# use ab_* functions to get a specific properties (see ?ab_property);
# they use as.ab() internally:
#> [1] "Erythromycin"
#> [1] "Erythromycin"

# \donttest{
if (require("dplyr")) {

  # you can quickly rename 'rsi' columns using set_ab_names() with dplyr:
  example_isolates %>%
    set_ab_names(where(is.rsi), property = "atc")
#> # A tibble: 2,000 × 46
#>    date       patient   age gender ward     mo           J01CE01 J01CF04 J01CF05
#>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <rsi>   <rsi>   <rsi>  
#>  1 2002-01-02 A77334     65 F      Clinical B_ESCHR_COLI R       NA      NA     
#>  2 2002-01-03 A77334     65 F      Clinical B_ESCHR_COLI R       NA      NA     
#>  3 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R       NA      R      
#>  4 2002-01-07 067927     45 F      ICU      B_STPHY_EPDR R       NA      R      
#>  5 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R       NA      R      
#>  6 2002-01-13 067927     45 F      ICU      B_STPHY_EPDR R       NA      R      
#>  7 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R       NA      S      
#>  8 2002-01-14 462729     78 M      Clinical B_STPHY_AURS R       NA      S      
#>  9 2002-01-16 067927     45 F      ICU      B_STPHY_EPDR R       NA      R      
#> 10 2002-01-17 858515     79 F      ICU      B_STPHY_EPDR R       NA      S      
#> # … with 1,990 more rows, and 37 more variables: J01CA04 <rsi>, J01CR02 <rsi>,
#> #   J01CA01 <rsi>, J01CR05 <rsi>, J01DB04 <rsi>, J01DE01 <rsi>, J01DC02 <rsi>,
#> #   J01DC01 <rsi>, J01DD01 <rsi>, J01DD02 <rsi>, J01DD04 <rsi>, J01GB03 <rsi>,
#> #   J01GB01 <rsi>, J01GB06 <rsi>, J01GB04 <rsi>, J01EA01 <rsi>, J01EE01 <rsi>,
#> #   J01XE01 <rsi>, J01XX01 <rsi>, J01XX08 <rsi>, J01MA02 <rsi>, J01MA14 <rsi>,
#> #   J01XA01 <rsi>, J01XA02 <rsi>, J01AA07 <rsi>, J01AA12 <rsi>, J01AA02 <rsi>,
#> #   J01FA01 <rsi>, J01FF01 <rsi>, J01FA10 <rsi>, J01DH51 <rsi>, …
# }