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# Transform Input to an Antibiotic ID

Source: `R/ab.R`
`as.ab.Rd`

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

## Usage

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

    is.ab(x)

    ab_reset_session()

    NA_ab_

## Arguments

x

  A character vector to determine to antibiotic ID.

flag_multiple_results

  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.

language

  Language to coerce input values from any of the 28 supported languages - default to the system language if supported (see `get_AMR_locale()`).

info

  A logical to indicate whether a progress bar should be printed - the default is `TRUE` only in interactive mode.

...

  Arguments passed on to internal functions.

## Value

A character vector with additional class `ab`

## Details

All entries in the antimicrobials 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()`.

`NA_ab_` is a missing value of the new `ab` class, analogous to e.g. base R's `NA_character_`.

## Source

World Health Organization (WHO) Collaborating Centre for Drug Statistics Methodology: https://atcddd.fhi.no/atc_ddd_index/

European Commission Public Health PHARMACEUTICALS - COMMUNITY REGISTER: https://health.ec.europa.eu/documents/community-register/html/index_en.htm

## WHOCC

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, https://atcddd.fhi.no) and the Pharmaceuticals Community Register of the European Commission (https://ec.europa.eu/health/documents/community-register/html/index_en.htm).

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 https://atcddd.fhi.no/copyright_disclaimer/.

## Download Our Reference Data

All reference data sets in the AMR package - including information on microorganisms, antimicrobials, and clinical breakpoints - are freely available for download in multiple formats: R, MS Excel, Apache Feather, Apache Parquet, SPSS, and Stata.

For maximum compatibility, we also provide machine-readable, tab-separated plain text files suitable for use in any software, including laboratory information systems.

Visit our website for direct download links, or explore the actual files in our GitHub repository.

## See also

- antimicrobials 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)

## Examples

    # these examples all return "ERY", the ID of erythromycin:
    as.ab("J01FA01")
    #> Class <ab>
    #> [1] ERY
    as.ab("J 01 FA 01")
    #> Class <ab>
    #> [1] ERY
    as.ab("Erythromycin")
    #> Class <ab>
    #> [1] ERY
    as.ab("eryt")
    #> Class <ab>
    #> [1] ERY
    as.ab("ERYT")
    #> Class <ab>
    #> [1] ERY
    as.ab("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

    # spelling from different languages and dyslexia are no problem
    ab_atc("ceftriaxon")
    #> [1] "J01DD04"  "QJ01DD04"
    ab_atc("cephtriaxone") # small spelling error
    #> [1] "J01DD04"  "QJ01DD04"
    ab_atc("cephthriaxone") # or a bit more severe
    #> [1] "J01DD04"  "QJ01DD04"
    ab_atc("seephthriaaksone") # and even this works
    #> [1] "J01DD04"  "QJ01DD04"

    # use ab_* functions to get a specific properties (see ?ab_property);
    # they use as.ab() internally:
    ab_name("J01FA01")
    #> [1] "Erythromycin"
    ab_name("eryt")
    #> [1] "Erythromycin"

    # \donttest{
    if (require("dplyr")) {
      # you can quickly rename 'sir' columns using set_ab_names() with dplyr:
      example_isolates %>%
        set_ab_names(where(is.sir), property = "atc")
    }
    #> # A tibble: 2,000 × 46
    #>    date       patient   age gender ward     mo           J01CE01 J01CF04 J01CF05
    #>    <date>     <chr>   <dbl> <chr>  <chr>    <mo>         <sir>   <sir>   <sir>
    #>  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
    #> # ℹ 1,990 more rows
    #> # ℹ 37 more variables: J01CA04 <sir>, J01CR02 <sir>, J01CA01 <sir>,
    #> #   J01CR05 <sir>, J01DB04 <sir>, J01DE01 <sir>, J01DC02 <sir>, J01DC01 <sir>,
    #> #   J01DD01 <sir>, J01DD02 <sir>, J01DD04 <sir>, J01GB03 <sir>, J01GB01 <sir>,
    #> #   J01GB06 <sir>, J01GB04 <sir>, J01EA01 <sir>, J01EE01 <sir>, J01XE01 <sir>,
    #> #   J01XX01 <sir>, J01XX08 <sir>, J01MA02 <sir>, J01MA14 <sir>, J01XA01 <sir>,
    #> #   J01XA02 <sir>, J01AA07 <sir>, J01AA12 <sir>, J01AA02 <sir>, …
    # }