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knitr::opts_chunk$set( collapse = TRUE, comment = "#>" )
library(conflicted) suppressMessages(conflict_prefer("filter", "dplyr")) library(DOPE) library(tibble) library(dplyr) library(stringr) library(usethis)
The lookup table has information on drug category, class and synonyms. It is made from the DEA and "No Slang" tables. The core of the table is the dea_factsheets table. It is tweaked to simplify complex names
The dea brands file has:
dea_brands <- DOPE::dea_brands %>% rename("brand" = brands) %>% mutate(across(where(is.character), tolower)) %>% mutate(brand = str_remove_all(brand, "®")) %>% mutate(brand = case_when(brand == "kadianms-contin" ~ "kadian", # two names TRUE ~ brand)) %>% bind_rows(c(category = "morphine", brand = "ms contin"))
The fact sheet file has:
These two do not fit well
dea_class_cat <- DOPE::dea_factsheets %>% mutate(across(where(is.character), tolower)) %>% mutate(category = case_when(category == "peyote and mescaline" ~ "mescaline", category == "ghb - gamma-hydroxybutyric acid" ~ "ghb", category == "ecstasy or mdma (also known as molly)" ~ "mdma", category == "flakka (alpha-pvp)" ~ "flakka", TRUE ~ category))
dea_street_names <- DOPE::dea_street_names %>% mutate(across(where(is.character), tolower)) %>% mutate(category = case_when(category == "fentanyl and fentanyl derivatives" ~ "fentanyl", TRUE ~ category))
# the these drugs do not have fact sheets but they appear on the DEA # DEA website (in slang) missing <- tribble( ~category, ~class, ~fact_path, "acetaminophen and oxycodone", "narcotics (opioids)", "DEA slang", "alprazolam", "benzodiazepine", "DEA slang" , "clonazepam", "benzodiazepine", "DEA slang" , "crack cocaine", "stimulants", "DEA slang", "hydrocodone", "narcotics (opioids)", "DEA slang", "marijuana concentrates", "cannabis", "DEA slang", "mushrooms", "hallucinogen", "DEA slang", "PCP", "hallucinogen", "DEA slang", "promethazine with codeine", "narcotics (opioids)", "DEA slang", "ritalin", "stimulants", "DEA slang", "synthetic cannabinoids", "designer drugs", "DEA slang", "synthetic cathinones", "stimulants", "DEA slang") # extras from NoSlang extraNewSlang <- tribble( ~category, ~class, ~fact_path, "2cb", "hallucinogen", "noSlang Term", "alpha-ethyltryptamine", "hallucinogen", "noSlang Term", "alpha-methyltryptamine", "hallucinogen", "noSlang Term", "amobarbital", "depressant", "noSlang Term", "amyl nitrite", "inhalant", "noSlang Term", "dextromethorphan", "depressant", "noSlang Term", "diazepam", "benzodiazepine", "noSlang Term", "dimethyltryptamine", "hallucinogen", "noSlang Term", "gbl", "depressant", "noSlang Term", "isobutyl nitrite", "inhalant", "noSlang Term", "methcathinone", "stimulant", "noSlang Term", "methaqualone", "depressant", "noSlang Term", "nitrous oxide", "inhalant", "noSlang Term" )
categories <- data.frame(allCat = c(dea_brands$category, dea_street_names$category, dea_class_cat$category, missing$category, extraNewSlang$category)) %>% distinct() %>% arrange()
library(sqldf) lookup_df <- sqldf("select cc.class, a.category, a.syn synonym from (select b.category, b.brand as syn from dea_brands as b union select s1.category, s1.slang as syn from dea_street_names as s1 union select s2.category, s2.brand as syn from dea_street_names as s2 where s2.brand <> NULL union select ns.drug, ns.street_name as syn from noslang_street_names as ns) as a left join dea_class_cat as cc on a.category = cc.category") #use_data(lookup_df, overwrite = TRUE)
Several records do not have a class.
na_lookup <- filter(lookup_df, is.na(class)) length(unique(na_lookup$category)) # 30 unique categories with no class # *am = depressants # *mine = hallucinogen as per DAN 3/29/21 # *2cb = hallucinogen # *amt = hallucinogen # *trite = depressants # *deine = narcotics (opioids) # crack = stimulants lookup_df2 <- lookup_df %>% mutate(class = case_when(str_detect(category, "(?=.*am$)|(?=.*trite$)|(gbl)|(?=.*qualone$)|(?=.*ital$)") == TRUE ~ "depressants", str_detect(category, "crack|(?=.*cathin)|(?=.*date$)|(ritalin)|(?=.*phetamine$)") == TRUE ~ "stimulants", str_detect(category, "(?=.*amt$)|(?=.*2cb$)|(?=.*mine$)|(dmt)|(?=.*room)|(pcp)|(peyote)") == TRUE ~ "hallucinogen", str_detect(category, "(?=.*deine$)|(?=.*one$)") == TRUE ~ "narcotics (opioids)", str_detect(category, "(?=.*marijuana)|(?=.*cannab)") == TRUE ~ "cannabis", category == "dextromethorphan" ~ "antitussives", category == "nitrous oxide" ~ "inhalant", TRUE ~ class ) ) #check missing again na_lookup <- filter(lookup_df2, is.na(class)) lookup_df <- lookup_df2
Add data from IQVIA
iqvia <- DOPE::iqvia %>% mutate(across(where(is.character), tolower)) lookup_df <- lookup_df %>% bind_rows(iqvia)
Fix pluralization
# get classes & categories unique(lookup_df$class) unique(lookup_df$category) lookup_df3 <- lookup_df %>% mutate(class = if_else(class != "cannabis", str_replace(class, "s$", ""), class), class = case_when(class == "narcotics (opioids)" ~ "narcotic (opioid)", TRUE ~ class), category = if_else(category != "mushrooms", str_replace(category, "s$", ""), category) )
orange_book <- tibble(synonym = c(dea_controlled$substance, dea_controlled$synonym)) %>% mutate(synonym = tolower(synonym)) %>% distinct() %>% mutate( difficult = str_count(synonym, "[(]") > 0 | str_detect(synonym, ",(?=\\S)") | str_detect(synonym, '[-|/|&|,|"| ]') ) %>% filter(!difficult) %>% anti_join(lookup_df, by = "synonym") %>% anti_join(lookup_df, by = c("synonym" = "class")) %>% anti_join(lookup_df, by = c("synonym" = "category")) %>% mutate(category = "Unknown", class = "Unknown") %>% select(class, category, synonym) lookup_df <- bind_rows(lookup_df3 , orange_book)
use_data(lookup_df, overwrite = TRUE)
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