diff --git a/data-backup/admiral_adlb.rda b/data-backup/admiral_adlb.rda
deleted file mode 100644
index 9bf8663e65..0000000000
Binary files a/data-backup/admiral_adlb.rda and /dev/null differ
diff --git a/data-backup/admiral_adsl.rda b/data-backup/admiral_adsl.rda
deleted file mode 100644
index 79f5921fdb..0000000000
Binary files a/data-backup/admiral_adsl.rda and /dev/null differ
diff --git a/data-raw/admiral_adlb.R b/data-raw/admiral_adlb.R
deleted file mode 100644
index f07345368b..0000000000
--- a/data-raw/admiral_adlb.R
+++ /dev/null
@@ -1,466 +0,0 @@
-# Name: ADLB
-#
-# Label: Lab Analysis Dataset
-#
-# Input: adsl, lb
-# nolint start: undesirable_function_linter
-library(admiral)
-library(pharmaversesdtm) # Contains example datasets from the CDISC pilot project
-library(dplyr)
-library(lubridate)
-library(stringr)
-# nolint end
-
-# Load source datasets ----
-
-# Use e.g. haven::read_sas to read in .sas7bdat, or other suitable functions
-# as needed and assign to the variables below.
-# For illustration purposes read in admiral test data
-
-data("lb")
-data("admiral_adsl")
-
-adsl <- admiral_adsl
-
-# When SAS datasets are imported into R using haven::read_sas(), missing
-# character values from SAS appear as "" characters in R, instead of appearing
-# as NA values. Further details can be obtained via the following link:
-# https://pharmaverse.github.io/admiral/articles/admiral.html#handling-of-missing-values # nolint
-
-lb <- convert_blanks_to_na(lb)
-
-# Look-up tables ----
-
-# Assign PARAMCD, PARAM, and PARAMN
-param_lookup <- tibble::tribble(
-  ~LBTESTCD, ~PARAMCD, ~PARAM, ~PARAMN,
-  "ALB", "ALB", "Albumin (g/L)", 1,
-  "ALP", "ALKPH", "Alkaline Phosphatase (U/L)", 2,
-  "ALT", "ALT", "Alanine Aminotransferase (U/L)", 3,
-  "ANISO", "ANISO", "Anisocytes", 4,
-  "AST", "AST", "Aspartate Aminotransferase (U/L)", 5,
-  "BASO", "BASO", "Basophils Abs (10^9/L)", 6,
-  "BASOLE", "BASOLE", "Basophils/Leukocytes (FRACTION)", 7,
-  "BILI", "BILI", "Bilirubin (umol/L)", 8,
-  "BUN", "BUN", "Blood Urea Nitrogen (mmol/L)", 9,
-  "CA", "CA", "Calcium (mmol/L)", 10,
-  "CHOL", "CHOLES", "Cholesterol (mmol/L)", 11,
-  "CK", "CK", "Creatinine Kinase (U/L)", 12,
-  "CL", "CL", "Chloride (mmol/L)", 13,
-  "COLOR", "COLOR", "Color", 14,
-  "CREAT", "CREAT", "Creatinine (umol/L)", 15,
-  "EOS", "EOS", "Eosinophils (10^9/L)", 16,
-  "EOSLE", "EOSLE", "Eosinophils/Leukocytes (FRACTION)", 17,
-  "GGT", "GGT", "Gamma Glutamyl Transferase (U/L)", 18,
-  "GLUC", "GLUC", "Glucose (mmol/L)", 19,
-  "HBA1C", "HBA1C", "Hemoglobin A1C (1)", 20,
-  "HCT", "HCT", "Hematocrit (1)", 21,
-  "HGB", "HGB", "Hemoglobin (mmol/L)", 22,
-  "K", "POTAS", "Potassium (mmol/L)", 23,
-  "KETONES", "KETON", "Ketones", 24,
-  "LYM", "LYMPH", "Lymphocytes Abs (10^9/L)", 25,
-  "LYMLE", "LYMPHLE", "Lymphocytes/Leukocytes (FRACTION)", 26,
-  "MACROCY", "MACROC", "Macrocytes", 27,
-  "MCH", "MCH", "Ery. Mean Corpuscular Hemoglobin (fmol(Fe))", 28,
-  "MCHC", "MCHC", "Ery. Mean Corpuscular HGB Concentration (mmol/L)", 29,
-  "MCV", "MCV", "Ery. Mean Corpuscular Volume (f/L)", 30,
-  "MICROCY", "MICROC", "Microcytes", 31,
-  "MONO", "MONO", "Monocytes (10^9/L)", 32,
-  "MONOLE", "MONOLE", "Monocytes/Leukocytes (FRACTION)", 33,
-  "PH", "PH", "pH", 34,
-  "PHOS", "PHOS", "Phosphate (mmol/L)", 35,
-  "PLAT", "PLAT", "Platelet (10^9/L)", 36,
-  "POIKILO", "POIKIL", "Poikilocytes", 37,
-  "POLYCHR", "POLYCH", "Polychromasia", 38,
-  "PROT", "PROT", "Protein (g/L)", 39,
-  "RBC", "RBC", "Erythrocytes (TI/L)", 40,
-  "SODIUM", "SODIUM", "Sodium (mmol/L)", 41,
-  "SPGRAV", "SPGRAV", "Specific Gravity", 42,
-  "TSH", "TSH", "Thyrotropin (mU/L)", 43,
-  "URATE", "URATE", "Urate (umol/L)", 44,
-  "UROBIL", "UROBIL", "Urobilinogen", 45,
-  "VITB12", "VITB12", "Vitamin B12 (pmol/L)", 46,
-  "WBC", "WBC", "Leukocytes (10^9/L)", 47
-)
-
-
-# Derivations ----
-
-# Get list of ADSL vars required for derivations
-adsl_vars <- exprs(TRTSDT, TRTEDT, TRT01A, TRT01P)
-
-adlb <- lb %>%
-  # Join ADSL with LB (need TRTSDT for ADY derivation)
-  derive_vars_merged(
-    dataset_add = adsl,
-    new_vars = adsl_vars,
-    by_vars = exprs(STUDYID, USUBJID)
-  ) %>%
-  ## Calculate ADT, ADY ----
-  derive_vars_dt(
-    new_vars_prefix = "A",
-    dtc = LBDTC
-  ) %>%
-  derive_vars_dy(reference_date = TRTSDT, source_vars = exprs(ADT))
-
-adlb <- adlb %>%
-  ## Add PARAMCD PARAM and PARAMN - from LOOK-UP table ----
-  # Replace with PARAMCD lookup function
-  derive_vars_merged_lookup(
-    dataset_add = param_lookup,
-    new_vars = exprs(PARAMCD, PARAM, PARAMN),
-    by_vars = exprs(LBTESTCD),
-    check_type = "none",
-    print_not_mapped = FALSE
-  ) %>%
-  ## Calculate PARCAT1 AVAL AVALC ANRLO ANRHI ----
-  mutate(
-    PARCAT1 = LBCAT,
-    AVAL = LBSTRESN,
-    # Only populate AVALC if character value is non-redundant with AVAL
-    AVALC = ifelse(
-      is.na(LBSTRESN) | as.character(LBSTRESN) != LBSTRESC,
-      LBSTRESC,
-      NA
-    ),
-    ANRLO = LBSTNRLO,
-    ANRHI = LBSTNRHI
-  )
-
-# Derive Absolute values from fractional Differentials using WBC
-# Only derive where absolute values do not already exist
-# Need to populate ANRLO and ANRHI for newly created records
-adlb <- adlb %>%
-  # Derive absolute Basophils
-  derive_param_wbc_abs(
-    by_vars = exprs(STUDYID, USUBJID, !!!adsl_vars, DOMAIN, VISIT, VISITNUM, ADT, ADY),
-    set_values_to = exprs(
-      PARAMCD = "BASO",
-      PARAM = "Basophils Abs (10^9/L)",
-      PARAMN = 6,
-      DTYPE = "CALCULATION",
-      PARCAT1 = "HEMATOLOGY"
-    ),
-    get_unit_expr = extract_unit(PARAM),
-    diff_code = "BASOLE"
-  ) %>%
-  # Derive absolute Lymphocytes
-  derive_param_wbc_abs(
-    by_vars = exprs(STUDYID, USUBJID, !!!adsl_vars, DOMAIN, VISIT, VISITNUM, ADT, ADY),
-    set_values_to = exprs(
-      PARAMCD = "LYMPH",
-      PARAM = "Lymphocytes Abs (10^9/L)",
-      PARAMN = 25,
-      DTYPE = "CALCULATION",
-      PARCAT1 = "HEMATOLOGY"
-    ),
-    get_unit_expr = extract_unit(PARAM),
-    diff_code = "LYMPHLE"
-  )
-
-## Get Visit Info ----
-# See also the "Visit and Period Variables" vignette
-# (https://pharmaverse.github.io/admiral/articles/visits_periods.html#visits)
-adlb <- adlb %>%
-  # Derive Timing
-  mutate(
-    AVISIT = case_when(
-      str_detect(VISIT, "SCREEN") ~ "Baseline",
-      !is.na(VISIT) ~ str_to_title(VISIT),
-      TRUE ~ NA_character_
-    ),
-    AVISITN = case_when(
-      AVISIT == "Baseline" ~ 0,
-      !is.na(VISITNUM) ~ VISITNUM
-    )
-  )
-
-adlb <- adlb %>%
-  ## Calculate ONTRTFL ----
-  derive_var_ontrtfl(
-    start_date = ADT,
-    ref_start_date = TRTSDT,
-    ref_end_date = TRTEDT,
-    filter_pre_timepoint = AVISIT == "Baseline"
-  )
-
-## Calculate ANRIND : requires the reference ranges ANRLO, ANRHI ----
-adlb <- adlb %>%
-  derive_var_anrind()
-
-## Derive baseline flags ----
-adlb <- adlb %>%
-  # Calculate BASETYPE
-  mutate(
-    BASETYPE = "LAST"
-  ) %>%
-  # Calculate ABLFL
-  restrict_derivation(
-    derivation = derive_var_extreme_flag,
-    args = params(
-      by_vars = exprs(STUDYID, USUBJID, BASETYPE, PARAMCD),
-      order = exprs(ADT, VISITNUM, LBSEQ),
-      new_var = ABLFL,
-      mode = "last"
-    ),
-    filter = (!is.na(AVAL) & ADT <= TRTSDT & !is.na(BASETYPE))
-  )
-
-## Derive baseline information ----
-adlb <- adlb %>%
-  # Calculate BASE
-  derive_var_base(
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    source_var = AVAL,
-    new_var = BASE
-  ) %>%
-  # Calculate BASEC
-  derive_var_base(
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    source_var = AVALC,
-    new_var = BASEC
-  ) %>%
-  # Calculate BNRIND
-  derive_var_base(
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    source_var = ANRIND,
-    new_var = BNRIND
-  ) %>% # nolint start
-  # Calculate CHG for post-baseline records
-  # The decision on how to populate pre-baseline and baseline values of CHG is left to producer choice
-  # nolint end
-  restrict_derivation(
-    derivation = derive_var_chg,
-    filter = AVISITN > 0
-  ) %>% # nolint start
-  # Calculate PCHG for post-baseline records
-  # The decision on how to populate pre-baseline and baseline values of PCHG is left to producer choice
-  # nolint end
-  restrict_derivation(
-    derivation = derive_var_pchg,
-    filter = AVISITN > 0
-  )
-
-## Calculate lab grading ----
-
-# Assign ATOXDSCL and ATOXDSCH to hold lab grading terms
-# ATOXDSCL and ATOXDSCH hold terms defined by NCI-CTCAEv4.
-# See (https://pharmaverse.github.io/admiral/articles/lab_grading.html#implement_ctcv4)
-grade_lookup <- tibble::tribble(
-  ~PARAMCD, ~ATOXDSCL, ~ATOXDSCH,
-  "ALB", "Hypoalbuminemia", NA_character_,
-  "ALKPH", NA_character_, "Alkaline phosphatase increased",
-  "ALT", NA_character_, "Alanine aminotransferase increased",
-  "AST", NA_character_, "Aspartate aminotransferase increased",
-  "BILI", NA_character_, "Blood bilirubin increased",
-  "CA", "Hypocalcemia", "Hypercalcemia",
-  "CHOLES", NA_character_, "Cholesterol high",
-  "CK", NA_character_, "CPK increased",
-  "CREAT", NA_character_, "Creatinine increased",
-  "GGT", NA_character_, "GGT increased",
-  "GLUC", "Hypoglycemia", "Hyperglycemia",
-  "HGB", "Anemia", "Hemoglobin increased",
-  "POTAS", "Hypokalemia", "Hyperkalemia",
-  "LYMPH", "CD4 lymphocytes decreased", NA_character_,
-  "PHOS", "Hypophosphatemia", NA_character_,
-  "PLAT", "Platelet count decreased", NA_character_,
-  "SODIUM", "Hyponatremia", "Hypernatremia",
-  "WBC", "White blood cell decreased", "Leukocytosis",
-)
-
-# Assign grade criteria
-# metadata atoxgr_criteria_ctcv4 used to implement NCI-CTCAEv4
-# user could change to atoxgr_criteria_ctcv5 to implement NCI-CTCAEv5
-# Note: Hyperglycemia and Hypophosphatemia not defined in NCI-CTCAEv5 so
-# user would need to amend look-up table grade_lookup
-# See (https://pharmaverse.github.io/admiral/articles/lab_grading.html#implement_ctcv5)
-grade_crit <- atoxgr_criteria_ctcv4
-
-
-# Add ATOXDSCL and ATOXDSCH
-adlb <- adlb %>%
-  derive_vars_merged(
-    dataset_add = grade_lookup,
-    by_vars = exprs(PARAMCD)
-  ) %>%
-  # Derive toxicity grade for low values ATOXGRL
-
-  derive_var_atoxgr_dir(
-    meta_criteria = grade_crit,
-    new_var = ATOXGRL,
-    tox_description_var = ATOXDSCL,
-    criteria_direction = "L",
-    get_unit_expr = extract_unit(PARAM)
-  ) %>%
-  # Derive toxicity grade for low values ATOXGRH
-  # default metadata atoxgr_criteria_ctcv4 used
-  derive_var_atoxgr_dir(
-    meta_criteria = grade_crit,
-    new_var = ATOXGRH,
-    tox_description_var = ATOXDSCH,
-    criteria_direction = "H",
-    get_unit_expr = extract_unit(PARAM)
-  ) %>%
-  # (Optional) derive overall grade ATOXGR (combining ATOXGRL and ATOXGRH)
-  derive_var_atoxgr() %>%
-  # Derive baseline toxicity grade for low values BTOXGRL
-  derive_var_base(
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    source_var = ATOXGRL,
-    new_var = BTOXGRL
-  ) %>%
-  # Derive baseline toxicity grade for high values BTOXGRH
-  derive_var_base(
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    source_var = ATOXGRH,
-    new_var = BTOXGRH
-  ) %>%
-  # Derive baseline toxicity grade for for overall grade BTOXGR
-  derive_var_base(
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    source_var = ATOXGR,
-    new_var = BTOXGR
-  )
-
-
-## Calculate R2BASE, R2ANRLO and R2ANRHI ----
-adlb <- adlb %>%
-  derive_var_analysis_ratio(
-    numer_var = AVAL,
-    denom_var = BASE
-  ) %>%
-  derive_var_analysis_ratio(
-    numer_var = AVAL,
-    denom_var = ANRLO
-  ) %>%
-  derive_var_analysis_ratio(
-    numer_var = AVAL,
-    denom_var = ANRHI
-  )
-
-## SHIFT derivation ----
-adlb <- adlb %>%
-  # Derive shift from baseline for analysis indicator
-  derive_var_shift(
-    new_var = SHIFT1,
-    from_var = BNRIND,
-    to_var = ANRIND
-  ) %>%
-  # Derive shift from baseline for overall grade
-  restrict_derivation(
-    derivation = derive_var_shift,
-    args = params(
-      new_var = SHIFT2,
-      from_var = BTOXGR,
-      to_var = ATOXGR
-    ),
-    filter = !is.na(ATOXDSCL) | !is.na(ATOXDSCH)
-  )
-
-## Flag variables (ANL01FL, LVOTFL) ----
-# ANL01FL: Flag last result within an AVISIT for post-baseline records
-# LVOTFL: Flag last valid on-treatment record
-adlb <- adlb %>%
-  restrict_derivation(
-    derivation = derive_var_extreme_flag,
-    args = params(
-      by_vars = exprs(USUBJID, PARAMCD, AVISIT),
-      order = exprs(ADT, AVAL),
-      new_var = ANL01FL,
-      mode = "last"
-    ),
-    filter = !is.na(AVISITN) & ONTRTFL == "Y"
-  ) %>%
-  restrict_derivation(
-    derivation = derive_var_extreme_flag,
-    args = params(
-      by_vars = exprs(USUBJID, PARAMCD),
-      order = exprs(ADT, AVAL),
-      new_var = LVOTFL,
-      mode = "last"
-    ),
-    filter = ONTRTFL == "Y"
-  )
-
-## Get treatment information ----
-# See also the "Visit and Period Variables" vignette
-# (https://pharmaverse.github.io/admiral/articles/visits_periods.html#treatment_bds)
-adlb <- adlb %>%
-  # Assign TRTA, TRTP
-  mutate(
-    TRTP = TRT01P,
-    TRTA = TRT01A
-  )
-
-## Get extreme values ----
-adlb <- adlb %>%
-  # get MINIMUM value
-  derive_extreme_records(
-    dataset_add = adlb,
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    order = exprs(AVAL, ADT, AVISITN),
-    mode = "first",
-    filter_add = (!is.na(AVAL) & ONTRTFL == "Y"),
-    set_values_to = exprs(
-      AVISITN = 9997,
-      AVISIT = "POST-BASELINE MINIMUM",
-      DTYPE = "MINIMUM"
-    )
-  ) %>%
-  # get MAXIMUM value
-  derive_extreme_records(
-    dataset_add = adlb,
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    order = exprs(desc(AVAL), ADT, AVISITN),
-    mode = "first",
-    filter_add = (!is.na(AVAL) & ONTRTFL == "Y"),
-    set_values_to = exprs(
-      AVISITN = 9998,
-      AVISIT = "POST-BASELINE MAXIMUM",
-      DTYPE = "MAXIMUM"
-    )
-  ) %>%
-  # get LOV value
-  derive_extreme_records(
-    dataset_add = adlb,
-    by_vars = exprs(STUDYID, USUBJID, PARAMCD, BASETYPE),
-    order = exprs(ADT, AVISITN),
-    mode = "last",
-    filter_add = (ONTRTFL == "Y"),
-    set_values_to = exprs(
-      AVISITN = 9999,
-      AVISIT = "POST-BASELINE LAST",
-      DTYPE = "LOV"
-    )
-  )
-
-## Get ASEQ ----
-adlb <- adlb %>%
-  # Calculate ASEQ
-  derive_var_obs_number(
-    new_var = ASEQ,
-    by_vars = exprs(STUDYID, USUBJID),
-    order = exprs(PARAMCD, ADT, AVISITN, VISITNUM),
-    check_type = "error"
-  )
-
-# Add all ADSL variables
-adlb <- adlb %>%
-  derive_vars_merged(
-    dataset_add = select(adsl, !!!negate_vars(adsl_vars)),
-    by_vars = exprs(STUDYID, USUBJID)
-  )
-
-# Final Steps, Select final variables and Add labels
-# This process will be based on your metadata, no example given for this reason
-# ...
-
-# Save output ----
-
-# Change to whichever directory you want to save the dataset in
-dir <- tools::R_user_dir("admiral_templates_data", which = "cache")
-if (!file.exists(dir)) {
-  # Create the folder
-  dir.create(dir, recursive = TRUE, showWarnings = FALSE)
-}
-save(adlb, file = file.path(dir, "adlb.rda"), compress = "bzip2")
diff --git a/data-raw/create_admiral_adlb.R b/data-raw/create_admiral_adlb.R
index 779d912e17..a92a07e45e 100644
--- a/data-raw/create_admiral_adlb.R
+++ b/data-raw/create_admiral_adlb.R
@@ -1,61 +1,13 @@
 #  Create dataset:   data/admiral_adlb.rda
 #  This script:  create_admiral_adlb.R creates dataset data/admiral_adlb.rda.
-#
 
-# Preliminary
-library(diffdf) # nolint
+# Create dataset data/admiral_adlb.rda
 
-# To clarify directories (can be removed)
-# nolint start: object_name_linter
-CACHE_DIR <- "~/.cache/R/admiral_templates_data/"
-DATA_DIR <- "data-dir"
-DATA_RAW <- "data-raw"
-TEMPLATE_DIR <- "inst/templates/"
+# Run template script to create adlb
+source("inst/templates/ad_adlb.R", echo = TRUE) # nolint
 
-# clean CACHE_DIR
-THE_FILE <- paste0(CACHE_DIR, "/adlb.rda")
-THE_FILE <- paste0(CACHE_DIR, "/adsl.rda")
-if (file.exists(THE_FILE)) file.remove(THE_FILE)
-# nolint end
-
-#
-# STEPS
-#
-# First, use template to create the R script (in data-raw/admiral_adlb.R).
-# Next, source this script and create the data (~/.cache/R/admiral_template_data/admiral_adlb.rda)
-# Finally, shorten this data (now ~ 1.2 MB) by selecting only certain USUBJID
-
-# orignal method  - OMIT
-if (FALSE) {
-  # ### original mehtod (method 1)
-  # # First,  create the R script (from a template)
-  adam_name <- "adlb"
-  save_path <- paste0("./data-raw/admiral_", adam_name, ".R")
-  use_ad_template(
-    adam_name = adam_name,
-    save_path = save_path,
-    open = FALSE,
-    overwrite = TRUE
-  )
-  # Second, source the script and save data in .cache
-  source("data-raw/admiral_adlb.R") # nolint
-  load("~/.cache/R/admiral_templates_data/adlb.rda")
-}
-
-#
-# Instead, USE template, as recommened by Buzz
-#
-source(paste0(TEMPLATE_DIR, "/ad_adlb.R")) # nolint
-load(paste0(CACHE_DIR, "adlb.rda"))
-
-#
-# limit rows, by selecting only these USUBJID
-#
-#' 01-701-1015, 01-701-1023, 01-701-1028, 01-701-1033,
-#' 01-701-1034, 01-701-1047, 01-701-1097, 01-705-1186,
-#' 01-705-1292, 01-705-1310, 01-708-1286
-
-usubjid <-
+# Limit rows by selecting only these USUBJIDs
+usubjids <-
   c(
     "01-701-1015",
     "01-701-1023",
@@ -70,42 +22,17 @@ usubjid <-
     "01-708-1286"
   )
 
-#  prepare for inner join
-user <- tibble(
-  USUBJID = usubjid
-)
-result <- inner_join(adlb, user)
-admiral_adlb <- result
-admiral_adlb
-
-#
-# Finally, save reduced ds
-#
-use_data(admiral_adlb, overwrite = TRUE)
-
-#
-#  TEST - is dataset identical to .... backup of unaltered dataset
-#
-e1 <- new.env()
-e2 <- new.env()
-load("data/admiral_adlb.rda", e1)
-
-# CHANGE to YOUR location of original dataset
-load("data-backup/admiral_adlb.rda", e2)
-
-# compare field names
-t <- tibble(e1 = names(e1$admiral_adlb), e2 = names(e2$admiral_adlb))
-t |> print(n = 111)
+admiral_adlb <- filter(adlb, USUBJID %in% usubjids)
 
-identical(e1$admiral_adlb, e2$admiral_adlb)
-diffdf(e1$admiral_adlb, e2$admiral_adlb)
+# Get previous dataset for comparison
+adlb_old <- admiral::admiral_adlb
 
-## Capture diffdf to file
+# Finally, save reduced dataset
+usethis::use_data(admiral_adlb, overwrite = TRUE)
 
-capture.output(
-  diffdf(
-    compare = e1$admiral_adlb, base = e2$admiral_adlb,
-    keys = c("STUDYID", "DOMAIN", "USUBJID", "AVAL", "VISIT")
-  ),
-  file = "data-raw/diffdf_adlb_23SEPT"
+# Compare with previous version
+diffdf::diffdf(
+  base = adlb_old,
+  compare = admiral_adlb,
+  keys = c("USUBJID", "PARAMCD", "AVISIT", "ADT")
 )
diff --git a/data-raw/create_admiral_adsl.R b/data-raw/create_admiral_adsl.R
index 2649141e10..a2077f883c 100644
--- a/data-raw/create_admiral_adsl.R
+++ b/data-raw/create_admiral_adsl.R
@@ -1,78 +1,23 @@
 #  Create dataset:   data/admiral_adsl.rda
-#  This script:  create_admiral_adsl.R creates dataset data/admiral_adsl.rda.
+#  This script, create_admiral_adsl.R, creates dataset data/admiral_adsl.rda.
 #
 
-# Preliminary
-library(diffdf) # nolint
+# Create dataset data/admiral_adsl.rda
 
+# Run template script to create adsl
+source("inst/templates/ad_adsl.R", echo = TRUE) # nolint
 
-# nolint start: object_name_linter.
-# To clarify directories (can be removed)
-CACHE_DIR <- "~/.cache/R/admiral_templates_data/"
-DATA_DIR <- "data-dir"
-DATA_RAW <- "data-raw"
-TEMPLATE_DIR <- "inst/templates/"
+admiral_adsl <- adsl # use correct name
 
-# clean CACHE_DIR
-THE_FILE <- paste0(CACHE_DIR, "/adlb.rda")
-THE_FILE <- paste0(CACHE_DIR, "/adsl.rda")
-if (file.exists(THE_FILE)) file.remove(THE_FILE)
-# nolint end
-
-#
-# STEPS
-#
-# First, use template to create the R script (in data-raw/admiral_adlb.R).
-# Next, source this script and create the data (~/.cache/R/admiral_template_data/admiral_adlb.rda)
-# Finally, shorten this data (now ~ 1.2 MB) by selecting only certain USUBJID
-
-# OMIT -- orignal method  - OMIT
-if (FALSE) {
-  # ### original mehtod (method 1)
-  # # First,  create the R script (from a template)
-  adam_name <- "adlb"
-  save_path <- paste0("./data-raw/admiral_", adam_name, ".R")
-  use_ad_template(
-    adam_name = adam_name,
-    save_path = save_path,
-    open = FALSE,
-    overwrite = TRUE
-  )
-  # Second, source the script and save data in .cache
-  source("data-raw/admiral_adlb.R") # nolint
-  load("~/.cache/R/admiral_templates_data/adlb.rda")
-}
-
-#
-#
-# Instead, USE template, as recommened by Buzz
-#
-source(paste0(TEMPLATE_DIR, "/ad_adsl.R")) # nolint
-load(paste0(CACHE_DIR, "adsl.rda"))
-admiral_adsl <- adsl
-
-#
-# Finally, save reduced ds
-#
-use_data(admiral_adsl, overwrite = TRUE)
-
-#
-#  TEST - is dataset identical to .... backup of unaltered dataset
-#
-e1 <- new.env()
-e2 <- new.env()
-load("data/admiral_adsl.rda", e1)
-
-# CHANGE to YOUR location of original dataset
-load("data-backup/admiral_adsl.rda", e2)
+# Get previous dataset for comparison
+adsl_old <- admiral::admiral_adsl
 
+# Finally, save reduced dataset
+usethis::use_data(admiral_adsl, overwrite = TRUE)
 
-identical(e1$admiral_adsl, e2$admiral_adsl)
-diffdf(compare = e1$admiral_adsl, base = e2$admiral_adsl, keys = c("STUDYID", "USUBJID"))
-capture.output(
-  diffdf(
-    compare = e1$admiral_adsl, base = e2$admiral_adsl,
-    keys = c("STUDYID", "USUBJID")
-  ),
-  file = "data-raw/diffdf_23SEPT"
+# Compare with previous version
+diffdf::diffdf(
+  base = adsl_old,
+  compare = admiral_adsl,
+  keys = c("STUDYID", "USUBJID")
 )
diff --git a/data-raw/derive_single_dose.R b/data-raw/create_ex_single.R
similarity index 100%
rename from data-raw/derive_single_dose.R
rename to data-raw/create_ex_single.R
diff --git a/data-raw/example_qs.R b/data-raw/create_example_qs.R
similarity index 100%
rename from data-raw/example_qs.R
rename to data-raw/create_example_qs.R
diff --git a/data-raw/example_query_source.R b/data-raw/create_queries_and_queries_mh.R
similarity index 93%
rename from data-raw/example_query_source.R
rename to data-raw/create_queries_and_queries_mh.R
index b598fe62af..e63259ff2b 100644
--- a/data-raw/example_query_source.R
+++ b/data-raw/create_queries_and_queries_mh.R
@@ -54,13 +54,20 @@ adae <- tibble::tribble(
   "APPLICATION SITE ERYTHEMA", "Application site erythema", 1
 )
 
+#  create queries.rda in data/
+usethis::use_data(queries, overwrite = TRUE)
+
 # try below:
 derive_vars_query(adae, queries)
 
-
 # example to use for ADMH:
 queries_mh <- queries %>%
   filter(SRCVAR %in% c("AELLT", "AEDECOD")) %>%
   mutate(SRCVAR = ifelse(SRCVAR == "AELLT", "MHLLT", "MHDECOD"))
 
+usethis::use_data(queries_mh, overwrite = TRUE)
+
+source("inst/templates/ad_admh.R", echo = TRUE) # nolint
+
+# Currently producing an error
 derive_vars_query(admh, queries_mh)
diff --git a/data/admiral_adlb.rda b/data/admiral_adlb.rda
index 485940b76b..40a6cecbdb 100644
Binary files a/data/admiral_adlb.rda and b/data/admiral_adlb.rda differ
diff --git a/data/queries.rda b/data/queries.rda
index 60234d13e3..cb7fbfb63d 100644
Binary files a/data/queries.rda and b/data/queries.rda differ
diff --git a/data/queries_mh.rda b/data/queries_mh.rda
index d186f5793d..09a3f843dd 100644
Binary files a/data/queries_mh.rda and b/data/queries_mh.rda differ