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Query the WHO ATC/DDD Classification System. Use whenever the user asks about ATC codes, drug classification hierarchy, Defined Daily Doses (DDD), or wants to look up drugs by ATC class or find the ATC code for a drug name.
Codex 또는 Claude로 설치 이 Prompt를 복사해 Codex, Claude 또는 다른 어시스턴트에 붙여 넣으면 Skill 페이지를 검토하고 설치를 진행할 수 있습니다.
SOC 직업 분류 기준
Query the DrugComb drug combination database for cancer cell-line synergy and sensitivity data. Use whenever the user asks about drug combinations, synergy scores (ZIP/Bliss/Loewe/HSA), combination sensitivity (CSS), or wants to look up how two drugs interact in a specific cancer cell line.
Query canonical DrugCombDB combination records. Use when the user asks about drug pairs, synergy values, or cell-line-specific combination evidence.
Query or inspect the FDA Orange Book - FDA-Approved Drug Products Listing resource for drug-centric tasks with emphasis on drug knowledgebase Use whenever Codex needs the calling pattern, downloadable entrypoint, or example query flow from this skill example script.
Query the RepurposeDrugs single-agent drug repurposing database. Use whenever the user asks about drug-disease repurposing associations, clinical trial phases for repurposed drugs, or wants to look up any entity (drug name, disease name, NCT ID) in RepurposeDrugs.
Query the Gene-Drug Knowledge Database (GDKD) for variant-specific gene–drug associations in oncology. Use when the user asks about cancer genomic biomarkers, drug sensitivity/resistance by gene or variant, targetable mutations, or clinical evidence for cancer therapeutics.
Query canonical TarKG drug-target triplets. Use when the user asks about drug-target interactions, relation labels, disease/pathway context, or quick lookups for drugs/targets in TarKG.
| name | 27_ATC_DDD |
| description | Query the WHO ATC/DDD Classification System. Use whenever the user asks about ATC codes, drug classification hierarchy, Defined Daily Doses (DDD), or wants to look up drugs by ATC class or find the ATC code for a drug name. |
Look up ATC classification and DDD data for drugs. Auto-detects entity type:
| Input Pattern | Detected As | Query Path |
|---|---|---|
N02BA A10BA02 C09XX01 | ATC code | local DDD lookup + RxNav member drugs |
aspirin metformin | drug name | RxNav ATC classification + local DDD match |
ATC code regex: ^[A-Z]\d{2}([A-Z]{1,2}\d{0,2})?$
| Function | Input | Returns |
|---|---|---|
load_local(path) | Excel path | list[dict] — cached ATC/DDD records |
search(entity) | single string | dict with entity, entity_type, local_hits, api_hits |
search_batch(entities) | list of strings | dict[str, dict] — keyed by entity |
summarize(result) | search result dict | compact LLM-readable text |
to_json(result) | search result dict | JSON string |
All functions accept use_api=True|False to toggle RxNav queries (default: on).
See if __name__ == "__main__" block in 27_ATC_DDD.py for runnable examples:
from importlib import import_module
atc = import_module("27_ATC_DDD")
# Drug name → ATC classes
r = atc.search("aspirin")
print(atc.summarize(r))
# ATC code → member drugs + DDD
r = atc.search("N02BA")
print(atc.summarize(r))
# Batch
results = atc.search_batch(["metformin", "A10BA02", "C09XX01"])
# JSON for pipeline
print(atc.to_json(atc.search("sparsentan")))
ATC_DDD_new and alterations 2026_final.xlsxatc_code, atc_level_name, new_ddd, unit, adm_route, noteDATA_DIR / XLSX_PATH in 27_ATC_DDD.pyrxnav.nlm.nih.gov/REST/rxclass/)