菜单
Query TAC 2017 ADR annotated drug labels for adverse drug reactions. Use whenever the user asks about ADRs extracted from FDA drug labels, MedDRA-normalized adverse reactions, or wants to look up a drug name, ADR string, or MedDRA code in the TAC 2017 ADR corpus.
用 Codex 或 Claude 帮你安装 复制这段 Prompt，粘贴到 Codex、Claude 或其他助手里，让它检查 Skill 页面并帮你完成安装。
基于 SOC 职业分类
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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.
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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 | tac2017-adr |
| description | Query TAC 2017 ADR annotated drug labels for adverse drug reactions. Use whenever the user asks about ADRs extracted from FDA drug labels, MedDRA-normalized adverse reactions, or wants to look up a drug name, ADR string, or MedDRA code in the TAC 2017 ADR corpus. |
Search 200 FDA drug labels annotated with adverse reactions, severity, and MedDRA normalization from the TAC 2017 shared task.
| Input Pattern | Detected As | Match Logic |
|---|---|---|
10019211 (8 digits) | MedDRA ID | exact on meddra_pt_id or meddra_llt_id |
ACTEMRA (known drug) | Drug name | exact (case-insensitive) on drug label name |
headache (known ADR) | ADR string | exact on ADR reaction string |
| anything else | Free text | substring on drug names, ADR strings, MedDRA PT/LLT names |
| Function | Input | Returns |
|---|---|---|
search(entity) | single entity string | list[dict] — matching label hit(s) |
search_batch(entities) | list of entity strings | dict[str, list[dict]] |
summarize(hits, entity) | hit list + query label | compact LLM-readable text |
to_json(hits) | hit list | list[dict] (JSON-serializable) |
list_drugs() | — | sorted list of all drug names |
stats() | — | dataset-level statistics dict |
Each hit returned by search() contains:
| Field | Type | Description |
|---|---|---|
drug | str | Drug label name |
source_file | str | XML filename |
sections | list[str] | Annotated section names (e.g. "adverse reactions") |
mention_counts | dict | Count per mention type (AdverseReaction, Severity, …) |
num_reactions | int | Total unique reactions in this label |
positive_adrs | list[str] | Positive (non-negated, non-hypothetical) ADR strings |
reactions | list[dict] | Each with adr, meddra_pt, meddra_pt_id, optional meddra_llt, meddra_llt_id, flag |
See if __name__ == "__main__" block in 37_TAC_2017_ADR.py for runnable
examples covering: drug name lookup, ADR string search, MedDRA ID search,
batch search, and JSON output.
from importlib.machinery import SourceFileLoader
tac = SourceFileLoader("tac2017", "/path/to/37_TAC_2017_ADR.py").load_module()
# Single drug
hits = tac.search("ACTEMRA")
print(tac.summarize(hits, "ACTEMRA"))
# ADR across all labels
hits = tac.search("headache")
print(tac.summarize(hits, "headache"))
# MedDRA PT ID
hits = tac.search("10019211")
# Batch
results = tac.search_batch(["ENBREL", "nausea", "10002198"])
gold_xml/ (99 test labels) + train_xml/ (101 training labels), each annotated XMLDATA_DIR variable in 37_TAC_2017_ADR.py