nSIDES Query Skill

Search drug adverse reactions across three complementary nSIDES sources by drug name.

Source	Content	Method	Scale
OnSIDES v3.1.0	Label-extracted ADEs (US/EU/UK/JP)	PubMedBERT NLP on product labels	1,955 ingredients, 5.5M drug-ADE pairs
OffSIDES	Off-label side effects	Propensity-score matching on FAERS	3,300+ drugs
KidSIDES	Pediatric safety signals by developmental phase	Disproportionality analysis on FAERS	Age-stratified ADE signals

Entity Detection

Input	Routing
any free text	substring match on drug / ingredient name across all three sources

No ID-based routing — all queries are natural-language drug names.

API

Function	Input	Returns
search(entity, limit)	drug name string	dict with keys: entity, onsides, offsides, kidsides
search_batch(entities, limit)	list of drug names	list[dict]
search_onsides(drug_name, limit)	drug name	list[dict] — ingredient, effect, meddra_id, source, label_count
search_offsides(drug_name, limit)	drug name	list[dict] — drug, condition, PRR, A/B/C/D
search_kidsides(drug_name, limit)	drug name	list[dict] — drug, event, nichd_phase, gam_score, ror
summarize(result)	single search() output	compact text
to_json(result)	single search() output	JSON string

Output Fields

OnSIDES row

• ingredient — RxNorm ingredient name
• effect — MedDRA adverse effect term
• meddra_id — MedDRA concept ID
• source — label origin country (US / EU / UK / JP)
• label_count — number of labels reporting this ADE

OffSIDES row

• drug — RxNorm drug name
• condition — MedDRA side effect name
• PRR — proportional reporting ratio (>1 = signal)
• A/B/C/D — 2×2 contingency counts
• mean_reporting_frequency — proportion of drug reports with this effect

KidSIDES row

• drug — drug concept name
• event — adverse event name
• nichd_phase — NICHD developmental phase (e.g. "Neonatal", "Infancy", "Adolescence")
• gam_score — GAM model score
• ror / ror_lower / ror_upper — reporting odds ratio with 95% CI

Usage

See if __name__ == "__main__" block in 15_nSIDES.py for runnable examples: single-drug query, batch query, text summary, and JSON output.

Data

File	Location	Size
onsides.db	DATA_DIR/onsides.db	SQLite, from OnSIDES v3.1.0 release
OFFSIDES.csv.gz	DATA_DIR/OFFSIDES.csv.gz	gzipped CSV
ade_nichd.csv.gz	DATA_DIR/ade_nichd.csv.gz	gzipped CSV (172 MB)
drug.csv.gz	DATA_DIR/drug.csv.gz	KidSIDES drug dictionary
event.csv.gz	DATA_DIR/event.csv.gz	KidSIDES event dictionary
dictionary.csv.gz	DATA_DIR/dictionary.csv.gz	NICHD phase dictionary

DATA_DIR default: resources_metadata/adr/nSIDES

Citations

• OnSIDES: Tanaka Y et al. OnSIDES database: Extracting adverse drug events from drug labels using NLP models. Med. 2025;100642. doi:10.1016/j.medj.2025.100642
• OffSIDES / TwoSIDES: Tatonetti NP et al. Data-driven prediction of drug effects and interactions. Sci Transl Med. 2012;4(125):125ra31. doi:10.1126/scitranslmed.3003377
• KidSIDES: Giangreco NP, Tatonetti NP. A database of pediatric drug effects to evaluate ontogenic mechanisms. Med. 2022.