fda-database
openFDA Drug and Adverse Event Database
Overview
openFDA provides public access to FDA regulatory data through a simple REST API. Key datasets include the FDA Adverse Event Reporting System (FAERS) with 20M+ adverse event reports, drug product labeling (NDC, SPL), drug approvals (Drugs@FDA), medical device reports, and recall enforcement actions. The API supports full-text search and structured queries using Elasticsearch-style syntax.
When to Use
- Retrieving adverse event reports for a drug to assess safety signals and side effect profiles
- Querying FAERS for disproportionality analysis (comparing drug vs. drug adverse event profiles)
- Looking up official drug labeling (indications, contraindications, warnings, dosing) by drug name or NDC
- Searching for drug recalls and enforcement actions by drug name or company
- Identifying all marketed products containing a given active ingredient
- Building pharmacovigilance pipelines that monitor drug safety signals from public regulatory data
- For clinical trial efficacy data use
clinicaltrials-database-search; for drug structures/targets usedrugbank-database-access
Prerequisites
More from jaechang-hits/sciagent-skills
scientific-brainstorming
Structured ideation methods: SCAMPER, Six Thinking Hats, Morphological Analysis, TRIZ, Biomimicry, plus more. Decision framework for picking methods by challenge type (stuck, improving, systematic exploration, contradiction). Use when generating research ideas or exploring interdisciplinary connections.
12gene-database
Query NCBI Gene via E-utilities for curated gene records across 1M+ taxa. Retrieve official gene symbols, aliases, RefSeq accessions, summary descriptions, genomic coordinates, GO annotations, and interaction data. Use for gene ID resolution, cross-species queries, and gene function summaries. For sequence retrieval use Ensembl; for expression data use geo-database.
11snakemake-workflow-engine
Python-based workflow management system for reproducible, scalable pipelines. Define rules with file-based dependencies; Snakemake automatically determines the execution order and parallelism. Supports local, SLURM, LSF, AWS, and Google Cloud execution via profiles; per-rule conda/Singularity environments. Use for bioinformatics NGS pipelines, ML training workflows, and any multi-step file-processing analysis. Use Nextflow instead for Groovy-based dataflow pipelines or when nf-core ecosystem integration is required.
11esm-protein-language-model
Protein language models (ESM3, ESM C) for sequence generation, structure prediction, inverse folding, and protein embeddings. Use when designing novel proteins, extracting sequence representations for downstream ML, or predicting structure from sequence. Local GPU or EvolutionaryScale Forge cloud API. For traditional structure prediction use AlphaFold; for small-molecule cheminformatics use RDKit.
11biopython-sequence-analysis
Biopython sequence analysis: parse FASTA/FASTQ/GenBank/GFF (SeqIO), NCBI Entrez (esearch/efetch/elink), remote/local BLAST, pairwise/MSA alignment (PairwiseAligner, MUSCLE/ClustalW), phylogenetic trees (Phylo). Use for gene family studies, phylogenomics, comparative genomics, NCBI pipelines. For PCR/restriction/cloning use biopython-molecular-biology; for SAM/BAM use pysam.
11shap-model-explainability
>-
11