DailyMed SPL Dataset
Overview
The DailyMed Full SPL Dataset refers to the downloadable full release of all drug labels in the United States. The dataset is hosted by the National Library of Medicine of the National Institute of Health (NIH). There are five subsets of drug labels available as full SPL releases: human prescription labels, human over-the-counter (OTC) labels, homeopathic labels, animal labels, and remaining labels.
Methodology and Generation
Pharmaceutical companies are required to submit a standard product label (SPL) to the Food and Drug Administration (FDA). SPLs are typically encoded in XML format, standardized by the Health Level Seven International (HL7) schema to ensure the labels are organized and machine readable. This includes the tagging of various sections within the label using Logical Observation Identifiers Names and Codes (LOINC®). After submission to the FDA, labels are stored by the National Library of Medicine, which makes all SPLs available for download via DailyMed.
Access and Analysis
Accessing the Full SPL release through DailyMed is completely free and does not require an account. Downloading the largest of the datasets requires at least 16.38GB of space on the user’s device. To download, navigate to the DailyMed website, then click “Download Data” under the header NLM SPL Resources. The page will present the option to download full drug labels, indexing and risk evaluation and mitigation strategy (REMS) files, or mapping files that link an SPL’s set id to other relevant information and metadata. To view the full SPL release with labels, click on the first. The full releases will be at the bottom of this page in five parts.
A more common way of leveraging the dataset is through DailyMed’s API client, RESTful. Querying via the RESTful API requires no account, key, or authentication, and returns data in either XML or JSON format. Related endpoints allow lookups by NDC code (/ndcs), drug name (/drugnames), RxNorm concept (/rxcuis), active ingredient (/uniis), and pharmacologic class (/drugclasses).
Standardized Healthcare Vocabularies
The main way by which sections of an SPL are standardized is through Logical Observation Identifiers Names and Codes (LOINC®) code tagging. This allows for streamlined indexing into areas such as indications and usage, adverse reactions, dosage and administration, and other common sections.
References
AMIA Informatics Summit. (2013 Mar 18.). Extending the “Web of Drug Identity” with Knowledge Extracted from United States Product Labels. Retrieved June 25, 2026.
Resources
Articles
Malec SA, Boyce RD. Exploring Novel Computable Knowledge in Structured Drug Product Labels. AMIA Jt Summits Transl Sci Proc. 2020 May 30;2020:403-412. PMID: 32477661; PMCID: PMC7233092.
Links
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