We extract grant funding records, clinical trial registries, PubMed abstracts, and NCBI genomic datasets from NIH. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Clinical Trials objects from nih.gov. All fields typed and schema-versioned.
"nct_id": "NCT04839210", "brief_title": "Efficacy of Drug X in Asthma", "phase": "Phase 3", "status": "Recruiting", "enrollment": 450, "conditions": "['Asthma', 'Respiratory Disease']", "sponsor": "National Heart, Lung, and Blood Institute (NHLBI)"
| # | nct_id | brief_title | official_title | conditions | interventions | phase |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Grants (RePORTER) objects from nih.gov. All fields typed and schema-versioned.
"project_num": "1R01CA251138-01A1", "project_title": "Targeting metabolic vulnerabilities in cancer", "contact_pi": "SMITH, JOHN", "organization": "University of California, San Francisco", "total_cost": 450000, "agency_ic": "National Cancer Institute"
| # | project_num | project_title | contact_pi | organization | fiscal_year | total_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Publications (PubMed) objects from nih.gov. All fields typed and schema-versioned.
"pmid": "34981023", "title": "Genomic epidemiology of SARS-CoV-2", "journal": "Nature", "publication_date": "2022-01-05", "doi": "10.1038/s41586-021-04215-w", "citation_count": 342, "authors": "['Doe J', 'Smith A']"
| # | pmid | pmcid | title | abstract | authors | journal |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Compounds (PubChem) objects from nih.gov. All fields typed and schema-versioned.
"cid": 2244, "iupac_name": "2-acetoxybenzoic acid", "molecular_formula": "C9H8O4", "molecular_weight": 180.16, "canonical_smiles": "CC(=O)OC1=CC=CC=C1C(=O)O", "synonyms": "['Aspirin', 'Acetylsalicylic acid']"
| # | cid | iupac_name | molecular_formula | molecular_weight | canonical_smiles | isomeric_smiles |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Funding Opportunities objects from nih.gov. All fields typed and schema-versioned.
"opportunity_number": "PA-20-185", "opportunity_title": "NIH Research Project Grant (Parent R01)", "agency_code": "NIH-OD", "open_date": "2020-05-05", "close_date": "2023-05-08", "award_ceiling": 0
| # | opportunity_id | opportunity_title | opportunity_number | agency_code | open_date | close_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our NIH pipelines navigate complex E-utilities rate limits, deeply nested XML schemas, and disconnected data silos to deliver unified research intelligence.
Capture NCT records, trial phases, sponsor details, primary outcomes, and enrollment numbers from ClinicalTrials.gov.
Track award amounts, principal investigators, institutional affiliations, and project abstracts across all fiscal years.
Extract abstracts, metadata, full-text open access articles, and MeSH terms from the world's largest biomedical literature database.
Automated management of API keys, rate limits, and exponential backoff to extract massive datasets reliably.
Extract chemical structures, SMILES strings, molecular weights, and genomic sequence metadata.
Link principal investigators across grants, publications, and clinical trials to build comprehensive expert profiles.
Extract decades of research data via baseline downloads, followed by incremental daily or weekly updates.
Track trial status updates, protocol amendments, and grant funding modifications with hash-based diffing.
Flatten deeply nested NCBI XML responses into structured, queryable tables for your data warehouse.
Standardise date formats, currency values, and MeSH term hierarchies across disparate NIH databases.
Brief in. Clean data out.
Specify the NIH databases, search parameters, or specific record IDs (NCTs, PMIDs). We design the extraction schema together.
We configure E-utilities polling, web crawlers, XML parsers, and rate-limit handling for NIH infrastructure.
Schema validation, cross-referencing PMIDs to RePORTER records, and checking for truncated abstracts before launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
NIH houses massive public datasets, but accessing them at scale requires navigating strict API quotas and complex data structures.
NIH enforces strict rate limits on their E-utilities APIs (3 to 10 requests per second). We manage API key rotation, exponential backoff, and distributed polling to extract massive datasets without triggering IP bans.
Databases like PubMed and ClinicalTrials.gov return highly nested XML. We build deterministic parsers that flatten hierarchical data, like MeSH term trees and nested author affiliations, into queryable relational schemas.
Many NIH search interfaces cap pagination at 10,000 results. Our pipelines automatically slice search parameters by date ranges or sub-categories to ensure 100% coverage of large cohorts.
Connecting a RePORTER grant to its resulting PubMed publications and ClinicalTrials records requires careful identifier matching. We extract and normalise cross-references (PMIDs, NCT IDs) to build unified graphs.
Clinical trials change status frequently. We hash record states and only emit diffs when trial protocols, enrollment numbers, or grant funding amounts are updated, saving downstream processing.
Track competitor clinical trials, pipeline developments, and primary completion dates to inform R&D strategy.
Aggregate millions of PubMed abstracts and MeSH terms to perform systematic reviews and identify literature gaps.
Analyse NIH RePORTER data to spot funding trends, identify top-funded institutions, and forecast emerging research areas.
Link principal investigators to grants, publications, and clinical trials to identify top experts in specific therapeutic areas.
Mine PubChem compounds and GenBank sequences to train machine learning models for drug discovery.
Evaluate biotech startups by auditing their NIH grant history, clinical trial progress, and publication impact factors.
"NIH houses the world's most critical biomedical knowledge, but its fragmented databases and nested XML schemas make large-scale analysis a massive engineering challenge."
Extracting intelligence from NIH requires navigating strict E-utilities rate limits, flattening deeply nested XML trees, and linking identifiers across disparate silos like PubMed, RePORTER, and ClinicalTrials.gov. DataFlirt manages this pipeline complexity so your data science teams can focus on biomedical discovery rather than infrastructure maintenance.
Everything supported by our nih.gov scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Our pipelines integrate directly with NCBI APIs, managing API keys, rate limits, and batch queries to maximise throughput without violating NIH usage policies.
We use high-performance C-based XML parsers (lxml) to process gigabytes of nested PubMed and ClinicalTrials data, transforming hierarchical trees into flat tables.
Pipelines run on AWS ECS with Airflow scheduling. We handle the orchestration of massive historical backfills alongside daily incremental updates with SLA-backed reliability.
Data delivered to where your team already works — no new tooling required.
About nih.gov scraping, legality, and pipeline operations.
Ask us directly →Yes. Data on nih.gov, including PubMed, RePORTER, and ClinicalTrials.gov, is public domain and funded by US taxpayers. We strictly adhere to NCBI's E-utilities usage guidelines and robots.txt to ensure compliant extraction.
We use registered API keys, distributed polling, and exponential backoff algorithms to respect the 3 to 10 requests per second limits while maintaining high overall extraction throughput.
Yes. We extract the funding references from PubMed and cross-reference them with NIH RePORTER project numbers to build a relational map between funding and research outputs.
We extract full-text XML for open-access articles available in the PMC Open Access Subset. Articles behind publisher paywalls are limited to metadata and abstract extraction.
We configure pipelines to match your needs. Clinical trials and new publications can be tracked daily, while grant funding data is typically updated on a weekly or monthly cadence.
Absolutely. We routinely process full baseline downloads of PubMed (millions of records) and ClinicalTrials.gov, followed by daily incremental updates to capture new and modified records.
We extract public metadata from dbGaP. However, controlled-access genomic data requires explicit approval from the NIH Data Access Committee (DAC) and cannot be scraped or bypassed.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a full baseline export of PubMed or a daily feed of ClinicalTrials.gov updates, we build and manage the infrastructure. Tell us your target datasets.
