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openFDA connector

Set up the openFDA connector in Kaivo: authentication, configuration, the 9 BigQuery tables it syncs, and answers to common questions.

Written By Lauri Raivio

Last updated 16 days ago

Kaivo is a fully managed data platform that syncs your openFDA data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your data from openFDA instead of moving it.

What is the openFDA connector

Sync your OpenFDA adverse events, recalls, and drug data into BigQuery with Kaivo to analyse safety reports and enforcement across FDA datasets.

CategoryOther
AuthenticationOther
SetupSelf-service

Getting started with the openFDA connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your openFDA account.
  3. Choose which tables to sync.
  4. Wait for the initial sync to finish.
  5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating openFDA

Follow the steps below to connect your openFDA account.

Tables and columns synced from openFDA

Kaivo syncs 9 tables from openFDA into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
animal__age__maxSTRING
animal__age__minSTRING
animal__age__qualifierSTRING
animal__age__unitSTRING
animal__breed__breed_componentJSON
animal__breed__is_crossbredSTRING
animal__female_animal_physiological_statusSTRING
animal__genderSTRING
animal__reproductive_statusSTRING
animal__speciesSTRING
animal__weight__maxSTRING
animal__weight__minSTRING
animal__weight__qualifierSTRING
animal__weight__unitSTRING
duration__unitSTRING
duration__valueSTRING
health_assessment_prior_to_exposure__assessed_bySTRING
health_assessment_prior_to_exposure__conditionSTRING
number_of_animals_affectedSTRING
number_of_animals_treatedSTRING
onset_dateSTRING
original_receive_dateSTRING
primary_reporterSTRING
receiver__citySTRING
receiver__countrySTRING
receiver__organizationSTRING
receiver__postal_codeSTRING
receiver__stateSTRING
receiver__street_addressSTRING
report_idSTRING
secondary_reporterSTRING
serious_aeSTRING
time_between_exposure_and_onsetSTRING
treated_for_aeSTRING
type_of_informationSTRING
unique_aer_id_numberSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • animal_veterinary_adverse_events__drug (30 columns)
  • animal_veterinary_adverse_events__drug__active_ingredients (8 columns)
  • animal_veterinary_adverse_events__outcome (5 columns)
  • animal_veterinary_adverse_events__reaction (8 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
companynumbSTRING
duplicateSTRING
fulfillexpeditecriteriaSTRING
occurcountrySTRING
patient__patientagegroupSTRING
patient__patientonsetageSTRING
patient__patientonsetageunitSTRING
patient__patientsexSTRING
patient__patientweightSTRING
patient__summary__narrativeincludeclinicalSTRING
primarysource__literaturereferenceSTRING
primarysource__qualificationSTRING
primarysource__reportercountrySTRING
primarysourcecountrySTRING
receiptdateSTRING
receiptdateformatSTRING
receivedateSTRING
receivedateformatSTRING
receiver__receiverorganizationSTRING
receiver__receivertypeSTRING
reportduplicate__duplicatenumbSTRING
reportduplicate__duplicatesourceSTRING
reporttypeSTRING
safetyreportidSTRING
safetyreportversionSTRING
sender__senderorganizationSTRING
sender__sendertypeSTRING
seriousSTRING
seriousnesscongenitalanomaliSTRING
seriousnessdeathSTRING
seriousnessdisablingSTRING
seriousnesshospitalizationSTRING
seriousnesslifethreateningSTRING
seriousnessotherSTRING
transmissiondateSTRING
transmissiondateformatSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • drug_adverse_events__patient__drug (26 columns)
  • drug_adverse_events__patient__drug__openfda__application_number (4 columns)
  • drug_adverse_events__patient__drug__openfda__brand_name (4 columns)
  • drug_adverse_events__patient__drug__openfda__generic_name (4 columns)
  • drug_adverse_events__patient__drug__openfda__manufacturer_name (4 columns)
  • drug_adverse_events__patient__drug__openfda__nui (4 columns)
  • drug_adverse_events__patient__drug__openfda__package_ndc (4 columns)
  • drug_adverse_events__patient__drug__openfda__pharm_class_cs (4 columns)
  • drug_adverse_events__patient__drug__openfda__pharm_class_epc (4 columns)
  • drug_adverse_events__patient__drug__openfda__pharm_class_moa (4 columns)
  • drug_adverse_events__patient__drug__openfda__pharm_class_pe (4 columns)
  • drug_adverse_events__patient__drug__openfda__product_ndc (4 columns)
  • drug_adverse_events__patient__drug__openfda__product_type (4 columns)
  • drug_adverse_events__patient__drug__openfda__route (4 columns)
  • drug_adverse_events__patient__drug__openfda__rxcui (4 columns)
  • drug_adverse_events__patient__drug__openfda__spl_id (4 columns)
  • drug_adverse_events__patient__drug__openfda__spl_set_id (4 columns)
  • drug_adverse_events__patient__drug__openfda__substance_name (4 columns)
  • drug_adverse_events__patient__drug__openfda__unii (4 columns)
  • drug_adverse_events__patient__reaction (6 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
application_numberSTRING
brand_nameSTRING
brand_name_baseSTRING
brand_name_suffixSTRING
dea_scheduleSTRING
dosage_formSTRING
finishedBOOL
generic_nameSTRING
labeler_nameSTRING
listing_expiration_dateSTRING
marketing_categorySTRING
marketing_end_dateSTRING
marketing_start_dateSTRING
product_idSTRING
product_ndcSTRING
product_typeSTRING
spl_idSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • drug_ndc_library__active_ingredients (5 columns)
  • drug_ndc_library__openfda__is_original_packager (4 columns)
  • drug_ndc_library__openfda__manufacturer_name (4 columns)
  • drug_ndc_library__openfda__nui (4 columns)
  • drug_ndc_library__openfda__pharm_class_cs (4 columns)
  • drug_ndc_library__openfda__pharm_class_epc (4 columns)
  • drug_ndc_library__openfda__pharm_class_moa (4 columns)
  • drug_ndc_library__openfda__pharm_class_pe (4 columns)
  • drug_ndc_library__openfda__rxcui (4 columns)
  • drug_ndc_library__openfda__spl_set_id (4 columns)
  • drug_ndc_library__openfda__unii (4 columns)
  • drug_ndc_library__openfda__upc (4 columns)
  • drug_ndc_library__packaging (8 columns)
  • drug_ndc_library__pharm_class (4 columns)
  • drug_ndc_library__route (4 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
versionSTRING
effective_timeSTRING
idSTRING
set_idSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • drug_product_labelling__description (4 columns)
  • drug_product_labelling__abuse (4 columns)
  • drug_product_labelling__active_ingredient (4 columns)
  • drug_product_labelling__active_ingredient_table (4 columns)
  • drug_product_labelling__adverse_reactions (4 columns)
  • drug_product_labelling__adverse_reactions_table (4 columns)
  • drug_product_labelling__animal_pharmacology_and_or_toxicology (4 columns)
  • drug_product_labelling__animal_pharmacology_and_or_toxicology_table (4 columns)
  • drug_product_labelling__ask_doctor (4 columns)
  • drug_product_labelling__ask_doctor_or_pharmacist (4 columns)
  • drug_product_labelling__boxed_warning (4 columns)
  • drug_product_labelling__carcinogenesis_and_mutagenesis_and_impairment_of_fertility (4 columns)
  • drug_product_labelling__clinical_pharmacology (4 columns)
  • drug_product_labelling__clinical_pharmacology_table (4 columns)
  • drug_product_labelling__clinical_studies (4 columns)
  • drug_product_labelling__clinical_studies_table (4 columns)
  • drug_product_labelling__contraindications (4 columns)
  • drug_product_labelling__controlled_substance (4 columns)
  • drug_product_labelling__dependence (4 columns)
  • drug_product_labelling__description_table (4 columns)
  • drug_product_labelling__do_not_use (4 columns)
  • drug_product_labelling__dosage_and_administration (4 columns)
  • drug_product_labelling__dosage_and_administration_table (4 columns)
  • drug_product_labelling__dosage_forms_and_strengths (4 columns)
  • drug_product_labelling__dosage_forms_and_strengths_table (4 columns)
  • drug_product_labelling__drug_abuse_and_dependence (4 columns)
  • drug_product_labelling__drug_abuse_and_dependence_table (4 columns)
  • drug_product_labelling__drug_and_or_laboratory_test_interactions (4 columns)
  • drug_product_labelling__drug_interactions (4 columns)
  • drug_product_labelling__drug_interactions_table (4 columns)
  • drug_product_labelling__general_precautions (4 columns)
  • drug_product_labelling__geriatric_use (4 columns)
  • drug_product_labelling__geriatric_use_table (4 columns)
  • drug_product_labelling__how_supplied (4 columns)
  • drug_product_labelling__how_supplied_table (4 columns)
  • drug_product_labelling__inactive_ingredient (4 columns)
  • drug_product_labelling__inactive_ingredient_table (4 columns)
  • drug_product_labelling__indications_and_usage (4 columns)
  • drug_product_labelling__indications_and_usage_table (4 columns)
  • drug_product_labelling__information_for_patients (4 columns)
  • drug_product_labelling__information_for_patients_table (4 columns)
  • drug_product_labelling__instructions_for_use (4 columns)
  • drug_product_labelling__instructions_for_use_table (4 columns)
  • drug_product_labelling__keep_out_of_reach_of_children (4 columns)
  • drug_product_labelling__labor_and_delivery (4 columns)
  • drug_product_labelling__laboratory_tests (4 columns)
  • drug_product_labelling__mechanism_of_action (4 columns)
  • drug_product_labelling__microbiology (4 columns)
  • drug_product_labelling__microbiology_table (4 columns)
  • drug_product_labelling__nonclinical_toxicology (4 columns)
  • drug_product_labelling__nonteratogenic_effects (4 columns)
  • drug_product_labelling__nursing_mothers (4 columns)
  • drug_product_labelling__openfda__application_number (4 columns)
  • drug_product_labelling__openfda__brand_name (4 columns)
  • drug_product_labelling__openfda__generic_name (4 columns)
  • drug_product_labelling__openfda__is_original_packager (4 columns)
  • drug_product_labelling__openfda__manufacturer_name (4 columns)
  • drug_product_labelling__openfda__nui (4 columns)
  • drug_product_labelling__openfda__original_packager_product_ndc (4 columns)
  • drug_product_labelling__openfda__package_ndc (4 columns)
  • drug_product_labelling__openfda__pharm_class_cs (4 columns)
  • drug_product_labelling__openfda__pharm_class_epc (4 columns)
  • drug_product_labelling__openfda__pharm_class_moa (4 columns)
  • drug_product_labelling__openfda__pharm_class_pe (4 columns)
  • drug_product_labelling__openfda__product_ndc (4 columns)
  • drug_product_labelling__openfda__product_type (4 columns)
  • drug_product_labelling__openfda__route (4 columns)
  • drug_product_labelling__openfda__rxcui (4 columns)
  • drug_product_labelling__openfda__spl_id (4 columns)
  • drug_product_labelling__openfda__spl_set_id (4 columns)
  • drug_product_labelling__openfda__substance_name (4 columns)
  • drug_product_labelling__openfda__unii (4 columns)
  • drug_product_labelling__openfda__upc (4 columns)
  • drug_product_labelling__other_safety_information (4 columns)
  • drug_product_labelling__overdosage (4 columns)
  • drug_product_labelling__package_label_principal_display_panel (4 columns)
  • drug_product_labelling__patient_medication_information (4 columns)
  • drug_product_labelling__pediatric_use (4 columns)
  • drug_product_labelling__pediatric_use_table (4 columns)
  • drug_product_labelling__pharmacodynamics (4 columns)
  • drug_product_labelling__pharmacodynamics_table (4 columns)
  • drug_product_labelling__pharmacogenomics (4 columns)
  • drug_product_labelling__pharmacokinetics (4 columns)
  • drug_product_labelling__pharmacokinetics_table (4 columns)
  • drug_product_labelling__precautions (4 columns)
  • drug_product_labelling__precautions_table (4 columns)
  • drug_product_labelling__pregnancy (4 columns)
  • drug_product_labelling__pregnancy_or_breast_feeding (4 columns)
  • drug_product_labelling__purpose (4 columns)
  • drug_product_labelling__purpose_table (4 columns)
  • drug_product_labelling__questions (4 columns)
  • drug_product_labelling__recent_major_changes (4 columns)
  • drug_product_labelling__recent_major_changes_table (4 columns)
  • drug_product_labelling__references (4 columns)
  • drug_product_labelling__references_table (4 columns)
  • drug_product_labelling__risks (4 columns)
  • drug_product_labelling__route (4 columns)
  • drug_product_labelling__safe_handling_warning (4 columns)
  • drug_product_labelling__spl_medguide (4 columns)
  • drug_product_labelling__spl_medguide_table (4 columns)
  • drug_product_labelling__spl_patient_package_insert (4 columns)
  • drug_product_labelling__spl_patient_package_insert_table (4 columns)
  • drug_product_labelling__spl_product_data_elements (4 columns)
  • drug_product_labelling__spl_unclassified_section (4 columns)
  • drug_product_labelling__spl_unclassified_section_table (4 columns)
  • drug_product_labelling__statement_of_identity (4 columns)
  • drug_product_labelling__stop_use (4 columns)
  • drug_product_labelling__storage_and_handling (4 columns)
  • drug_product_labelling__teratogenic_effects (4 columns)
  • drug_product_labelling__use_in_specific_populations (4 columns)
  • drug_product_labelling__use_in_specific_populations_table (4 columns)
  • drug_product_labelling__user_safety_warnings (4 columns)
  • drug_product_labelling__warnings (4 columns)
  • drug_product_labelling__warnings_and_cautions (4 columns)
  • drug_product_labelling__warnings_and_cautions_table (4 columns)
  • drug_product_labelling__warnings_table (4 columns)
  • drug_product_labelling__when_using (4 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
address_1STRING
address_2STRING
center_classification_dateSTRING
citySTRING
classificationSTRING
code_infoSTRING
countrySTRING
distribution_patternSTRING
event_idSTRING
initial_firm_notificationSTRING
more_code_infoSTRING
postal_codeSTRING
product_descriptionSTRING
product_quantitySTRING
product_typeSTRING
reason_for_recallSTRING
recall_initiation_dateSTRING
recall_numberSTRING
recalling_firmSTRING
report_dateSTRING
stateSTRING
statusSTRING
termination_dateSTRING
voluntary_mandatedSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • drug_recall_enforcement_reports__openfda__application_number (4 columns)
  • drug_recall_enforcement_reports__openfda__brand_name (4 columns)
  • drug_recall_enforcement_reports__openfda__generic_name (4 columns)
  • drug_recall_enforcement_reports__openfda__is_original_packager (4 columns)
  • drug_recall_enforcement_reports__openfda__manufacturer_name (4 columns)
  • drug_recall_enforcement_reports__openfda__nui (4 columns)
  • drug_recall_enforcement_reports__openfda__original_packager_product_ndc (4 columns)
  • drug_recall_enforcement_reports__openfda__package_ndc (4 columns)
  • drug_recall_enforcement_reports__openfda__pharm_class_cs (4 columns)
  • drug_recall_enforcement_reports__openfda__pharm_class_epc (4 columns)
  • drug_recall_enforcement_reports__openfda__pharm_class_moa (4 columns)
  • drug_recall_enforcement_reports__openfda__pharm_class_pe (4 columns)
  • drug_recall_enforcement_reports__openfda__product_ndc (4 columns)
  • drug_recall_enforcement_reports__openfda__product_type (4 columns)
  • drug_recall_enforcement_reports__openfda__route (4 columns)
  • drug_recall_enforcement_reports__openfda__rxcui (4 columns)
  • drug_recall_enforcement_reports__openfda__spl_id (4 columns)
  • drug_recall_enforcement_reports__openfda__spl_set_id (4 columns)
  • drug_recall_enforcement_reports__openfda__substance_name (4 columns)
  • drug_recall_enforcement_reports__openfda__unii (4 columns)
  • drug_recall_enforcement_reports__openfda__upc (4 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
application_numberSTRING
sponsor_nameSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • drugs__openfda__application_number (4 columns)
  • drugs__openfda__brand_name (4 columns)
  • drugs__openfda__generic_name (4 columns)
  • drugs__openfda__manufacturer_name (4 columns)
  • drugs__openfda__nui (4 columns)
  • drugs__openfda__package_ndc (4 columns)
  • drugs__openfda__pharm_class_cs (4 columns)
  • drugs__openfda__pharm_class_epc (4 columns)
  • drugs__openfda__pharm_class_moa (4 columns)
  • drugs__openfda__pharm_class_pe (4 columns)
  • drugs__openfda__product_ndc (4 columns)
  • drugs__openfda__product_type (4 columns)
  • drugs__openfda__route (4 columns)
  • drugs__openfda__rxcui (4 columns)
  • drugs__openfda__spl_id (4 columns)
  • drugs__openfda__spl_set_id (4 columns)
  • drugs__openfda__substance_name (4 columns)
  • drugs__openfda__unii (4 columns)
  • drugs__products (11 columns)
  • drugs__products__active_ingredients (5 columns)
  • drugs__submissions (11 columns)
  • drugs__submissions__application_docs (8 columns)
  • drugs__submissions__submission_property_type (4 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
consumer__ageSTRING
consumer__age_unitSTRING
consumer__genderSTRING
date_createdSTRING
date_startedSTRING
report_numberSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • food_adverse_events__outcomes (4 columns)
  • food_adverse_events__products (7 columns)
  • food_adverse_events__reactions (4 columns)
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
address_1STRING
address_2STRING
center_classification_dateSTRING
citySTRING
classificationSTRING
code_infoSTRING
countrySTRING
distribution_patternSTRING
event_idSTRING
initial_firm_notificationSTRING
more_code_infoSTRING
postal_codeSTRING
product_descriptionSTRING
product_quantitySTRING
product_typeSTRING
reason_for_recallSTRING
recall_initiation_dateSTRING
recall_numberSTRING
recalling_firmSTRING
report_dateSTRING
stateSTRING
statusSTRING
termination_dateSTRING
voluntary_mandatedSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
date_submittedSTRING
nonuser_affectedSTRING
number_health_problemsFLOAT64
number_product_problemsFLOAT64
number_tobacco_productsFLOAT64
report_idFLOAT64
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Nested subtables

Repeating fields are split into their own tables, listed here with their column counts.

  • tobacco_problems_reports__reported_health_problems (4 columns)
  • tobacco_problems_reports__reported_product_problems (4 columns)
  • tobacco_problems_reports__tobacco_products (4 columns)

How the openFDA sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where openFDA supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.

Frequently asked questions

How long does the initial sync take for openFDA?

It depends on how much history is in your openFDA account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.

Can I sync only some tables or columns?

Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.

What happens when openFDA's schema changes?

New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in openFDA, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.

How do I handle GDPR or data deletion requests?

Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in openFDA instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the openFDA connector in Kaivo and all of its synced data is deleted with it.

Common use cases for openFDA data

Adverse event analysis

Use drug_adverse_events and food_adverse_events to study reactions and outcomes over time.

Recall tracking

Report on food_enforcement_reports and drug_recall_enforcement_reports by classification and date.

Drug reference

Use drug_ndc_library and drugs to enrich your data with product and sponsor detail.

Safety monitoring

Combine adverse events with product data to monitor safety signals.

Use openFDA data in your AI and BI tools

Once openFDA data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with openFDA data.

Claude

Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →

Power BI

Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →

Data Studio

Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →

Tableau

The premium analytics standard, with native BigQuery integration. Setup guide →

Google Sheets

Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →

Excel

Connect via Power Query's BigQuery connector. Setup guide →

Metabase

Open-source BI tool with strong BigQuery support. Setup guide →

See our pricing page for openFDA connector pricing and plan details.

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