global_trial_search
ChatGPTSearch for global clinical trials from clinicaltrials.gov, ChiCTR, ISRCTN, ANZCTR, and other sources. It searches title, description, conditions, interventions, eligibility, outcomes, etc. Args: query (str): The search term. Uses simple_query_string syntax with AND as default operator. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "start_date". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". study_phase (optional): Filter study phase. Acceptable values: 'Early Phase 1', 'Phase 1', 'Phase 2', 'Phase 3', 'Phase 4', 'Not Applicable'. intervention_type (optional): Filter by intervention type. Acceptable values: 'Behavioral', 'Biological', 'Combination Product', 'Device', 'Diagnostic Test', 'Dietary Supplement', 'Drug', 'Genetic', 'Procedure', 'Radiation', 'Other'. overall_status (optional): Filter by overall status. Acceptable values: 'Not yet recruiting', 'Pending', 'Recruiting', 'Enrolling by invitation', 'Active, not recruiting', 'Suspended', 'Terminated', 'Completed', 'Temporary halt', 'Withdrawn', 'Unknown', 'Available', 'Ongoing', 'Approved for marketing', 'Stopped early'. facility_country (optional): Filter by facility country. Acceptable ISO 2-letter country codes, like 'US', 'GB', 'CA', 'MX', etc. start_date_from (datetime, optional): Filter by start date from. start_date_to (datetime, optional): Filter by start date to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching trials found - trials (list): List of clinical trials, each containing: - id: the unique trial identifier of a clinical trial - official_title - brief_title - overall_status - intervention_type - enrollment_count - trial_phase - interventions - start_date - official_url: the url to clinical trial official page. You can retrieve the webapge and find more details. - facility_country: ISO 2-letter country codes for facilities, like 'US', 'GB', 'CA', 'MX', etc.
global_trial_search
ChatGPTSearch for global clinical trials from clinicaltrials.gov, ChiCTR, ISRCTN, ANZCTR, and other sources. It searches title, description, conditions, interventions, eligibility, outcomes, etc. Args: query (str): The search term. Uses simple_query_string syntax with AND as default operator. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "start_date". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". study_phase (optional): Filter study phase. Acceptable values: 'Early Phase 1', 'Phase 1', 'Phase 2', 'Phase 3', 'Phase 4', 'Not Applicable'. intervention_type (optional): Filter by intervention type. Acceptable values: 'Behavioral', 'Biological', 'Combination Product', 'Device', 'Diagnostic Test', 'Dietary Supplement', 'Drug', 'Genetic', 'Procedure', 'Radiation', 'Other'. overall_status (optional): Filter by overall status. Acceptable values: 'Not yet recruiting', 'Pending', 'Recruiting', 'Enrolling by invitation', 'Active, not recruiting', 'Suspended', 'Terminated', 'Completed', 'Temporary halt', 'Withdrawn', 'Unknown', 'Available', 'Ongoing', 'Approved for marketing', 'Stopped early'. facility_country (optional): Filter by facility country. Acceptable ISO 2-letter country codes, like 'US', 'GB', 'CA', 'MX', etc. start_date_from (datetime, optional): Filter by start date from. start_date_to (datetime, optional): Filter by start date to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching trials found - trials (list): List of clinical trials, each containing: - id: the unique trial identifier of a clinical trial - official_title - brief_title - overall_status - intervention_type - enrollment_count - trial_phase - interventions - start_date - official_url: the url to clinical trial official page. You can retrieve the webapge and find more details. - facility_country: ISO 2-letter country codes for facilities, like 'US', 'GB', 'CA', 'MX', etc.
usfda_company_search
ChatGPTSearch for applicant companies with FDA-approved devices by name. You can get the company id before searching for devices for a specific company. Args: query (str): The search term to match against company names and aliases. Uses simple_query_string syntax with AND as default operator. Try to search parent companies for better results, for example, "siemens" instead of "siemens healthineers". offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 10. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - companies (list): List of company objects, each containing: - id (int): Unique company identifier - name (str): Company name - avg_review_days (int): Average review days for the company - device_cnt (int): Num of approved devices
usfda_company_search
ChatGPTSearch for applicant companies with FDA-approved devices by name. You can get the company id before searching for devices for a specific company. Args: query (str): The search term to match against company names and aliases. Uses simple_query_string syntax with AND as default operator. Try to search parent companies for better results, for example, "siemens" instead of "siemens healthineers". offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 10. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - companies (list): List of company objects, each containing: - id (int): Unique company identifier - name (str): Company name - avg_review_days (int): Average review days for the company - device_cnt (int): Num of approved devices
usfda_device_search
ChatGPTSearch for FDA-approved devices. It supports pagination and returns a list of matching devices along with the total count. Args: query (str): The search term to match against device id, device name, indications, and device classification name. Uses simple_query_string syntax with AND as default operator. When you want to fetch a list of devices from a specific company/product code, you can use the empty string "" as the query and filter by application_company_id/product_code. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "decision_date", "device_name", "fda_review_days". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". device_class (optional): Filter by device class. Acceptable values: "1", "2", "3", 'Unclassified', 'Not classified', 'HDE'. submission_type (optional): Filter by submission type. Acceptable values: "510(K)", "PMA", "HDE", "EUA", "De Novo". application_company_id (int, optional): Filter by application company id. product_code (str, optional): Filter by product code. Devices with the same product code are considered similar. decision_date_from (datetime, optional): Filter by decision date from. decision_date_to (datetime, optional): Filter by decision date to. clinical_trial_flag (bool, optional): Filter by if devices have associated clinical trials. combination_product_flag (bool, optional): Filter by if devices are combination products. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - devices (list): List of device objects, each containing: - id (int): Unique device ID - device_name (str): Name of the device - device_class (str): Device class (e.g., "1", "2", "3", 'Unclassified', 'Not classified', 'HDE') - application_company_id (int): Unique ID for the applicant company - application_company_name (str): Name of the applicant company - date_receive (datetime): Date when the device was received by the FDA - decision_date (datetime): Date when the device was approved by the FDA - submission_type (str): Type of submission (e.g., "510(K)", "PMA", "HDE", "EUA", "De Novo") - medical_specialty_name (Optional[str]): The medical specialty associated with the device - product_code (Optional[str]): Product code assigned to the device. Devices with the same product code are considered similar. - clinical_trial_flag (bool): Indicates if the device has associated clinical trials - combination_product_flag (bool): Indicates if the device is a combination product - summary_pdf_link (list): List of URLs to summary PDF documents for the device. You can read the PDFs to get more detailed information about the device, including bench testing, clinical data, and more. - aggregations (dict): Aggregation results for device class, medical specialty, submission type, product code, decision date by year, and average review days.
usfda_device_search
ChatGPTSearch for FDA-approved devices. It supports pagination and returns a list of matching devices along with the total count. Args: query (str): The search term to match against device id, device name, indications, and device classification name. Uses simple_query_string syntax with AND as default operator. When you want to fetch a list of devices from a specific company/product code, you can use the empty string "" as the query and filter by application_company_id/product_code. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "decision_date", "device_name", "fda_review_days". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". device_class (optional): Filter by device class. Acceptable values: "1", "2", "3", 'Unclassified', 'Not classified', 'HDE'. submission_type (optional): Filter by submission type. Acceptable values: "510(K)", "PMA", "HDE", "EUA", "De Novo". application_company_id (int, optional): Filter by application company id. product_code (str, optional): Filter by product code. Devices with the same product code are considered similar. decision_date_from (datetime, optional): Filter by decision date from. decision_date_to (datetime, optional): Filter by decision date to. clinical_trial_flag (bool, optional): Filter by if devices have associated clinical trials. combination_product_flag (bool, optional): Filter by if devices are combination products. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - devices (list): List of device objects, each containing: - id (int): Unique device ID - device_name (str): Name of the device - device_class (str): Device class (e.g., "1", "2", "3", 'Unclassified', 'Not classified', 'HDE') - application_company_id (int): Unique ID for the applicant company - application_company_name (str): Name of the applicant company - date_receive (datetime): Date when the device was received by the FDA - decision_date (datetime): Date when the device was approved by the FDA - submission_type (str): Type of submission (e.g., "510(K)", "PMA", "HDE", "EUA", "De Novo") - medical_specialty_name (Optional[str]): The medical specialty associated with the device - product_code (Optional[str]): Product code assigned to the device. Devices with the same product code are considered similar. - clinical_trial_flag (bool): Indicates if the device has associated clinical trials - combination_product_flag (bool): Indicates if the device is a combination product - summary_pdf_link (list): List of URLs to summary PDF documents for the device. You can read the PDFs to get more detailed information about the device, including bench testing, clinical data, and more. - aggregations (dict): Aggregation results for device class, medical specialty, submission type, product code, decision date by year, and average review days.
usfda_guidance_search
ChatGPTSearch for FDA latest guidance. It searches guidance title, topic, docket number, and pdf content. Args: query (str): The search term. Uses simple_query_string syntax with AND as default operator. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "issue_date". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". issue_date_from (datetime, optional): Filter by issue date from. issue_date_to (datetime, optional): Filter by issue date to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching guidances found - guidances (list): List of guidances, each containing: - title - docket_number (optional) - issue_date (optional) - fda_url: the url to fda guidance page. You can retrieve the webapge and find more details. - pdf_link (optional): the direct link to the guidance pdf document. You can read the PDF to get more detailed information about the guidance.
usfda_guidance_search
ChatGPTSearch for FDA latest guidance. It searches guidance title, topic, docket number, and pdf content. Args: query (str): The search term. Uses simple_query_string syntax with AND as default operator. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "issue_date". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". issue_date_from (datetime, optional): Filter by issue date from. issue_date_to (datetime, optional): Filter by issue date to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching guidances found - guidances (list): List of guidances, each containing: - title - docket_number (optional) - issue_date (optional) - fda_url: the url to fda guidance page. You can retrieve the webapge and find more details. - pdf_link (optional): the direct link to the guidance pdf document. You can read the PDF to get more detailed information about the guidance.
usfda_maude_search
ChatGPTSearch for medical device adverse events in FDA MAUDE database. Args: query (str): The search term to match against adverse event report. Uses simple_query_string syntax with AND as default operator. When you want to fetch adverse events from a specific deivce/product code, you can use the empty string "" as the query and filter by device_id/product_code. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "date_received". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". product_code (str, optional): Filter by product code. device_id (str, optional): Filter by device id. date_received_from (datetime, optional): Filter by date received from. date_received_to (datetime, optional): Filter by date received to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - maude (list): List of maude objects, each containing: - report_number (str) - report_title (str) - date_received (datetime) - device_id (str, optional): device id associated with the report - device_name (str, optional): device name associated with the report - product_code (list, optional): list of product codes associated with the report - event_type (str) - device_problem (list, optional) - patient_problem (list, optional) - brand_name (list, optional) - generic_name (list, optional) - manufacturer_name (list, optional) - aggregations (dict): Aggregation results for device problem, patient problem, event type, product code, date received by year.
usfda_maude_search
ChatGPTSearch for medical device adverse events in FDA MAUDE database. Args: query (str): The search term to match against adverse event report. Uses simple_query_string syntax with AND as default operator. When you want to fetch adverse events from a specific deivce/product code, you can use the empty string "" as the query and filter by device_id/product_code. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "date_received". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". product_code (str, optional): Filter by product code. device_id (str, optional): Filter by device id. date_received_from (datetime, optional): Filter by date received from. date_received_to (datetime, optional): Filter by date received to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - maude (list): List of maude objects, each containing: - report_number (str) - report_title (str) - date_received (datetime) - device_id (str, optional): device id associated with the report - device_name (str, optional): device name associated with the report - product_code (list, optional): list of product codes associated with the report - event_type (str) - device_problem (list, optional) - patient_problem (list, optional) - brand_name (list, optional) - generic_name (list, optional) - manufacturer_name (list, optional) - aggregations (dict): Aggregation results for device problem, patient problem, event type, product code, date received by year.
usfda_recall_search
ChatGPTSearch for FDA medical device recalls. It supports pagination and returns a list of matching recalls along with the total count. Args: query (str): The search term to match against recall title, recall number, reason for recall, product description, action, recalling firm, and application_company_name. Uses simple_query_string syntax with AND as default operator. When you want to fetch a list of recalls from a specific company/product code/device, you can use the empty string "" as the query and filter by application_company_id/product_code/device_id. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "date_initiated". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". recall_status (optional): Filter by recall status. Acceptable values: "Completed", "Open, Classified", "Terminated" application_company_id (int, optional): Filter by application company id. product_code: (str, optional): Filter by product code. Devices with the same product code are considered similar. device_id (str, optional): Filter by device id. recall_class (optional): Filter by recall class. Acceptable values: "1", "2", "3". date_initiated_from (datetime, optional): Filter by date initiated from. date_initiated_to (datetime, optional): Filter by date initiated to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - recalls (list): List of recall objects, each containing: - recall_title (str): Title of the recall - recall_number (str): Unique recall number - recall_class (int): Class of the recall (1, 2, or 3) - date_initiated (datetime): Date when the recall was initiated - date_posted (datetime, optional): Date when the recall was posted - date_created (datetime, optional): Date when the recall was created - date_terminated (datetime, optional): Date when the recall was terminated - recall_status (str): Status of the recall - reason_for_recall (str, optional): Reason for the recall - root_cause_description (str): Root cause of the recall - recalling_firm (str): Name of the recalling firm - product_code (List[str], optional): List of 3-letter FDA product codes associated with the recall. Devices with the same product code are considered similar. - device_id (List[str], optional): List of device IDs associated with the recall - application_company_id (List[int], optional): List of application company IDs associated with the recall - application_company_name (List[str], optional): List of application company names associated with the recall - official_url (str): the url to fda recall official page. You can retrieve the webapge and find more details. - aggregations (dict): Aggregation results for application company name, device id, root cause description, product code, and initiated by year.
usfda_recall_search
ChatGPTSearch for FDA medical device recalls. It supports pagination and returns a list of matching recalls along with the total count. Args: query (str): The search term to match against recall title, recall number, reason for recall, product description, action, recalling firm, and application_company_name. Uses simple_query_string syntax with AND as default operator. When you want to fetch a list of recalls from a specific company/product code/device, you can use the empty string "" as the query and filter by application_company_id/product_code/device_id. offset (int, optional): Number of results to skip for pagination. Defaults to 0. size (int, optional): Maximum number of results to return. Defaults to 25. sort_by: Field to sort by. Defaults to '_score'. Acceptable values: "_score", "date_initiated". sort_order: Sort order. Defaults to 'desc'. Acceptable values: "asc", "desc". recall_status (optional): Filter by recall status. Acceptable values: "Completed", "Open, Classified", "Terminated" application_company_id (int, optional): Filter by application company id. product_code: (str, optional): Filter by product code. Devices with the same product code are considered similar. device_id (str, optional): Filter by device id. recall_class (optional): Filter by recall class. Acceptable values: "1", "2", "3". date_initiated_from (datetime, optional): Filter by date initiated from. date_initiated_to (datetime, optional): Filter by date initiated to. Returns: dict: A dictionary containing: - total_hits (int): Total number of matching companies found - recalls (list): List of recall objects, each containing: - recall_title (str): Title of the recall - recall_number (str): Unique recall number - recall_class (int): Class of the recall (1, 2, or 3) - date_initiated (datetime): Date when the recall was initiated - date_posted (datetime, optional): Date when the recall was posted - date_created (datetime, optional): Date when the recall was created - date_terminated (datetime, optional): Date when the recall was terminated - recall_status (str): Status of the recall - reason_for_recall (str, optional): Reason for the recall - root_cause_description (str): Root cause of the recall - recalling_firm (str): Name of the recalling firm - product_code (List[str], optional): List of 3-letter FDA product codes associated with the recall. Devices with the same product code are considered similar. - device_id (List[str], optional): List of device IDs associated with the recall - application_company_id (List[int], optional): List of application company IDs associated with the recall - application_company_name (List[str], optional): List of application company names associated with the recall - official_url (str): the url to fda recall official page. You can retrieve the webapge and find more details. - aggregations (dict): Aggregation results for application company name, device id, root cause description, product code, and initiated by year.
