AEMS Think Trends Licenses (Brand Name)

assify, and route adverse event documents by submission type, FDA Center, product category, source, urgency, and case-processing requirements. The intake agent shall identify whether a document relates to drugs, biologics, devices, veterinary products, tobacco products, combination products, or other FDA-regulated products. Key capabilities include: � Automated ingestion of scanned PDFs, forms, emails, images, attachments, and electronic documents. � Classification of documents by Center-specific workflow, product type, and reporting pathway. � Detection of new cases, follow-up cases, duplicate submissions, incomplete submissions, and supporting attachments. � Intelligent routing to appropriate review queues, case-processing teams, or downstream systems. B. Agentic OCR and Intelligent Data Extraction Think Trends Software Agentic OCR shall combine optical character recognition, computer vision, natural language processing, large language models, and rule-based validation agents to extract key adverse event data elements from complex documents. The platform shall extract and structure critical case information, including: � Reporter, patient, animal, subject, or consumer information. � Product information, including drug, biologic, device, tobacco, or veterinary product details. � Adverse event terms, symptoms, outcomes, seriousness, and event narratives. � Dates, timelines, exposure details, dose, route, duration, lot numbers, manufacturer information, and product identifiers. � Medical history, concomitant products, lab results, device problem codes, clinical narratives, and follow-up information. � Center-specific data elements required for CVM-Drugs and CVM-Food, CDRH, CTP, CDER, CBER and HFP. C. Center-Specific Adverse Event Processing Agents The Contractor shall configure specialized AI agents within Think Trends Software to support unique regulatory and operational needs across FDA Centers. Each agent shall apply Center-specific data models, validation logic, terminology, business rules, and review workflows. Examples include: � CVM Agent: Processes veterinary adverse event reports, animal species, breed, weight, product exposure, dosage, outcome, and veterinarian/reporter information. � CDRH Agent: Processes device-related adverse events, device identifiers, manufacturer information, malfunction details, patient impact, and device problem descriptions. � CTP Agent: Processes tobacco product adverse experiences, product use patterns, health effects, consumer narratives, and product category information. � HFP Agent: Processes HFP-specific adverse event reporting requirements and associated workflows. � CDER Agent: Process drug product adverse experiences, product use patterns, health effects, consumer narratives, and product category information. � CBER Agent: Processes biologics product adverse experiences, product use patterns, health effects, consumer narratives, and product category information. D. Case Validation, Quality Control, and Human-in-the-Loop Review Think Trends Software shall incorporate validation agents to compare extracted data against business rules, required fields, confidence thresholds, terminology standards, and case-processing logic. Records that meet defined thresholds may proceed automatically, while exceptions shall be routed for human review. Key quality-control features include: � Confidence scoring at field, document, and case levels. � Source traceability to page, section, table, and line references. � Automated flagging of missing, inconsistent, conflicting, or low-confidence data. � Human-in-the-loop review screens for case processors and safety reviewers. � Reviewer acceptance, correction, override, and approval workflows. � Full audit trail of AI extraction, human edits, and final approved values. E. Data Standardization and Regulatory Output Generation Think Trends Software shall transform extracted adverse event information into structured formats required for case management, analytics, and downstream regulatory processing. The platform shall support configurable mappings to FDA data standards, Center-specific systems, XML structures, APIs, and reporting formats. Capabilities include: � Normalization of adverse event terms, product names, dates, identifiers, and narrative fields. � Mapping to Center-specific safety data models and controlled terminology. � Generation of structured case records for downstream review and processing. � API-based integration with FDA systems, case-processing platforms, data lakes, document repositories, and workflow tools. � Export to XML, JSON, CSV, database tables, or other required formats. F. Agentic Workflow Automation and Triage Think Trends Software shall automate repetitive case-processing steps while maintaining reviewer control for regulatory decisions. The system shall support configurable AI agents capable of executing multi-step workflows, requesting missing information, summarizing case narratives, identifying seriousness indicators, detecting duplicates, and prioritizing work queues. Workflow automation shall include: � Case prioritization based on seriousness, product risk, event severity, due dates, and Center-defined rules. � Automated summarization of long adverse event narratives and supporting attachments. � Duplicate and follow-up detection across submissions. � Exception handling and escalation workflows. � Generation of reviewer-ready case summaries. � Dashboard visibility into case volumes, processing status, aging, backlog, error rates, and productivity metrics. G. AI-Enabled Redaction for FOIA Compliance ThinkTrends will provide AI-powered redaction capabilities to support FDA's obligations under the Freedom of Information Act (FOIA). The platform will automatically identify and redact personally identifiable information (PII), protected health information (PHI), commercially confidential data, law-enforcement-sensitive content, and other exemption-covered materials from adverse event documents prior to public release or response to FOIA requests. Key capabilities include: � Automated detection and redaction of PII and PHI, including patient names, addresses, dates of birth, medical record numbers, Social Security numbers, and other personal identifiers. � Identification and suppression of trade secrets, proprietary formulations, manufacturing processes, and commercially confidential submitter information protected under FOIA Exemption. � Detection of law-enforcement-sensitive and inter-agency deliberative content subject to FOIA Exemptions. � Configurable exemption profiles aligned to FDA FOIA policy, Center-specific guidance, and applicable federal regulations. � Confidence-scored redaction recommendations with source traceability, enabling FOIA reviewers to accept, modify, or override AI-proposed redactions. � Human-in-the-loop review workflow allowing FOIA analysts to validate, annotate, and finalize redacted documents before release. � Generation of redacted PDF and document versions with visible redaction markers, exemption codes, and reviewer audit annotations. � Full audit trail recording every AI-proposed redaction, reviewer decision, exemption code applied, and final release determination. � Support for bulk redaction processing across large FOIA request batches, including multi-document packages and rolling requests. � Integration with FDA FOIA trac