Renamed: 356H Machine Learning (ML) Facility Supply Chain Role Classification Previously: 356H ML Facility Supply Chain Role Classification
Manual classification of facility supply chain roles from FDA industry submissions (356h forms) is time-consuming and inefficient
Renamed: Risk-based FAR Review & Decision Support Previously: Field Alert Reports (FAR) Prioritization Model
Manual and subjective assessment process for Field Alert Reports (FARs) can lead to inconsistency in prioritizing and assessing reports, potentially leading to ineffective resourc…
Analytics-Driven Supplement Evaluation (ASE)
Exponential increase in post-approval chemistry, manufacturing, and controls (CMC) change submissions, with 80% being Changes Being Effected (CBE-30/0) notifications that may be s…
Renamed: FAR-based Facility Signal Detection Tool Previously: Post-market Surveillance Reports Signal Detection and Cluster Analysis.
Need for proactive detection of quality signals in post-market surveillance reports using statistical process control and topic modeling to identify potential drug quality hazards…
MedWatch Dashboard
Need to proactively identify emerging issues and clusters within MedWatch reports using advanced analytics.
Quality Surveillance Dashboard (QSD)
Need for consistent, data-driven assessment of drug manufacturing facilities and proactive detection of potential quality signals that could indicate problems with drug safety or…
Annual Report CMC
FDA receives numerous annual reports from drug manufacturers containing important manufacturing and quality information, but key details can be difficult to locate quickly within…
Renamed: Application References Previously: Application-DMF Reference
FDA receives extensive drug application submissions that contain valuable references to related applications, but these relationships aren't always captured in existing regulatory…
Renamed: Extracting DMF Facilities from unstructured documents Previously: DMF (Drug Master File) Facilities
FDA receives Drug Master File (DMF) submissions containing valuable information about manufacturing facilities, but this data exists in various document formats that require manua…
Renamed: Information Visualization Platform (InfoViP) to Support Analysis of FAERS safety reports Previously: Information Visualization Platform (InfoViP) to Support Analysis of adverse event reports
The AI is intended to support the analysis of FAERS Individual Case Study Reports in post-market safety surveillance by automating duplicate detection, creating temporal visualiza…
Renamed: Module 3 Facilities Extraction Previously: Module 3 Faculties
FDA receives drug application submissions (ANDA, NDA, BLA) that contain important manufacturing facility information in Module 3 documents, but this data requires manual review to…
Packaging Materials and Suppliers
FDA needs to efficiently identify which Drug Master Files (DMFs) contain specific packaging materials and understand how these materials connect to drug applications, but this inf…
Real World Data/Evidence
FDA receives numerous submissions containing real-world data and evidence, but identifying and cataloging these studies across various submission types is time-intensive and criti…
Regulatory Starting Material
FDA needs comprehensive visibility into the upstream supply chain for drug manufacturing, particularly tracking regulatory starting materials and their suppliers across approved a…
Creating a development network
The AI is intended to solve the problem of inconsistent data formats and inefficient access to unstructured clinical data across multiple healthcare sites. It aims to standardize…
Drug Shortage Predictive Model
Drug shortages have increased significantly since 2017 and worsened during COVID-19, creating critical gaps in patient access to essential medications. FDA seeks to develop predic…
Category Subcategory Classification - Safety Reports Bot
Manual analysis and data entry of safety report submissions is time-intensive and requires staff to review scanned PDFs and determine appropriate categories.
Use case package 1: Empirical application of the Sentinel EHR and claims Data Partner network to address ARIA insufficient inferential requests (UC1)
This AI project is designed to solve the problem of determining whether available data sources and analytical methods are suitable for specific pharmacoepidemiologic research ques…
CI5: Development and refinement of toolkits for routine use in the EHR and claims Data Partner network
This project is designed to solve the problem of inconsistent or inefficient data analysis capabilities across the EHR and claims Data Partner network. It aims to create standardi…
Use case package 2 (UC2): Empirical application of the Sentinel EHR and claims Data Partner network to enhance ARIA insufficient inferential requests and atypical descriptive requests
This AI project is designed to solve the problem of translating theoretical innovative methods into practical, real-world applications within the Innovation Center (IC) developmen…
FE5: Incorporate a range of frequently used engineering features from EHRs into the Sentinel common data model in the Sentinel EHR and claims linked Data Partner network
This AI project is designed to solve the problem of extracting valuable clinical information trapped in unstructured free-text fields within electronic health records. It aims to…
Develop an empirical algorithm to automate negative control identification in Sentinel System using the “Data-driven Automated Negative Control Estimation (DANCE)” algorithm
This AI project is designed to solve the problem of optimizing the Data-driven Automated Negative Control Estimation (DANCE) algorithm for real-world implementation in large elect…
Support tools that can be used in conjunction with Electronic Health Record (EHR) data, such as machine learning and natural language processing (NLP), and the use of Artificial Intelligence (AI) chart review tools
This AI project is designed to solve the problem of rapidly responding to urgent or emerging drug safety signals that require immediate attention and coordinated action. It aims t…
Sentinel System Task Order to address an Emerging Safety Need
This AI project is designed to solve the problem of efficiently validating emerging safety signals through chart review when traditional structured data is insufficient. It aims t…