HIVE AI Pilot

Overview

Development stage

PilotSource: b) Pilot – The use case has been deployed in a limited test or pilot capacity.

High-impact designation

Not high-impactSource: c) Not high-impact

Impact justification

Not reported

Start date

2025-07 (month precision)Source: Jul-25

Withheld from public reporting

NoSource: a) No

Mission

Topic area

Health and Medical

Operational functions

Summarization Derived by keyword rules; see methodology

Problem the AI is intended to solve

The AI is intended to assist in solving several problems related to the review process for INDs. Specifically, it aims to address issues of inefficiency, delays in identifying deficiencies and information overload. By providing recommendations for review disciplines, it helps reviewers to quickly identify potential review disciplines that are required. By identifying grossly deficient submissions early on, it reduces the workload and highlighting key data helps reviewers to focus on higher-level tasks that require their expertise.

Expected benefits

Overall, is designed to improve efficiency and effectiveness of the regulatory review process, allowing for quicker and well-informed decision making

System outputs

The system's output include: 1. review discipline recommendations - automated suggestions for the most appropriate review disciplines for each incoming submission. 2. highlighted key data - generates reports highlighting critical information to facilitate quicker understanding by RPMs and reviewers. 3. Summaries - reports summarizing large documents to potentially accelerate review.

Technology

AI classification

Generative AISource: Generative AI: AI that generates new or synthetic content (e.g., images, videos, audio, text, code).

System name(s)

HIVE

Custom-developed code

Yes

Public source code

the code is not open source, it resides within FDA gitlab repository and is not publicly available

Sourcing

How it was built

Contract and in-houseSource: c) Developed with both contracting and in-house resources

Vendor (as reported)

SAIC

Vendors (standardized)

SAIC

A vendor is the supplier named by the agency. It does not identify the underlying model or AI technology.

Data and privacy

Involves PII

Yes

Privacy Impact Assessment

not publicly available

Authorization to Operate

Yes

Demographic features

k) None of the above

Training and evaluation data

use a dataset of previously submitted IND applications, which provided a comprehensive understanding of the types of data and information included in these submission. Feedback and annotations from experienced RPMs and reviewers on a subset of the historical submission, which helps fine-tune the model's understanding of what constitutes a high-quality submission.

Federal Data Catalog

data can not be publicly disclosed as is proprietary information from submissions

Governance

0 of 8 minimum-practice questions answered. A blank answer means the agency reported nothing; it does not mean the practice is absent.

Potential impacts and how they were identified

Not reported