Document and literature analysis
Identify concepts, compare themes, and develop draft summaries from large collections of scientific literature or regulatory materials. Source references and reviewer checks help make the results traceable.
Capability / YouSophia
Artificial Intelligence (AI) / Super Intelligence (SI)
Explore how AI and emerging intelligence approaches can help federal health teams navigate complex evidence while keeping people accountable for review and decisions.
THE WORK AT A GLANCE
INPUTScientific evidenceLiterature, submissions and data
ASSISTAI-supported analysisOrganize, summarize and explore
REVIEWHuman judgmentValidate findings against sources
Our focus
Responsible intelligence for scientific and regulatory work
We bring a thoughtful, multidisciplinary approach to the needs of public-sector teams and the people they serve.
01 /
Scientific knowledge synthesis
Support literature review and structured extraction from scientific and regulatory documents.
02 /
Safety signals and patterns
Explore analytical approaches to identify trends in clinical, post-market, and other health data.
03 /
Human oversight and validation
Assess limitations, validate outputs independently, and keep qualified reviewers involved in consequential decisions.
04 /
Responsible AI guidance
Consider governance, transparency, and appropriate use of emerging AI tools in scientific workflows.
A visual perspective
Responsible AI in context
These connected elements help frame the work and the people it is intended to support.
01Scientific question
02AI-assisted exploration
03Human validation
04Traceable insight
Illustrative framework; activities depend on mission needs.
From evidence to insight
A practical, human-led AI workflow
AI can help teams work through large and varied collections of information. The value comes from matching the method to the question, evaluating the output, and keeping scientific judgment with qualified people.
01 /Frame
Define the scientific or regulatory question, intended users, data sources, and limits of the analysis.
02 /Apply
Use suitable tools to extract concepts, summarize literature, or surface patterns for further investigation.
03 /Validate
Check outputs against source material, assess uncertainty, and document errors or gaps.
04 /Review
Place findings in context for subject matter experts, who retain responsibility for interpretation.
In practice
What this work can look like.
Activities are shaped around the mission, the available evidence, and the needs of the people doing the work.
ILLUSTRATIVE OUTPUTS
Use-case assessments, source-linked evidence summaries, validation notes, and governance recommendations.
01Summarize and compare themes across scientific literature or regulatory documents with links back to source material.
02Organize unstructured text for a reviewer to examine potential safety signals or emerging topics.
03Assess whether a proposed AI use case has appropriate data, validation, oversight, and documentation.
A closer look
Responsible use across the analytical lifecycle
AI-assisted work should be designed around a specific question and the people who will evaluate the results. The right approach depends on the available data, the consequences of error, and the review environment.
Safety and signal exploration
Use analytical tools to highlight patterns in adverse event reports or other datasets for further investigation. A potential pattern is a starting point for expert assessment, not a conclusion by itself.
Governance and evaluation
Document intended use, data limitations, validation methods, and responsibilities. Assess outputs for accuracy, omissions, and appropriate use before incorporating them into a workflow.
Illustrative scenario
Putting the work in context.
A team exploring an emerging safety topic could define a question, gather relevant sources, use approved tools to organize potential themes, and have subject matter experts verify each finding against the underlying evidence.
AI capability / Agentic AI
Agentic AI for health data and systems.
Agentic AI can coordinate defined tasks across approved information and tools. In health and regulatory settings, these workflows need clear permissions, traceable evidence, testing, and human checkpoints appropriate to the work.
Health data preparation
Explore agents that help identify data quality issues, organize metadata, flag inconsistent terminology, and prepare proposed mappings for review by data specialists.
Evidence and knowledge
Coordinate searches across permitted scientific literature, guidance, and internal knowledge sources; assemble source-linked summaries for expert validation.
Regulatory review support
Assist with organizing materials, tracking outstanding questions, and drafting review support documents while keeping scientific and regulatory decisions with authorized people.
Connected system workflows
Assess opportunities for agents to work across approved systems, retrieve relevant information, and propose next steps within defined interfaces and access boundaries.
Analytical assistance
Help route analytical requests, gather appropriate data and context, and prepare reproducible analysis plans or draft outputs for qualified reviewers.
Governance and evaluation
Define permitted actions, test accuracy and reliability, document source provenance, and monitor outcomes with escalation and human approval points.
01 / DEFINESet the task
Specify the objective, approved data, tools, and access.
02 / RETRIEVEGather context
Find relevant information from permitted sources.
03 / ASSISTPrepare a proposal
Organize evidence and suggest a reviewable next step.
04 / REVIEWKeep people in control
Validate outputs and approve consequential actions.
Illustrative applications depend on project requirements, approved technologies, data permissions, and appropriate safeguards.