Researching AI for Safer, Smarter Clinical Trials

At Keiji AI, we conduct foundational AI research across the full lifecycle of clinical development, from systematic literature review and evidence synthesis to real-world data analysis, trial design, patient recruitment, clinical data processing, and regulatory submission. We build cutting-edge large language models and agentic AI systems that are practical, safety-aware, and aligned with clinical and regulatory standards.

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Research Focus Areas

Literature Mining & Evidence Synthesis

Automating systematic reviews, meta-analysis, and PRISMA-compliant workflows with LLMs.

KEY PUBLICATIONA foundation model for human-AI collaboration in medical literature mining

Trial Design & Protocol Generation

AutoTrial and Panacea models to optimize eligibility criteria, endpoints, and arms.

KEY PUBLICATIONAutoTrial: Prompting Language Models for Clinical Trial Design

Patient-Trial Matching & Simulation

Foundation models that simulate digital twins, match EHRs to protocols, and forecast trial feasibility.

KEY PUBLICATIONMatching patients to clinical trials with large language models

AI Data Scientist

Tools for validating AI performance on OMOP/CDISC datasets in real-world studies.

KEY PUBLICATIONCan Large Language Models Replace Data Scientists in Biomedical Research?

Our Research Principles

Scientific Rigor

We ground our models in peer-reviewed science and transparent benchmarking.

Clinical Relevance

Our work targets problems that matter — trial feasibility, patient access, and evidence generation.

Safety-Aware Modeling

We align to CDISC, PRISMA, and real-world regulatory standards in all workflows.

Open Collaboration

We work with academia, regulators, and pharma sponsors to ensure impact beyond papers.

Join Our Research Team

If you're passionate about advancing AI for health, we'd love to collaborate. Explore opportunities to contribute to cutting-edge research at Keiji AI.

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