Research behind TrialMind
Peer-reviewed methods organized around the six teams TrialMind serves, from trial design and real-world evidence to clinical operations, portfolio decisions, HTA, and investigator-led research.
Research by workflow
Six research areas. The same six doors into the product.
Drug-discovery and multimodal research remains part of the scientific foundation. Evidence-based medicine is split into the specific RWE, intelligence, and HEOR decisions it supports.
For biometrics and quantitative science teams
Biostatistics & Trial Design
Methods for designing more feasible trials, simulating outcomes, and creating analysis-ready evidence for statistical teams.
Representative publications
4 papers in this research area
Prompting Language Models for Clinical Trial Design
Wang, Xiao, Sun · EMNLP 2023
Zero-Shot Clinical Trial Document Similarity Search using Self-Supervision
Wang, Sun · Findings of EMNLP 2022
Personalized Clinical Trial Digital Twin Generation
Das, Wang, Sun · KDD 2023
Clinical trial outcome prediction with multi-modal generative AI
Theodorou, Wang, Sun · Patterns 2025
For RWE, epidemiology, and data science teams
Real-World Evidence
Reliable methods for cohort analysis, longitudinal patient modeling, comparative effectiveness, and safety studies on real-world data.
Representative publications
9 papers in this research area
Scaling Medical Tabular Data Predictors via Data Consolidation, Enrichment, and Refinement
Wang et al. · IJCAI 2024
Learning Transferable Tabular Transformers Across Tables
Wang, Sun · NeurIPS 2022
Synthesize high-dimensional longitudinal electronic health records via hierarchical autoregressive language model
Theodorou, Xiao, Sun · Nature Communications 2023
Improving medical machine learning models with generative balancing for equity and excellence
Theodorou et al. · npj Digital Medicine 2025
For strategy, search, and portfolio teams
Competitive & Portfolio Intelligence
Clinical-trial foundation models and predictive methods for landscape analysis, probability of success, and evidence-backed portfolio decisions.
Representative publications
5 papers in this research area
Benchmarking and Developing Large Language Models Using One Million Clinical Trials
Wang et al. · npj Digital Medicine 2025
A foundation model for clinical trial search, summarization, design, and recruitment
Lin et al. · medRxiv 2024
Sequential Predictive Modeling of Clinical Trial Outcome with Meta-Learning
Wang, Sun · ACM-BCB 2023
Hierarchical Interaction Network for Clinical Trial Outcome Predictions
Wang, Sun · Patterns 2022
For clinical development and trial operations teams
Clinical Development & Operations
Research that improves site selection, patient-trial matching, recruitment, and the operational decisions that determine whether a trial finishes.
Representative publications
4 papers in this research area
Fair ranking with missing modalities for clinical trial site selection
Theodorou et al. · Patterns 2024
Matching patients to clinical trials with large language models
Jin, Wang et al. · Nature Communications 2024
Cross-modal pseudo-siamese network for patient-trial matching
Gao, Xiao, Glass, Sun · KDD 2020
Dynamic Doctor Representation Learning for Clinical Trial Recruitment
Gao, Xiao, Glass, Sun · AAAI 2020
For evidence synthesis, value, and access teams
HEOR & Market Access
Human-AI evidence synthesis methods for systematic reviews, reproducible screening, and evidence bases that can stand up to HTA scrutiny.
Representative publications
3 papers in this research area
Empowering Biomedical Evidence Exploration and Synthesis with Deep Knowledge Graph Research
Wang et al. · Nature Machine Intelligence 2026
Accelerating clinical evidence synthesis with large language models
Wang et al. · npj Digital Medicine 2025
A foundation model for human-AI collaboration in medical literature mining
Wang et al. · Nature Communications 2025
For investigators, departments, and research informatics
Research Institutions
Foundational AI, including drug-discovery and multimodal methods, plus data-science agents that help investigators run reproducible biomedical studies.
Representative publications
6 papers in this research area
Making large language models reliable data science programming copilots for biomedical research
Wang et al. · Nature Biomedical Engineering 2026
Benchmarking Data Science Agents for Biomedical Research
Wang, Danek, Sun · Preprint 2025
Bridging Biomedical Foundation Models via Knowledge Graph
Wang et al. · ICLR 2024
Contrastive Learning from Unpaired Medical Images and Text
Wang, Sun · EMNLP 2022
From research to product
Publication is the start of the evidence chain
The workflow defines the research question
We start from the decision a biometrics, RWE, operations, intelligence, HEOR, or academic team has to make.
Methods are measured, not merely demonstrated
Peer review, purpose-built benchmarks, and comparisons against established baselines make performance inspectable.
Evidence remains traceable
Sources, assumptions, and intermediate decisions stay connected to the final output so teams can review and reproduce the work.
Explore the evidence
Read the papers, then see where the methods are used.
The publication archive contains every paper under its primary ICP category, with keyword filtering for methods that cross workflows.
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From top pharma companies to academic medical centers
