Scaling Up Formal Representation of Clinical Trial Protocols in Ensemble Logic Using LLMs: A Preliminary Study

2026-07-23

AI Summary

Clinical trial protocols are predominantly presented as unstructured narrative text, which hinders the explicit representation of dynamic eligibility criteria and temporal constraints, thereby limiting automated reasoning and simulation. This work proposes CT-TEL, a novel workflow that leverages large language models (LLMs) to automatically translate narrative protocols into Temporal Event Logic (TEL) formulas—enabling computable, formal modeling of trial specifications for the first time. By incorporating bidirectional translation between natural language and logical formulas alongside semantic similarity evaluation, the method successfully generates high-fidelity TEL models across 23 real-world trials. The results demonstrate the feasibility of scalable, symbolic modeling of clinical trials and open new avenues for simulation under the emerging “symbolic biomedicine” paradigm.

Abstract

The reliance on unstructured free text for documenting clinical trial protocols creates a significant barrier to automated reasoning, cohort discovery, and trial simulation. The lack of formal structure obscures critical temporal phenotypes, such as dynamic eligibility criteria and event timing constraints. Although Temporal Ensemble Logic (TEL) offers an expressive framework for modeling these elements, manual encoding remains a prohibitive bottleneck. We introduce the CT-TEL workflow: a scalable pipeline leveraging Large Language Models (LLMs) to translate narrative clinical protocols into TEL formulas. We applied CT-TEL to generate logical models for 23 real-world trials from ClinicalTrials.gov. We evaluated translation fidelity via a back-translation approach, using LLMs to convert TEL formulas back into natural language and measuring semantic similarity against source texts. The resulting semantic retention suggests that LLMs may offer a pathway for mapping informal protocols to computable logic, providing preliminary evidence toward scalable clinical trial emulation within the emerging "Symbolic Biomedicine" paradigm championed by the corresponding author.

Problem

• clinical trial protocols
• formal representation
• temporal phenotypes
• automated reasoning
• unstructured text

Innovation

• Temporal Ensemble Logic
• Large Language Models
• Clinical Trial Protocol
• Formal Representation
• Symbolic Biomedicine