parsing-trial-eligibility

Parsing trial eligibility & matching patients

A ClinicalTrials.gov study exposes its eligibility as a single free-text block (protocolSection.eligibilityModule.eligibilityCriteria) plus a few typed fields (sex, minimumAge, maximumAge, healthyVolunteers). This skill turns that prose into structured inclusion / exclusion criteria and matches each rule against patient facts that OpenMed extracted — producing an explainable eligible | ineligible | unknown verdict per criterion.

This is decision support, not enrollment. The output is a candidate list and a rationale for a clinician to review, never an automated eligibility decision.

When to use

• You pulled a study with searching-clinicaltrials and need its eligibility as machine-readable rules.
• You have a (synthetic) patient profile and want to screen it against one or many trials, with a per-criterion reason.
• You want to highlight which patient facts are missing to decide a criterion.

Quick start

The typed gates are deterministic — apply them first. The free-text criteria need parsing into bullet-level inclusion/exclusion items.

# Study from ClinicalTrials.gov v2 (see searching-clinicaltrials)
elig = study["protocolSection"]["eligibilityModule"]

raw = elig["eligibilityCriteria"]            # free text, often markdown bullets
sex = elig.get("sex", "ALL")                 # ALL | FEMALE | MALE
min_age = elig.get("minimumAge")             # e.g. "18 Years"
max_age = elig.get("maximumAge")             # e.g. "75 Years"
healthy_ok = elig.get("healthyVolunteers")   # bool

def split_criteria(text: str) -> dict[str, list[str]]:
    """Split the prose into inclusion / exclusion bullet lists."""
    sections, current = {"inclusion": [], "exclusion": []}, None
    for line in text.splitlines():
        low = line.strip().lower()
        if "inclusion criteria" in low:
            current = "inclusion"; continue
        if "exclusion criteria" in low:
            current = "exclusion"; continue
        bullet = line.strip(" -*•\t")
        if bullet and current:
            sections[current].append(bullet)
    return sections

criteria = split_criteria(raw)