Protocol Amendment Handling

The automated extraction and structuring of textual changes from a formal protocol amendment document. This capability ingests the amendment PDF or document, identifies the specific sections where eligibility criteria have been modified, and extracts the old text, new text, and the rationale for change. It uses NLP models fine-tuned on regulatory document structures to distinguish between administrative updates and clinically significant criteria modifications that require screening logic updates.

An automated diffing engine that compares the newly parsed criteria set against the currently active, machine-readable criteria library. The system identifies three core change types:

• Addition: A new inclusion or exclusion criterion has been introduced.
• Deletion: An existing criterion has been removed from the protocol.
• Modification: An existing criterion's value, comparator, or temporal constraint has been altered (e.g., changing a lab value threshold from '> 150 mg/dL' to '> 180 mg/dL'). This detection triggers a structured change request for downstream review.

The process of automatically updating the executable database queries (e.g., SQL or FHIR API calls) that screen patient repositories when an eligibility criterion is modified. Upon detecting a change, the system re-translates the updated structured criterion into a new query. For example, if a washout period is extended from 14 to 30 days, the system regenerates the temporal query logic to reflect the new time window, ensuring the active screening algorithm always matches the latest protocol version.

A system architecture that maintains a strict, auditable link between a specific protocol version and the screening logic used to evaluate patients. When an amendment is approved, the system activates the new criteria set and deactivates the previous version, preventing patients from being screened against outdated rules. This capability ensures that all patient matches are tagged with the protocol version identifier used for their eligibility determination, providing a complete audit trail for regulatory inspections.

An automated assessment that runs the newly amended criteria against the pool of patients who were previously deemed eligible or are currently in screening. The system identifies:

• Newly Ineligible Patients: Patients who no longer meet the amended criteria.
• Newly Eligible Patients: Patients who were previously excluded but now qualify. This capability provides clinical operations teams with immediate visibility into how an amendment affects recruitment numbers and existing participant status, enabling proactive patient management.

The automated extraction and structuring of the rationale provided in the protocol amendment for each criteria change. This capability parses the free-text justification, maps it to the specific modified criterion, and stores it as structured metadata. This ensures that the clinical reasoning behind a change—such as a safety signal from another trial or new biomarker evidence—is preserved and auditable, supporting regulatory submissions and institutional review board (IRB) communications.

The foundational NLP process that extracts and structures free-text inclusion/exclusion criteria into a machine-readable format. This step is critical for enabling automated amendment handling, as it creates the structured target that must be updated. Key capabilities:

• Identification of logical operators (AND, OR, NOT)
• Extraction of temporal constraints (e.g., 'within 6 weeks')
• Normalization of clinical entities to standard ontologies like SNOMED CT

The process of breaking a complex, multi-part eligibility criterion into its atomic, independently evaluable logical components. When a protocol amendment modifies a single clause within a compound criterion, decomposition allows the system to surgically update only the affected sub-component rather than re-parsing the entire rule. This ensures deterministic version control and minimizes regression testing scope.

A deterministic software system that evaluates a set of patient facts against a predefined library of clinical trial eligibility rules to produce a pass/fail decision. In the context of amendment handling, the rule engine must support hot-swapping of rule versions without downtime. It maintains an auditable log of which rule version was active for each patient screening event, ensuring regulatory traceability.

The process of converting parsed, structured eligibility criteria into executable database queries (e.g., SQL or FHIR API calls). When an amendment changes a criterion, the corresponding query must be regenerated and validated. This card covers:

• Query templating for rapid regeneration
• Semantic equivalence testing to ensure the new query logic matches the amended intent
• Rollback mechanisms for erroneous amendments

The systematic review of reasons why pre-screened patients failed to meet trial eligibility. Amendment handling directly impacts this analysis by re-evaluating previously failed patients against new, relaxed criteria. An effective system automatically triggers a retrospective re-screen of the failure cohort whenever an inclusion criterion is broadened or an exclusion criterion is removed, unlocking hidden recruitment potential.

An automated process designed to evaluate a single patient against the multiple sub-study arms of a master protocol (e.g., basket or umbrella trials) simultaneously. Amendment handling complexity increases exponentially here, as a single protocol change may affect only a subset of active arms. The system must maintain distinct eligibility rule sets per arm and propagate amendments only to the targeted sub-studies.