EpistemIQ

What it is

EpistemIQ is a governance-first method for surfacing where AI outputs may exceed the evidence, miss context, or create silent failure modes in drug-development and clinical-operations decisions. It integrates with existing documentation and review cycles to make risks visible early—before they become regulatory gaps, reputational issues, or slowdowns in study start-up.

Why it matters

• Regulatory integrity: flags where evidence, traceability, or explainability are insufficient for FDA/EMA standards.
• Reputation & trust: reduces downstream corrections that erode sponsor credibility with investigators and partners.
• Speed with safety: prevents rework and delays by catching issues at protocol/feasibility and early ops stages.

Core capabilities

• Gap detection: identifies missing assumptions, weak provenance, and over-generalized model claims.
• Evidence mapping: links AI outputs to data sources, parameters, and domain constraints for auditability.
• Decision guardrails: embeds go/no-go criteria and benefit-realization checks into clinical ops milestones.
• Portfolio view: provides a risk scoreboard across indications/programs to prioritize fixes and scale what works.

Example applications

• Protocol feasibility & site selection (EHR analyses, enrollment modeling, inclusion/exclusion drift).
• Regulatory document support (traceability, claims discipline, audit-ready rationale).
• Vendor evaluation (model disclosures, monitoring plans, bias & drift controls).

Validation & engagements

Discussed in executive roundtables (MIT, MassBio, Align AI). Confirmed speaking: ABM Alliance (multi-day) on ethical AI and clinical operations transformation.

IP & status

Patent pending in the U.S. (Application No. 63/858,627). Methodology and implementation details are reserved for partner discussions under NDA. This page describes high-level concepts and benefits only.

Visit my About page for contact details, collaborations, and upcoming speaking engagements.