The methodology that makes regulated AI inspection-defensible.
PQIOS is the operating system I run for AI quality governance in regulated life sciences. Pharmacy already has a fifty-year vocabulary for absorbing agents that bring possibility and vulnerability in the same step. PQIOS translates that vocabulary forward — modified for non-deterministic outputs, agentic workflows, and the regulatory regimes that just finalised.
What this platform talks about.
Forward to governanceGovernance is the focal point — the structure that makes quality survivable. Behind it, three domains of depth: bioanalytical, bioequivalence, clinical trials. Each domain is read through four sub-areas: operations · technical · regulatory · market. Behind that, four areas any reader comes from: academic, research, industry, business. Many inputs · one synthesis.
The four-layer stack.
From substrate to vectorPQIOS organises around four layers. Each layer is built on the one below it. None of the layers is optional. The combination is what makes the stack defensible against the failure modes regulated AI deployment actually produces — not against theoretical risk, but against the audit trail that an FDA inspector or an EMA assessor will read in three years.
The three operational domains the methodology covers.
Domain depthBioanalytical.
LC-MS/MS · LBA · hybrid platforms · PK/PD substrate · biomarker quantification · the analytical spine of every BE, biomarker, immunogenicity, and PK study. Production-floor depth across method validation, transfer, and regulator-facing dossier work.
Bioequivalence.
Crossover · RSABE · NTI products · CI 0.80–1.25 · ICH M13A · regulatory frameworks across FDA, EMA, MHRA, HPRA, CDSCO, WHO PQ. The regulator-facing spine of generic and biosimilar approval pathways.
Clinical trials.
Phase I–IV · ICH-GCP · ICH M11 structured-protocol (Step 4 19 Nov 2025) · TMF/eTMF · adaptive designs · decentralised trials · synthetic control arms. The full study lifecycle from start-up to closure.
What the methodology produces.
Output deliverablesPQIOS is not a deck. It is the policy layer for a fleet of agents that produce regulator-grade documentation. The outputs are the same documents pharma quality and regulatory affairs teams have been writing by hand for decades — generated faster, validated continuously, audit-trail-native by design.
Risk classifications.
EU AI Act Annex III risk-tier mapping for AI deployments within scope, designed to be inspector-ready when implemented within the organisation's QMS.
Validation lifecycles.
IQ/OQ/PQ for non-deterministic systems. PCCP architectures for adaptive AI. GAMP 5 Second Edition aligned.
Audit trails.
ALCOA+ enforcement at the architectural level. 21 CFR Part 11 records that survive a Form 483.
Change control.
Adaptive AI change-control plans. Model-update governance. Drift detection feeding back into validation.
SOPs & procedures.
Standard operating procedures generated against the latest published guidance. Regulator-cited references throughout.
CAPA workflows.
Adaptive immunity in operation. Each incident strengthens the next round of validation.
Regulatory dossiers.
Submission-ready documentation. ICH M11 structured-protocol fluent. Cross-jurisdictional alignment.
Effectiveness checks.
Post-deployment effectiveness across the immunity lifecycle. Continuous improvement feedback loop.
The methodology in continuation.
HorizonThe methodology continues to grow as the regulated AI landscape clarifies — every regulator publication, every operational case, every audit observation feeds back into the policy layer through the daily-research engine that iFeed maintains. The methodology is durable because it is built on substrate that does not move quickly. It is current because the substrate is continuously refreshed.
Beyond the working methodology, iFeed is building the surfaces that turn it into accessible practice for the wider community: iFeed Academy — the cohort-learning platform — and a hosted community for practitioners. Both are scaffolded; both surface here as they come online, subject to interest and substrate readiness. See Academy →
/ open-endedThe methodology layer here updates as the regulated AI landscape clarifies — every regulator publication, every operational case, every audit observation feeds the policy layer. Updates land in irregular drops, not on a fixed calendar. If a section goes silent for a stretch, the cadence is working as designed; the next visible drop will have substrate behind it. Register for the weekly note if you want the next drop in your inbox.