iFeed · methodology · documented in the open

The methodology behind iFeed.

iFeed reads regulated healthcare change before it becomes operational risk. The method starts with quality-system discipline, clinical-research experience, and inspection memory; then turns that knowledge into learning material, signals, and governed AI-enabled work.

Read the method → Architect · signature builds
Layer: iFeed methodology Framework: Antidote+Vaccine Architect: Sunita Nawale Used by: iFeed · LMS · Platform
/ 00

What the methodology covers.

Domains and decisions

Governance is the focal point: the structure that keeps regulated work reliable. The method draws from three domains — bioanalytical, bioequivalence, and clinical trials — and reads each through operational, technical, regulatory, and market signals. The same logic supports Signals, LMS knowledge pages, and platform work.

/ 1 · Readers / 2 · Domains / 3 · Signals / 4 · Decision Academic Research Industry Business Bio analytical Bio equivalence Clinical trials Operations Technical Regulatory Market Focal point Governance QMS · quality
/ Areas
Who uses iFeed.
Academic, research, industry, and business readers who need regulated healthcare change explained clearly.
/ Sub-areas
What iFeed watches.
Operational, technical, regulatory, and market movement across each domain.
/ Domains
Where the depth sits.
Bioanalytical · bioequivalence · clinical trials. The three operational domains.
/ Focal point
Governance.
The structure that turns evidence, risk, and responsibility into defensible work.
/ 01

The four parts of the method.

From quality practice to governed AI

The iFeed methodology has four parts. It starts with regulated-quality language, adds operational domain knowledge, translates both into governance, and then applies that governance to AI-enabled work. The aim is simple: decisions that can be explained, evidenced, and defended later.

/ Part 01
Quality · Governance · Compliance.
The regulated-quality foundation. GxP frameworks · 21 CFR Part 11 · ICH M10/M11 · ALCOA+ · ISPE GAMP 5 Second Edition · draft EU GMP Annex 22 (in consultation 2025). The core vocabulary regulators in major markets expect to recognise in documents related to regulated systems.
quality
/ Part 02
Three operational domains.
Bioanalytical method validation · bioequivalence study oversight · clinical trial operations. Production-floor depth across analytical platforms, regulatory regimes, study lifecycles, and the working context around the science.
domain depth
/ Part 03
Methodology: policy translated into practice.
Where quality practice and domain knowledge become usable governance: what good output looks like, what evidence it needs, and what a reviewer should be able to trace.
IP
/ Part 04
AI and technology governance.
How the method applies to EU AI Act obligations, FDA AI-enabled device guidance, PCCP thinking, validation of non-deterministic systems, and human accountability in AI-supported work.
AI governance
"The method joins three things that regulated teams cannot separate: quality practice, domain knowledge, and AI-enabled execution." — iFeed methodology note
/ 02

The three operational domains the methodology covers.

Domain depth
Domain 01

Bioanalytical.

LC-MS/MS · LBA · hybrid platforms · PK/PD · 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.

ICH M10FDA BMV 2018EMA GLBIVLC-MS/MSLBA
Domain 02

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.

ICH M13ARSABENTIPKcrossover
Domain 03

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.

ICH-GCPICH M11eTMFDCTadaptive
/ 03

What the methodology produces.

Output deliverables

The methodology produces the documents and decisions regulated teams already need: risk classifications, validation logic, audit trails, change control, SOPs, CAPA, dossiers, and effectiveness checks.

RA
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.

VL
Validation lifecycles.

IQ/OQ/PQ for non-deterministic systems. PCCP architectures for adaptive AI. GAMP 5 Second Edition aligned.

AT
Audit trails.

ALCOA+ at the architectural level. 21 CFR Part 11 records prepared for inspection review.

CC
Change control.

Adaptive AI change-control plans. Model-update governance. Drift detection feeding back into validation.

SO
SOPs & procedures.

Standard operating procedures generated against the latest published guidance. Regulator-cited references throughout.

CA
CAPA workflows.

Adaptive immunity in operation. Each incident strengthens the next round of validation.

RD
Regulatory dossiers.

Submission-ready documentation. ICH M11 structured-protocol fluent. Cross-jurisdictional alignment.

EC
Effectiveness checks.

Post-deployment effectiveness across the immunity lifecycle. Continuous improvement feedback loop.

/ 04

How the methodology is maintained.

Maintained method

The methodology changes when regulation, operations, or AI practice changes in a way that affects real decisions. It is maintained against new guidance, cases, and audit observations.

/ Current and maintained

The same methodology informs iFeed LMS, PQIOS, ClinAssure, iFeed Studio, and Weekly Signals. Those systems remain separate. This page explains the common logic that holds them together. Explore collaboration →

/ open-ended
/ Cadence note
The methodology is maintained as the field changes.

This page updates when the explanation needs to become clearer. Build work can continue inside LMS or platform systems while this page keeps the shared method understandable.