Event Catalog

Master closed-loop CAPA with repeatable failure investigation and root cause analysis tools that satisfy FDA audit expectations in GMP environments.

John E. Lincoln

Practical strategies for reducing pharmaceutical deviation backlogs without sacrificing investigation quality — covering risk-based depth, defensible closure, CAPA, and inspection readiness.

Charles H. Paul

Learn where AI genuinely helps CAPA and investigations — and where it creates regulatory risk by replacing evidence-based analysis with generated logic.

Charles H. Paul

Implement a proven human error investigation methodology — classify error categories, identify root causes, develop effective CAPA, and apply Human Factors to prevent recurring GMP issues.

Dr. Ginette Collazo

A step-by-step guide to investigating sterility test failures — covering FDA regulations, root cause tools, lot impact assessment, and audit-ready documentation.

Danielle DeLucy

Move beyond superficial root causes — build defensible deviation reports, sustainable CAPA, and change control aligned with 21 CFR 820.100 and GMP expectations.

Charles H. Paul

Master the fundamental steps of deviation investigation — use objective evidence to determine root cause, develop effective CAPA, and avoid FDA 483 observations.

Danielle DeLucy

Master closed-loop CAPA with repeatable failure investigation and root cause analysis tools that satisfy FDA audit expectations in GMP environments.

John E. Lincoln

A practical investigation framework for tracing sterility failures through laboratory, manufacturing, environmental, and contamination-source evidence to establish a defensible root cause, determine the impact on affected batches, and support appropriate corrective actions.

Practical strategies for reducing pharmaceutical deviation backlogs without sacrificing investigation quality — covering risk-based depth, defensible closure, CAPA, and inspection readiness.

Charles H. Paul

Learn where AI genuinely helps CAPA and investigations — and where it creates regulatory risk by replacing evidence-based analysis with generated logic.

Charles H. Paul