nexvigilant/.true

ksb-framework

Auto-apply Knowledge-Skills-Behaviors framework to guide Claude's reasoning

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Thalidomide Legacy: Understanding the pivotal 1960s tragedy that catalyzed modern pharmacovigilance...

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Regulatory Development: Evolution from reactive post-market observation to proactive safety systems...

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Global Harmonization: ICH guidelines development and international regulatory convergence...

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Technology Evolution: From paper-based reporting to AI-enhanced surveillance systems...

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Population Health Impact: Understanding medication safety within broader public health frameworks...

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Health Equity Considerations: Ensuring safety monitoring addresses diverse populations and access issues...

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Pandemic Preparedness: Role of pharmacovigilance in emergency use authorizations and vaccine safety...

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Global Health Perspective: Medication safety monitoring in resource-limited settings...

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FDA Guidance: Understanding FAERS, FDA's role in post-market surveillance, and regulatory expectations...

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EMA Framework: EU Pharmacovigilance legislation, GVP modules, and European regulatory approach...

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ICH Guidelines: E2A through E2F implementation and global harmonization principles...

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Regional Variations: PMDA (Japan), Health Canada, and emerging market regulatory approaches...

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Core Ethical Principles: Beneficence, non-maleficence, autonomy, and justice in safety monitoring...

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Informed Consent: Understanding patient rights in safety data collection and usage...

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Transparency Standards: Balancing public disclosure with competitive and privacy considerations...

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Professional Responsibility: Individual and organizational obligations for patient safety...

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AI/ML Terminology: Machine learning, natural language processing, predictive analytics, neural networks...

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Application Areas: Pattern recognition, signal detection, automated case processing, risk prediction...

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Validation Requirements: Ensuring AI tools meet regulatory standards and maintain human oversight...

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Ethical AI: Bias mitigation, transparency, explainability, and responsible implementation...

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AI Impact on PV Landscape: Understanding of how artificial intelligence is transforming pharmacovigilance practice including au...

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AI Ethics in Drug Safety: Comprehension of ethical considerations in AI-enabled pharmacovigilance including algorithmic transp...

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PV AI Governance Frameworks: Understanding of governance structures required for AI in pharmacovigilance including organizational...

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AI Competency Requirements: Understanding of evolving workforce competency requirements in AI-enabled pharmacovigilance includin...

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PV AI Technology Ecosystem: Comprehensive understanding of the AI technology ecosystem relevant to pharmacovigilance including c...

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AI System Validation Principles: Understanding of validation principles for AI systems in pharmacovigilance including GAMP 5 AI consi...

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Type A Reactions: Dose-dependent, predictable, pharmacologically mediated responses...

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Type B Reactions: Dose-independent, unpredictable, idiosyncratic responses...

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Type C Reactions: Chronic effects from long-term exposure...

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Type D Reactions: Delayed effects appearing after treatment discontinuation...

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Type E Reactions: End-of-treatment withdrawal effects...

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Type F Reactions: Failure of therapy due to drug interactions or resistance...

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Pharmacokinetic Factors: Absorption, distribution, metabolism, excretion variations...

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Pharmacodynamic Interactions: Receptor binding, dose-response relationships, therapeutic windows...

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Drug-Drug Interactions: Synergistic, antagonistic, and additive effects...

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Drug-Disease Interactions: Impact of comorbidities on drug safety profiles...

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Pharmacogenetic Influences: Genetic polymorphisms affecting drug metabolism and response...

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Causality Assessment Methods: WHO-UMC, Naranjo, Bradford-Hill criteria...

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Temporal Relationship Analysis: Onset timing, dose-response patterns, dechallenge/rechallenge...