Validations: Model Verification/Validation & Explainability
KPI Sets for Model Validation Programs KPI Sets for Model Validation Programs Understanding the Importance of Model Validation in Pharmaceutical Development Model validation in the pharmaceutical industry, particularly with the advent of artificial intelligence and machine learning (AI/ML), has become a critical aspect of ensuring compliance within Good Automated Manufacturing Practice (GxP) guidelines. It is imperative to establish clear Key…
Peer Review Checklists for Model Evidence Peer Review Checklists for Model Evidence in AI/ML Model Validation Introduction to AI/ML Model Validation in GxP Analytics In recent years, the incorporation of artificial intelligence (AI) and machine learning (ML) in Good Practice (GxP) analytics has brought a wave of innovations in pharmaceutical development and clinical research. However, the validation of these AIs…
Linking Model Specs to URS and Risk Linking Model Specs to URS and Risk Introduction to AI/ML Model Validation in GxP Analytics In the pharmaceutical industry, the application of artificial intelligence (AI) and machine learning (ML) is becoming increasingly integral to regulatory compliance, drug development, and clinical operations. However, ensuring proper validation of these models is essential for maintaining quality…
Acceptance Criteria That Survive Review Acceptance Criteria That Survive Review Introduction to Model Verification and Validation in GxP Analytics The integration of artificial intelligence (AI) and machine learning (ML) models in Good Practice (GxP) environments has revolutionized the pharmaceutical landscape, particularly in areas such as drug development, clinical trials, and regulatory compliance. The implementation and lifecycle management of these models…
Interpreting Model Degradation Signals The rapid growth of artificial intelligence (AI) and machine learning (ML) in pharmaceutical and healthcare settings necessitates robust validation processes to ensure that models remain reliable and compliant with Good Automated Manufacturing Practice (GxP) regulations. This tutorial serves as a comprehensive guide to interpreting model degradation signals, detailing the process of verification and validations, the significance…
Top V&V Mistakes—and How to Fix Them Understanding Verification and Validation in AI/ML Model Development The validation and verification (V&V) process is critical in the world of Good Automated Manufacturing Practice (GxP) analytics, especially when it involves Artificial Intelligence (AI) and Machine Learning (ML). These technologies introduce complexities that demand rigorous scrutiny, ensuring models meet specified performance criteria and comply…
Inspection Storyboards for V&V and XAI Inspection Storyboards for V&V and XAI In the ever-evolving landscape of pharmaceutical sciences, the integration of Artificial Intelligence (AI) and Machine Learning (ML) for enhancing GxP (Good Practice) analytics has become pivotal. As AI/ML models gain traction, their validation and verification (V&V) require a structured approach to ensure compliance with regulatory standards established by…
Model Cards & Fact Sheets for GxP: A Comprehensive Guide to AI/ML Validation In the rapidly evolving world of pharmaceutical and biotechnology sectors, the incorporation of artificial intelligence (AI) and machine learning (ML) into Good Practice (GxP) frameworks has emerged as a fundamental necessity. This tutorial aims to provide a step-by-step guide on the creation and utilization of Model Cards…
Template Libraries: Protocols and Reports for Models Template Libraries: Protocols and Reports for Models Introduction to AI/ML Model Validation in GxP Analytics The use of Artificial Intelligence (AI) and Machine Learning (ML) in Good Practice (GxP) analytics is becoming increasingly prevalent in the pharmaceutical industry. The validation of these models is critical to ensure their reliability, accuracy, and compliance with…
Automation of V&V Evidence Collection Understanding the Framework of Verification and Validation in AI/ML In the context of pharmaceutical validation, specifically concerning AI/ML models, it is essential to comprehend the overarching principles of verification and validation (V&V). Verification entails ensuring that the model meets the specified requirements and works as intended, whereas validation focuses on confirming that the model accurately…