Articles tagged with “fda-guidance”

Understand FDA Predetermined Change Control Plans (PCCPs) for AI/ML Software as a Medical Device. Review Section 515C, FDA guidance, and implementation.

Examine clinical evidence generation for AI diagnostic SaMD. This report covers real-world performance studies, FDA guidelines, and post-market surveillance.

Analyze the FDA CDER 2026 guidance pipeline for artificial intelligence in drug manufacturing and digital health technologies in pharmaceutical development.

Review the evolving FDA regulatory framework for AI/ML SaMD. This guide explains PCCPs, total product lifecycle management, and 2026 compliance standards.

Examine how digital twins in clinical trials function as virtual control arms. This report reviews FDA guidance, AI models, and implementation requirements.

Analysis of FDA digital health guidance covering SaMD, AI, and cybersecurity. Understand 2026 updates, risk categorization, and regulatory compliance pathways.

Compare FDA's Computer Software Assurance (CSA) vs CSV for AI systems. Learn risk-based validation strategies for machine learning in life sciences.

Analyze the transition from CSV to FDA's Computer Software Assurance (CSA). This guide details risk-based validation strategies and compliance impacts.

Learn cybersecurity requirements for AI medical devices. Covers FDA guidance, EU regulations, SBOM mandates, and defenses against adversarial AI attacks.

Learn the key differences in regional eCTD submission guides from the FDA, EMA, & Health Canada. This guide covers Module 1 variations and the shift to eCTD v4.

Learn the compliant process for answering off-label HCP inquiries. This guide details FDA guidance, medical information SOPs, and software for case management.

Learn what must be included in a pharma quality agreement. This 2026-updated guide covers key clauses, sponsor vs. CDMO responsibilities, and GMP regulatory requirements including FDA 2016 guidance, EU GMP Annex 1 (2023), ICH Q9(R1), and DSCSA.

Lifecycle approach to biotech process validation: PPQ and CPV planning, execution, and monitoring under FDA, EMA Annex 1/15, ICH Q9(R1), Q12, and Q13 guidance.

Learn how Generative AI (GenAI) applies to Medical Affairs in pharma. This guide covers key use cases, compliance guardrails, and the risks of using LLMs.

Learn about the FDA's AI guidance for drug development. This article explains the 7-step credibility framework, context of use (COU), and risk-based approach.

Understand the FDA's final Computer Software Assurance (CSA) guidance, a risk-based shift from CSV for pharma & biotech. Learn key principles for compliance.

Learn how to integrate GAMP 5 (2nd Ed.) and FDA's final Computer Software Assurance (CSA) guidance (Sept 2025, updated Feb 2026). Shift from CSV to risk-based validation.

Learn how generative AI and LLMs assist in drafting pharma IND & CTA submissions. This guide covers benefits, risks, GxP compliance, FDA/EMA 2026 joint AI principles, and tools like AutoIND and Narrativa.

A comprehensive guide to the Target Product Profile (TPP) for drug development, updated for 2026. Learn TPP components, FDA and ICH guidance, IQVIA adoption data, and how to align your TPP with the final drug label.

An in-depth guide to adaptive trial design, updated for 2026. Covers ICH E20 guideline, FDA Bayesian guidance, AI-powered trial optimization, and how prespecified changes based on interim data make clinical trials more efficient and ethical.

Learn how to manage protocol deviations in clinical trials. Updated for ICH E6(R3) and FDA 2024 draft guidance, covering classification, reporting, and prevention for data integrity and GCP compliance.

Learn the 9 ALCOA+ principles for GxP data integrity. Updated for 2026 with ICH E6(R3) finalization, EU GMP Chapter 4 ALCOA++ draft, and latest FDA enforcement trends

Analysis of AI medical devices in 2025. Learn about market growth, 950+ FDA-cleared devices, new regulations like the EU AI Act, and key clinical challenges.

A practical guide to clinical trial phases 1–3 for pharma IT: objectives, compliance, costs, and IT infrastructure for modern drug development.