Regulatory Use & Lifecycle Management

Contestability & redress

Data & digital tools: 

If necessary, establish processes or mechanisms for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms (Ref. ISO 24368; WHO Ethics and Governance of AI for Health).

Personnel Training:

If necessary, train system users about processes/mechanisms for questioning and for redress for individuals and groups that are adversely affected by decisions based on algorithms. Train both developers and end users in appropriate strategies for challenging model decisions and outcomes.​

Links:

ICH Q1: https://database.ich.org/sites/default/files/Q1A%28R2%29%20Guideline.pdf

ICH Q2(R2): https://database.ich.org/sites/default/files/ICH_Q2%28R2%29_Guideline_2023_1130_ErrorCorrection_2025.pdf

ICH Q10: https://database.ich.org/sites/default/files/Q10%20Guideline.pdf

ICH Q12: https://database.ich.org/sites/default/files/Q12_Guideline_Step4_2019_1119.pdf

ICH M15: https://database.ich.org/sites/default/files/ICH_M15_EWG_Step2_DraftGuideline_2024_1031.pdf

ISO/IEC 23894:2023 (Information technology — Artificial intelligence — Guidance on risk management): https://www.iso.org/standard/77304.html

ISO/IEC TR 24027:2021 (Information technology — Artificial intelligence (AI) — Bias in AI systems and AI aided decision making): https://www.iso.org/standard/77607.html

ISO/IEC 27001:2022/Amd 1:2024 (Information security, cybersecurity and privacy protection — Information security management systems — Requirements): https://www.iso.org/standard/88435.html

ISO/IEC 27701:2025 (Information security, cybersecurity and privacy protection — Privacy information management systems — Requirements and guidance): https://www.iso.org/standard/27701

ISO 42001:2023 (Information technology — Artificial intelligence — Management system): https://www.iso.org/standard/42001

ISPE GAMP Guide: Artificial Intelligence: https://ispe.org/publications/guidance-documents/gamp-guide-artificial-intelligence?utm_source=HubSpot&utm_medium=Popup&utm_campaign=Guide%20GAMP%20AI&hsCtaAttrib=192776150296

ASME V&V 40: https://www.asme.org/codes-standards/find-codes-standards/assessing-credibility-of-computational-modeling-through-verification-and-validation-application-to-medical-devices

FDA AI/ML TPLC guidance: https://www.fda.gov/regulatory-information/search-fda-guidance-documents/artificial-intelligence-enabled-device-software-functions-lifecycle-management-and-marketing

EMA and FDA set common principles for AI in medicine development: https://www.ema.europa.eu/en/news/ema-fda-set-common-principles-ai-medicine-development-0

EMA Reflection paper on the use of Artificial Intelligence (AI) in the medicinal product lifecycle: https://www.ema.europa.eu/system/files/documents/scientific-guideline/reflection-paper-use-artificial-intelligence-ai-medicinal-product-lifecycle-en.pdf

National Cyber Security Centre Machine learning principles: https://www.ncsc.gov.uk/collection/machine-learning-principles

Artificial Intelligence Playbook for the UK Government: https://www.gov.uk/government/publications/ai-playbook-for-the-uk-government/artificial-intelligence-playbook-for-the-uk-government-html

UK Government Implementing the UK’s AI regulatory principles: initial guidance for regulators: https://www.gov.uk/government/publications/implementing-the-uks-ai-regulatory-principles-initial-guidance-for-regulators/implementing-the-uks-ai-regulatory-principles-initial-guidance-for-regulators