May 4, 2023 Industry Updates,Insights

ICH-Q9(R1): Formal Revision to Quality Guideline for Quality Risk Management 

In May 2023, the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) published a formal revision to its Quality Guideline covering Quality Risk Management – ICH Q9.  The ICH-Q9 guideline is a process for the assessment, control, communic...

In May 2023, the International Council for Harmonization of Technical Requirements for Pharmaceuticals for Human Use (ICH) published a formal revision to its Quality Guideline covering Quality Risk Management – ICH Q9.  The ICH-Q9 guideline is a process for the assessment, control, communication, and review of risks to the quality of the drug product across the product lifecycle. 

The overall objective of the revised guideline document is to improve current quality risk management programs by creating more objective risk assessments, with the understanding that more objective risk assessments could potentially reduce quality defects as well as drug shortages.  

Four New Subsections 

While the primary principles and concepts included in the original ICH Q9 guideline document from 2005 remain the same, there are four new subsections in the revised guideline.  

Three of the four new subsections are included in Section 5 of the revised guideline document covering risk management methodology and focus specifically on: 

  • Formality (Section 5.1) 
  • Risk-based decision-making (Section 5.2) 
  • Subjectivity (Section 5.3) 

The fourth new subsection, covering Quality Risk Management integration into associated industry and regulatory operations, is included in Section 6 of the revised guideline and focuses on: 

  • Product availability risks (Section 6.1), 

Excerpts from Section 5 

Section 5.1 – Formality in QRM 

Formality in quality risk management is not a binary concept (i.e., formal/informal); varying degrees of formality may be applied during quality risk management activities, including when making risk-based decisions. As such, formality can be considered a continuum (or spectrum), ranging from low to high.  When determining how much formality to apply to a given quality risk management activity, certain factors (e.g., uncertainty, importance, and complexity) may be considered.  The overall approach for determining how much formality to apply during quality risk management activities should be described within the quality system.  Resource constraints should not be used to justify lower levels of formality in the quality risk management process. Risk scores, ratings, and assessments should be based on an appropriate use of evidence, science, and knowledge. Regardless of how much formality is applied, robust management of risk is the goal of the process. 

  

Section 5.2 – Risk based Decision-Making 

Effective risk-based decision-making begins with determining the level of effort, formality and documentation that should be applied during the quality risk management process.  Higher levels of formality in quality risk management may require higher levels of structure in relation to risk-based decision-making. There can be varying degrees of structure regarding approaches for risk-based decision-making, and these can fall along a spectrum. In this new sub-section, some descriptions are provided for highly structured vs. less structured processes for risk-based and rule-based decision-making processes.  These descriptions are useful because they address uncertainty and facilitate informed decision making by regulators and the pharmaceutical industry. They also help recognize where uncertainty remains, so that appropriate risk controls can be identified to enhance understanding of those variables and further reduce the level of uncertainty. 

  

Section 5.3 – Managing and Minimizing Subjectivity 

Subjectivity or bias can impact every stage of a quality risk management process, especially the identification of hazards and the estimation of probability of occurrence and severity of harm. It can also impact the estimation of risk reduction and the effectiveness of decisions made from quality risk management activities. Subjectivity can be introduced through differences in how risks are assessed and in how hazards, harms, and risks are perceived by different stakeholders. Subjectivity can also appear when risk questions are inadequately defined, and when tools have poorly designed risk scoring scales.  While subjectivity cannot be completely eliminated, all participants involved with quality risk management activities should acknowledge, anticipate, and address the potential for subjectivity. 

 

Excerpt from Section 6 

Section 6.1 – Product Availability Risks Arising from Quality/Manufacturing Issues 

While manufacturing and supply chain diversity can enable product availability, increasingly complex supply chains lead to interdependencies. These interdependencies can lead to systemic quality/manufacturing risks that impact the strength of the supply chain. The application of quality risk management enables the proactive identification and implementation of preventive measures that support product availability. 

An effective pharmaceutical quality system drives both robust supply chains and sustainable GMP compliance. The pharmaceutical quality system also uses quality risk and knowledge management to provide an early warning system that supports oversight and response to evolving quality/manufacturing risks. When risk-based drug shortage prevention and mitigation activities are performed, the level of formality that is applied to those activities may vary (see section (5.1)) and should be aligned with the level of risk associated with a loss of availability of the product(s).   

Three examples of Quality/Manufacturing factors that can affect supply reliability, as well as product availability, are provided in this new sub-section. These are Manufacturing Process Variability and State of Control, Manufacturing Facilities and Equipment, and Oversight of Outsourced Activities and Suppliers. 

 

How RegDev Can Help 

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