Deviation Handling and Quality Risk Management
This guidance Based on WHO recommended requirements, these documents provide further explanations with examples in order to facilitate implementation.
Deviation handling
Quality Risk Management was mainly designed to be used prospectively when manufacturing operations are defined and validated.
The potential deviations are identified and avoided by implementing risk control measures and preventive actions.
QRM is based on the identification of product attributes and operational parameters which are critical to manufacturing operations in order to identify in advance their associated risks.
This guidance document describes to used as criteria for the categorization and treatment of events, and eventually, deviations.
The application of risk management in dealing with deviations is not only practical but provides a framework for a decision-making process based on a scientifically sound and objective approach, taking decisions to be confidently upheld before the regulatory authorities.
Under this approach, a sequence of steps may be identified when handling events and possible deviations:
1.Event Detection
Decision Making Process / Deviation Categorization
Deviation Treatment
Root cause investigation
CAPA
Event detection:
How personnel react when in presence of an event is the first challenge to the system, and it largely depends on their level of training, qualification, commitment, and support form upper management.
The personnel are expected to be alert and aware of possible undesirable events and clearly know what to do in terms of documenting and communicating them. React and make decisions can be systematized and improved by the use of a decision tree to initially screen events based on their risk and impact on the product, record, and investigate if needed.
Deviation Categorization
The decision tree is a simplified risk assessment that answers the following questions when an event is encountered: A. Can the event affect a product attribute, manufacturing operational parameter or the product’s quality?
B. Does the event contradict or omit a requirement or instruction contemplated in any kind of approved written procedure or specification?
Incidents
If the answer is NO for questions a. and b. above,
That event may be considered an Incident (irrelevant event, not impacting product´s quality).But needs to be documented (e.g.: recorded in batch record or logbook, as appropriate) in case it needs to be retrieved later as part of an investigation as applicable.
The following are possible examples of incidents.
Each event needs to be analyzed as described above developing an objective and justified criteria avoiding the natural bias.
Incidents could be categorized differently with proper justification:
– Temporary power failure in a warehouse where no temperature sensitive materials are stored, with no temperature excursion from the established range.
– Production process parameters or environmental monitoring data reach alert levels but are still within acceptable range.
On the Other hand, if the answer be YES for questions a. and b. above and based on the decision tree, the event shall follow a deviation category. Deviations should require a higher level of analysis and documentation, and are usually covered by a deviation handling procedure.
A decision needs to be made to categorize the deviation as Minor, Major or Critical. This decision is based on possible impact (or hazard) and risk on the process and product quality by the use of any QRM tool.
Minor Deviations
When the deviation does not affect any quality attribute, a critical process parameter, or an equipment or instrument critical for process or control, it would be categorized as Minor.
Examples of minor deviations are given below:
– Skip of FEFO principle (first expired-first out) in raw material handling. – Balance out of tolerance used to determine gross weight of raw materials upon reception.
– Pressure differential out of established limits in class D washing area.
– Inadequately trained personnel to perform warehouse cleaning activities.
Major Deviations
The deviation affects a quality attribute, a critical process parameter, an equipment or instrument critical for process or control, of which the impact to patients (or personnel/environment) is unlikely, the deviation is categorized as Major requiring immediate action, investigation, and documented.
Examples of major deviations are given below:
– Use of unapproved reference standard to test an API or drug product.
– Inadequately trained personnel to perform sterility tests.
– Production started without line clearance.
– Filter integrity test has been carried out using equipment with no documented installation qualification completed. – Gross misbehavior of staff in a critical aseptic process.
– Pressure differential out of established limits in aseptic fill areas.
– Operational parameter out of range for a parameter defined as non-critical.
– Untrained personnel responsible for segregating the approved and rejected raw material in the warehouse
Critical Deviations
The deviation affects a quality attribute, a critical process parameter, an equipment or instrument critical for process or control, of which the impact to patients (or personnel or environment) is highly probable, including life threatening situation, the deviation is categorized as Critical requiring immediate action, investigated, and documented
Examples of critical deviations are given below:
– Expired or rejected API component used.
– Sterilization record of product-contact material used in aseptic filling process not available or unacceptable.
– Incomplete inactivation stage of fermentation.
– Temperature out of control limit during detoxification stage.
Note 1:
All Deviations need to be analyzed based on objective and justified criteria and they could be categorized differently in minor, major and critical deviations with proper justification.
Note 2:
A pre-existent QRM will always help answering these questions and categorizing the events. When a QRM information is not available, all process parameters are potentially critical until there is sufficient data (process and/or developmental) to justify the contrary.
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