The document discusses best practices for risk assessment, which is the first step in Quality by Design (QbD). It recommends that risk assessment should focus on linking process parameters (CPP) to critical quality attributes (CQA) and how they ultimately impact the quality target product profile (QTPP). Failure Mode and Effects Analysis (FMEA) is not always the ideal tool for early development projects due to a lack of process understanding. Instead, it suggests using a simpler rating system of impact vs probability of occurrence to prioritize risks. Building these linkages from QTPP to CQA to CPP is key to developing a successful control strategy and executing QbD projects.
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First Step in QbD - How to Get it Right
1. First Step in QbD:
How to get it Right
ISPE 2014
Sun Kim, PhD
2. Are You ...
1. Starting a QbD project & want to skip
common pitfalls?
2. Tried QbD but management and colleagues
were skeptical?
3. undecided if QbD is for your organization?
3. QbD in 3 Steps
1. Risk Assessment:
Build Relationships from QTPP, CQA to CPP (CMA)
2. Design Space
3. Control Strategy
9. Sampling of LinkedIn Comments
“It is like a loop I always have to dealt with,
everytime!” - S of Angelini
“The first part of your blog literally had me
laughing out loud. This is so true and relevant.”
-I of Teva
“I completely agree with you that FMEA,
especially in the early development, is not the
ideal tool” - F of PTM Consulting”
10. Sampling of LinkedIn Comments
“How refreshing to see this. Thank you so
much for noting that the FMEA emperor may be
missing some clothing.” - D, Statistician
“The formality of risk assessment should align
with the level of product and process
understanding. FMEA definitely has its place,
but later in the development process.” - S of
UpsherSmith
11. Agenda
0. Story
1. Why Risk Assessment is Critical to QbD
2. Why You shouldn’t blindly apply FMEA for
QbD development projects.
3. A Smarter Risk Assessment Approach
12. Why Risk Assessment determines
success and failure of QbD
1. 1st step & planning stage of QbD
2. Output is Control Strategy
3. Precursor to Design Space studies
13. Why Risk Assessment determines
success and failure of QbD
1. 1st step & planning stage of QbD
a. Scientists dread these types of meetings
b. If this doesn’t go well, the momentum fizzles
c. Links QTPP-CQA-CPP-CS
14. Why Risk Assessment determines
success and failure of QbD
1. 1st step & planning stage of QbD
a. Scientists hate these types of meetings
b. If this doesn’t go well, the momentum fizzles
c. Links QTPP-CQA-CPP-CS
2. Output: Control Strategy
a. Prioritized list of projects or experiments
15. Why Risk Assessment determines
success and failure of QbD
1. 1st step & planning stage of QbD
a. Scientists hate these types of meetings
b. If this doesn’t go well, the momentum fizzles
c. Links QTPP-CQA-CPP-CS
2. Output Control Strategy
a. Prioritized list of projects
3. Precursor to Design Space studies
a. Links to Design Space
16. FMEA (Failure Mode Effects and Analysis)
Goal: “Identify all possible failures...prevent…”
Ref: ASQ
17. 1. Most attributes become “Critical.”
A. FMEA’s definition:
RPN (Risk Priority Number) =
Severity x Occurrence x Detectability( or Controllability)
B. Classic definition
Risk Index =
Severity x P(Occurrence)
http://plato.stanford.edu/archives/win2012/entries/risk/#DefRis
W. Gilchrist, ?Modelling Failure Modes and Effects Analysis,? International Journal of Quality and Reliability Management 10 (5), 16-23, 1993.
S. Kmenta, Scenario-based FMEA Using Expected Cost, A new perspective on evaluatng risk in FMEA, IIE Workshop,January 22, 2002.
S. Kmenta and K. Ishill, Scenario-Based Failure Modes and Effects Analysis using Expected Costs, Journal of Mechanical Design 126, 1027-1036,
2004.
D. Wheeler, ?Problems with Risk Priority Numbers,Quality Digest, 2011 Available at:
http://www.qualitydigest.com/inside/quality-insider-article/problems-risk-priority-numbers.html
18. 2. Inappropriate ordinal scale
At the development stage where scale-up details are not
available, scientist do not yet understand the manufacturing
process well enough to list realistic failure modes.
Recommendation:
Use Low-Med-High or better yet, 0-1-3-9 scale
http://plato.stanford.edu/archives/win2012/entries/risk/#DefRis
W. Gilchrist, ?Modelling Failure Modes and Effects Analysis,? International Journal of Quality and Reliability Management 10 (5), 16-23, 1993.
S. Kmenta, Scenario-based FMEA Using Expected Cost, A new perspective on evaluatng risk in FMEA, IIE Workshop,January 22, 2002.
S. Kmenta and K. Ishill, Scenario-Based Failure Modes and Effects Analysis using Expected Costs, Journal of Mechanical Design 126, 1027-1036,
2004.
D. Wheeler, ?Problems with Risk Priority Numbers,Quality Digest, 2011 Available at:
http://www.qualitydigest.com/inside/quality-insider-article/problems-risk-priority-numbers.html
19. 3. Mediocre Control Strategy
Typical Examples:
equipment maintenance, training or monitoring
- feed control valves, steam traps, tank, flange, piping leaks
- pH, DO, backpressure monitoring
Ref: Pharmaceutical Engineering, May/June 2010, Vol. 30, No. 3, P.1-11
20. Smarter Approach
1. Scientist-driven: Y=f(X), QFD=C&E + FMEA
2. Process Map: TRD (Technical Requirements Document), IMPD
(Investigational medicinal product dossier)
3. Link how a CPP matters to the Patient
(QTPP)
4. Risk = Impact x P(Occurrence)
Yoji Akao, Quality Function Deployment: Integrating
Customer Requirements Into Product Design,
Productivity Press, 1990.
21. How will a Process Parameter
affect a Patient?
Linking QTPP-CQA-CPP/CMA
31. The First Step in QbD
1. Risk Assessment is the Blueprint of QbD.
2. Focus on building Y=f(x) for QTPP-CQA-CPP/CPP
3. Save time by using Templates and a simple rating system
Recommendation:
● Use LeanQbD approach - Get it at LeanQbD.com
● More Tips from QbDWorks.com
Who particiated in a Risk Assessment? Who has facilitated a Risk Assessment? Who used FMEA-based approach?
Since most of us are tired, I’ll just gossip rather than a formal presentation.
Controversial.
Who is implementing QbD now?
Ok who fits in category 1,
now 2,
now 3?
What are the 3 steps in QbD?
Have you experienced this situation? Maybe it was a little exaggerated to emphasize the point. If you have done a Risk Assessment using FMEA, the chances are that you have. After spending 3 months in risk assessment meetings, too many attributes become critical. This defeats the purpose of conducting risk assessment.
FMEA is not at fault. FMEA sessions become productive when the participants have gained some experience in the product or process.
Let’s take a step back. What is the main purpose of Risk Assessment? To identify the top critical attributes and devise a control strategy around the high risk items so that we don’t miss the obvious ones.
What it is not: list all possible things that could go wrong. The chances are that the length of the list depends on our imagination and time.
LinkedIn QbD group
Think of QbD as your child
Another uneasy feeling for QA comes from pressure to remove or ignore intermediate controls prematurely, or what could be called QbB, Quality by Blindfold.
Think of QbD as your child
This is what the development will work on for the next months and years.
starting with high-risk items
Think of QbD as your child
Multiplication is not defined for ordinal metrics. It is well known in the literature that RPN does not preserve rank order. So why not use probability and cost metrics instead of ranks?
risk = the statistical expectation value of an unwanted event which may or may not occur.
Risk calculation is inflated due to detectability.
FMEA’s Risk calculation uses the equation below:
Risk Priority Number = Severity x Occurrence x Detectability( or Controllability)
Three factors:
1. Severity
2. Occurrence
3. Detectability (or Controllability)
Let’s compare this with the classic definition of risk.
Risk Index = Impact of Risk event x Probability of Occurrence
Two factors:
1. Impact
2. Probability
Notice how FMEA’s (http://en.wikipedia.org/wiki/Failure_mode_and_effects_analysis) risk priority number (RPN) has an extra factor -- Detectability (or Controllability). According to the classic definition, (Ref: http://plato.stanford.edu/archives/win2012/entries/risk/, http://en.wikipedia.org/wiki/Risk_management) controllability or detectability are already included in the Occurrence factor.
For example, drug potency is a quality attribute and let’s say the manufacturer has a good control strategy or detectability with sensors, then the occurrence will be low. The same goes for the opposite condition. If the manufacturing process has low detectability or controllability for potency, then occurrence of potency going out of specification will be high. As you can see, detectability (or controllability) is a sub-factor of Occurrence. In other words, by adding detectability, FMEA’s formula inflates the Risk number. This is why much of the Quality Attributes end up in the red zone.
Recommendation: Stick with the classic risk definition: Impact x Occurrence.
Fighting over the ordinal rating of 3 versus 4 is meaningless at this stage. I’ve seen hours of disagreement over severity, occurrence, controllability and detectability. If you have an ordinal scale from 0 to 10, you will be wasting much time.
Recommendation: Go with Low-Med-High or better yet, 0-1-3-9 scale (will discuss in the next article)
After finishing FMEA, you will get a list of “high risk” or Critical Quality Attributes (CQA). But how can we control those CQA’s? Remember, the purpose of risk assessment is to devise a control strategy to prevent major failures. However, CQA’s are just symptoms or results. We can not directly control them. What we can control are CPP’s (Critical Process Parameters).
Control strategy or plan should be on how to contorl the CPP’s. In order to do this, scientists must understand the relationship between CQA’s and CPP’s. If we mathematically model the manufacturing processes in a transfer function of Y=f(X), CQA’s are Y’s (output) and CPP’s are X’s (input).
With FMEA, control plan remains at the trivial level such as equipment maintenance or monitoring plans. At the development stage, where the process itself still can be changed and equipment details are unavailable, information on the Transfer Function, Y=f(X), is of more value -- how process parameters affect the quality attributes. With this knowledge, scientists can design or order equipments around the appropriate range of these parameters.
Most importantly, your organization will have missed out on the opportunity to understand the process.
FMEA sessions are productive when the team has some mature knowledge of the process. Some folks may argue the author doesn’t understand FMEA. During my PhD at Stanford University, I’ve researched, practiced, taught, and published peer-reviewed journal articles on FMEA. There is no doubt I highly appreciate the tool. However a tool is a tool — works great for the right application–may not for the wrong ones.