QbD Analytical

Analytical QbD

In football, part of the coach’s job is to analyze an upcoming opponent, identify both their strengths and weaknesses, and then develop plays that are tailored to a game plan designed for victory. When the quarterback calls the play in the huddle, everyone settles into the pre-planned formation and the goal is forward progress, preferably into the end zone. If something goes wrong, the tapes are reviewed in order to learn from the mistake. Football, like any team sport, uses a carefully planned and executed strategy to eliminate failure, and ultimately win the game.

In business, especially one that deals with human lives, it only makes sense that this same calculated risk-based and iterative approach to reducing error should be applied. Many would argue that the most effective way to do this in pharma would be by using a Quality by Design (QbD) methodology. However, just like in the example of football, in order to do it successfully, it takes an entire team of dedicated experts with the right mind set working toward the same goal.

Rosario LoBrutto, Senior Director, Head of Development Parenterals at Teva

Rosario LoBrutto is currently Senior Director, Head of Development Parenterals at Teva. Throughout his career, he has designed, coordinated, and implemented QbD programs and provided risk management trainings to product development units (quality, analytical, formulation, process chemists), and quality control, regulatory, and operations units. He understands the value of risk assessment and the need for a strategy that achieves proactive failure reduction as opposed to reactive troubleshooting. “Quality by design is part of the development strategy to get the best possible method or analysis technique and to implement the right risk analysis at the right time to understand the critical sources of variability and how to proactively control it,” explains LoBrutto.

In his interpretation of the ICH Harmonised Tripartite Guideline for Pharmaceutical Development Q9, a guidance document for QbD, LoBrutto breaks the QbD process down into three phases of risk facilitation as it relates to analytics:

• Risk Identification
• Risk Analysis
• Risk Evaluation

These three phases are the necessary prerequisites to build the backbone for the risk mitigation process. The key is to organize the data systematically and visualize the entire complex processes, in order to better facilitate decision making. Like football, LoBrutto says the first step in applying QbD to analytics is identifying the possible areas of weakness, or the risks.

Risk Facilitation Methods

This Risk Identification phase of the process is applied in the early stages of the project. This is where the team identifies the critical method attributes (CMA) and analytical method variables (AMV) using brainstorming and cause and effect diagrams. CMAs are an element of method performance that must be measured to assess whether a method is capable of producing the desirable reportable result. The AMV is any variable that forms part of the method definition and can be varied continuously or specified at controllable unique levels. LoBrutto recommends creating an analytical method fishbone, or Ishikawa, diagram of the method variables and CMAs. The head of the fish represents a CMA identified during the brainstorm session, and each bone of the fish represents the AMV potentially influencing that CMA.

In the next phase, Risk Analysis, a heat map or traffic light is created, which is a color-coded matrix of each CMA and method variable. The purpose is to indicate the potential impact a method variable could have on a CMA. Red indicates a high risk, green is low, and yellow is somewhere in the middle. If it is deemed yellow or red, that variable is denoted as a critical method variable (CMV).

Throughout this process, LoBrutto says a knowledge management system should be used to capture the process as decisions are made and control strategies are established. He explains, “Knowledge management is an iterative process, so you need to have a very robust knowledge management system to capture the development strategies tested, the decisions made by the team, the challenges observed, as well as the risk mitigation strategies implemented to ensure a robust and rugged method is developed and validated and eventually transferred to the launch site.” While his team utilizes a knowledge management software tool called Light Pharma, there are various tools available for this purpose. After launch, a system should be used to continually monitor the analytical methods as part of continual improvement efforts.

In the final phase, Risk Evaluation, failure mode effect analysis (FMEA) is applied. This is a systematic tool to help identify the probability of a variable to deviate higher or lower from set point (target), its severity if it does deviate, and its current detection. It evaluates the probability of variable deviating from a certain defined set point (qualitative or quantitative), impact on the reportable result, and the ability to detect and prevent deviation in the variable from the target set point, prior-to-system suitability, after-system suitability, and prior-to-injection of sample (in case of chromatographic method). “Your goal is to assess the potential root causes for variables to deviate from set point and then, based on the cause and magnitude of the impact, determine the best control strategy to mitigate the risk,“ says LoBrutto.

You Can’t Do This From The Top Down

The QbD methodology is more than just learning the steps necessary to integrate it into a company’s analytical processes, and one of the biggest challenges a company can face when implementing any new process or policy is getting their employees on board with the change. It is no different when it comes to QbD. Management certainly has the ability to approach it with a “this is the way it’s going to be” attitude, but how effective will that be? “If it is driven from top down, it may not be readily accepted,” says LoBrutto. “A culture needs to be instilled where it’s embedded in the organization. The people have to realize the value and the importance of it, embrace the change, and then lead the way. Have them look at method failures or systems suitability failures and have them look back retrospectively. What could have been done differently and how could it have been progressed differently by using analytical QbD?”

Going forward, how do you know once you’ve implemented analytical QbD that its working and the mindset of your people have changed? LoBrutto says the answer is in the metrics. “In the short term, you could review the number of system suitability failures, laboratory investigations, or the number of iterations for methods development due to poor method performance. If you applied quality by design, it’s quite possible those numbers have gone down because now you’re developing and building quality into the method from the start,” says LoBrutto. “As a longer term objective, how many successful method transfers do you have? That’s another true metric. A lot of times you have method transfer failure, and that’s because robust and/or rugged methods may not have been developed up front during development.”

When implementing any new process, it’s common for employees to be averse to change. “There are a lot of experts in the organization who believe they know, based on prior experience, what’s worked before. They want to know why they even have to change,” he says. “The message here is that often the knowledge is not retained by the experts. When a person leaves the organization or transfers from one product to another, it’s hard to obtain that prior information.” For junior employees, LoBrutto encourages them to leverage on the expertise of those subject matter experts who are the most seasoned when it comes to hands-on experience with methods development/troubleshooting, supplemented with knowledge gained through their academic studies and current literature. He adds, “If you talk to your peers who have been in the industry and have experienced these similar types of methods and they share their knowledge with you about what could go wrong, and the new group on the new project leverages on that knowledge, now they’re not going to make the same mistakes, right? Knowledge is power only when you share it.”

Another important component of successfully implementing QbD is ensuring your team has the right training, specifically around the risk management tools. First, they must understand the process summarized above. Second, it is equally important they understand the tools used throughout the work flows in order to assess the risk, evaluate the risk, and then actually perform experiments in a structured way to reduce and control the risk.

Why Use Analytical QbD?

The hesitation around implementing a QbD program at any company usually stems from the extra investment of both time and money (new equipment, training, statisticians, etc.), which can vary based on the needs of the project. However, the extra work upfront can alleviate unnecessary costs down the road. Lobrutto says if a company looks at the overall dollars spent on systems suitability failures, deviation investigations, and method transfers, the return on investment is actually significant because quality by design reduces or even eliminates a lot of those costs.

For example, if a deviation investigation were to require 100 person hours from someone making a salary of $150K over 250 work days, that is cost of about $7,500 for every deviation investigation completed. Method transfers can take up to one to two weeks to complete with multiple people working on one transfer. If one fails, many man hours and money is wasted. “When you’re reducing that, you reduce capital requirements, you reduce resource costs, and you reduce non-value added time, which is the time spent replicating those experiments again,” he explains. “You’re also not having the additional conversations and documentation in regards to the closing the deviation, because it could have been avoided.”

He adds that by truly challenging the robustness of your methods, you provide a structured approach aligned with a risk- and science-based approach to methods development and methods validation, which results in business benefits for both the company and the patient. “When you incorporate analytical Quality by Design throughout the lifecycle of the method, this embeds quality into the DNA of the method and can generate a positive return on your investment because you are lowering operating costs, reducing deviation investigations, and reducing system suitability failures. At the end of the day, this translates into significant business benefits because you have greater knowledge, more robust methods, better knowledge preservation, better understanding of the risks, and control strategies to mitigate the risks, which allows you to develop right first time methods and truly meet the needs of your business.”

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