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The adoption of quality by design in small-molecule drug development and manufacturing continues to evolve as the industry seeks ways to augment process understanding for APIs. T he science- and risk-based approach in quality by design (QbD) entails greater product and process understanding as a means to ensure product quality. These concepts are embodied in ICH guidelines Q8 (R2) Pharmaceutical Development, Q9 Quality Risk Management, Q10 Pharmaceutical Quality System, and most recently, Q11 Development and Manufacture of Drug Substances (Chemical Entities and Biotechnological/ Biological Entities) (1–4), which offer a lifecycle approach to continual improvement to drug manufacturing. Traditional versus enhanced approaches ICH Q11 focuses specifically on the development and manufacture of drug substances.

It specifies that a company can follow “traditional” or “enhanced”approaches or a combination of both in developing a drug substance (4). In the traditional approach, set points and operating ranges for process parameters are defined, and the drug-substance control strategy is typically based on process reproducibility and testing to meet established acceptance criteria (4). In an enhanced approach, risk management and scientific knowledge are used more extensively to identify and understand process parameters and unit operations that affect critical quality attributes (CQAs) (4).

In an effort to establish a consensus and develop consistency, industry and regulators have frequently described quality by design (QbD) by dividing it into three fundamental, interrelated concepts: control strategy, design space, and criticality.1 Figure 1 describes a QbD approach for developing design space, establishing control strategy, and delineating criticality for an active pharmaceutical ingredient (API) that essentially serves as a map for how these conceptual elements were used to establish design space for the torcetrapib API manufacturing process. A preliminary assessment of the QbD strategy for the manufacture of the API typically begins early in development when chemists and engineers evaluate synthetic route selection as well as intermediate quality attributes (QAs) impacting API specifications. As a default, established API specification limits serve as a primary control standard for QAs and surrogate control in the absence of a process control strategy and relevant intermediate specifications.

The API specification, by default, serves as a predictor of critical QAs (CQAs) because the combination of their measurements may directly correlate to potential impact to the safety and efficacy of the drug product and thus to the

patient. API CQAs may include physical characteristics beyond such things as the impurity specification of the API, e.g., particle size, polymorphic form, and salt selection are Mrelevant for drug product manufacture.3 The analytical

control strategy for an API manufacturing process that evolves during development is routinely focused with the attention on the formation and purge of impurities and their cascade effects on the multiple process steps, including the

potential impact to the API’s CQAs. To establish design space, a formal, prospective risk assessment is executed in accordance with ICH Q9 (B in Fig. 1). A process risk assessment is performed as a precedent to formally develop a design space for the commercial manufacturing process so that potential critical process parameters (CPPs) can be identified. In general, a process risk assessment considers prior knowledge, mechanistic understanding of the chemistry, and relevant chemical manufacturing experiences.

Starting and Raw Materials

Before parameters and ranges can be evaluated in any multivariate designed experiment, the appropriate quality of SMs (or key intermediates) and raw materials must be established. For the torcetrapib manufacturing process, some of the specifications of compound 4 were deemed CQAs because of their direct impact on controlling the relative genotoxic impurities in steps 5 and 6. In addition, ECF (raw material) is a commodity chemical used in step 5 that is incorporated into the structure of the API. Fate and purge development work, batch history, and appropriate communications with vendors are a few methods to establish appropriate specifications for SMs and raw materials. Appropriate specifications were established for each of these materials before any of the multivariate designs were initiated for torcetrapib, and by default, some of these specifications were deemed CQAs. The validity of a multivariate experimental design used to establish a design space depends on understanding the functional relationship between these CQAs/specifications and the API CQAs.

CONCLUSION ON CASE STUDY

We have provided a case study of a QbD effort, including a risk assessment, for the torcetrapib drug substance process. Fundamentally, different from the drug product, API processes have multiple steps. Understanding the functional relationship between FAs, QAs, and process parameters as they progress through the manufacturing process is the most universally challenging aspect of QbD for API development. Analytical specifications and control strategy aspects of the QbD plan remain the foundation for change throughout the evolution of the manufacturing process (from phase I to launch).

The role of the chemist and engineer during the course of development is to effectively eliminate as many of the CQAs and CPPs as possible from the commercial manufacturing process through continuous improvement efforts. Designed experiments generate the data required to establish a design space for commercial manufacturing processes, while providing the process understanding that facilitates sound business decisions. First principles ofchemistry can expand  this “toolbox” to include kinetic models, computer predictive programs, and more diverse concepts of prior knowledge

EMBEDDED PRESENTATION

The enhanced approach further includes the development of appropriate control strategies applicable over the lifecycle of the drug substance that may include the establishment of design space(s) (4). Manufacturing process development should include, at a minimum, according to ICH Q11:Identifying potential CQAs associated with the drug substance so that those characteristics having an impact on drug-product quality can be studied and controlled t
Defining an appropriate manufacturing process t
Defining a control strategy to ensure process performance and drugsubstance quality (4).

An enhanced approach to manufacturing process development would additionally include: t
A systematic approach to evaluating, understanding, and refining the manufacturing process, including identifying—through prior knowledge, experimentation and risk assessment—the material attributes (e.g., of raw materials, starting materials, reagents, solvents, process aids, intermediates) and process parameters that can have an effect on drug-substance CQAs t
Determining the functional relationships that link material attributes and process parameters to drug-substance CQAs (4).

The enhanced approach, in combination with quality risk management, is used to establish an appropriate control strategy. Those material attributes and process parameters important to drug-substance quality should be addressed by the control strategy. The risk assessment can include an assessment of manufacturing process capability, attribute detectability, and severity of impact as they relate to drug-substance quality (4). For example, when assessing the link between an impurity in a raw material or intermediate and drugsubstance CQAs, the ability of the drugsubstance manufacturing process to remove that impurity or its derivatives should be considered in the assessment (4).

The risk related to impurities can usually be controlled by specifications for raw material/intermediates and/or robust purification capability in downstream steps. It is important to understand the formation, fate (whether the impurity reacts and changes its chemical structure), and purge (whether the impurity is removed via crystallization, extraction, etc.) as well as their relationship to the resulting impurities that end up in the drug substance as CQAs (4). The process should be evaluated to establish appropriate controls for impurities as they progress through multiple process operations (4).

Regulatory expectations In March 2011, the European Medicines Agency and Food and Drug Administration launched a three-year pilot program for a parallel assessment by both agencies of certain quality and chemistry, manufacturing and control (CMC) sections of new drug applications submitted to FDA and marketing authorization applications (MAAs) submitted to EMA that are relevant to QbD, such as development, design space, and real-time release testing.

The objective of the pilot, which is scheduled to end Mar. 31, 2014, is to ensure consistent implementation between the European Union and the United States of ICH guidelines Q8, Q9, Q10, and Q 11 and to facilitate sharing of regulatory decisions (5–7). In August 2013, the agencies reported that the first EMA–FDA parallel assessment of QbD elements of an initial MAA was successfully finalized as well as some consultative advice procedures.

In a question-and-answer format, EMA and FDA reported on their expectations as they relate to quality target product profiles (QTPPs), CQAs, classification of criticality, and application of QbD in analytical method development (7). With respect to the QTPP, the agencies specified that they expect applicants to provide the QTPP, which describes prospectively the quality characteristics of a drug product that should be achieved to ensure the desired quality, safety, and efficacy of the drug product. With respect toCQAs, the agencies expect applicants to provide a list of CQAs for the drug substance, finished product, and excipients when relevant. This list should also include the acceptance limits for each CQA and a rationale for designating these properties as a CQA.

Furthermore, there should be a discussion of how the drug substance and excipient CQAs relate to the finished product CQAs based on prior knowledge, risk assessment, or experimental data. The basis of the control strategy is to ensure that the drug substance and finished product CQAs are consistently within the specified limits (7). Another issue was whether the agencies would accept a three-tier classification of criticality for process parameters.

The agencies responded that ICH Q8 (R2) specifies that a critical process parameter is one whose variability has an impact on a CQA and needs to be monitored or controlled to ensure the process produces the desired quality. EMA and FDA cited a regulatory submission in which the applicant proposed an approach to risk assessment and determination of criticality that included a three-tier classification (“critical,” “key,” and “noncritical”) for quality attributes and process parameters. Using this classification, a “critical” factor was defined as a factor that led to failure during experimentation.

A factor that had not led to failure within the range studied, but still may have an impact on product quality, was considered as a “key” factor. The agencies said that they do not support the use of the term “key process parameters (KPP)” because it is not ICH terminology and there is differing use of the term “key” among applicants.

Although FDA and EMA said they are amenable to this terminology in the pharmaceutical development section to communicate development findings, they are not in describing the manufacturing process, process control, and control of critical steps and intermediates, where the description of all parameters that have an impact on a CQA should be classified as critical (7).

The agencies further specified that process manufacturing descriptions be comprehensive and describe process steps in a sequential manner, including batch size(s) and equipment type. The critical steps and points at which process controls, intermediate tests, or final product controls are conducted should be identified (7). Steps in the process should have the necessary detail in terms of appropriate process parameters along with their target values or ranges.

The process parameters that are included in the manufacturing process description should not be restricted to the critical ones; all parameters that have been demonstrated during development as needing to be controlled or monitored during the process to ensure that the product is of the intended quality need to be described (7).

The agencies also commented on QbD as it relates to analytical methods using risk assessments and statistically designed experiments to define analytical target profiles (ATP) and method operational design ranges (MODR) for analytical methods (7). “There is currently no international consensus on the definition of ATP and MODR,” noted the agencies. “Until this is achieved, any application that includes such proposals will be evaluated on a case-by-case basis” (7).

The agencies noted, however, that an ATP can be acceptable as a qualifier of the expected method performance by analogy to the QTPP as defined in ICH Q8 (R2), but the agencies would not consider analytical methods that have different principles (e.g., highperformance liquid chromatography and near-infrared [NIR] spectroscopy) equivalent solely on the basis of conformance with the ATP. “An applicant should not switch between these two types of methods without appropriate regulatory submission and approval,” they said.

The agencies also noted that similar principles and data requirements could apply for MODRs. For example, data to support an MODR could include: appropriately chosen experimental protocols to support the proposed operating ranges/conditions and demonstration of statistical confidence throughout the MODR. Issues for further reflection include the assessment of validation requirements as identified in ICH Q2 (R1) throughout the MODR and confirmation of system suitability across all areas of the MODR (7).

The agencies further indicated that future assessment of the pilot program will include other lessons learned in areas such as design-space verification, the level of detail in submissions for design space and risk assessment, continuous process verification, and continuous manufacturing. QbD at work A review of recent literaure reveals some interesting applications of QbD in drug-substance development and manufacturing.

For example, scientists at Bristol-Myers Squibb reported on a process-modeling method using a QbD approach in the development of the API ibipinabant, a cannabinoid receptor 1 antagonist being developed to treat obesity (8). In its development, the molecule had volume requirements of 6 kg for toxicology studies and formulation development, which later increased to 175 kg for late-stage clinical trials. The researchers used mechanistic kinetic modeling to understand and control undesired degradation of enantiomeric purity during API crystallization. They implemented a work flow, along with kinetic and thermodynamic process models, to support the underlying QbD

Those material attributes and process parameters that are found to be important to drug-substance quality should be addressed by the control strategy.

In August 2013, FDA and the European Medicines Agency reported on lessons learned from an EMA–FDA parallel assessment of QbDelements examined from submissions in their pilot program.

EMBEDDED PRESENTATION

approach and reported on the use of risk assessment, target quality specifications, operating conditions for scale-up, and plant control capabilities to develop a process design space (8). Subsequent analysis of process throughput and yield defined the target operating conditions and normal operating ranges for a specific pilot-plant implementation. Model predictions were verified from results obtained in the laboratory and at the pilot-plant scale (8).

Future efforts were focused on increasing fundamental process knowledge, improving model confidence, and using a risk-based approach to re-evaluate the design space and select operating conditions for the future scale-up (8). Scientists at Merck & Co. reported on their work in applying QbD to set up an improved control strategy for the final five steps in the production route of a legacy steroidal contraceptive, which has been produced for more than 20 years within its facilities (9).

A generic ultra-high-performance liquid chromatography method was developed according to QbD principles to create a range of proven acceptance criteria for the assay and side-product determination for the final five steps in the production route of the API (9). Scientists at Eli Lilly reported on a systematic approach consisting of a combination of first-principles modeling and experimentation for the scaleup from bench to pilot-plant scale to estimate the process performance at different scales and study the sensitivity of a process to operational parameters, such as heat-transfer driving force, solvent recycle, and removed fraction of volatiles (10).

This approach was used to predict process outcomes at the laboratory and pilot-plant scale and to gain a better understanding of the process. The model was also used further to map the design space (10). In other work, scientists reported on the application of latent variablesbased modeling to a reaction process in a small-molecule synthesis based on continuous-flow hydrogenation (11). In another study, scientists reported on using a QbD approach for designing improved stability studies (12).

Also, scientists at UCB and the Institut des Sciences Moléculaires de Marseille in France recently reported on the feasibility of using online NIR spectroscopy as a process analytical technology tool to monitor in real time the API and residual solvent content to control the seeding of an API crystallization process at industrial scale. A quantitative method was developed at laboratory scale using statistical design of experiments and multivariate data analysis (13).

References

1. ICH, Q8 (R2) Pharmaceutical Development (2009).

2. ICH, Q9 Quality Risk Management (2005).

3. ICH, Q10 Pharmaceutical Quality System (2008).

4. ICH, Q11 Development and Manufacture of Drug Substances (Chemical Entities and Biotechnological/Biological Entities)(2012).

5. FDA, “FDA, EMA Announce Pilot for Parallel Assessment of Quality by Design Applications,” Press Release, Mar. 16, 2011.

6. EMA, “European Medicines Agency and US Food and Drug Administration Announce Pilot Program for Parallel Assessment of Quality by Design Applications,” Press Release, Mar. 16, 2011.

7. EMA, “EMA–FDA Pilot Program for Parallel Assessment of Quality-by-Design Applications: Lessons Learnt and Q&A Resulting from the First Parallel Assessment,” Press Release, Aug. 20, 2013.

8. S.B. Brueggemeier et al., Org. Proc. Res. Dev. 16 (4) 567-576 (2012).

9. J. Musters et al., Org. Process Res. Dev. 17 (1) 87-96 (2013).

10. I. Figueroa, S. Vaidyaraman and S. Viswanath, Org. Process Res. Dev., online, DOI: 10.1021/op4001127, July 22, 2013.

11. Z. Shi, N. Zaborenkdo, and D.E. Reed, J. Pharm. Innov. 8 (10) 1-10 (2013).

12. S.T. Colgan, J. Pharm. Innov. 7 (3-4) 205-213 (2012). 13. C. Schaefer et al., J. Pharm. Biomed. Anal., online, DOI.org/10.1016/j. jpba.2013.05.015. May 20, 2013. PT

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All of us talk about using common sense for everything we do. However, in certain instances we do things that are quite contrary because we are in our comfort zone. Many times the world tells us that we did not use our “common sense” or pay attention to the feedback or there is a time lapse. When this happens, the world wants to rationalize our intentions and motives.

Even infants use their “common sense” to figure out the virtues of moving from crawling to walking to running in about one year. They understand the exhilaration and benefits of their newfound freedom. Similar euphoria is experienced when we have technology innovations or exceed financial goals.

DEEPER INSIGHTS

Ensure Measurement Accuracy, Consistency & Repeatability

In the manufacturing world common sense tells us that producing quality product the first time without interruptions (QbD) is more satisfying compared to the process where we have to stop and examine the progress at intermediate steps (QbA). It seems that the pharmaceutical manufacturing industry has considerable hesitation (1) in it’s ability to move from Qb (Quality by) A (Analysis) to D (Design). This observation is based on my review of discussions on different websites, in print and at conferences.

After more than five years of discussions we are still talking about how to get to “D”. This suggests that there are some reasons for not getting there. Pharma either is not able to overcome “B (bureaucracy) and “C (consternation) in its drive from “A” to “D” or has defiantly decided to live with analysis of raw materials, intermediates and final products to ensure we produce consistent quality products. Regulatory bodies have jumped into the fray by proposing methods of “how to” of QbD (2,3). They might be useful for new processes and products.

My question to all readers is how we are going to have a QbD process if we do not understand and apply fundamentals of chemistry and chemical engineering to our processes. Regulatory guidance is not going to deliver QbD. There are just too many guidances and they could complicate matters.

Had pharma moved from “A to D” we would be discussing its virtues, values and the amounts of monies saved and the  reduction in compliance paper work. In defense of the pharmaceutical industry it has not lost “common sense” in its move from QbA to QbD. There are opportunities that have been missed and it is up to the technocrats to show their value. I believe that the industry is also victim of its own success.

We do need to understand and explore some of the hurdles that are in the way to move from “A” to “D”. These could be that we do not understand value of improved profits (most unlikely) or do not have financial justification (likely) or are reluctant to move out of our comfort zone to a simpler lifestyle of less work and regulation (likely). Actually the causes are a combination of all of the above plus more. They need to be discussed.

Current Discussion

Much of the “how to” of the QbD discussion is geared towards formulations. APIs are excluded from the discussion. It is suggested that modeling, six sigma, design of experiments and other statistical tools along with Process Analytical Technologies (PAT) will facilitate “A” to “D” move. I believe that we are putting the cart before the horse or spinning wheels. These methods have value and will help “only” after we have a complete understanding and command of the interaction of chemistry, chemicals, process variables and unit operations.

Modeling without understanding of process fundamentals is time consuming, expensive and is not going to get us to “D”. Since significant data is needed for mathematical analysis, without process understanding we are creating a difficult situation for ourselves. If the modelers believe that volumes of data and its analysis, without understanding and control of the process variables, will deliver an economic and sustainable process that will produce quality product, which would not require repeated analysis of intermediates and final product and we will able to move the process from “A” to “D”, then they know something some of us do not know or understand.

In addition, there is a perception that various analytical instruments and tools will automatically deliver quality product. These tools tell us “the state of the process” but do not fix the process unless correct process control schemes are incorporated. Only our understanding along with proper use of these tools will create an optimum process. I think our misbeliefs have created a difficult situation. Simplicity and economic methods are needed to deliver quality products.

Some additional reasons for our reluctance to convert existing processes to QbD processes can be our fear of the unknown such as regulatory re-approval hurdles and associated costs or the profits are so high that everyone is comfortable with their current levels or, as said earlier,(1) we cannot justify innovation. Another reason for lack of QbD is a lack of economies of scale in our processes.

QbD is an opportunity. We need to take simple steps and have to have small wins to bring common sense back into our daily fold of process development, scale up and commercialization. Without wins we will be stuck in “analysis paralysis” mode and “A” to “D” movement will become the fad of the day and like any other fashion will disappear. Small wins are an inspiration for big wins.

The manufacture of a drug dose is a two-step process. The first step is the manufacture of the active pharmaceutical ingredient and the second step is its formulation to a dispensable dose. Since APIs are left out of pharmaceutical manufacturing conversations, discussion in this paper is focused on their manufacturing. The considerations are applicable to formulations also. Without a quality API and correct dose the drug would not deliver the desired effect. Under or over dosing would have detrimental effects.

Pharmaceutical current state

Business and manufacturing aspects – At branded (ethical) and generic pharmaceutical companies, we are always in a hurry to get the product to the market. Depending on the dosage, drug efficacy and the sale price API, their annual volume can vary from less than thousand pounds to few thousand pounds. Volume at a branded company during the patent life belongs to one company but it could be produced at multiple sites i.e. lower economies of scale.

Since the APIs are fine/specialty chemicals, it is natural for any chemist or chemical engineer to produce them in the same equipment where other similar chemicals are produced. The practice of producing APIs, due to similarity of chemistries and equipment needs, began at fine/specialty chemical plants more than hundred years ago.

From a financial perspective this practice makes sense as it avoids investment for every product. Since process inefficiencies are absorbed through product pricing, businesses do not have to be concerned about low process yields or lack of having sustainable processes. Thus, the need for an optimum process has never been a pharma business concern i.e. having a QbD process has never been an issue.

Regulatory Aspects – Since the drugs are for human consumption, their quality and consistency is paramount. This need has created different regulatory bureaucracies. As explained earlier, different products due to their low volume are produced in the same equipment where other products are produced. Regulatory bodies in order to prevent cross contamination established “good manufacturing practices”. These guidelines are minimal at best.

All of the above necessitate that record keeping of every step including raw materials, intermediates, equipment cleaning and testing be done so that no mistakes happen and if they happen, they can be tracked and corrected. This has become a gargantuan task and more time is spent on cleaning the equipment and paperwork than having the correct and optimum process. QbA has become a way of life.

Due to lack of competition the pharmaceutical industry has not been proactive in developing innovative manufacturing technologies because the current practices have delivered the desired profits. By not having the optimum process and equipment that should be used for a designated API manufacturing, companies have relied on in-process analysis to replicate laboratory milestones.  However, with efficient and optimized processes the industry can exceed these guidelines. It is very possible that better technologies can reduce the paperwork but this option has never been shared, if explored. Reduced paperwork will improve profits.

Future

As patents expire, additional companies enter the business due to the potential for high profits. Entry of “me-too” companies (definition: those who produce many of the same or similar products as their competitors) will lower production volumes per site from the “pre-patent expire” levels. Most of these companies will be from the developing countries. Since these new entrants attain their expected profits, the need for efficient processes and manufacturing technology innovation is not a priority.

The financial investment for process innovation and improvements is difficult to justify at low production levels. This exacerbates the “A” to “D” move further. Thus the pharmaceutical industry, branded and generic, will lumber along with the QbA methodology unless the business philosophy changes or is threatened. This is discussed later.

To recap, the pharmaceutical industry, unless it makes changes in its business model, is not ready and equipped to implement QbD for existing and new products – especially the API manufacturing step. This is also true for the formulated products.

Suggested regulatory guidances/guidelines are not a gospel but an indication of the kind of data that needs to be generated by the companies to create a quality product. From web and print chatter I can see that without understanding and command of the process, such an effort will add costs and confusion. Since no one, including pharmaceutical companies and regulatory bodies know the costs and related benefits for existing products, I am not sure how many would venture to move from “A” to “D”.  Simplicity is needed.

If we want QbD practices to become the pharmaceutical manufacturing norm, industry will have to change (1). If we do not change voluntarily, business circumstances might force the change. We have seen this in many industries and need to pay attention. Creative destruction (4) is needed for pharmaceutical companies as well as regulatory bodies. Having QbD processes is not difficult and/or expensive. It requires a different mindset and a revamp of our thinking.

QbD processes can be arrived at two different ways. For lack of better names for these methods I have labeled them “Me-Too” and “Consolidated” model. They are discussed below.

“Me-Too” Model

“Me-Too” companies have to rely on “square plug in a round hole (5)” as their manufacturing philosophy. The process is fitted in the existing equipment and most likely is a copy of their lab process that has been submitted for regulatory approval. These processes are generally inefficient, unsustainable and require monitoring of everything as described above.

If the companies want to stay the course of producing every product that is approved, there are two paths to QbD. First is to audit the processes, operating methods and production planning to see how the processes can be simplified to minimize QbA practices. The second path for QbD is to have equipment that is “right sized” for the process. Of course chemical engineering practices have to be applied in each case.

“Right sizing” requires investing in new equipment and commercialization of the optimum process. Manpower and financial investment along with re-approval of the products might be needed. It is very likely few companies will want to go this route, as they might not be able to justify such an investment for the existing products.

Modular equipment might help to reduce the investment but would require careful equipment selection, sizing and production planning. If not done right, companies would have even worse asset utilization compared to current conditions. Many companies may consider these alternates too challenging and complex and might stay with the current QbA methodology.

In a recent article (6) Figure 2 compares the costs of API manufacture in the West, India and China. A review suggests opportunities. Companies in all three regions purchase their raw materials from the same source. Thus their material costs are about the same. Companies in each region have opted for different margins. These margins can be significantly improved through QbD practices.

The reduction of conversion cost from 50 to 35% in the West through process simplification, which is not out the realm of possibilities, can significantly improve profit margins (7,8). If similar improvements are adopted in processes in India and China, their margins will also improve, making them more aggressive for further expansion in API and formulated products. Simplification will result in cycle time reduction, for example, production capacity will increase with no or minimal investment. I do not believe anyone would mind a “free” side benefit.

“Me-Too” companies can adopt QbD for their new products. They will have to think through these practices at the laboratory level and carry them to commercialization. The lessons of benefits can be extended to their existing products.

“Consolidated” Model

Companies adopting this or a similar model will be producing a limited number of products instead of many in the “Me-Too” model. Since the number of products is limited they will supply a higher volume percentage of the global needs. Manufacturing technologies for these products will be the most innovative and sustainable. These technologies will be simple to execute and will be QbD based. Some of the products in their basket could be produced continuously.

Companies in this model would have some of the following attributes for their API manufacturing and their formulation practices.

1. Have a technology that is the best, revolutionary and simple.

2. Have complete command of the process and require no or minimal in-process quality analysis.

3. Produce better than 50% or a very large percentage of the global needs for the API and possibly the formulated product.

4. Process equipment is designed for the product.

5. Dedicated product lines at a site to produce multiple products that are independent of each other.

Companies in this model will be creating procedures and manufacturing methods that will far exceed what is outlined in regulatory guidelines. They would be able to show case what is possible with excellent processes.

Due to economies of scale they will be purchasing their raw materials in significantly large quantities, and would be able to get price discounts to achieve higher profit margins. QbD processes will reduce their paperwork, as there will be significantly reduced changeovers. Reduced paperwork is extra profit. Regulatory compliance will be easier.

Compared to the “Me-Too” model the “Consolidated” model will result in better business practices resulting in minimal supply shortages, better cash flow, lower inventories, lower investment in total equipment and infrastructure and definitely less regulatory paper work. Due to better and sustainable technology this model will have a better conversion yield and a lower cost.

Irrespective of what path companies choose to attain QbD, companies will have to incorporate and exploit chemicals, their chemistry and chemical engineering principles to get there.(9) Companies will have to select options. They can apply QbD to new products (least expensive) or existing products (more expensive compared to new products). QbD in the long run will be a win-win.

Expenses to achieve QbD processes will be offset through savings that will come from efficient processes and reduced paperwork. If companies want to stay with QbA methods it will be an option of their choosing but then they also will have to live with the threat of being driven out of business at some point.

QbA –> QbD is an imagination and creativity challenge (10), which can be met if the companies want to. There are two unknowns in the “A” to “D” move. They are: 1) what would be the combined cost of each re-approval (pharmaceutical companies and regulatory) and would the savings offset the expense and 2) do the regulatory bodies have sufficient and knowledgable manpower to handle the paperwork and inspections. My conjecture is that no one has the answer and any improvement or change will have to be justified on a case by case basis (11).

References

1. Malhotra, Girish: Who and What Killed QbD, Pharmaceutical Processing, Volume 26, No. 4, May 2011, pg 10-14

2. Quality by Design for ANDAs: An Example for Modified Release Dosage Forms Accessed February 13, 2012

3.  Process Validation: General Principles and Practices Accessed February 13, 2012

4. Malhotra, Girish: Pharmaceutical Manufacturing: Is it antithesis of creative destruction? http://www.pharmamanufacturing.com/articles/2008/091.html October 2008

5. Malhotra Girish: Square Plug In A Round Hole: Does This Scenario Exist in Pharmaceuticals? Chemical Week, August 25, 2010

6. Pollack, P., Bardot, A, and Dach, R., API Manufacturing: Facts and Fiction, Contract Pharma, January/February 2012 Vol. 14, No. 1 Pgs. 56-66

7. Malhotra, Girish: Chemical Process Simplification: Improving Productivity and Sustainability, John Wiley & Sons,ISBN: 978-0-470-48754-9, January 2011

8. Malhotra, Girish: Can the Combination of Creative Destruction and “Steve Jobs Traits” Lead to Pharma QbD Spring? Profitability through Simplicity (http://pharmachemicalscoatings.blogspot.com/2012/04/can-combination-of-creative-destruction.html), April 15, 2012

9. Malhotra, Girish: Focus on Physical Properties To Improve Processes, Chemical Engineering, Vol 119, No. 4, April 2012, Pg 63-66

10. Malhotra, Girish: QbA –>QbD: An imagination and creativity challenge, Chemica OGGI/ Chemistry TODAY March/April 2011, Vol. 29 Number 2, Pgs. 42-44

11. Malhotra, Girish: Neglected Tropical Disease (Infectious Diseases) Drugs: What are they telling us about Innovations! March 7, 2012

QbD in API Manufacturing

With a quality-by-design approach, robust processes consistently deliver quality product. Small drug manufacturers looking to adopt a quality-by-design (QbD) approach aim to scientifically determine product and process characteristics that will meet specific criteria set after careful analysis of the intended drug application.

These critical quality attributes (CQAs) of the final drug product (and often of the API) include the physico chemical properties and performance behavior of the formulated drug (drug substance). The manufacture of small-molecule APIs often requires the production of multiple intermediates using different processes. To consistently achieve these CQAs, it is necessary to ensure that each of these processes is robust. Critical process parameters (CPPs) are, therefore, important components of an effective control strategy for ensuring that the API process consistently delivers product with the appropriate CQAs.

Linking CQAs with CPPs
While true CQAs are found in the final specification for a drug product, there are several different aspects of a formulated drug, and particularly the API, that are affected by process parameters. These aspects, therefore, must be linked to the CPPs for each manufacturing process required for the preparation of an API, according to Chris Senanayake, vice-president of chemical development for Boehringer Ingelheim Pharmaceuticals. These characteristics include, but are not limited to, total purity, individual impurity levels, the polymorph(s), solvates, pH, water content, and particle size.

For the API, the most common CQAs are related to impurities from chemical processes and the solid-state properties (e.g., particle size, polymorphism) of the drug substance, according to Gert Thurau, group leader, Technical Regulatory at Roche. It is essential to control impurities for the safety of the drug product, while control of the solid-state properties of the drug substance is necessary to achieve consistent product properties, including bioavailability. “Once these attributes have been defined, it is possible to define what is important to the process and build a process that comes closer to quality by design and is, therefore, highly robust,” he says.

The assay and impurity profile of an API are essentially inter-related and are important because low impurity levels translates to safety for patients, while a high assay indicates appropriate efficacy, according to Vishwanath Nadig, associate director of quality assurance for Dr. Reddy’s Custom Pharmaceutical Services (CPS). Nadig adds that moisture content is also important because, in some cases, the presence of moisture may accelerate degradation of the drug substance.

These CQAs should be selected such that if the final product has these attributes, then it will work for its intended purpose. CPPs should then be selected because they have a relationship to the final CQAs and, when controlled, will assure the manufacture or a product with the right CQAs, according to Senanayake. “CPPs are the process parameters that affect the critical quality attributes of the API, and it is important to determine the range for each critical process parameter expected to be used during routine manufacturing and process control,” adds Mark TePaske, director of regulatory affairs, quality, and compliance for Cambrex.

Most importantly, it is essential to establish appropriate CPPs for each individual process step because they will ultimately affect the quality of the drug, which in turn can impact efficacy, according to Nadig. “Establishing and meeting CPPs and CQAs allows quality to be built into the process and affords robustness beyond release testing,” adds TePaske.  He also notes that well-defined CPPs ensure that a process operates in a state of control and in a validated state, which is crucial, because process validation is a cGMP requirement.

The definition of the CQAs for the final drug product and API is the first step in a comprehensive risk-based approach to product and process development, according to Thurau. “The starting point of the analysis is typically the quality target product profile, which leads to defining the critical quality attributes for the final product, and in turn, the critical quality attributes for the drug substance. Since the most important CQAs of the final API are the process-related impurities, which mostly result from the starting and raw materials, it is essential to understand the chemistry of the individual process steps,” he explains. In addition to risk assessment, Senanayake adds that prior knowledge, designed experiments, and regulatory expectations all play a role in determining CQAs and CPPs.

Risk-assessment approaches

Once CQAs are defined, typically during the initial scale-up phase, it is necessary to identify the appropriate CPPs. “At Boehringer Ingelheim, we believe that using a design of experiment (DOE) approach is the best method for demonstrating the interdependency of CPPs and the CQAs for individual process steps,” Senanayake says. Along with general risk assessments, the use of design failure mode and effects analyses (FMEA) is also effective for defining critical parameters of drug products, drug substances, and production processes, according to Nadig. “When applied appropriately, these two approaches are sufficient for defining the important attributes,” he says.

While orthogonal experiments can also be used, Senanayake notes that with DOE, knowledge is gained about the design space for each process that cannot be obtained using screening experiments, although they are useful when determining certain aspects of processes, such as the most effective solvents or catalysts. TePaske adds that once defined, critical attributes should be affirmed experimentally and control limits established, with processes, procedures, equipment and/or facilities revised as needed.

It should be noted that the risk-assessment methods used today are much more rigorous than the processes used in the past. “Historically, process and CQA definition was driven by the process development chemist, and the depth and breadth of the investigations were chemist-dependent,” observes TePaske. As a result, process development was primarily viewed as a laboratory exercise.  He goes on to note that current approaches are more disciplined, and studies are defined by multidisciplinary project teams. “These teams review and reconcile findings and risk assessments, and the concerns of the production, materials, quality, engineering, and other departments involved in manufacturing are integrated into the development process.

In effect, CQA definition and process development have evolved from a laboratory exercise to a global preparation for process validation and commercial GMP manufacturing.” He concludes that this team-oriented approach is the best practice because it integrates the needs of all of the disciplines involved in commercial manufacturing and virtually eliminates the possibility that CQAs and CPPs that cannot be performed in the available facilities and equipment will be defined.

Connecting CPPs to CQAs
Based on the results of the quality risk assessment, various reaction and work-up conditions can be investigated, and the products from each process step can be carefully analyzed with regard to their impurity profiles and other properties, according to Thurau. “For example, the structures of the impurities can be determined, and consequently the process conditions can be adjusted to minimize the impurities and/or their fate in downstream steps can be determined. The result is the elimination of the impurities or the determination of safe limits for them,” he explains. He stresses that it is important in this part of the process to be systematic, and to consistently maintain a link between the CPPs being evaluated and the drug product and drug substance CQAs.

Barriers to developing CPPs
While there are many benefits to a QbD approach and the establishment of CPPs that are linked to final product and drug substance CQAs, there are challenges to implementing such an approach. For Senanayake, the time and resources required remain the biggest barrier to obtaining a useful understanding of a process. “These barriers must be overcome, though, because having thorough knowledge of a process once it has reached commercial manufacturing is critical for success, and therefore, it is necessary to take the time to fully understand the design space,” he asserts.  Thurau agrees that the major limitations are practical in nature and can typically be overcome.

He does, however, note that there are some open questions on the definitions and differences in the applicability of the concept by various health authorities. “As registrations for products developed and manufactured using the QbD approach become more detailed and explicit about criticality, the hope is that the increased knowledge will lead to more flexible approaches to change management (do and tell) as opposed to the current set approach (tell and do).

Both Nadig and TePaske point to the need for participation of knowledgeable team members from across different functions of the organization as a challenging aspect of QbD and the establishment of effective CQAs and CPPs. “The multidisciplinary approach requires up-front involvement of disciplines whose primary job responsibility has historically been manufacturing and requires a new way of thinking,” says TePaske. He also adds that the risk-assessment approach often focuses on what can be done, which can stifle innovation.

Practical use of CPPs
Despites these barriers and limitations, many companies have recognized the value of a QbD approach and the importance of linking critical process parameters for individual process steps with the critical quality attributes of small-molecule APIs and the corresponding formulated drug products. Boehringer Ingelheim, for example, is monitoring process robustness at each development stage and focusing on understanding how this robustness translates to the commercial scale using batch histories, according to Senanayake. In addition, the company is trying to complete DOEs on the important steps in its manufacturing processes. “Our success to date is demonstrated by our validation efforts and the control charts we have established for individual steps,” he says.

At Dr. Reddy’s CPS, when defining CPPs for each process step, a cross-functional team meets to discuss the key sensitivities of the process parameters and material attributes, which are first weighted in importance, and then tolerances on the variables are established, according to Nadig. DOE screening is then performed to identify the critical parameters, followed by optimization and definition of the design space to understand what will happen to the CQAs under different parameter settings. “Importantly, we are trying to engage senior members from cross-functional teams during these pre-planning meetings so that an exhaustive risk assessment is conceptualized and a mitigation plan worked out,” he comments. The company also emphasizes the importance of clear communications, participation with the customer, and giving weight to all stakeholder concerns throughout the process.

Potential consequences
The consequences of not establishing CPPs that are effectively linked to CQAs can be severe. “If the proper controls for an intermediate step in the manufacturing process are not in place, then it is possible for a material to be produced that does not meet specifications for unknown reasons. Such a situation can in turn result in a recall if the intermediate is carried through the entire commercial process. In addition, without proper controls, processes often deliver poor quality product or product of inconsistent quality,” asserts Senanayake. In addition, according to Thurau, if inappropriate process parameters or in-process material attributes are established, the quality of the final product may appear high, but it is the result of testing quality into it, and not of process design and process understanding. Finally, TePaske stresses that operation in a state of control is fundamental to process validation and continued process performance in a validated state.

Quality by Design—Bridging the Gap between Concept and Implementation

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