The meanings of quality have developed over time. The said concept of ‘Quality’ is also equally applicable for pharmaceutical products as a whole. In fact, ‘Quality’ concept initially started with final product testing followed by Statistical Quality Control (SQC) during the middle of the 20th century. But it was observed that SQC cannot minimise the inherent risk associated with the product during production as it failed to be detected by testing. Accordingly, Good Manufacturing Practice (GMP) was implemented and made mandatory by all drug regulation authority all over the world, including India, for manufacturing drugs and pharmaceuticals during the last decade of the 20th century.
Today, the primary objective of most of the pharma manufacturing units is to reduce operational costs while ensuring regulatory compliance. Cost pressures are increasingly acute as many pharma manufacturers face a dwindling product pipe-line associated with greater competition from generics.
Conventional approach to GMP in pharma manufacturing facility is rooted to batch processing, following SOP meticulously and subsequently laboratory testing on a few collected samples so as to evaluate the quality. Although this approach is successful to provide quality pharma to the public, however, significant opportunities and tools are available today to further improve pharma manufacturing and quality assurance through innovation in the areas of product and process development, process analysis, and process control.
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Dr Debabrata Roy
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The pharma industry has presently failed to compete with other industries in terms of manufacturing efficiency and productivity due to high cost and burden involved in revalidating any process change, even though changes are warranted to improve the quality. Pharma manufacturers are reluctant to change process which are confirmed, validated, and accepted by the regulators.
The pharma industry’s commitment on maintaining status quo has produced inefficiency and higher wastage. It is estimated that worldwide potential cost savings from efficiency improvement in pharma industry could be as high as $90 billion dollars per year. On the other hand, it is a known fact that R&D are the major cost centre in pharma companies, while manufacturing accounts for more than twice the expenses of R&D, representing around 36 per cent of total costs. The true cost of manufacturing becomes apparent when one considers the non-value- added activities and waste which represent 80 per cent and 50 per cent respectively.
| Current and the future state of quality management (three generations of quality management tools (QMT)) (Table-1) | ||
| Pharmaceutical industry today(Reactive) | Pharmaceutical industry tomorrow (Proactive) | |
| First generation QMT | Second generation QMT | Third generation QMT |
| Quality by Testing (QbT) | Statistical Process Control (SPC) / Statistical Quality Control (SQC) | Quality by Design (QbD) |
| Inspect, reject or accept | Examines historical output of a process to identify the limits of a stable process and sources of error | Prevents problems or defects from occurring and is a continuous real time quality assurance |
Impact on quality is evident in an environment which does not accept changes as well. From the available statistical data it was observed that the number of drug recalls has increased drastically on a yearly basis, 75 per cent of which are attributed to manufacturing defects. The reject percentage or ‘not-of-standard-quality’ (NSQ) in the pharma industry ranges from five to 10 per cent (indicates the working practice at around two sigma level) compared to 0.0001 per cent (six sigma level) in the semi conductor industry. The reject percentage cost to pharma industry ranges in between $4.5 – 9 billion per year which is quite a lot compared to $90 billion spent on manufacturing.
GMP has found its place in the field of pharma industry gradually. However, recent initiatives on scientific risk-based framework and Process Analytical Technology (PAT), which supports innovation and efficiency in a GMP environment, suggest a new way of thinking for the 21st century. In August 2002 US Food and Drug Administration (US FDA) launched a new initiative entitled ‘Pharmaceutical cGMPs for the 21st Century: A Risk-Based Approach.’
Quality by Design (QbD)
QbD is a systematic approach to pharma development which starts with predefined objectives and emphasises product and process understanding based on sound science and quality-risk management. It is a prospective approach-based on ‘Quality by Design philosophy’ unlike the present system of ‘Quality by Testing’ which is a retrospective approach.
A comparison of current state of manufacturing with QbD (Table 2) may apparently indicate that they belong to two conflicting families. One of the characteristics of a GMP manufacturing environment is the abundance of documented processes such as standard operating procedures (SOPs), testing methods, environmental controls and training programme. This documentation can be divided into technical standards and operational procedures. Technical standards, such as product specifications, validated settings and production conditions, can only change following a change control exercise. Operational procedures, such as the way people interact with equipment and the way that product flows, are based on custom and experience, and will change regularly in response to deviation or safety concerns.
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Comparison of QbD Programme with current status in QA (Table-2)
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| Aspect | Current state (GMP) | Desired QbD state |
| Pharmaceutical development | Empirical; univariate | Systematic; multivariate |
| Manufacturing process | Validation on three batches; focus on reproducibility | adjustable within design space; focus on control strategy |
| Process control | In-process | PAT utilisation |
| Product specification | Based on batch data | Based on product performance |
| Control strategy | Intermediate and end product testing | Risk-based; real-time release |
The challenge for the pharma industry to move towards QbD is to design new operational procedures that comply with all external regulatory requirements, but at the same time support continuous improvement. In the GMP norms, critical specifications and technical standards are very well defined, deviations from which are obvious and thus action can be taken after change control. Operational procedures, however, are often light on detail and as a result, variations in these may not be detected. For example, the way an operator sets up a workstation may vary with respect to time and outcomes. A check sheet may ensure that critical steps have been completed, but the manner in which the end-result was achieved is not noticeable. Work variation is possible if people use slightly different methods to achieve the same result.
The GMP environment is already rich in science. Science is used to develop the batch manufacturing process followed by laboratory testing and evaluate quality of the product to release into market. The employees who ‘handle’ the product have a defined role to produce product in a controlled and consistent manner.
Traditional improvements as per GMP norms are carried out through change control to avoid frequent deviation from the SOP rather than to reduce the variation. The fear of change and the present systems to control it, together make hindrance for continuous improvement. However, some pharma plants already operate with well-controlled and optimum processes. For these plants the move towards QbD should not be such a challenge. Implementation of risk-based approach is the main challenge for the pharma industry to move towards QbD, which is firmly based on science and engineering principles. However, recent changes in regulatory thinking made this challenge less problematic. The principles of Process Analytical Technology (PAT) initiative seems to be extremely well aligned with QbD thinking.
As per GMP norms, critical attributes and technical standards are well defined, however, operational procedures are often not in detail, as a result, variations in these may not be detected. Work variation thus possible if people use slightly different methods to achieve the same result. In a system of QbD, SOPs and other manufacturing instructions would be viewed as a means to expose problems and encourage improvement. Technical standards will be identified and fixed in line with regulatory requirements; all other operational procedures would be reviewed on a systematic basis and standardised with respect to time, sequence, content, and outcome. The challenge for the pharma industry in turning to QbD is the design of new operational procedures that are consistent with all external regulatory requirements, but also support continuous improvement.
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Key challenges for QbD adoption (Table-3)
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| Challenges occur within companies | Challenges are directly related to the FDA |
| Internal misalignment | Inconsistency of QbD across DRA |
| Lack of belief in business case | Lack of tangible guidance |
| Lack of technology to execute | Regulators not prepared to handle |
| Alignment with third parties | Does not inspire confidence |
| Misalignment of international regulatory bodies | |
| Current interaction with companies is not conducive to QbD | |
As per GMP norms, product manufacturing cycle time is quality driven; it may take longer time to release a batch than to produce it. Different departments usually have clear individual responsibilities and objectives. Departments have often separate responsibilities and objectives and working in isolation or in conflict with one another. Individual departments may be unaware of the impact on overall product flow due to delays or problems from their part. However, as per QbD, cycle time and quality would be of equal importance. This overlaps with PAT framework of reducing production cycle time. When a deviation in cycle occurs, it may indicate potential quality issues. The moment product flow is interrupted, quality issues may immediately be identified otherwise the same might have been hidden from view or only detected during final release. For example, when an operator in a traditional pharma plant is required to produce a tablet to a specified disintegration time, the time it takes to set up the tablet press to produce tablets meeting the required technical standard is not controlled. In a QbD process, the operator would have a work time standard. If it is not possible to produce the tablet to the required disintegration specification within this time, a call for help would be made. This may expose a problem in the upstream process, in this case granulation, which would otherwise be masked.
The challenge for pharma industry to move towards QbD is to reduce the grey zones of responsibility, slow response, and late calls for help when problems occur, and move towards an environment where problems are immediately identified, shared and resolved across the plant.
GLOSSARY
- Target Product Quality Profile (TPQP): The target product profile (TPP) has been defined as a ‘prospective and dynamic summary of the quality characteristics of a drug product that ideally will be achieved to ensure the desired quality and thus the safety and efficacy of drug product is realised.’
- Critical quality attributes (CQA): A CQA has been defined as ‘a physical, chemical, biological or microbiological property or characteristic that should be within an appropriate limit, range, or distribution to ensure the desired product quality.’
- Critical process parameters (CPP): Critical process parameters (CPP) are process inputs that have a direct and significant influence on critical quality attributes when they are varied within regular operation range.
- Design space: Design space defines the relationship between critical quality attributes (CQAs) and critical process parameters (CPPs) and identifies acceptable operating ranges for CPPs. It is the region where acceptable product can be produced. It can be considered to be a snap-shot in time representative of the current process knowledge and also contains the proven acceptable ranges (PAR) for CPPs and acceptable values for their associated CQAs.
- Risk assessment: Risk is defined as the combination of the probability of occurrence of harm and the severity of that harm. It is a systematic process of organising information to support a risk decision to be made within a risk management process and consists of the identification of hazards and the analysis and evaluation of risks associated with exposure to those hazards.
- Product Analytical Technology (PAT): A desired goal of the PAT framework is to design, analyse, and control pharma manufacturing processes through the measurement of Critical Process Parameters (CPP) which affect Critical Quality Attributes (CQA) and to consistently ensure a predefined quality at the end of the manufacturing process.
The concept actually aims at understanding the processes by defining their CPPs, and accordingly monitoring them in a timely manner (preferably in-line or on-line) and thus being more efficient in testing while at the same time reducing over processing, enhancing consistency and minimising rejects.
The long-term goals of PAT
- Reduce production cycling time
- Prevent rejection of batches
- Enable real time release
- Increase automation
- Improve energy and material use
- Facilitate continuous processing
Currently, NIR spectroscopy applications dominate the PAT projects. A possible next-generation solution is Energy Dispersive X-Ray Diffraction (EDXRD).
Conclusion
The goal of QbD is to bring quality medicine to patients in a more reliable way which benefits all stakeholders. Manufactures will see production improvements with significantly reduced batch failures, stock-out etc. Regulators have greater confidence in robust quality of products they are being asked to approve and will be able to reduce intensity of their regulatory oversight, again assisting the industry to innovate and improve continually. Patients will be benefited from a greater consistency in medicines they take and a reduced likelihood of unexpected product unavailability or withdrawal.
However, to adopt these new quality approaches, a comprehensive training programme for technical personnel is very much warranted at least by the pharma manufacturers of India. Launching training programme in a company is a strategic management decision which needs to be initiated by top level management. All the elements of the training framework as well as the formalised improvement strategy need top-level management commitment for successful execution. Especially, without a strong commitment on the part of top level management, the training programme activities are seldom successful. It is pertinent to mention here that many pharma manufacturing organisations in India never seem to have time for training. Either these organisations do not properly prioritise training or they see it as an unnecessary expenditure of capital with no obvious correlation to revenue.
Although, the senior personnel in most of the big industries are well knowledgeable and acquainted with the modern day regulatory norms covering GMP aspects (may not be well conversant with the QbD approach), however, the new entrants from college and university are lacking technical knowledge and competency to face the challenges of present day stringent international regulatory norms.
This is an important issue and all stakeholders should come forward to make a comprehensive training platform for the technical persons associated with the pharma industry which may finally lead India as a number one nation in the ‘World of Pharmacy’.