As pharmaceuticals industry across the globe is becoming fiercely competitive and regulatory regimes are becoming more stringent, incorporating high end technology to ensure highest standards of quality and efficiency through manufacturing process lines has become an established norm among the industry players today.
However, conventional pharmaceutical manufacturing players are hesitant to incorporate innovative Process Analytical Technology (PAT) or incorporate complete automation fearing regulatory hurdles in their production lines.
According to Ashok Kumar, Deputy Director of Indian Immunological Ltd, Hyderabad, conventional players are yet to incorporate innovative process analytical technologies for two reasons: One is cost and the other is possibilities of regulatory hiccups. “It is not that easy for an industry to shift its existing manufacturing process lines with new and innovative technology. It involves the risks of both cost and regulatory compliance. Unless proved and perfected not many will be willing to venture into innovation at the first step. Unless it is a global player with huge revenue turnovers and surplus capital funding, the SMEs and smaller players are reluctant for upgradation except in some exceptional cases,” opined Kumar.
Despite knowing that precise, real-time process analytics is indispensable for future chemical production, not many manufacturers are keen on innovation. Particularly when there is a growing scrutiny of USFDA and other western regulators against the Indian and other third world players, it is time that the industry incorporated innovative and automated process technologies that comply with increasingly higher standards in terms of quality control and process efficiency.
PAT is of utmost importance to the pharmaceutical industry given its ability to increase quality and efficiency. A long time has elapsed since it was merely required to integrate sensors into the process chain. In fact, the holistic approach of PAT, combining process design, analytics and control, allows continuous tracking of critical process parameters and adjustment of critical quality attributes of the intermediate and end-products. There is an increasing tendency for conventional sensors to be supplanted by spectroscopic methods which give access to more detailed process data and, in consequence, a sound insight into system components on the molecular level.
Conventional pharmaceutical manufacturing is generally accomplished using batch processing with laboratory testing conducted on collected samples to evaluate quality. This conventional approach has been successful in providing quality pharmaceuticals to the public. However, today significant opportunities exist for improving pharmaceutical development, manufacturing, and quality assurance through innovation in product and process development, process analysis and process control.
Unfortunately, the pharmaceutical industry generally has been hesitant to introduce innovative systems into the manufacturing sector for a number of reasons. One reason often cited is regulatory uncertainty, which may result from the perception that our existing regulatory system is rigid and unfavourable to the introduction of innovative systems. For example, many manufacturing procedures are treated as being frozen and many process changes are managed through regulatory submissions. In addition, other scientific and technical issues have been raised as possible reasons for this hesitancy. Nonetheless, industry's hesitancy to broadly embrace innovation in pharmaceutical manufacturing is undesirable from a public health perspective.
Efficient pharmaceutical manufacturing is a critical part of any effective health care system. The health of global population (and animals in their care) depends on the availability of safe, effective and affordable medicines. Pharmaceuticals continue to have an increas ingly prominent role in health care. Therefore pharmaceutical manufacturing will need to employ innovation, cutting edge scientific and engineering knowledge, along with the best principles of quality management to respond to the challenges of new discoveries (e.g., novel drugs and nanotechnology) and ways of doing business (e.g. individualized therapy, genetically tailored treatment). Regulatory policies must also rise to the challenge.
Way back in August 2002, USFDA had launched a new initiative entitled “Pharmaceutical CGMPs for the 21st Century: A Risk-Based Approach” mainly to eliminate the hesitancy to innovate. On similar lines the Indian government should also come forward some encouraging programmes to ensure that more players come forward to adopting innovative technology and ensure transparency and maintain highest standards of product quality and efficiency.
The initiative launched by USFDA had several important objectives, which ultimately helped improve the access to quality health care services. The objectives are intended to ensure that: the most up-to-date concepts of risk management and quality systems approaches are incorporated into the manufacture of pharmaceuticals while maintaining product quality, manufacturers are encouraged to use the latest scientific advances in pharmaceutical manufacturing and technology; to ensure bridging discrepancies the agency's submission review and inspection programs operate in a coordinated and synergistic manner; regulations and manufacturing standards are applied consistently by the agency and the manufacturer; management of the agency's risk-based approach encourages innovation in the pharmaceutical manufacturing sector and even agency resources are used effectively and efficiently to address the most significant health risks.
Over the years pharmaceutical manufacturing had continued to evolve with increased emphasis on science and engineering principles. Effective use of the most current pharmaceutical science and engineering principles and knowledge — throughout the life cycle of a product — can improve the efficiencies of both the manufacturing and regulatory processes. Having learned this, the USFDA had designed its initiative to do just that by using an integrated systems approach to regulating pharmaceutical product quality. The approach is based on science and engineering principles for assessing and mitigating risks related to poor product and process quality.
Analytical process and its need
A process is generally considered well understood, first, when all critical sources of variability are identified and explained; second, variability is managed by the process and thirdly, when product quality attributes can be accurately and reliably predicted over the design space established for materials used, process parameters, manufacturing, environmental and other conditions. The ability to predict reflects a high degree of process understanding. Although retrospective process capability data are indicative of a state of control, these alone may be insufficient to gauge or communicate process understanding. A focus on process understanding can reduce the burden for validating systems by providing more options for justifying and qualifying systems intended to monitor and control biological, physical, and/or chemical attributes of materials and processes. In the absence of process knowledge, when proposing a new process analyzer, the test-to-test comparison between an online process analyzer and a conventional test method on collected samples may be the only available validation option.
In some cases, this approach may be too burdensome and may discourage the use of some new technologies. Transfer of laboratory methods to on, in, or at-line methods may not necessarily be PAT. Existing regulatory guidance documents and compendial approaches on analytical method validation should be considered. Structured product and process development on a small scale, using experimental design or in-line process analysers to collect data in real time, can provide increased insight and understanding for process development, optimization , scale-up, technology transfer, and control. Process understanding then will continue in the production phase when other variables (e.g. environmental and supplier changes) may possibly be encountered. Therefore, continuous learning over the life cycle of a product is important.
Pharmaceutical manufacturing processes often consist of a series of unit operations, each intended to modulate certain properties of the materials being processed. To ensure acceptable and reproducible modulation, consideration should be given to the quality attributes of incoming materials and their process-ability for each unit operation. During the last three decades, significant progress has been made in developing analytical methods for chemical attributes (e.g. identity and purity). However, certain physical and mechanical attributes of pharmaceutical ingredients are not necessarily well understood. Consequently, the inherent, undetected variability of raw materials may be manifested in the final product. Establishing effective processes for managing physical attributes of raw and in-process materials requires a fundamental understanding of attributes that are critical to product quality. Such attributes (e.g., particle size and shape variations within a sample) of raw and in-process materials may pose a significant challenge because of their complexities and difficulties related to collecting representative samples. For example, it is well known that powder sampling procedures can be erroneous.
Formulation design strategies that provide robust processes that are not adversely affected by minor differences in physical attributes of raw materials. Because these strategies are not generalized and are often based on the experience of a particular formulator, the quality of these formulations can be evaluated only by testing samples of in-process materials and end products. Currently, these tests are performed off line after preparing collected samples for analysis. Different tests, each for a particular quality attribute, are needed because such tests only address one attribute of the active ingredient following sample preparation.
During sample preparation, other valuable information pertaining to the formulation matrix is often lost. Several new technologies are now available that can acquire information on multiple attributes with minimal or no sample preparation. These technologies provide an opportunity to assess multiple attributes, often non-destructively.
Currently, most pharmaceutical processes are based on time-defined end points (e.g. blend for 10 minutes). However, in some cases, these time-defined end points do not consider the effects of physical differences in raw materials. Processing difficulties can arise that result in the failure of a product to meet specifications, even if certain raw materials conform to established pharmacopeial specifications, which generally address only chemical identity and purity.