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Dear Readers, Welcome to the latest issue of Mi
The pharmaceutical industry is currently experiencing a period of change in which new ways of discovering, developing, making and delivering medicines are being inspired by breakthroughs in science, engineering and digital innovations.
New ways of thinking are being applied to drug development, from continuous pharmaceutical manufacturing to new and improved ways of developing, transporting and delivering medicines.
The incorporation of engineering principles into the research and manufacturing of medicines is at the core of the current revolution in the pharmaceutical industry.
Increasing global health care needs, together with continuously expanding and more stringent regulatory requirements, are forcing the pharmaceutical industry to invest in smarter, more integrated processes and advanced analytics to enhance the speed and quality of research and decrease the time it takes to get new medicines from the laboratory to the patient.
Manufacturing processes in the pharmaceutical industry are changing to become more flexible and data-driven. One way this is being achieved is through increased automation and monitoring of processes. This leads to fewer inconsistencies, mistakes, and better control over variations in pharmaceutical manufacturing.
Continuous manufacturing is another important development. Compared to batch manufacturing, which relies on many sequential steps and intermediary storage and transport processes, continuous processes can lead to more streamlined production, improved process monitoring and more efficient use of resources.
In combination with PAT, Continuous manufacturing allows pharmaceutical companies to monitor Quality Attributes (QAs) during the manufacturing process instead of relying on labor intensive end-product testing.
Industry 4.0 is contributing further equipment connections and automation of manufacturing and quality systems. New technologies are enabling real time process monitoring and optimization, as well as earlier detection of process deviations.
However, successful deployment of these technologies is dependent on many other factors. Data integrity, workforce training, cybersecurity and change control are some of the other critical elements needed to apply technology in the manufacturing of pharmaceuticals.
Artificial Intelligence and Machine Learning are redefining pharmaceutical research. These technologies help process, analyze and even predict molecular interactions and facilitate the identification of drug candidates and the design of experiments. In addition, these technologies can transform and optimize many activities related to the pharmaceutical industry.
Some of these technologies can facilitate and optimize different steps of the development and production of pharmaceuticals. Predictive algorithms in production can be used to eliminate process variability.
AI and other data science techniques can be used to integrate and process numerous data sets in order to optimize and coordinate the production of pharmaceuticals.
Digital laboratory platforms can facilitate and speed up scientific work. The use of AI to generate data is a good start, but these data should always be validated by traditional scientific methods.
The role of analytical sciences in the manufacturing, development, and quality assurance functions of the pharmaceutical industry is going to increase, given the expansion of therapeutic areas and the complexity of molecules.
The identity, purity and potency of drug substances and drug products, as well as their impurities and stability, can now be measured with greater precision using a variety of modern analytical techniques such as high-performance and ultra-high-performance liquid chromatography, liquid chromatography-mass spectrometry, spectroscopy and particle characterization techniques.
Some analytical laboratories have traditionally relied on the development and validation of test methods. Recently, the automation of sample preparation, and the use of advanced analytical instruments and computer software, as well as the integration of laboratory information management systems, have positively impacted the integrity and reproducibility of laboratory work.
Quality by Design (QbD) calls for the understanding of relationships among drug substance materials, process parameters and product attributes. Risk management, design of experiments and critical quality attributes are helpful in process development. The use of a qualitative risk management approach in combination with the validation of pharmaceutical products can be effective in transitioning from a predominantly reactive to a more proactive quality system.
The new wave of advanced therapeutic modalities presents both new challenges and opportunities for engineering and science. These modalities often require complex and sophisticated manufacturing, analysis and storage/transportation.
The use of single-use systems has improved the speed and efficiency of manufacturing biopharmaceuticals, especially with the use of advanced automation in fluid transfer and process control.
Moreover, recent innovations in cell culture and fermentation have decreased the time needed to develop biologics. Challenges remain in purification and characterization of biologics.
Risks of contamination are present at various steps of the biopharmaceutical manufacturing process and throughout the supply chain. Until recently, assurance of product consistency during advanced process development required the integration of process engineers and microbiologists. Recently, there has been a shift towards process continuity and integration of process engineers with microbiologists.
Flexibility in assuring the balance of rigor and control in managing risks will be vital for the future of the biopharmaceutical industry.
The integration of automation in modern pharmaceutical manufacturing, coupled with a robust quality management system, should enable the pharma industry to gain flexibility while improving outcomes for patients. GMPs and GLPs are key to any pharmaceutical business. Validated computerized systems and sound documentation are necessary.
Data integrity is important as laboratories and pharmaceutical manufacturing facilities become digital. A system should be validated to ensure the reliability, reproducibility and integrity of records.
Risk-based validation, together with electronic audit trails, provision and management of controls, and sound governance of records, enables the oversight of increasingly interconnected systems.
Expectations of regulatory authorities encourage manufacturers to have robust systems to manage deviations and investigation of the root cause and implement corrective and preventative actions.
Continuous improvement and compliance should be integrated throughout the strategic and operational planning of an organization to ensure these elements become embedded in the quality culture of the organization. This positively impacts operational resilience and instills confidence in the medicines available to patients.
A design that is considerate of the environment is becoming more important for design of pharmaceutical facilities and processes. There are multiple pieces of equipment that can be integrated within a pharmaceutical facility to minimize the overall environmental impact of the operation. Other areas, including green chemistry and process intensification, help in improving the sustainability of processes.
For process sustainability, there are a variety of design considerations that help operational staff meet the requirements of quality and safety of a product. Compatibility of various sustainability initiatives with the rigorous requirements of pharmaceutical manufacturing must be ensured.
No single technology can entirely address the needs of the next generation of pharmaceutical excellence on its own. It will require collaboration amongst drug developers, equipment manufacturers, analytical technology providers, contract development and manufacturing organizations, research institutions, and regulatory specialists.
Integrated engineering teams have the potential to close the gap that exists between scientific discovery and commercial manufacturing. Early partnerships with equipment and technology providers may allow for better facility design, facilitate technology transfer and enhance the overall alignment of the process requirements and the capabilities of manufacturing.
Likewise, significant investment in workforce development is essential to train the workforce to acquire the skills necessary to synthesize pharmaceutical knowledge with other allied and interrelated fields such as automation, data science and engineering, process engineering and advanced analytics. The continued pace of changes in technologies and the pharmaceutical regulatory environment dictate that lifelong learning become the new standard for all professionals.
The future of pharmaceutical excellence is to integrate the science and the engineering of manufacturing with an emphasis on digital intelligence and patient safety.
Smarter manufacturing and new engineering advances along with the adoption of continuous and sustainable processes, coupled with the new frontiers of data science and artificial intelligence can create a renewed era of quality and productivity in the pharmaceutical industry.
The true long-term value of these opportunities, however, will be determined by the strategic integration of data, and processes and a commitment to patient safety and centrality. While pharmaceutical science and engineering will always be intertwined, it is equally important to view the true scope and focus of the field well beyond the four walls of a pharmaceutical manufacturing plant and develop safe and effective therapies that help patients around the world.
