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Dear Readers, Welcome to the latest issue of Micr
Pharmaceutical science has always demanded precision. Small differences in a product can have major consequences, and identifying or preventing these differences often requires extensive and sophisticated efforts by the pharmaceutical industry. However, the requirements on pharmaceutical and other laboratory services are changing.
Merely achieving a desired level of precision will not be sufficient to meet these requirements.
For example, consider the services needed to carry out laboratory testing or to manufacture pharmaceutical products. It is not enough to achieve a desired level of precision; these services must also enhance performance and increase the throughput of services offered while continuing to meet quality and compliance requirements.
This is the environment in which pharmaceutical and laboratory services find themselves today. To address this situation, services must be designed to incorporate the three key elements of precision, performance, and productivity.
This is particularly the case for services related to research and development, and clinical trials. The concept of precision is wider and more encompassing than the concepts of repeatability and reproducibility.
The extent to which services provided to the pharmaceutical industry have embraced the concept of precise judgment is open to conjecture. It is clear, however, that certain services, such as analytical testing, have embraced the concept of precise forecasting.
Having a baseline measurement is good, but to really know and understand the details and insights that drive the measurement is valuable. Looking at performance from a system perspective is becoming more pervasive.
A piece of lab equipment can be designed to have a high degree of performance but if it is incorporated into the lab in a way that is not efficient, it will not improve the lab’s overall performance.
Like equipment in a lab, the tools and equipment in a facility can be sophisticated, but if the overall process is not integrated and if there are discontinuous systems, the facility can be inefficient and unproductive.
Because of this, the systems and processes in a facility need to be analyzed and performance assessed at the system level.
From a business and entrepreneurship perspective, the best products and services facilitate and improve a process.This is especially true for products and services for the research, development, and pharmaceutical industries.
A true competitive edge will come from designing products that embrace intelligent productivity while also improving process control and integrating quality and safety throughout.
How intelligent instruments, automation, advanced analytics and connected workflows are redefining the standards for pharmaceutical manufacturing, analytical science and modern laboratories
It means eliminating rote work, automatically performing tasks, enhancing information and processing it to produce useful business insights, while adhering to regulations. Laboratory automation has evolved to encompass more than simple liquid handling. Today, automation can comprise of more complex, multistep procedures.
One consequence of these advances is a shift from a labor-intensive to a more automated work environment in which the laboratory scientist’s role is transformed to focus more on the review and evaluation of data and less on routine, mundane tasks.
Laboratory automation not only allows for improvement in repeatability, traceability and integrity of samples, it can facilitate standardization and integration of a multitude of interconnected laboratory workflows and processes.
In addition to the benefits listed above, standardization and integration of a laboratory’s work processes and procedures enable data to be collected in a repeatable and reliable manner to facilitate applications of artificial intelligence and advanced analytics.
The automation of scientific work processes and instrumentation allows integration of numerous diverse scientific and analytical instruments and equipment to form a cohesive and interoperable ecosystem.
These integrated systems allow scientific and analytical equipment to be extended to and interfaced with a variety of enterprise systems and services. Today’s science and analytical instruments have the potential to transform science and engineering work by collecting, collating, analyzing and interpreting scientific data and preparing scientific reports.
Artificial Intelligence (AI) is rapidly progressing and providing opportunities for automation across different fields. The collaborative efforts between the pharmaceutical and AI industries have increased, allowing better opportunities and advancements in laboratory services and related fields.
AI is an influential and valuable resource that can change and evolve laboratory services and related fields. Deep learning has strong potential to positively disrupt and revolutionize the pharmaceutical, life sciences, biotech and chemistry sectors. AI will allow for the automated, prioritized and intelligent design and execution of scientific experiments.
The quality and volume of data will largely influence the intelligence and decisions derived from AI. Therefore, it is imperative to improve data and operational intelligence. AI will extend and amplify human intelligence.
Traditional pharmaceutical processes consist of lengthy, time consuming and labor intensive operations, including collecting, analyzing and interpreting data. Recent advancements have disrupted and enhanced traditional processes and allowed for the concurrent or real time analysis and execution of processes and related services.
Continuous, real time process analytics and control will allow for the collaborative and concurrent efforts of laboratories, processes and services to better identify and understand process anomalies and enhance quality and related services.
It is commonly understood that pharmaceutical manufacturing requires an extensive understanding of the processes used, as opposed to an overreliance on finished product testing.
PAT enables real time processing and/or automation of actions to adjust or correct processing based on predefined constraints or parameters. Other multidisciplinary technology enablers, such as artificial intelligence and advanced sensing/analytical technology, can complement PAT to provide supershopm, real time processing and/or automation.
Through the application of PAT to pharmaceutical manufacturing processes, quality can be designed and ensured throughout the process. This philosophy is consistently aligned with the overall direction of advanced and/or intelligent manufacturing.
Downtime in pharmaceutical manufacturing and laboratory facilities can be costly. Traditional maintenance strategies do not always ensure equipment availability and serviceability. Achieving adequate maintenance strategies relies on the equipment failing and then taking corrective action.
Predictive maintenance shifts the focus from equipment failure to degradation. The goal of predictive maintenance is to identify equipment degradation and failure. This can be accomplished through analysis of equipment performance and/or utilizing real time and historical data.
Detect, Predict and Act upon equipment degradation to ensure continued equipment availability and serviceability.
Effectively managing increasing and more complex sample throughput is a challenge for many laboratories. Productivity in these situations can be greatly improved with the assistance of automation.
The main advantage of automation is the reduction in error and increase in speed for repetitive tasks.
Some tasks that can be automated include sample preparation and liquid handling for high throughput screening. Other tasks include the automation of cell culture and microbiology.
Reducing the manual intervention in laboratory processes improves data integrity. Although data integrity and quality are important for regulations and compliance, the data can also improve laboratory productivity and throughput. The data in a laboratory should be accurate, complete, consistent and readily available to the end users.
One of the most valuable resources in a laboratory is the time of the scientists and quality staff. Time spent dealing with and correcting data errors is time lost productivity.
If automation is integrated with laboratory information systems, data integrity and productivity would be improved.
The next lab will use technology to move data between diverse systems. These systems will provide the following:
Context + Traceability + Security + Integrity
It’s important to note the difference between meaningfully connecting various technologies and just indiscriminately connecting everything to everything.
The intersection of Pharmaceuticals and Technology brings an opportunity to improve efficiency of laboratories and other research facilities.
The Laboratories of the Future will be characterized by the use of innovative technologies and instruments that collect, exchange, and analyze data; and will allow members of a research team to be in different geographical locations.
Digital and advanced analytics will integrate sample and workflow data to allow researchers and scientists to focus on high-level, cognitive activities and away from routine, repetitive tasks.
Therefore, determining the extent of integration of technologies in the laboratory of the future will be very crucial.
The pharmaceutical technology system can be represented in a format of a layered ecosystem. The layers are as shown below.
This layer consists of the hardware of the system e.g. instruments and manufacturing equipment.
This layer defines the communication systems that integrate the hardware of the technology.
This layer represents the information produced by the system e.g. the quality of the product and the services offered by the system.
This layer represents the intelligence of the system e.g. machine learning and artificial intelligence.
This layer consists of the key decision makers in an organization e.g. scientists, engineers, quality personnel and management.
The pharmaceutical industry is moving towards measuring the performance of its technologies based on the results achieved rather than specified performance.
Results achieved rather than specified performance raises a lot of questions, for example,
AI, automation, robotics, analytics, and other technologies will be continuously interconnected and integrated. The growth of these technologies will be outpaced by the growth of the systems built around them.
There will be a strong demand within the pharmaceutical industry for integrated systems and technologies that enable:
Improved accuracy and control with consistency in the outcome of a given process.
Improved equipment and system performance with respect to speed and volume of work.
These will be the norm in the pharmaceutical industry.
The Pharmaceutical Industry’s focus on better and more reliable outcomes will depend on continuous improvement in technologies that integrate Precision, Performance, and Productivity.
