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The top trends influencing automation in the Life Science industry 2018

Posted on March 26, 2018 by

Trevor Marshall, Director of Enterprise System Integration

AutomationThe need for process optimisation, regulatory compliance and supply chain improvements are driving investment in automation technologies across the Life Science industry. As a result, the systems used to automate process steps during the manufacture of pharmaceuticals are evolving rapidly, with new instrumentation and control products coming to market.

Here, our director of enterprise system integration, Trevor Marshall will discuss the impact that multi-product manufacturing facilities, single-use technologies, continuous manufacturing and industry 4.0 will have on automation.  See the publication link to Contract Pharma here._


Multi-product manufacturing facilities

Trevor Marshall, director of enterprise system integration talks automation trends for 2018

The growth in recent years of more targeted therapies that need to be manufactured in smaller volumes means the industry is transitioning away from “one-line-one-product” setups in favor of multi-product manufacturing facilities. These sites must be designed to be more agile, with the capability to react to changing demands quickly. The trend towards contract manufacturing is also driving the need for more flexible facilities which need to meet the needs of multiple customers.

In short, flexibility is the key element for success, and modern facilities need to be able to re-orientate their processes according to the requirements of individual products. For example, in biopharmaceutical processing, different products very rarely use the same process functionality and equipment, often creating a need for equipment changes between products. It is vital then that automation systems are designed to offer as much as flexibility as the business demands. The upshot is that sites are now being designed in a way that ensures a high degree of segregation between process steps, provides cross contamination control and limits product exposure to the environment.

Continuous manufacturing

Pharmaceutical companies have historically been slow to investigate new manufacturing techniques, preferring a more risk-adverse approach to modifying the validated batch manufacturing design. Cost pressures and the need to find ways to increase productivity have led to the introduction of new continuous manufacturing techniques across several unit operations in the Life Science industry.

Oral solid dose tableting lines, continuous API production and continuous chromatography in biological processes are but a few examples of where continuous manufacturing provides greater productivity for companies. With this also comes new challenges from an automation perspective, not only in the continuous manufacturing process but also in the batch record and genealogy requirements for the product.

Single-use technologies

The trend towards more targeted, high potency and biological drugs is similarly underpinning the adoption of single-use technologies, such as single-use bioreactors and other unit operations. This again is having a significant impact on the way that automation is delivered. Single-use systems reduce or eliminate the time required to perform cleaning and steaming, and they allow manufacturers to switch quickly from one product to another, or from batch to batch.

The integration of process control systems and manufacturing execution system (MES) solutions with start-to-finish technologies and single-use manufacturing platforms is helping the industry to deploy biopharmaceutical manufacturing with increased productivity and efficiency, and at a lower cost, which can significantly reduce the time-to-market for new products.

Single-use components are also an enabling technology for smaller scale production of biopharmaceuticals, including antibodies, proteins, vaccines and cell therapies, which would otherwise be much more difficult to produce. In addition, as the world of gene therapy continues to evolve, the industry can expect to see even greater reliance on single-use technologies.

Industry 4.0

Industry 4.0 refers to the new tools and processes that are enabling smart, decentralised production, with intelligent factories, integrated IT systems, the Internet of Things (IoT) and flexible, highly integrated manufacturing systems.

Industry 4.0 is simply the latest wave of technological advances that will drive the next phase of pharmaceutical manufacturing by using proven solutions and approaches to decision making to improve quality, reliability and reducing waste.

The potential that Industry 4.0 holds for automation is massive with individual management processes throughout manufacturing expected to become automated. For example, if a temperature gauge makes a higher than expected reading, the system will detect this and rectify the situation rather than requiring an operator to intervene and make an assessment about the required course of action. Future developments may also allow machine learning algorithms to be able to adjust manufacturing lines and production scheduling quickly. New developments will also pave the way for predictive maintenance and the opportunity to identify and correct issues before they happen.

These developments may, on the surface, appear to be quite arbitrary but automation could effectively eliminate human error and delay from manufacturing – preventing waste and upping efficiency. The financial benefits are huge.

Due to regulatory constraints, the pharmaceutical industry has been slower to adopt this type of cutting-edge technology. While embracing the potential for Industry 4.0 is going to be critical to future operational efficiency for all manufacturers, it may be a long time before the industry is able to complete the digital transformation and have fully automated and connected facilities that can take advantage of all the age of digital manufacturing has to offer.

Enterprise manufacturing intelligence

Automation and technology create the opportunity to leverage data and analytics to improve processes. The access to and bringing together of more meaningful data means a better view of operations, allowing for better analytics and real-time responsive decision-making. Combining all manufacturing data to this end is often referred to as enterprise manufacturing intelligence (MI).

With Industry 4.0 comes the introduction of cloud and edge computing which offer organisations the ability to gain insights that are currently not available. Digitising and connecting data across entire supply chains with embedded context will lead to improvements in asset performance. More importantly, the adoption of advanced analytics will improve insights gained in the science of making life saving drugs.

Edge devices will make it easier to connect machines and offer the ability to create organisation-wide data lakes. These edge devices can also be used to run analytics in real-time close to the equipment, while big data is analysed in the cloud.

Big data also allows for the creation of better digital twins (a digital replica of a physical product) made up of data gathered from the entire manufacturing process of a product. When it comes to digital twins, the more quality that is gathered, the more accurate the replica is. The insights found in a digital twin often provide great value to a business. With this digital information available across multiple sites, batches and suppliers, sophisticated advanced analytics can provide a digital twin that best represents the ‘golden batch’ that manufacturers strive for. Extension of the traditional golden batch, where data was very much process control-based, will be supplemented and surrounded with environmental data, raw material data, training data and any other digital data available that goes toward influencing the golden batch.

This digital twin then offers a comparable ideal which can feed into automation systems and create alerts to any problems based on specific data sets.  Issues on a manufacturing line such as temperature spikes or variations in machine speed can be highlighted. Machine learning, simulation and real-time and historical data can create alerts for potential failures with the potential to advise and even implement a specific course of action to remedy the problem.


Established manufacturing software systems, such as automation and MES, combined with the next wave of digital technologies have the potential to power significant performance improvements within pharmaceutical manufacturing facilities.

Companies that take the initiative early stand to gain the biggest competitive advantage, ensuring they can operate with greater agility, cost-efficiency and compliance.

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