Advanced Technologies 3 Key Solutions for Smart Pharma Manufacturing

Related Vendors

GEA Pharma Systems AG

FabRx Ltd.

Merck KGaA

Glatt Ingenieurtechnik GmbH

Italvacuum, Srl

more less

TRM Filter d.o.o.

less

Like all other industries, the pharma manufacturing industry is also transforming itself by adopting enhanced and next-gen technologies which will help the sector to improve its production processes, save costs and at the same time also deliver better quality drugs. So, which are these three smart pharma manufacturing solutions? Read on to find out…

The global pharmaceutical manufacturing market size is predicted to reach 1,599.9 billion dollars by 2030 from 425.9 billion dollars in 2021, at a CAGR of 15.9 % between 2022 and 2030, states a release by market research firm Acumen Research and Consulting. These figures are significant and also showcases that the industry is poised for growth. With the expected rise of the sector, companies are also adopting or are on the lookout for innovative technologies and processes to optimize their production methods in order to improve efficiency, save costs, and deliver quality drugs in a shorter period of time; a constant challenge for the sector.

The trilogy of the pharma manufacturing world

3D printing

3D printing is not new to the pharma sector but its benefits still make it one of the most prominent solutions of the sector today. The additive manufacturing technology can be used to produce small batches of dosage forms for clinical trials as well as customized medicines. Alvaro Goyanes, CEO and Cofounder of the Fabrx firm, which specializes in developing 3D printing technology for fabricating pharmaceuticals, explains, “Pharmaceutical 3D printing is a disruptive technology, making the pharmaceutical manufacturing industry more versatile and decentralized. It allows for the manufacture of small batches of unique dosage forms rapidly. This is not only useful for clinical trial batch manufacture, making them faster and cheaper, but also for personalized medicine.”

He adds that this improves patient treatment adherence, treatment efficacy and patient well-being while avoiding adverse effects. Current techniques are old fashioned, slow and prone to errors. Pharmaceutical 3D printing allows for the automated, safe manufacture of personalized medicine at the point of care, making it more accessible for more patient groups.

A leading example of this technology in the pharma space is the 3D printed tablet (Spritam) developed by Aprecia Pharmaceuticals. The drug is used for the treatment of seizures in patients with epilepsy and the firm has also obtained an approval from the US FDA (Food and Drug Administration) for the drug.

Continuous manufacturing

As the name suggests, the continuous manufacturing (CM) technology is a nonstop production process in which pharma products are produced on a single production line. Easier to scale, the technology eliminates the need for physical intervention and is being adopted by most of the global drug companies today. “Continuous manufacturing presents a new approach to OSD (Oral Solid Dosage) form production and meets the industry’s demands for faster product development, reduced costs and increased manufacturing flexibility,” opines Dr. Jim Holman, Senior Director, Technology Management - Pharma Solids, Gea.

He mentions, “By providing higher yields, lower utility consumption and reduced waste, the technology is enabling drug makers to move away from stepwise and time-consuming batch processing to a fully integrated and closely controlled process that gives excellent product consistency by intrinsic design.” The industry agrees with this as the transition from batch to continuous production is truly one of the most vital developments in pharma processing.

Taking this point ahead, Dr. Carsten Schmidt, Head of Drug Product Development, Global Drug Product Development as part of Global CMC Development at Merck says, “Some of the positively affecting manufacturing costs of CM products versus batch products are reduced processing time (going down from weeks to hours) and, especially important during formulation and process development of new products, the significantly reduced API demand for process development and tech transfer from R&D to commercial sites.” He continues that the space required to run a continuous manufacturing line is much smaller compared to classical manufacturing equipment which also lowers the manufacturing costs of CM products.

Artificial Intelligence

In the pharma manufacturing sector, Artificial Intelligence (AI) is becoming a game changer as it can enhance accuracy, efficiency, quality, speed and even reduce costs. “AI enables predictive maintenance, quality control, and supply chain optimization,” shares Dorota Owczarek, AI Product Lead at AI development company, nexocode. “AI-powered systems can analyze vast amounts of data and identify patterns, enabling smarter decision-making and reducing the time and cost of bringing a new drug to market. Additionally, AI can enhance the safety and efficacy of drugs by providing real-time monitoring and control of the manufacturing process.”

In short, this next-gen technology can be used for different purposes in the pharma manufacturing space such as predictive manufacturing, quality assurance, predictive maintenance for pharmaceutical production line, streamlining production schedule and even for supporting the intensification of continuous manufacturing.

Merging continuous manufacturing, AI and PAT

In the pharma manufacturing sector, continuous manufacturing is being merged with AI and PAT (Process Analytical Technology) to deliver quality products. “Advanced data-driven modeling based on AI solutions can be applied to comprehensively monitor and predict the whole biopharmaceutical manufacturing process (and not just single unit operations),” shares Owczarek. “This is especially vital in continuous manufacturing. The emerging trend in moving towards continuous manufacturing drives the development of more robust artificial intelligence-based systems that automate process management.”

She explains that complex non-linear process models can be analyzed and interpreted automatically through advanced artificial neural networks or deep learning algorithms that identify exceptions and provide alerts and feedback. PAT probes can be used to detect critical quality attributes in real-time. The slurry can be sent to waste as soon as the deep learning model finds an out-of-specification material or uniformity anomaly, suggesting an abnormal content mix to ensure final product quality and save production time for the quality production process.

“The improved data quality and decreased lead time provided by real-time PAT monitoring and data analysis in conjunction with an integrated system control support a real-time release (RTR) and the quality by design (QbD) strategy. This method reduces the need for post-process quality testing, meets the regulatory framework and process safety, and considerably lowers inventory levels and lead times,” says Owczarek.

Schmidt gives us firsthand information about the benefits of using these solutions at the German multinational science and technology company Merck KGaA. He elaborates, “The implementation of CM at Merck drives innovation by the implementation of innovative analytical technologies such as PAT, the implementation of advanced models and control systems finally paving the way to RTR. It helps to further increase the level of process control and understanding and thereby increases the level of product quality.”

He adds that as all unit operations are under steady control and are adjusted automatically within pre-defined limits, the final product´s characteristics remain within much tighter limits leading to reduced need for re-work or even batch rejections which contributes to reduced product´s cost by continuous manufacturing.

“The use of continuous manufacturing technologies and inline PAT monitoring is a key driver of building QbD into the complete product lifecycle, from R&D through to manufacturing, with the ultimate aim of getting safer medicines to market in a more efficient and cost-effective way,” says Holman. “Using model-based supervisory advanced process control (APC) to capture unique equipment, material and PAT characteristics creates a system that increases precision and optimizes the yield, capacity and OEE of the continuous manufacturing equipment.”

With the implementation of these three solutions, the industry is already witnessing a significant change in its production processes. As more advanced technologies enter the market over the next few years, the pharma manufacturing industry will aim to incorporate these innovative solutions in order to becoming more efficient, productive and smart.

(ID:49190592)