The pharmaceutical industry continues to exponentially increase as new methods and technology become a launchpad for innovations, especially within the cell and gene therapy industry. According to a Pharmaceutical Research and Manufacturers of America (PhRMA) report (1), it takes, on average, 10–15 years and costs roughly $2.6 billion for a new drug to go from discovery to market. PhRMA also reported that 74% of clinical development are new approaches to treating disease across what is currently in the pipeline. Additionally, scientists and researchers are leaning toward a tailored approach to personalized medicine. FDA has predicted that by 2025 they will approve between 10–20 cell and gene therapy products per year (2).

Traditional ways of looking at the discovery and development of pharmaceutical and biopharmaceutical products, therapies, and treatments are not meeting the industry’s demand. As new approaches are being researched, conventional wisdom has forced biopharma companies to choose between two options in developing products: either build their own facilities, which can take years and cost millions, or outsource to contract manufacturing organizations (CMOs)/contract development and manufacturing organizations (CDMOs), which, especially in the wake of COVID-19, are facing years of backlogs.

To solve this manufacturer’s dilemma, companies are considering an innovative way to accelerate the development of pharmaceuticals and biotherapeutics—cleanroom licensing. Cleanroom licensing is a hybrid approach between do-it-yourself (DIY) and outsourcing to a CMO/CDMO that gives early phase or startup bio/pharma companies the opportunity to achieve their goals in a shorter timeframe than anticipated. This article will explore the benefits and challenges that companies, especially early startups, face in manufacturing and how cleanroom licensing puts them on the path from discovery to delivery.

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Ravi Samavedam is chief innovation officer at Azzur Group.

When referring to this article, please cite it as R. Samavedam, “Threading the Needle Between DIY and CDMO,” 

BioPharm International, Manufacturing and Facilities

Articles

In the all-too-common debate over building lab facilities versus outsourcing, the best strategy may be the middle ground: licensing.

Threading the Needle Between DIY and CDMO

The world around us is rapidly changing. From modern medicine breakthroughs to a worldwide health crisis response, life sciences manufacturers must turn their focus to speed and reliability. One way they are doing this is by employing advanced single-use systems (SUSs) in connected facilities. It is well known that single-use equipment can help manufacturers increase efficiency and profitability by simplifying production and reducing the need for clean-in-place operations. But when many think of single-use technologies (SUTs), they often think of low automation; when in truth, the next generation of SUTs is highly advanced and offers a wide range of flexibility manufacturers need. These advances in SUSs help manufacturers add equipment that allows them to complete faster changeovers, provide flexibility in recipe management, and improve uptime. Technical advances are helping manufacturers get their pharmaceutical products to market faster while providing opportunities for increased automation. When the project goals are to maximize flexibility and data capture, while laying the foundation for digital transformation, early automation design collaboration is key to successfully starting up or adding intelligent technologies to a single-use facility.

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Ryan Campbell is the technical consultant manager for Rockwell Automation. Kevin Schreier is the director of process engineering for IPS-Integrated Project Services, LLC.

When referring to this article, please cite it as R. Campbell and K. Schreier, “From Design to Qualification: Creating the Most Efficient Single-Use Facilities,” 

Through collaboration and transparency, engineering and automation companies can achieve great efficiencies and success for their customer by integrating intelligent design into a facility.

From Design to Qualification: Creating the Most Efficient Single-Use Facilities

As pharmaceutical manufacturing grows in pace and complexity, companies are increasingly looking to Pharma 4.0 as a solution, with its promise of simplified workflows, shortened timelines, and more cost-effective routes to market. But while Pharma 4.0 offers many opportunities, the route to achieving Pharma 4.0 is challenging. Prioritizing the wrong technologies early in the transformation process can have severe and long-lasting impacts, and at every step of the journey pharmaceutical companies are faced with stumbling blocks that can halt progress.

Nicola Gardner is senior product marketing manager at Thermo Fisher Scientific.

When referring to this article, please cite it as N. Gardner, “Smoothing the Path to Pharma 4.0: Challenges and Solutions,” 

By taking a digital maturity-first approach to Pharma 4.0, manufacturers can optimally position themselves for success.

Smoothing the  Path to Pharma 4.0:  Challenges and Solutions

Today’s work environment presents unique challenges, ranging from managing huge quantities of data to recruiting and maintaining employees with the critical skills needed for manufacturing operations. Through these challenges, how can companies ensure that a business maintains regulatory compliance, ensures quality, retains process knowledge, and safeguards business continuity? This can be done by leveraging machine learning and data analysis from original equipment manufacturers (OEMs) with the expertise to provide system operational feedback.

Effective use of data represents one way that manufacturers can address these issues.Through the examination of an example, the authors of this article will show how the use of machine learning, artificial intelligence (AI), and subject matter experts (SMEs) enabled one major pharmaceutical customer to better manage their water systems. Digitalization empowered SMEs from the equipment supplier to use operational history, process acumen, troubleshooting knowledge, key performance indicator (KPI) analysis, and data transparency for critical insights into every facet of system operation. This also provided financial benefits to the end user by managing production cycles, capital circumvention, quality assurance, increased reliability, alarm avoidance, decreased labor cost for troubleshooting, and many more. The use of data management can also drive increased automation so that plant labor can focus on more high-value activities with the confidence their water systems are running optimally.

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When referring to this article, please cite it as C. Robinson and J. Robes, “Machine Learning and Data Analysis for Optimal Productivity of Pharmaceutical Water Systems,” 

Leveraging smart technology and SMEs for significant operational and financial benefits.

BioPharm International, Manufacturing and Facilities November 2022

Threading the Needle Between DIY and CDMO

From Design to Qualification: Creating the Most Efficient Single-Use Facilities

Smoothing the Path to Pharma 4.0: Challenges and Solutions

Machine Learning and Data Analysis for Optimal Productivity of Pharmaceutical Water Systems