Cutting Time from R&D to Manufacturing

Life science tech transfer and validation gain efficiency as companies employ a modular S88 approach, cutting development costs and speeding time to market.

Threading R&D to manufacturing. (Source: Johnson & Johnson)
Threading R&D to manufacturing. (Source: Johnson & Johnson)

In the changing life science industry, a company’s success hinges on its ability to introduce new products safely and quickly, connecting R&D to bulk production and piecing data together in a meaningful way. Historically, the approach to bringing a product to market has been fragmented—steps like R&D, clinical batch production and bulk production have been treated as individual operations, each involving single-purpose systems and a reliance on tribal knowledge.

The traditional manufacturing execution system (MES) has been designed for one product and one process, with the goal of maximizing yield at the lowest cost. But the next-generation facility must be able to rapidly respond to product (and process) changes, in part because the facility may accommodate multiple products. Across the industry, companies are looking for ways to systematize tech transfer to introduce new products and make process changes in a cost-effective and agile way.

Fragmentation to integration

To create innovative systems, companies have spent considerable time examining the drawbacks of the current processes. The islands of automation—and resulting islands of data—that evolved from single-purpose solutions have led to overall systems that lack efficient connectivity, with many handoffs between levels of the manufacturing hierarchy. Each island is, understandably, concentrated on producing the life science product and documentation to meet its own specific requirements, without consideration of the full product lifecycle.

Companies often lack the flexibility to introduce recipe changes or new products in a cost-effective manner. “It’s very cumbersome to take [the master control] recipe and roll that out across the plants in a seamless way,” says Douglas Gray, director of standards, analytics and visualization at Johnson & Johnson.

But many life science companies, including Amgen and Johnson & Johnson, have been adopting a product lifecycle framework that promotes partnership between supply chain, production, maintenance, quality and distribution. Beginning with the end user in mind, the approach is driven by product flow from R&D to patient use.

“Ultimately, we believe in making sure we’ve got a system and process from R&D that will drive the recipe all the way down into facilities,” Gray says. “Across the globe, we’ll have one general recipe, multiple site recipes, and then those will be automatically executed in various control systems in a consistent manner.”

The end-to-end strategy is helping companies meet customer needs by reducing the time to fulfill technical, regulatory and business requirements. Gray explains a three-part content-execution-visualization (CEV) framework, beginning with the right content being input, followed by consistent execution (similar production across the globe with real-time data tracking in ready-to-use contexts). The framework concludes with the visualization of data that allow for process and product analysis that support faster and better-informed decisions.

The S88 approach in tech transfer

One of the keys to success in product lifecycle management is the S88 framework used to standardize automation. The ANSI/ISA-88 (S88) is a standard for batch control that provides a structured way to segment operations. S88 separates recipes from equipment control, which allows changes to be made to either the control software or the recipe without affecting the other. This means that software can be designed based on the capabilities of the equipment, unlimited by a specific product recipe. Another main feature of S88 is modular design: recipes and blocks of information that can be copied or reassembled, which can save time during maintenance or implementation of new projects.

“S88 is about taking all the activities we perform, breaking them down into reusable blocks of information, then selfishly (and diligently) reusing them wherever we can,” says Marc Hooybergs, senior director of global execution systems at Johnson & Johnson.

Though S88 is a useful tool for the development of control software, it also provides value as a philosophy: The segmented approach can be used to reduce time and cut costs in the rollout of master recipes from corporate headquarters to manufacturing sites that may have different equipment, raw materials, packaging, etc. Additionally, the platform provides common terminology to help keep vendors and manufacturers on the same page.

Reducing development time

The approach can lead to reduced NPI cycle time by simplifying regulatory filing and development through the use of reusable blocks of code, Hooybergs explains. With a general recipe built in the R&D stage (containing regulatory submission information), unique manufacturing sites can transform and auto-generate their DeltaV master recipes. Tech transfers can be 40 percent faster, and require 50 percent less effort to validate.

The data model provides stakeholders with real-time visibility into manufacturing to make better decisions as the process is happening rather than after the fact, while full electronic batch release helps to expedite product shipment. Scientists can also benefit from better understanding as the focus shifts from obtaining the right documentation to obtaining useful data for process knowledge.

Presented at this year’s Emerson Global Users Exchange in Denver, recent DeltaV standardization efforts by Janssen (part of Johnson & Johnson Pharmaceutical Research & Development) have shown major gains, with five sites deploying standard DeltaV site infrastructure in parallel. One site reported saving 2,500 hours, while another saved $100,000 per skid. One consumer plant in India had a 90 percent reduction in recipe generation.

Looking to the future, Amgen’s Greg Bischoff emphasizes the need for streamlining automation and data transfer as the industry shifts its focus to patient-based value. Of particular importance is the need for continued innovation in single-use instrumentation (flow, pressure, dissolved oxygen sensors, etc.) as automation becomes more sophisticated. To promote the delivery of the right drugs to the right patients at the right time, systems must be in place to integrate patient data all the way through manufacturing and the supply chain, and to produce the drugs in a safe and agile manner.

The need for additional alignment

Though the S88 approach is helping to standardize life science automation and tech transfer strategy, it is not a silver bullet. “Many disciplines, tools and techniques must be aligned to a vision of standardization for true change to take place within an organization,” says Jeff Hackney, manager of North American life sciences business development at Emerson Process Management. “Process design, automation design, recipe design, business processes, SOPs, QA, QC and more must be considered holistically to achieve the goals being set forth in the industry.”

Any changes in the production of life science products must be accompanied with appropriate SOPs, data management, sample tracking and analytic technologies to ensure patient safety. Experts are exploring the possibilities of standardizing in other areas. Examples include the incorporation of more versatile manufacturing components to reduce inventory demands and increase flexibility, or the creation of a single bioreactor standard for a predefined equipment list so that facilities can conform SOPs to their equipment, design by omission rather than addition.

Will building a new facility ever be as easy as assembling modular blocks like children’s toys? No. There will always be a need to customize and reconfigure recipes and control logic. But the S88 tech transfer platform is already helping companies by significantly reducing development time and cutting costs, speeding time to market and allowing capital to be allocated to other advancements in science and automation.

 

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