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Front-end focus and new approaches are speeding scale-up and reducing costs, while scale-down and scale-out become increasingly important.
Years ago, scaling up the production of a new therapy was a linear, iterative process that demanded patience and deep pockets. Best practices, and more than a little trial and error, moved processes from the bench to the manufacturing floor. Over the past decade, as manufacturing operations have become more complex, engineering advances in modeling, digitalization, single-use process equipment, and process intensification have made scale-up more systematic, for both small and large molecules.
“A decade ago, most scale-up would have been a very linear process with lab-scale going to kilo lab-scale to pilot plant-scale and, for successful products, to an in-house existing batch production facility. Now there are many more nodes of partnerships and equipment choices to be made,” says Joe Hannon, CEO of Scale-Up Systems. “It’s no longer just about getting reaction, workup, and isolation steps to work as best they can in existing multi-purpose equipment, but also about reconfiguring modular components in a continuous process to fit the equipment to the requirements of the chemistry. This is allowing a lot more innovative thinking and is pushing the boundaries in developing chemistry in ways that were not considered feasible until recently,” he says.
As a result, scale-up is becoming a more finely tuned process, with scale-out and scale-down playing more important roles. “The era of blockbuster production strategies has transitioned into scale-out and even scale-down for most of the bioproduction market,” says Michelle Stafford, global product marketing manager, Enterprise Solutions, GE Healthcare. “Multiproduct production models that utilize single-use technologies are now more common, and scale-out is becoming the norm, where increased flexibility and platform standardization enable faster changeover between batches and faster tech transfer,” she says.
At the same time, contract development and manufacturing organizations (CDMOs) have assumed a dominant position in scale-up and must master a wide range of scales to meet clients’ needs. “Speed to clinical phases is faster now, and biopharmaceutical manufacturers are targeting smaller patient populations and specialized drugs in order to access the market faster, reach patients, and get financial returns sooner than ever before,” says Stéphane Varray, head of commercial development in Lonza Pharma and Biotech’s mammalian and microbial development and manufacturing business unit. “Based on that paradigm shift, manufacturing scale needs to be adaptable along the full lifecycle of the product. Moving from a small scale to a larger-or vice versa-must be done smoothly, in the context of a regulatory framework that is growing more complex,” he adds.
“Overall, the scale-up process remains the same, regardless of the volume of product being produced, but strategies have changed,” says Sebastien Ribault, senior director of MilliporeSigma’s global Bioreliance end-to-end delivery and sales, and managing director of MilliporeSigma’s Biodevelopment Centers, the company’s CDMO division. “We are not using one scale in the lab and another one in the facility anymore, but multiple scales in the facility,” he says. In 2010 and 2011, he says, the company invested in developing models to help its scientists understand how biomolecules behave at various scales, he says. As a result, he says, it has scaled all biopharmaceutical processes up directly (i.e., in one pass) since 2012, where previously, efforts may have required going back to the drawing board.
Within the past five years, pharmaceutical manufacturers have become more comfortable with advanced process control and are embracing other advanced manufacturing concepts, says Fernando Muzzio, professor of pharmaceutical science at Rutgers and head of the Center for Structured Organic Particulate System (C-SOPS), which has been focusing on tech transfer and commercialization of continuous manufacturing processes for solid dosage forms.
Hannon, whose company specializes in scale-up simulation software for small-molecule APIs, sees a definite change in the way that manufacturers are approaching simulation. Where five years ago, they might simply require that a unit operation undergo simulation studies and specify the time required, they are now using simulation to couple batch kinetics with continuous equipment characteristics. “They want to operate flow chemistry optimally on the first run,” he says. “We are now seeing more of an appetite for deep process understanding around the reaction and impurity-formation mechanisms to support right-first-time operation in flow on scale,” says Hannon.
Branded pharmaceutical and even generic-pharmaceutical manufacturers are increasingly interested in continuous manufacturing, says Muzzio, which allows development and manufacturing to take place at the same scale on the same equipment, eliminating the equipment scale issues that have dogged scale-up in the past. Most new chemical entities (NCEs) that are going from lab to larger scale still face scaling challenges, however, in that the next level equipment is significantly larger than the laboratory equipment, says Hannon. “Sound chemical engineering principles such as mixing and heat transfer must be engineered in for successful operation. And scale-down (i.e., being able to mimic production scale conditions closely in a laboratory setting) remains key to scale-up success, especially when troubleshooting a process,” he says. Beyond troubleshooting, Muzzio sees growing interest in scaling down to smaller lines for continuous solid-dosage form manufacturing. “Some companies are working with 5 kg/h, and a few, with 1 kg/h, which is ideal for products that use very small amounts of powder,” he says.
He recalls one company that opted to start with a very small line and to duplicate that line four times to manufacture a large-volume product continuously. “This approach makes sense, because the integration of process, software, and sensors accounts for a significant fraction of overall costs. If you simply copy one line, the additional capacity will not add too much to overall costs.” However, he notes, scale down must be approached carefully to avoid having to redo scale-up later on. In addition, he says, scale-down can be particularly challenging with powders, which can be much more difficult to transfer and mix at small scale than at larger scales.
Process intensification is becoming more important in biopharmaceutical manufacturing evidenced upstream by perfusion bioreactors and downstream by continuous chromatography. Tangential flow filtration (TFF) is becoming more prominent. In August 2019, Samsung Biologics scaled up alternating tangential flow (ATF) in a perfusion bioreactor at its manufacturing facility in South Korea. Samsung expects it to reduce processing time by 30%. Pressures to reduce cost of goods sold (COGS) and to meet smaller, specialized market demands are driving use of process intensification. “The goal is to increase productivity per some form of tangible measurement, such as in time, volume, or dollar,” says Andrew Yang, global product marketing leader for upstream bioprocessing at GE Healthcare. By integrating technologies, simplifying operations and offering insights via analytics, he says, it “offers a path to risk reduction and economic global manufacturing in an increasingly fragmented market.”
As Ribault notes, manufacturing scales have come down overall. MilliporeSigma is no longer using 10,000–15,000-L volumes for most of its work. “Now, our facilities are running at 2000 L or below. When we need more volume, we operate with multiples of 2000 L,” he says. The philosophy behind scale-up has remained the same, however. “You still need to understand the platform and the differences not only for downstream but the impact of change of scale for upstream, which means gaining a clear understanding of the impact of agitation and power input, and also the quality of the molecule. Agitation and oxygenation give you a cell that will result in the right level of product quality. That is what we focus on when we scale up,” he says.Modeling and scale-down studies are playing a greater role in providing key process knowledge required for scale-up. AbbVie, for example, used a combination of mass-transfer studies (KLa), computational simulation (i.e., the use of computational fluid dynamics to model shear-rate distribution within the bioreactor), and scale-down (i.e., developing proof-of-concept on a small scale in the lab, then scaling up to 200 L) in one recent project, in which the time required to reach process performance qualification (PPQ) was reduced to 18 weeks (1).
Ribault predicts that the use of digital twin technology will become more important. “In the future, we won’t need to run some steps at the bench and will be able to run process in-silico before running at bench,” he says. Multivariate data analysis is also becoming more important in allowing developers to use production data to determine optimal characteristics for components and equipment parameters and use those characteristics in a model to optimize scale-up and manufacturing, says Stafford.
In general, scale-up success demands coordination with tech transfer, and good project management and documentation are key, says Ribault, who notes that smaller research company clients may need to understand that research data alone cannot move a project to good manufacturing practice (GMP). “We don’t want to rush because we know the bare minimum that is required to scale up without intermediate scale and engineering runs. If we deviate from that bare minimum, we will not be managing the risk properly. In the attempt to save a few weeks, we may wind up wasting a few months, or even quarters,” he says.
To address these challenges, CDMOs and customers together should take a careful and forward-looking approach to planning for commercial supply, says Varray. This should include a clear idea of the scale of development, planning for a biologics license application, and a sophisticated regulatory approach. “This plan may be drafted as soon as Phase I is cleared. External partners can work together with customers to adapt manufacturing set-up and regulatory strategy while the clinical phase is ongoing,” he says.
Process intensification enables scaling out or building incremental capacity rather than scaling up to larger equipment. As this approach gains acceptance, the distinctions between scaling up and scaling out are blurring. “With the adoption of high titer processes, process intensification including continuous processing, and perfusion, the definition of scale-up and scale-out are synonymous such that requirement for product volumes are lower that can be achieved with single-use technology and replicated with increasing demand,” says Kenneth Dawson Green, manufacturing team leader with Samsung Biologics.
At large scale (15,000 L), utilizing stainless-steel bioreactors, Samsung replicates the number of bioreactors required to achieve the optimal volumetric scale (up to 180,000 L), he explains. However, for single-use, the typical working volume is between 2000–5000 L and replicated to achieve desired scale, he says. Increasingly, single-use and stainless-steel technologies are being used in hybrid systems such that the bioreactor seed train may utilize single use bioreactors, and the production scale utilizes stainless steel. Samsung uses hybrid systems for both upstream and downstream processes, Green says, factoring applicability, cost, ease of operation, operational risk, and waste-minimization into equipment selection, he notes.
It remains to be seen whether scale-out will become the preferred route for biopharmaceutical manufacturing in the future. At this point, both approaches are needed. “Adoption of continuous manufacturing, including perfusion, has led to the requirement for reduced product volumes with higher productivities for some products. The option to scale-out vs scale-up presents lower process risk and enables more efficient tech transfer when processes are transferred at the same scale,” says Green. However, he notes this approach is more practical with single-use technology and clinical products for which capital investment may be deferred. “For larger volume commercial products including biosimilars, large-scale stainless-steel equipment will remain the most cost-efficient platform,” Green says.
Increased cell- and gene-therapy development also poses questions for scale-up. “In cell and gene therapy, we see both forms of scale-up and out,” says Phil Vanek, general manager of cell and gene therapy strategy at GE Healthcare, who says all three approaches are needed. While many of the therapies today are autologous or patient specific, Vanek says, for certain applications (e.g., acute injury or non-durable treatment duration) allogeneic versions of autologous therapies may be preferred for access or cost reasons. “We use scale up where we can make multiple doses to serve large markets; scale out to meet the needs of patient- specific therapies, and, perhaps most importantly, scale-down in the appropriate high dynamic range platforms to do process development,” Vanek says. Process development can typically be cost-prohibitive, so platforms that mimic large-scale (up or out) systems, but at smaller scale, will allow quicker process optimization, regardless of scale,” he says. At this point, Vanek says, “The jury’s still out on whether scale-out or scale-up will prevail.”
1. Y. Wang, “Achieving Seamless Scale-Up and Tech Transfer: Case Study in Single-Use,” brighttalk.com, March 11, 2019.
Vol. 43, No. 9
When referring to this article, please cite it as A. Shanley, “Scale-Up: Getting It Right the First Time," Pharmaceutical Technology 43 (9) 2019.