The pharmaceutical market is changing rapidly thanks to the success of biologics and other cell and gene therapies. By 2016, biologics accounted for six of the top eight drugs by revenue, according to a study by Mordor Intelligence. The FDA, meanwhile, expects to be approving 10–20 new gene and cell therapies annually from 2025—having approved the first in 2017.
With a change in the market comes new challenges for pharmaceutical and biotechnology companies, and their suppliers, especially in the manufacture of new therapies. Overcoming these problems requires novel approaches, including the digitization and integration of bioprocessing steps. This was among the topics for a recent series of seminars and tours given to journalists at the GE Healthcare Life Sciences site in Uppsala, Sweden, which coincided with a Bioprocess Days event held for GE staff and customers.
A major trend driven by biologics is the fragmentation of the market. According to Günther Jagschies, PhD, senior director, strategic customer relations, for GE Healthcare Life Sciences, there’s a growing trend toward redundancy in medications. For example, psoriasis could see 6 to 10 new monoclonal antibodies (mAbs) plus at least 10 biosimilars to existing products on the market in the next couple of years.
In addition, we are witnessing the fragmentation of production technology, said Jagschies. Companies are now producing antibodies, different types of modified antibody, and classic products manufactured via fermentation, such as insulins, in the same facility. With many products competing for the same niche, market share is smaller, and, thanks to multiple production technologies, so are batch sizes.
“As a consequence of precision medicine, a wider range of modalities are being manufactured,” says Ben Newton, chief digital officer at GE Healthcare Life Sciences, speaking exclusively to GEN. “A few years ago, there were huge batch sizes of small molecules, such as pills, and now it’s all infusion with antibodies.”
With lower volumes of niche drugs, he explains, pharmaceutical and biotech companies are looking to increase their operational efficiency to decrease drug development and manufacturing costs. And part of that is turning to the digital laboratory, which—for Newton—is focused around optimization of process development and automation of drug development and biomanufacturing.
“It’s an imperative for our customers because of emerging technology, such as computer and sensor tech, which wasn’t there 10 to 15 years ago,” adds Christopher Kopinski, global head analytics, GE Healthcare Life Sciences.
“All these imperatives are thrown into sharper focus in the gene and cell therapy space—you don’t just have an antibody, you have real live cells,” notes Newton, who argues that analysis and automation throughout development and manufacturing are essential. “The timescales are more acute, and any freezing and thawing puts into sharp focus quality, efficacy, and viability. So, the ability to monitor and manage that vein-to-vein supply chain is going to be imperative.”
According to a presentation by Catarina Flyborg, general manager for cell and gene therapy at GE Healthcare Life Sciences, cell therapies spend 10–20 days in production, but today’s thinking is to reduce this to 5 days or less. Likewise, cell and gene therapies have complex supply chains requiring expertise in engineering, logistics, and biology. “Getting the right product to the right person needs machine learning (ML) and AI,” she says.
Equipping the digital lab
For Newton, GE Healthcare Life Sciences’ vision of the digital laboratory begins at the R&D phase. He explains that 40% of all pharmaceutical R&D studies are probably a waste of time, as the results are insufficiently captured or capitalized on to make decisions. From Phase I to approval, there’s only an 8% chance of success.
One way to optimize clinical trials is stratifying patient populations using big data. In one example, GE Healthcare is working with the Vanderbilt-Ingram Cancer Centre to provide AI tools to study the health records of patients who’ve received immunotherapy. Among other things, the aim is to select patients for clinical trials who are likely to respond to treatment and to identify those at risk of side effects.
“Predicting which patients respond most effectively is critical,” explains Newton. “Getting them the right kind of therapy early can be essential for their survival, but you can also take a patient off a drug that’s not working.” Subsequently, he says, patients can be followed to see if they relapse. Other digital solutions include laboratory workflow and execution systems, which can free scientists from reporting and documentation.
From the R&D phase, digital tools can be used to help companies design their manufacturing process including, for example, predicting cell culture performance in antibody production using a GE bioreactor digital twin. According to Newton, this feeds existing data from a customer into an analytical engine to help optimize yield, media changeover, and harvest times. The parameters can be retained and compared to future experiments.
“If you understand your process well enough to know where there’s a deviation or something going wrong, you can correct course, or reduce or prevent an undesirable outcome,” Newton says. The knowledge from the digital twin can also be shared, reducing the learning curve when a process is started at a different site.
Other software offered by the company includes OptiRunTM digital solutions, which GE is trialling with selected gene and cell therapy, and antibody-manufacturing customers. It’s due to launch in August. The company claims OptiRun can remotely monitor biomanufacturing equipment at different sites, saving scientists from sitting beside the instruments to generate data (like flow rates) in real time. In addition, scientists working in gene and cell therapies can use AI tools to compare these parameters with yields of CAR-T cells, and other outcomes.
Delivering a customer–supplier partnership
Another aspect to GE Healthcare’s approach is using analysis and automation to better understand the link between raw material variability and the performance of biomanufacturing processes. “It’s an imperative for us to understand our products,” says Newton. “If we can control their attributes, and how they behave in cell culture and chromatography, we can ensure our products deliver high performance, and we can stay a leader in our field.”
With this in mind, GE Healthcare and Amgen launched a project to share real-time data between GE Healthcare’s raw material manufacturing site in Logan, UT, and Amgen’s process development centre in Cambridge, MA. “We spent a couple of years connecting devices, looking at processes and the quality attributes of the materials we make there,” says Newton.
According to Kopinksi, the project marked a major leap from a pre-digital factory with manual processes and low-level automation. In the past, Amgen received a certificate of analysis listing chemical and physical properties of each batch of cell culture media. “With the Amgen partnership, we’re physically connected. As materials are made, and batches produced, we assess the effect of those parameters on outcomes, and that data is fed in real-time to Amgen so they can course-correct their manufacturing,” Newton says.
The information exchange is two-way, he explains. While Amgen receives product information to optimize their processes, GE Healthcare receives information on product performance, which they could use to optimize their products. “Once you offer real-time data about raw materials, you truly become a partner,” Newton says.
Connecting everything together
The novel aspect of the GE Healthcare Life Sciences approach is offering a one-stop shop automated solution to gene and cell therapy clients, Flyborg explains to GEN. “We know the customer doesn’t want all things from GE, but we have the ability to connect an overall workflow, and the ability to help customers with process optimization, as well as training and education. We are one of the few to offer digital services, unit workflow, and turnkey installation to a customer—that’s our differentiator.”
With that in mind, GE Healthcare Life Sciences has acquired companies, such as cryochain technology company Asymptote, to address gaps in their existing hardware solutions. The aim is to package hardware and software into sealed, automated sub-components for customer purchase, to ensure good, consistent quality products with a low risk of human error and contamination.
To allow customers to connect instruments together, the company has just launched Chronicle.bio—an automation software suite to steer GE Healthcare’s cell therapy hardware. The software is aimed at the medium-sized customer, who wants to make small batches, but doesn’t want to go to full manufacturing scale. For the moment, Chronicle.bio is compatible with several benchtop-sized instruments.
The ultimate dream is to create a cell therapy platform that can handle any cell type or manufacturing process—at any scale. Perhaps even “cell therapy in a box.”
“If you get costs down, more people can access and get the full benefit of cell and gene therapy,” Flyborg says. She is excited by the prospect that cell therapy could cure solid tumors and—from there—other diseases, by looking at different types of natural killer (NK) cells. And, when companies do, she hopes GE Healthcare will be right alongside them.
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