Biopharmaceutical industry adoption of digital manufacturing techniques—those in which process data is used to model and control processes—has increased in recent years.
According to analysis by PwC, emerging challenges like globalization, supply chain complexity, price, and cost pressure have helped the biopharmaceutical industry overcome its previous reluctance and embrace innovation. Similarly, Bain & Co says cost pressure has prompted industry to invest in digital manufacturing.
These views are shared by Véronique Chotteau, PhD, of Sweden’s Royal Institute of Technology (KTH) cell technology group, who says biopharma adoption of digital manufacturing is accelerating.
“There is a clear movement towards digitalization in the biopharmaceutical industry,” according to Chotteau, who coordinates an EU project developing in-line sensors and high-throughput miniaturized bioreactors for industrial use.
“The range of applications for digitalization within bioprocessing is very large, stretching from Internet of Things (IoT), cloud and database handling, to automation and systems based on mathematical model.”
And the change is being driven by large pharma companies willing to invest in the necessary infrastructure, Chotteau adds, citing AstraZeneca’s use of digitization and lean manufacturing at its facility in Södertälje, Sweden, as an example.
This new found willingness to invest in innovative manufacturing technologies reflects the emergence of a new generation of executives who understand their benefits, Chotteau says.
“Manufacturing of biologics relies on cells, nowadays often mammalian cells, which are both complex and have an inherent variability. Facing this complexity, the field has traditionally relied on human surveillance supported by redundancy. However, due to a combination of improved technology and generation shift, this is now changing,” she points out.
“Two or three decades ago, today’s leaders deciding on investments and technical focus in companies, were PhD students either working with sensors, mathematical models, and feedback control, which became Process Analytical Technology (PAT), or AI.
“These technologies have also evolved a lot, which make them attractive today and near to offering solutions.”
Chotteau, who is also director of the KTH’s Competence Centre for Advanced Bioproduction by Continuous Processing (AdBIOPRO), says the move away from batch-mode production is another factor.
“Continuous bioprocesses, not to mention perfusion process, are obviously now a rising interest, with support from FDA and EMA,” she tells GEN. The need for on/in-line monitoring, mathematical models, and feedback control for these processes is much larger than legacy batch operation, which is also a motor for increased PAT and this type of approach.”
Expertise
Staff with experience will also play a role in helping industry maintain its digital momentum, according to Johan Rockberg, PhD, associate professor in antibody engineering and directed evolution at the KTH Royal Institute of Technology. Currently, Rockberg says, there is a shortage of digital manufacturing expertise with knowledge often siloed rather being shared between different scientific disciplines.
“This means that industry is struggling to find talent and needs also to arrange a puzzle of disciplines to cover all its needs. There is greater need mobility between the sectors, in particular for addressing needs in manufacturing of cell and gene therapy products,” he explains.
Addressing the shortfall will require support from academia, according to Rockberg, who suggests that universities are yet to fully adapt education programs to the digital needs of the industry.
“To date the volume of students [seeking education in digital biopharmaceutical manufacturing] has not been large, which means as well that it is not often prioritized,” he continues. “Another aspect is that academic research in bioprocessing worldwide is rather limited due to funding policy, although this has been slightly better since a couple of years, and this means as well that the number of high educated people in bioprocessing is rather low.”
