By Jason Beckwith, PhD, Stephen Goldrick, PhD, William Nixon, PhD, and Stavros Kourtzidis, PhD
The emergence of the COVID-19 pandemic in 2020 increased the demand and competition for a skilled biomanufacturing workforce while accelerating a technological change in the field, specifically the advancement and exploitation of new modalities such as automation, artificial intelligence, and supply chain expertise.
As the industry focused on vaccines and virus-associated therapies, particularly mRNA vaccines and therapeutics, the pandemic quickly and sharply raised the demand for staff to support the operations scale-up across the biomanufacturing industry.
Post-pandemic, the industry is currently experiencing personnel retention and attraction challenges, combined with an associated large-scale rise in compensation demands from an “experienced talent pool” undergoing career transfers.
The demand for new talent in the biomanufacturing industry was already growing before the COVID-19 pandemic, with an increase of 26% from 2018 to 2020. By the end of 2021, a further 32% increase in demand was observed in the United States and Europe, against a 10% rise in the supply of expertise (Figure 1).
The onset of COVID-19 provided severe disruption to biopharma business models. Specific to experienced staff, existing models struggled with issues like attraction, development, leadership, and structure. The increase in drug manufacturing, speed, and responsiveness, with an associated increase in expertise demand, saw companies typically turning to shallow local talent pools, eventually moving to expensive migration models.
Cytiva, in collaboration with Longitude, developed the Global BioPharma Resilience Index (a survey to rank biopharma capabilities in twenty countries). “Access to talent” was cited as a main area in which the industry was at its weakest, combined with manufacturing agility and supply chain flexibility.1
While the adoption of emerging and innovative technology may address some of the challenges, the issue of sourcing experienced staff may propagate. The global survey of approximately 1,000 executives stated that the obtainment of manufacturing talent is a substantial challenge, citing cost as the key concern.
Biopharma business transformation
Prior to COVID-19, manufacturers viewed digital transformation as a long-term objective. Today, it is a necessity. We are witnessing a rapid uptake of digital technologies within the biopharma sector in order to facilitate internal and external operations. The increasing role of artificial intelligence and large-scale data analytics have created a requirement for a broader set of skills. This has positioned the sector in direct competition with the technology industry.
Current gaps in automation are limited to real-time monitoring and data analysis across workflow. Automation systems for equipment monitoring and coordination, process tracking, monitoring and control, and efficient utilization of facilities and resources, are used to support a flexible manufacturing strategy. There is a requirement to significantly expand the biomanufacturing workforce in order to realize the full potential of the bioeconomy. The shift towards automation and digitalization in manufacturing has generally created a common skillset across traditional manufacturing technologies that could be translated for the biomanufacturing workforce.
Industry 4.0 is poised to transform the production process and how facilities are run. Bioprocessing 4.0 will not rely on one specific technology or optimized process but will instead be a collection of interconnected solutions bringing innovation across the entire ecosystem of equipment, increasing automation, and connectivity.
The growing level of complexity, combined with the introduction of innovative technologies, are changing the skills and demand requirement for new hires, with more diverse technical and scientific skills sought, such as digitization and automation (Figure 2).
Cost of talent
While the cost of talent and talent availability have been cited as a concern, the specific issue may be due to lack of efficiency in the hiring process. The key drivers to ensure the biopharma industry has continued access to the people with the advanced skills required include:
* Availability of a talent pool, including industry migration
* Correctly benchmarked compensation levels aligned with talent pool dynamics
* Efficient “candidate sourcing” methodology
* Reduced time to hire, i.e., streamlining
The cost of talent is increased by delaying the “time to hire.” It is common for biomanufacturing companies to have vacancies open for six months to one year. The delay in the “time to hire” is compounded by the recruitment methods adopted by the industry, commonly utilizing inexperienced internal recruitment methods, such as using recruiters deficient of sector knowledge or networks.
In addition, reliance on inaccurate and historic compensation data can lead to failure to secure experienced talent, distinct from the creative companies that are providing competitive offers. These factors combined increase the business cost and can be preventable.
However, even though wages are rising, expectedly resultant from the increased expertise required and talent market dynamics, the augmented cost is directly related to an increased “time to hire,” leaving business-critical posts vacant for extended periods of time. In addition, to align to the fluctuating micro-economic climate, providing competitive and creative compensation models should also be considered.
As one of the authors (Beckwith) of this article has noted, ‘’To secure experienced talent, hiring teams need to not only be agile, but they also need to be quick. Inefficient hiring processes will lead to losing candidates to companies with stronger hiring methods.”
Research conducted by Evolution2,3 using a data sample of >30,000 biomanufacturing personnel, in collaboration with the University of Dundee and University College London, has developed a predictive analysis model to highlight strategic market intelligence to industry leaders specific to the talent market. The aim is to measure, model, and predict a “supply versus demand” of biomanufacturing key personnel across “business-critical” roles required for the successful operation of the biomanufacturing industry.
The outcome data aims to allow specific planning, where required, on creative talent acquisition, specific to segments of biomanufacturing workflows.
Current modeling, over the previous three years, illustrates a critical shortage of biomanufacturing talent is due to arrive in 2026 (Figure 3).
As companies reassess their manufacturing networks and strategies, a Q2 2022 correction is underway, with demand for talent back at Q4 2020 levels, an increase which is predicted throughout 2022 and onwards.
Over the past 12 months, the biomanufacturing industry has seen increased capital investments as biologics, cell gene therapy, and new modality capacity ramps up. A selection of investments in 2021 is presented below:
- Fujifilm Diosynth Biotechnologies, $2 billion, large-scale cell-culture biomanufacturing facility in North Carolina, US, operational by the spring, 2025. Additional investments in Texas and UK.
- Lonza, $935 million, Biomanufacturing facilities in Switzerland & Portsmouth. Microbial capacity expansion (Switzerland) plus additional capacity for cell culture, purification, and analytical services (Singapore).
- Samsung Biologics, $1.7 billion, new biomanufacturing plant, South Korea.
- Thermo Fisher Scientific, $875 million, cell- and gene-therapy manufacturing and traditional biomanufacturing expansion, US.
The market dynamic snapshot in Figure 4 shows some companies are retaining strong hiring activities.
Many challenges are apparent as the biomanufacturing industry audits itself post-Covid-19. An immediate emphasis on the skills gap and talent access is urgently required, with a higher priority placed on strategic recruiting to get ahead of the growth and demand curve, while also keeping abreast of the competition for talent.
On the other side, universities supplying industry candidates will need to be aware of the rapid advances in technologies used in biomanufacturing and the complexities of regulation and compliance.
Jason Beckwith, PhD (firstname.lastname@example.org), works as the managing director of the Evolution Search Group and carries out research activities at the University of Dundee School of Business; Stephen Goldrick, PhD, serves as a lecturer at University College London in digital bioprocess engineering, specializing in the application of advanced data analytics and mathematical modelling to the biotechnology sector; William Nixon, PhD, is Emeritus Professor at the University of Dundee School of Business; and Stavros Kourtzidis, PhD, is a lecturer at the University of Dundee School of Business.