by Iwan Roberts, Vice President, Technology and Innovation Strategy, Cytiva
The biopharma industry is in the middle of an uncomfortable contradiction. On one hand, scientific innovation is advancing at unprecedented speed. Cell and gene therapies, mRNA platforms, and other advanced therapeutics are moving rapidly from discovery into the clinic. On the other, the industry is struggling to deliver those innovations at scale, at speed, and at cost. Manufacturing, not science, is looming larger as the bigger barrier to delivering on scientific promise.
The latest findings from the Global Biopharma Index make that disconnect clear. Despite strong scientific progress, many companies remain behind on revenue, market share, and time-to-market targets. The issue is not a lack of innovation, but an inability to operationalize it. Digital investment is therefore no longer the preserve of large, mature players looking to optimize existing operations; it is becoming a competitive necessity. The question is no longer whether companies should digitize, but whether they can compete if they do not.
The real bottleneck isn’t science, it’s systems
Advanced therapies are fundamentally different from traditional biologics. Their manufacturing processes are more complex, less standardized, and inherently more variable. It requires navigation across different disciplines from recombinant protein production, the chemistry of nanoparticle delivery, or synthetic synthesis, to primary cells culture. Biotherapeutic processing has always been defined by the process, but the complexity, and inherent variation, in advanced therapies is creating so much data. We will only be able to improve the manufacturing processes and platforms if we improve the data collection, coordination, and decision-making processes.
Yet many organizations are still trying to scale advanced therapies with fragmented systems, siloed data, and disconnected workflows. The result is often data collection for its own sake: information that is captured, but not structured, connected, or trusted enough to improve decisions. That model does not hold at this level of complexity. Digitalization is not about incremental efficiency; it is about making new modalities viable for controlled commercial manufacture.
Cytiva’s Global Biopharma Index reinforces the point: high-growth firms are significantly more likely to deploy AI, automation, and advanced analytics across their operations. But these technologies only create value when they are built on a deliberate data foundation. The call to action is clear: companies must move beyond collecting data for data’s sake and build operating models where “data is the deliverable.” That is the foundation required to realize the full value of AI, automation, and advanced analytics.
Collaboration only works if it’s digital
No one should be building advanced therapy manufacturing in isolation. As the market matures, expertise is no longer concentrated among the early pioneers; it is increasingly distributed across CDMOs, technology providers, and specialist service partners. This gives developers access not only to capacity, but also to the technical and manufacturing expertise needed to advance new modalities. At the same time, these partners are becoming more deeply involved in shaping development and manufacturing strategies from the outset.
But deep collaboration only works when it is digitally connected. Without shared data models, integrated systems, and transparent workflows, partners create friction rather than momentum: decisions slow, risk rises, and accountability blurs. Digital platforms provide the common operating foundation that allows multiple organizations to work from the same version of truth. In advanced therapies, collaboration alone is not enough; connected collaboration is what turns distributed expertise into tangible value to the developer.
Scale from the start is non-negotiable
One of the most persistent failures in advanced therapy manufacturing is the transition from development to commercial scale. Processes that work at the originator lab often don’t scale – lacking the fundamental data that underpins process understanding and enables tech transfer. The result is delay, cost, and poor control that puts delivery to patients at risk.
The advanced therapy industry has debated the concept of scaling production from the outset, but too often it remains theoretical until tested under a baptism of fire when clinical programs force the CMC timelines. The sector bears the scars from its failures where inefficient and uncontrolled processes could not be re-developed and had to support commercial supply with associated consequences to business success.
Early digital tools use allows the theoretical to become actionable. They allow teams to model processes before they are built, test scenarios virtually, and generate structured data that carries through development, scale-up, and commercialization. Without that continuity, scaling remains reactive and risky.
According to Cytiva’s Global Biopharma Index, nearly 60 percent of companies report delays in bringing therapies to market.
Data is becoming the foundation of regulatory confidence
In advanced therapy manufacturing, data is not just operational, it is regulatory.
Regulators increasingly evaluate manufacturing across the entire value chain. Process understanding, data integrity, and traceability must hold up not only within one organization, but across all collaborators. Digital investment enables this.
Structured, traceable data environments improve visibility, strengthen auditability, and support faster, more confident decision-making. Organizations can respond to regulatory questions with evidence, not interpretation.
In a landscape where regulatory inconsistency is already a concern, this level of clarity creates a meaningful advantage.
Manufacturing is becoming more distributed
The industry is moving toward more distributed and regional production models. This shift is driven by the need for resilience, improved access, and reduced logistical complexity. It is particularly relevant for advanced therapies, where proximity to patients can matter.
But distributed manufacturing only works when it is digitally connected. Standardized data models and shared analytics allow performance to be monitored across sites, even when operations are run by different organizations. Lessons learned in one facility can be applied quickly elsewhere.
This aligns with broader trends toward regionalization and supply chain rebalancing. Without digital infrastructure, these models fragment. With it, they scale.
Automation without context creates risk
Automation is a clear priority in advanced therapy manufacturing, especially in areas like cell therapy where manual handling introduces variability. But automation on its own is not enough.
Without integrated data, context, and traceability, automation can obscure process understanding instead of improving it. Regulators require transparency. Operators need insight.
Digital integration ensures automation strengthens process understanding instead of masking it. It connects actions to outcomes and creates the visibility needed to interpret what is happening in real time. As therapies grow more complex, that connection becomes foundational.
The talent gap reinforces the need for digital
Even if processes were standardized, the industry would still face a major constraint, talent.
Severe shortages in specialized and digital skills continue to challenge biopharma organizations.
Digital tools can help address this. By embedding knowledge into systems, through data, workflows, and analytics, companies reduce reliance on individual expertise. Training becomes more consistent and decision-making more standardized.
This does not eliminate the need for talent, but it changes how that talent is deployed and enables greater consistency across increasingly complex operations.
The next competitive advantage is execution
Biopharma does not have an innovation problem. It has an execution problem.
Success is increasingly tied to ecosystem strength, how well companies connect manufacturing, supply chains, talent, and regulation into a cohesive system. Digital investment is the connective layer across all of it. It enables collaboration that works, scaling that holds, and regulatory alignment that accelerates progress. It also delivers the visibility required to manage risk in increasingly complex systems.
The shift that will define the winners
This transformation is less visible than a new therapy entering the clinic, but it is increasingly the hidden infrastructure that determines whether innovation can reach patients at scale.
The companies that succeed will not simply be those with the best science. They will be the ones that build the most connected, data-driven manufacturing ecosystems. Everything else follows from that, speed, quality, compliance, and ultimately patient access.
Digital investment is no longer a supporting strategy. It is the system the industry will run on.