Report - Digital Transformation in Biopharma: The Gap Between Hype and Implementation

As new bio/pharmaceutical manufacturing and development approaches move toward commercialization, traditional industry modalities are under intense pressure (1-7). At the same time, automation, advanced analytics, digital twins, artificial intelligence, and other technologies are evolving quickly and promising to transform how medicines are developed, produced, and delivered.

However, adoption of these technologies has been seemingly sporadic, with recent headlines indicating that some organizations testing cutting-edge digital tools for operations while others continue to navigate legacy systems, limited resources, and/or regulatory uncertainty (1, 8-19). To better understand where the industry truly stands today, what barriers professionals are facing, and what opportunities are most within reach, we conducted a survey of industry professionals that focused on digital transformation and technology adoption.

We then analyzed our findings alongside recent news to:

1. See how they compared

2. Create a holistic view of the industry’s digital evolution

We uncovered a fascinating dynamic: while headlines celebrate cutting-edge scientific breakthroughs like generative artificial intelligence (AI) outperforming nature in protein design (20) and the clinical progress of complex gene therapies (21), the survey data show that the foundational manufacturing and quality systems supporting these innovations are modernizing at a much slower pace. The news highlights what the industry is innovating on, while the survey results explain why the industry is struggling to modernize, pointing to internal barriers around legacy systems, costs, and workforce skills.

How is digital adoption progressing and what role do workforce skills play?

The biopharmaceutical sector is in a transitional phase of digital adoption. The ambitious, complex therapies featured in the news contrast sharply with the survey's finding that most organizations are still grappling with the basics of digital transformation.

As FDA is releasing draft guidance on regenerative medicine advanced therapy for sponsors of cell therapies, gene therapy, and tissue products (22) and on innovative trial design for rare-disease cell and gene therapies (23); advances in technologies are offering effective data handling for manufacturing (24); organizations are launching agentic AI collaboratives (25); and industry conference presenters discuss levering AI for rigorous good practices compliance, our survey data reveal that more than one-third of the industry is still in the "early exploration/pilot projects" or "not yet started" phase of digital transformation. This juxtaposition suggests a significant gap between the digital infrastructure needed for next-generation biologics and the current reality for many manufacturers.

The workforce skills gap presents another challenge in achieving the aforementioned digital integration goals. While tariff and trade policy initiatives are geared toward bringing more and more drug manufacturing to US soil (26,27), nearly half of survey respondents said their organization’s workforce was unprepared for digital transformation, be that skills, training, and/or mindset, with only 5.0% saying they were “highly prepared.” This deficit is a critical, yet often unstated, obstacle to successfully implementing the bioprocessing automation and data-driven quality systems that are becoming essential for modern drug production.

"By the way, that’s going to be a big deal,” says PharmTech editorial advisory board member Eric Langer, president & managing partner, BioPlan Associates, Inc. “We are surveying international workers around attitudes about jobs in the US—70% of the global bioprocess industry is outside of the US. Finding qualified [good manufacturing practice (GMP), staff to work in the US is going to be harder.”

Langer adds that the challenge to US biologics capacity will come if/when reshoring occurs by CDMOs and bio-facilities to the US. “Those that are incentivized to avoid massive tariffs and make bricks-and-mortar commitments may not be able to hire the right staff without poaching their neighbors’ GMP operators,” he notes. “Currently, according to our 22 Annual Report, 35% of facilities cannot hire enough process development or operators. If US sites are inhibited from global hiring due to H-1B visas, immigration fears, etc., then the number of facilities unable to staff-up is very likely to rise. This will create its own capacity and investment problems.”

What’s motivating the digital transformation in biopharma?

The primary motivation for digital transformation is overwhelmingly internal and economic. While headlines cover external factors like President Trump's directive on drug pricing (28) or the 100% tariff on imported drugs (26), the survey findings show that day-to-day digital strategy is driven by the need to improve the bottom line.

Indeed, nearly two-thirds of survey respondents identify "efficiency and cost savings" as the single biggest driver of digital adoption. This internal focus is amplified by broader market conditions discussed in the news, such as the "pressures of capital markets" and the need for Big Pharma to "do more with less" (29). The threat of tariffs reshaping supply chains further reinforces this cost-saving imperative by pressuring companies to build more efficient, localized manufacturing sites (26).

This internal focus is reinforced by a near-total absence of external drivers according to the survey results. Regulatory expectations (5%) and competitive differentiation (0%) are not seen as primary motivators. This is a fascinating contrast to the volume of recent FDA guidance and regulatory strategy (16,22,23,30), indicating that while companies must comply with regulations, the proactive investment in digital tools is justified internally by cost savings, not by a desire to get ahead of regulators.

Can a pragmatic focus today morph into an ambitious tomorrow?

Current digital adoption focuses on practical, foundational areas, while future investment priorities signal a major strategic shift toward the advanced analytics needed to power the next generation of therapies.

Today's digital efforts are centered on the workforce and core GMP functions. The top areas for adoption, as identified by survey respondents, are workforce training (52.6%) and quality assurance/control (47.3%). This reflects a foundational need to get the basics right, aligning with the industry's focus on building "anti-fragile manufacturing compliance" through strategic CAPA, or corrective and preventive actions (31).

The leap to AI is poised to play a key role in future investments in the industry, with the near future vision heavily weighted toward data intelligence. Nearly 80% of respondents believe advanced analytics, AI, and machine learning is the digital technology investment area bound to have the greatest impact in the next 3-5 years, making it the top investment priority. This directly aligns with news from the PDA Regulatory Conference 2025 highlighting how the industry is leveraging AI for GMP compliance (32) and exploring AI's impact on drug manufacturing (33).

Does AI implementation in biopharma meet its potential?

There appears to be an AI paradox in biopharma, with high hopes being met with low implementation. Despite powerful consensus on the importance of AI, its practical implementation is still in its infancy, creating a paradox between the strategic vision celebrated in headlines and the current operational reality.

Recent news that generative AI can outperform nature in protein design (20) and newly release FDA guidance on guidance utilizing AI for postmarket CGT surveillance (30) are matched by the survey finding that nearly four out of five respondents believe AI will be “very important” or “critical/transformational”.

Yet, less than one-third said their organization has started implementing AI, with 68% still in pilot or "actively exploring" phases. These results highlight the gap between recognizing AI's potential and overcoming the internal barriers to actually deploying it at scale.

What are the biggest barriers to digital transformation in biopharma?

The survey findings clearly indicate that the most significant barriers to digital transformation are internal, providing crucial "behind the headlines" context for the industry's innovation stories.

Integration challenges with legacy systems (37%), high implementation costs (32%), and a lack of internal expertise (26%) are the primary roadblocks. These are the practical hurdles companies must overcome to enable the kind of "end-to-end biologic innovation" (34) and continuous manufacturing that new facilities are designed to support (35).

Alongside these practical hurdles, there is notable apprehension about data management. More than one-quarter of survey respondents are "somewhat" or "very concerned" about ensuring data integrity. This concern aligns with recent headlines on the use of real-world evidence in drug development and ensuring supply chain security, both of which depend entirely on trustworthy digital systems and robust data governance (32,33,36).

What’s next?

Looking ahead, the biopharma sector is poised for a necessary digital acceleration, driven by the strategic priority of investing in advanced analytics and AI—as indicated by our survey results—to support high-impact innovations, such as the use of generative AI in protein design and the FDA’s utilization of AI for postmarket CGT surveillance. This technological commitment, alongside the growing implementation of bioprocessing automation, will be crucial for overcoming the limitations of moderate adoption and building the efficient, localized manufacturing sites required to meet market pressures and achieve anti-fragile GMP compliance. Successfully navigating the integration of these data-centric tools, despite existing legacy system challenges and an apparent skills gap, will determine the industry’s future capacity to deliver on the promises of personalized and complex gene therapies.

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