Biopharma manufacturing at inflection point amid rise of complex biologics, AI: report

Biopharmaceutical manufacturing has reached an inflection point as the production of increasingly complex biologics is being outpaced by AI-accelerated drug discovery and clinical development, ultimately contributing to widespread drug-launch delays, according to a new report from professional services firm Accenture.

Based on an analysis of FDA Complete Response Letters (CRLs), the report found that 64% of drug-launch delays in 2024 were tied to chemistry, manufacturing and controls (CMC) issues, with many of those delays stemming from the production of complex biologics. It also noted that biologics now represents 55% of the clinical pipeline, placing mounting pressure on manufacturers to modernize operations and scale production more efficiently.

At the same time, AI-driven acceleration in drug discovery and clinical trials is compressing development timelines and increasing pressure on manufacturing and technical operations teams. Combined with broader geopolitical volatility, supply chain disruption, and rising competition, the industry is facing growing urgency to build more resilient and adaptable manufacturing networks.

Accenture’s report makes the case that resilience increasingly depends on harnessing data and intelligent technologies to create smarter, faster, and more scalable manufacturing systems. Yet, while 28% of surveyed top biopharma companies reported access to advanced intelligent tools supporting predictive or partially autonomous operations, most organizations remain in the early stages of scaling these capabilities, with digital innovation still confined to isolated initiatives.

Scaling intelligent manufacturing

The report emphasizes the importance of advanced analytics, AI, digital twins, intelligent agents, and robotics in helping manufacturers improve efficiency, reduce variability, and strengthen operational resilience.

However, adoption remains uneven across the industry, with a significant portion of top biopharma companies still navigating their digital transformation journeys.

According to the survey, 35% of executives said their organizations function as “connected organizations,” which is defined as having achieved moderate levels of automation, integration, and system standardization across multiple functions, enabling more seamless data flows and improved decision-making.

Still, even among those, only 19% of respondents reported operating in a “predictive” environment, where integrated systems combine historical and real-time data with AI models to proactively optimize processes and support operational decision-making. Less than 10% reported operating in “adaptive” environments featuring partially autonomous, self-optimizing processes powered by AI, machine learning, and robotics.

Despite these limitations, companies further along in their digital journeys are already reporting measurable gains. More than half of connected organizations (54%) cited improvements in day-to-day supply efficiency, resulting in faster time-to-market and leaner cost structures. Meanwhile, 45% reported significant advancements in technology transfer through streamlined data and knowledge sharing across R&D, manufacturing, and quality teams.

Accenture also highlighted broader gains tied to intelligent technologies, including expedited recipe development, faster regulatory filings, improved material traceability, and more adaptive manufacturing environments capable of reducing waste and improving yield.

From pilots to scale

Despite these successes, the report argues that most biopharma companies have yet to mature their digital capabilities to the point where they can support standardized global operations, rapid scaling, or fully autonomous manufacturing environments.

Researchers identified three persistent barriers slowing progress: digital pilots confined to low-risk, low-impact areas; core data infrastructure not yet capable of supporting scale; and initiatives remaining siloed across functions such as product development, manufacturing science and technology (MS&T), quality, regulatory, and information technology.

This results in fragmented digital programs that struggle to scale, deliver limited return on investment, and increasingly create what the report describes as “digital dead ends.” According to Accenture, these disconnects are widening the gap between digital ambition and operational execution, threatening to stall momentum and potentially force costly rework if left unresolved.

Building the digital thread

Still, these hurdles create an opportunity for biopharma companies to rethink the role of intelligent technologies and unlock improvements across the entire product development lifecycle, the report contends.

To get there, Accenture emphasized the importance of an integrated end-to-end strategy built around intelligent technologies and a connected digital thread spanning R&D, process development, and manufacturing.

The report points to AI-enabled approaches already showing measurable impact, including reducing time-to-market by up to 40%, improving process development throughput by 30%, cutting batch lead times in half, as well as significantly increasing manufacturing yields while lowering costs and future capacity demands.

Antibody-drug conjugates (ADCs) were a modality highlighted in the report where AI and machine learning tools are being used to identify optimal targets, optimize antibody sequences, and predict linker-payload combinations earlier in development. These capabilities could help shorten timelines from candidate selection to commercial approval, according to the report.

Ultimately realizing the full benefits of a lab-to-line strategy will require companies to focus on three core priorities, argues Accenture: tailoring solutions to specific processes and assessing tools through the lens of measurable business outcomes, building a solid and secure data-and-systems foundation, and redesigning roles and processes to exploit new digital capabilities.