Industry Outlook 2026: Navigating AI, Sustainability, and Operational Resilience

To formulate a definitive roadmap for the pharmaceutical development and manufacturing landscape of 2026, the PharmTech content team connected with more than 30 industry experts, representing a comprehensive cross-section of the industry, including contract research organizations, contract development and manufacturing organizations (CDMOs), specialized manufacturers, genomic sequencing firms, consultants, and scientific AI innovators. These experts revealed that 2026 will be defined by a shift from incremental technological pilots to a profound system-level change.

Neil Smith, CPG President at Schneider Electric, captures the essence of this transition, noting that the coming year will “reward manufacturers who connect the dots” by modernizing data foundations and deploying agentic AI to “free trapped value from legacy manufacturing constraints.”

How is AI adoption changing in the industry?

The pharmaceutical industry has moved past the "inflated expectations" and "disillusionment" that characterized the previous two years. Beena Wood, chief product officer at Qinecsa Solutions, describes 2025 as a year during which the industry simultaneously balanced breakthrough technological announcements against the disillusionment of failed pilots and the rise of a "shadow AI economy." Regarding this state of uncertainty, Wood states, "Unless we open the box of specific AI implementation within an organization, it's in superposition of either transformative success or an epic failure." She notes that while many organizations faced "failed pilots" and a "trough of disillusionment," 2026 marks the "plateau of productivity" for those who have established the necessary prerequisites.

Mirit Eldor, managing director, Elsevier, declares 2026 as the true “year of the agent,’ explaining that while agentic AI was discussed heavily in 2025, it is only now making a measurable difference in R&D processes. This shift is supported by specific examples from leaders like Lilly (1) and the EPFL (2), which show that autonomous agents are finally “making the difference in life sciences.”

The impact of AI on drug discovery and development has become transformative. Dr. Eva-Maria Hempe, executive director, public sector EMEA, NVIDIA, explains that AI serves as a "flashlight" in the vast chemical space, helping researchers orient themselves and identify drug compounds in months rather than years.

Veronica DeFelice, director of biologic products, Sapio Sciences, adds that in 2026, identifying disease targets relies on in silico exploration before any wet-lab validation begins, transforming target discovery from a manual search into a "continuous analytical workflow."

Manish Garg, principal engineer and associate director, Hikma Pharmaceuticals, emphasizes that AI "dramatically cuts costs and timelines" by efficiently analyzing vast data sets that would be impossible to process via traditional trial-and-error methods.

Furthermore, Neil Ward, vice-president and general manager of EMEA, Pacific Biosciences, notes that genomic data are set to grow immensely, making AI the only viable way to interpret the "tens of thousands of lines of code" involved in analyzing a single person’s genome.

In the manufacturing and operational sphere, AI has moved beyond discovery into the "embedded reasoning layer" of production, according to Megha Sinha, CEO, Kamet Consulting Group. “In discovery, AI will increasingly sit on top of curated scientific and clinical knowledge, prioritizing what to explore—targets, molecules, indications—rather than “replacing” the science,” she adds. “In manufacturing, the real step-change will come from agentic systems that combine digital twins, process data, and regulatory rules to recommend parameter changes, highlight risks, and propose implementation plans instead of just flagging anomalies.”

Smith highlights the emergence of "agentic systems" that proactively recommend actions, such as golden clean-in-place cycles to reduce waste, chemical, and water use. Laine Mello, director of marketing, Ecolab, notes that predictive maintenance tools are now "catching equipment issues before they cause batch failures."

However, Andrew Mitchell, senior director Business Development, BioVectra, points out a significant barrier: the high cost of licenses. "You clearly can't use a public, open data AI model," Mitchell argues, noting that companies must invest in proprietary AI agents that are specific to their organization. Wood echoes this caution, warning that "no amount of AI sophistication will help" if the underlying data foundations are fragmented, non-interoperable, or not validated for AI use cases. “The good organizations are the ones who are starting to do those boring foundations so they can scale very quickly afterwards,” she adds.

What are the impacts of geopolitical trends?

Geopolitical uncertainty, trade tensions, and rising tariffs have forced a radical reimagining of supply chain architecture. Matt Paterson, chief strategy officer, Quotient Sciences, observes that biotech and pharma clients are "optimizing and diversifying their geographic footprint" to mitigate the effects of political instability. Many organizations are adopting a multi-region strategy, qualifying facilities in both the United States and the United Kingdom to ensure continuity of supply for life-altering medicines.

Henrik Johanning, senior vice president, Epista Life Science, points out that "network reconfiguration is accelerating" as manufacturers respond to single-source dependencies and "global regulatory convergence."

Raj Puri, chief commercial officer, Argonaut Manufacturing, describes the "chilling effect" of unpredictable tariffs, sharing an account of being "hit with a seven-figure tariff on one of the key pieces of equipment" during a three-year investment plan for a new manufacturing site. Despite this "unwelcome surprise," Puri notes that tariffs have "created additional interest in US-based CDMOs" as a potential strategy to keep down cost of goods sold.

Campbell Bunce, PhD, chief scientific officer, Abzena, confirms this trend toward "on-shoring," noting a "genuine shift" and a "big focus in the US" for manufacturing drug substances. “We’re seeing a lot of our customers make deliberate moves to ensure that security of supply is within the US.”

In India, the strategy is shifting toward local sourcing and significant inventory buildup to de-risk operations, according to Saharsh Davuluri, vice chairman and managing director, Neuland Laboratories. He reports an "increasing trend in which our customers...would like to see several months, sometimes six months, of API stock being held in their warehouses" to prevent disruptions from geopolitical issues.

Sinha predicts, that by 2026, leading organizations will treat supply chains as "living decision engines: platforms that connect products, SKUs, licenses, sites, tariff exposure, and regulatory requirements in one knowledge layer and then let you simulate, ‘If this lane fails or this tariff goes live, which tech transfers, marketing authorization holder changes, label updates, and tenders are affected, and what’s the fastest viable plan B?’”

What advances are expected in next-gen modalities?

The therapeutic pipeline of 2026 is dominated by high-value, complex molecules. Mitchell identifies antibody-drug conjugates, radioligand therapies, and RNA therapies as the "boom" sectors of the moment.

Bunce highlights "antibody oligo conjugates" as a particularly exciting area, specifically for treating muscular dystrophies. He cites Novartis's acquisition of Avidity for $12 million as a clear indicator of the "exciting nature" of utilizing these approaches for difficult-to-treat indications (3).

The growth of high-potency APIs is also reshaping facility requirements, says Lidia Garcia Martin, MSAT & new productions head, Recipharm. She explains that these compounds offer notable clinical promise but demand "sophisticated handling, containment, and process control."

Ashu Tandon, chief commercial officer, Aragen, confirms that as FDA approvals for high-potent small molecules rise, customers are aggressively looking to "secure high potent containment capacities." This shift places a premium on robotics and closed-system technologies that "reduce manual handling and mitigate exposure risks."

Ward adds that breakthroughs in treating repeat expansion disorders, such as Huntington’s disease, will spark a surge of investment in 2026, requiring the broader adoption of long-read sequencing to analyze complex DNA repeats.

DeFelice notes that biologics discovery will focus on "multi-specific antibodies and engineered proteins that address complex biological targets through novel binding mechanisms. These formats are designed to interact with multiple targets or modulate disease pathways in ways that traditional monoclonal antibodies cannot.”

How are sustainability efforts moving beyond compliance?

Sustainability has transitioned from a simple reporting requirement to a foundational operating principle in 2026. Carolina Egea Millet, general manager, Agarose Bead Technologies, notes that manufacturers are redesigning production methods to "reduce solvent consumption and minimize waste," particularly in downstream purification, which accounts for a substantial proportion of total water and resource usage.

Mello adds that companies are discovering that "reducing water and energy consumption isn't just good for the planet; it's improving their bottom line and making operations more resilient."

Smith argues that it is time to retire the use overall equipment effectiveness (OEE)—which can be "misleading" as it only measures actual vs. planned utilization (eg, a “100% OEE for a production line that only runs once a week does not mean you are running a capital-efficient plant”)—in favor of a capital and carbon efficiency metric that bridges financial and sustainability goals.

Garcia Martin suggests that “high-potency manufacturers are prioritizing energy-efficient HVAC systems as well as facility layouts that minimize waste and unnecessary airflow demands. Process selection is also evolving, with solvent-free or solvent-reduced techniques gaining traction, supported by closed systems and isolators that limit emissions and improve material efficiency.”

What workforce and digital skills gap developments are occurring?

The rapid digitalization of the industry has created a "widening skills gap" between traditional good manufacturing practice (GMP) roles and newer, data-driven positions, according to Johanning. He observes that digitalization is separating "traditional GMP roles" from "automation- and data-driven roles."

Remco Munnik, owner and founder, ARCANA Life Sciences Consulting, adds that in the past, a pharma professional was primarily a scientist who became an administrator, but now they must be a "data analyst or data scientist" capable of extracting insights from machine learning and statistics.

Sinha argues that the goal is not to turn every scientist into a software engineer but to create "T-shaped orchestrators" who understand the cross-functional nature of the business and can work with "AI-generated impact assessments." She suggests training teams to "supervise agents, not configure tools," teaching experts how to interrogate system-generated plans.

To attract and retain this talent, Puri emphasizes that "the only long-term, sustainable advantage we have as a CDMO is our staff," as facilities and equipment can be replicated, but human expertise cannot.

What does the regulatory frontier look like?

Smith, Johanning, and Egea agree that regulatory expectations are intensifying around data integrity and traceability. Johanning points to the maturity of European Union GMP Annex 1 implementation (5), noting that many sterile facilities are finding that "procedural compliance is insufficient" and requires tangible upgrades to utilities, particularly water and HVAC systems. He also highlights Annex 11 and Annex 22, which drive expectations for the lifecycle management of computerized systems and ensure digital tools are governed under the pharmaceutical quality system (6,7).

Frits Stulp, Partner Life Sciences, Implement Consulting Group, introduces the concept of "trusted regulatory spaces," secure cloud environments where regulators and industry professionals can work in the same document to "accelerate the regulatory process." He calls this a "partnership for patients" and believes it will change the game by allowing faster discussions between applicants and regulators.

Munnik discusses the work of the Regulatory Optimisation Group (8), which has been working with European regulators and seeks to automate lifecycle management changes, such as name or address updates, by submitting them directly into a database so everyone is informed at the same time and to improve "speed to market, but also compliance."

How are digital twins and prevention impacting clinical trials?

Clinical trials are also undergoing a digital metamorphosis, according to Paterson, Dr. Gen Li, founder and president, Phesi, and Meri Beckwith, Co-CEO, Lindus Health. Li predicts that 2026 will be the year that digital twins "finally hit the mainstream" in clinical development, as regulators like FDA finalize risk-based guidance for digital trial arms. This would allow sponsors to optimize protocols, reduce costly amendments, and accelerate timelines. Li also predicts that "prevention" will emerge as the new blockbuster, as researchers investigate GLP-1 therapies for more than 100 diseases beyond diabetes and obesity, including cardiovascular disease and osteoarthritis.

Beckwith observes that pharma is finally treating "clinical operations as a strategic advantage," using AI for precision patient matching and site selection. He emphasizes that there will be increasing pressure for real-world evidence (RWE) that reflects actual clinical use, driving innovation in continuous data collection via connected devices.

Garg adds that the advancement of generative AI for de novo drug design and the use of RWE in regulatory submissions will be primary drivers of innovation in 2026.

How should facilities and infrastructure be future-proofed?

Looking ahead, Smith and Garg agree that manufacturers are being urged to upgrade aging infrastructure to meet the demands of Industry 4.0. Smith points out that the average operational technology asset has been in service for 11 years, and many lack the "embedded security and AI integration" required for autonomous operations. Consequently, 2026 will see an accelerated hardware refresh cycle as companies move toward modular, interoperable industrial internet of things (IoT) systems.

Garg recommends that manufacturers plan for significant investment in upgrading existing facilities into "smart factories" that incorporate IoT sensors, robotics, and cloud computing. Garcia Martin suggests that facilities must ensure adaptability, with flexible process suites that can transition "seamlessly from development to commercial production."

Davuluri notes that the API sector has traditionally been "primitive" in its adoption of automation and must catch up by implementing distributed control systems, flow chemistry, and electronic batch records to stay on par with modern biologics manufacturing.

What’s occurring in pharmacovigilance and patient safety?

The future of pharmacovigilance is shifting from reactive reporting to "intelligent surveillance," notes Wood, who envisions a system that can detect unusual reactions across multiple languages in hours rather than months, cross-referencing global cases and identifying genetic marker correlations using real-world data. She notes that while this is "theoretically possible," the industry must first overcome the "uncomfortable truth" of fragmented data foundations. Wood advocates for "translational safety," which involves connecting the dots earlier in development rather than waiting for post-market surveillance. This proactive shift requires fundamentally rethinking how decisions are made under uncertainty, ensuring that scientists do not get "stuck because the decisions are unclear" due to disconnected data systems.

How does synthesis represent a turning point for industrial intelligence?

As the industry maneuvers through 2026, the convergence of AI automation, supply chain regionalization, and sustainable efficiency is creating a new operational reality, according to Garg, Smith, and Hempe. The golden clean-in-place cycles, T-shaped orchestrators, and trusted regulatory spaces are not merely concepts but the necessary components of a modern industrial strategy. Smith concludes that 2026 marks a "turning point for industrial players who move beyond incremental fixes and embrace system-level change."

The experts agree that the objective of 2026 is to compress time-to-market while protecting margins and patient safety. Whether it is through the deployment of digital twins to optimize clinical protocols, the use of biocatalytic manufacturing to scale siRNA production, or the strategic application of 505(b)(2) pathways to repurpose existing APIs, the focus remains on agility and evidence-based decision making. The insights from these industry leaders suggest that while the challenges of tariffs, skills gaps, and regulatory complexity are significant, the technological tools and collaborative frameworks available in 2026 offer an unprecedented opportunity to redefine how life-saving medicines are discovered, manufactured, and delivered to patients worldwide.

References

1. Lilly. Lilly Partners with NVIDIA to Build the Industry's Most Powerful AI Supercomputer, Supercharging Medicine Discovery and Delivery for Patients. Press release. Oct. 28, 2025. investor.lilly.com/news-releases/news-release-details/lilly-partners-nvidia-build-industrys-most-powerful-ai.
2. EPFL. Artificial Intelligence & Machine Learning. epfl.ch/schools/ic/research/artificial-intelligence-machine-learning (accessed Jan. 9, 2026).
3. Novartis. Novartis Agrees to Acquire Avidity Biosciences, an Innovator in RNA Therapeutics, Strengthening its Late-stage Neuroscience Pipeline. Press Release. Oct. 26, 2025. novartis.com/news/media-releases/novartis-agrees-acquire-avidity-biosciences-innovator-rna-therapeutics-strengthening-its-late-stage-neuroscience-pipeline.
4. Ecovadis. Sustainability Certification: A Guide to Green Standards and Accreditation. ecovadis.com/glossary/sustainability-certification (accessed Jan. 9, 2026).
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6. European Commission. EU GMP Annex 11: Computerised Systems. health.ec.europa.eu/system/files/2016-11/annex11_01-2011_en_0.pdf. (accessed Jan. 12, 2026).
7. European Commission. EU GMP Annex 22: Artificial Intelligence. health.ec.europa.eu/document/download/5f38a92d-bb8e-4264-8898-ea076e926db6_en?filename=mp_vol4_chap4_annex22_consultation_guideline_en.pdf. (accessed Jan. 12, 2026).
8. Heads of Medicines Agencies. Regulatory Optimisation Group. hma.eu/about-hma/working-groups/regulatory-optimisation-group-rog.html. (accessed Jan. 12, 2026).