Vice President – Business Development
LGM Pharma

Mike Stenberg

Pharma's 2026 predictions revisited: AI tools have arrived, but organizational readiness, data governance, and regulatory gaps now limit real-world impact.

H1 2026 in Review: AI Adoption, Onshoring, and Data Gaps

Six months after industry experts laid out their predictions for 2026, many of those experts return to see what's tracking, what's shifted, and what it means for drug development and manufacturing professionals in H2.

The throughline across every prediction is the same: the technology moved faster than the organizations meant to use it. Manish Garg, serialization, regulatory compliance, and track and trace expert, who framed AI in drug discovery as a speed play back in December 2025, now sees the real story as strategic. As he puts it, "What's become clearer in the first half of 2026 is that the more meaningful shift is happening at the strategy level, not just the speed level."

That readiness gap shows up in regulatory enforcement, too. Mike Stenberg, LGM Pharma, points to FDA's first warning letter specifically citing improper AI use in manufacturing “with a major oversight related to specifications and procedures."

On the data side, Remco Munnik, Arcana Life Sciences, argues that Europe's database-driven submissions push is exposing a more fundamental problem than technology adoption, adding that "AI only works when the underlying data governance is solid."

Supply chain predictions largely held, with Campbell Bunce, Abzena, confirming that selective US onshoring and a biologics surge, including ADCs and antibody oligo conjugates, are playing out roughly as forecast. Meanwhile, Megha Sinha frames the year's real headline plainly: "the technology has now arrived, and the binding constraint turns out to be the organizational readiness, the employee sentiment, and the data."

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Is Organizational Readiness Pharma's Real AI Barrier in 2026?

Back in December 2025, several industry leaders staked out predictions for what 2026 would bring to drug development and manufacturing. Now, at the midpoint of the year, many of those experts return to see how their predictions held up. They find a pattern showing up across nearly every prediction: the tools arrived quickly, but the organizations meant to run them didn't catch up nearly as fast.

When referring to AI in drug discovery, Manish Garg, industry expert, originally called it a race for speed. Six months in, he's revised that read entirely, telling 

 "What's become clearer in the first half of 2026 is that the more meaningful shift is happening at the strategy level, not just the speed level."

Regulators are catching the same gap from the enforcement side. Mike Stenberg, LGM Pharma, flags a milestone warning letter as proof that the oversight is already here. "Earlier this year, FDA issued its first warning letter that specifically cites improper use of AI in manufacturing with a major oversight related to specifications and procedures," he says.

Underneath both trends sits a harder problem: data. Remco Munnik, Arcana Life Sciences, tracking Europe's shift toward database-driven submissions, put it as "AI only works when the underlying data governance is solid."

Elsewhere, the forecasts are holding steady; US onshoring is advancing selectively, biologics approvals are climbing, and Campbell Bunce, Abzena, says the industry's trajectory matches almost exactly what was predicted six months ago. Megha Sinha sums up where that leaves manufacturers, saying, "the technology has now arrived, and the binding constraint turns out to be the organizational readiness, the employee sentiment, and the data."

The full picture, including what each expert got right, what they missed, and where they're recalibrating for H2, is best heard in their own words.

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As the pharmaceutical industry crosses the midpoint of 2026, the landscape is defined by a complex interplay of rapid technological advancement, shifting geopolitical alliances, and evolving regulatory frameworks. Following a series of interviews conducted in July 2026 with seven pharmaceutical manufacturing and development experts, a clear picture emerges: while the industry has embraced the potential of next-generation modalities and AI, the "last mile" of execution—particularly regarding regulatory compliance, data consistency, and organizational readiness—remains a formidable hurdle (

Continued below the infographic - click to enlarge

Infographic: Pharma Manufacturing 2026 Midyear Reality Check

This report synthesizes these expert perspectives to provide a comprehensive look at the trends defining H1 2026 and the challenges awaiting the industry in the final months of the year.

We also wanted to hear from you. Findings from a poll of our LinkedIn followers reflect the core tensions identified by the seven experts in their midyear 2026 assessments, particularly regarding the gap between technological potential and operational reality (Table).

I. The Rise of Next-Generation Modalities: ADCs, AOCs, and the GLP-1 Surge

The first half of 2026 has seen a significant surge in the development of complex biologics and bioconjugates. 

, notes that his earlier predictions regarding the rise of these molecules have been largely borne out by clinical progress and regulatory approvals.

"We're seeing a lot of excitement, a lot more investment, in these next-generation molecules, and we're seeing that kind of borne out in the clinic and through some of the approval processes as well," Bunce observes.

Bunce specifically highlights the "surge in ADCs" (antibody-drug conjugates), noting that there are now approximately 23 approved ADCs worldwide. Recent milestones include the approval of AbbVie’s Decnupaz, an anti-CD123 conjugate for dendritic cell neoplasia, which utilizes a novel PPD dimer toxin payload. Beyond traditional ADCs, the industry is witnessing intense interest in antibody-oligoconjugates (AOCs), with companies like Avidity and Dyne progressing treatments for muscular dystrophies (Figure 1).

Bunce predicts this trend will only strengthen as biotechs face immense pressure to reach "value inflection points" by securing patient safety and efficacy data quickly. To meet this demand, CDMOs are shifting toward high-throughput "front-end design" processes and integrated manufacturing platforms that truncate timelines by combining protein production and conjugation activities.

Simultaneously, the "GLP-1 boom" continues to reshape manufacturing priorities and patient access models. 

Mike Stenberg, vice president of Business Development at LGM Pharma

, points to the rapid normalization of direct-to-consumer (DTC) and telehealth channels as a major development in how patients access these drugs.

"The biggest story for me is what's spilling over into how people access these drugs. Direct-to-consumer platforms have gone from a novelty to nearly universal in under two years,” Stenberg states. “Meanwhile, we continue to see new routes of dosage administration being explored."

While transdermal and subdermal delivery systems are still in early development, the approval of the first oral solid dose GLP-1s represents a milestone in administration routes. 

Saharsh Davuluri, CEO and managing director of Neuland Laboratories

, adds that while small molecules remain a core modality, the need to invest in new modalities like peptides and oligos is creating a challenge in capital allocation. He notes that Neuland is currently commissioning new peptide manufacturing facilities to meet increasing demand, particularly for large-scale production.

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Pharma manufacturing and development experts reassess their 2026 predictions for the industry and look ahead to the second half of the year.

Midyear 2026 Industry Report: Taking Stock of Pharma Manufacturing, AI, and Regulatory Trends

II. Geopolitics and Global Supply Chain Reshaping

The "China+1" strategy has evolved into a more aggressive push for multi-region redundancy and onshoring. Experts agree that geopolitical tensions and new tariffs have transformed supply chain resilience from a strategic choice into an operational necessity.

serialization, regulatory compliance, and track and trace expert, observes that the framing he used at the end of 2025 was already too conservative by early 2026. "I'm seeing companies building genuine multi-region redundancy, not just adding one backup supplier and calling it done,” Garg explains. “The supply chain resilience conversation is no longer primarily about geography. It's increasingly about data visibility."

Garg argues that geographic diversification alone is insufficient; companies must combine it with real-time traceability and serialization data infrastructure to respond to disruptions quickly. Davuluri echoes this sentiment, highlighting India’s sustained role as a critical manufacturing hub, particularly for APIs and peptides. However, he notes a surprising lack of new CDMO investment commitments on US soil compared with the "flurry of announcements last year."

A significant challenge identified by Davuluri is the increasing volume of out-licensing deals coming from Chinese innovators to “big pharma.” This creates a complex manufacturing dilemma for non-Chinese CDMOs, he notes. "When you have big pharma in-licensing some of these new drugs from Chinese innovators, who determines the manufacturing plans? Is it the Chinese company that is licensing out, or is it the big pharma company?" Davuluri asks.

Despite this complexity, Stenberg sees a clear trend toward onshoring drug product manufacturing closer to the end market. He notes that while APIs and raw materials often remain globally sourced, finished dose is where domestic investment makes the most sense for gaining operational, regulatory, and economic control over the "last mile."

III. The AI Evolution: From Productivity to Operational Participation

Artificial Intelligence has moved past the "hype" phase into practical application, though its deployment remains uneven due to validation and auditability requirements. 

Megha Sinha, founder and CEO of Kolter AI

, reports that "agentic systems" are now actively participating in plant floor operations.

"Inside the plant, agentic systems are already detecting out-of-spec results, pulling batch records, drafting root cause analyses, and cutting investigation time by 50% or more in validated GxP environments,” Sinha notes (Figure 2). “That is a shift from AI as a productivity layer to AI as an operational participant."

However, she argues that these systems stop short of solving the industry's costliest problem: translating manufacturing changes into regulatory consequences across dozens of markets. Current digital twins model shipments and capacity but cannot compute the specific filing requirements or grace periods triggered by a process change.

Henrik Johanning, senior vice president of quality & strategy at Epista Life Science

, notes that AI governance has matured rapidly. "The conversation has matured from 'What can AI do?' to 'Can the regulated process defend what AI helped create?' That is a significant shift," he observes.

Regulatory expectations now require AI tools to sit within the pharmaceutical quality system, necessitating defined intended use, risk assessments, and human oversight. Stenberg warns that the pace of AI adoption will continue to look slow because the industry proceeds carefully given the regulatory scrutiny. He points to the 

first FDA warning letter citing improper use of AI in pharma manufacturing

IV. Data Quality: The "New Moat" and the NDC-12 Identity Transformation

The experts we spoke with all agree that technology is no longer the primary bottleneck in pharma manufacturing; rather, it is the quality and governance of the underlying data. Garg emphasizes that data quality has become the central competitive differentiator for AI in manufacturing, stating, "The companies that are realizing real AI value in early 2026 are almost uniformly the ones that invested in their [enterprise resource planning (ERP)], serialization, and master data infrastructure in 2023 and 2024. Data quality isn't just a barrier; it's the new moat."

This focus on data is critical as the industry faces 

. Garg describes the FDA's 12-digit National Drug Code rule as an "enterprise identity transformation" that will affect virtually every system in the supply chain, from ERP and serialization to labeling and reimbursement platforms. "The parallel I keep using is DSCSA... History is about to repeat itself for organizations that make the same mistake with NDC-12 [by treating it as check-the-box compliance]," Garg warns.

Remco Munnik, founder of Arcana Life Sciences

, notes that while management has a "strong appetite to 'solve everything with AI,'" the reality is that AI only works when foundational data governance, such as identification of medicinal products, or IDMP, is solid. He identifies "digitalization with consistency" as the primary challenge for the remainder of the year, ensuring that data are interoperable across regulatory, quality, and manufacturing systems.

V. The Regulatory Landscape: Annex 1, Reform, and Convergence

In Europe, the implementation of EU GMP Annex 1 continues to drive facility investments. Johanning reports a strong focus on HVAC, water systems, and barrier technologies as companies move from theoretical risk management to real capital decisions. "The real maturity test is whether [quality risk management] changes decisions, not whether the risk assessment exists," he remarks (Figure 3).

While global regulatory convergence has helped align terminology around data integrity and quality systems, Johanning notes that "operational friction" persists due to regionalization and local release models. Munnik adds that the 

 is making significant progress toward a future in which lifecycle changes are handled via structured database updates rather than document-based submissions, with tangible success targeted for 2027 (Figure 4).

On the inspection front, Stenberg analyzed recent FDA data and found that while inspections increased in 2025/2026, the growth was almost entirely domestic. "Inspections did increase, but growth was almost entirely domestic, with foreign inspections in countries like China and India seeing far more modest growth despite the number of registered facilities there continuing to increase," Stenberg notes. Critically, the core GMP deficiencies found during these inspections, such as issues with written procedures and investigations of failures, remain unchanged from previous years, according to Stenberg.

VI. The Human Factor: Skills Gaps and Change Management

The transition to digital-first manufacturing has exposed a significant skills gap and the need for rigorous change management. Johanning notes that while companies are upskilling, quality, engineering, and IT still too often operate in separate, deep lanes. He argues the constraint is the ability to make "good GMP risk decisions" across these disciplines.

Munnik observes that economic pressures often cause companies to postpone the rotational programs and skill-building needed to bridge this gap (Figure 5). "When budgets tighten, rotations and skill-building are often the first to be postponed, even though they are exactly what is needed to close the gap," he says.

Sinha adds that the "orchestrator" roles often touted by companies are frequently "title-deep rather than skill-deep." She frames the shift as a fundamental change in the job itself, moving from 

 them. Davuluri emphasizes that a major part of this transition is ensuring that scientific talent feels secure and views AI as a tool to aid their effectiveness rather than a replacement.

VII. The Road to H2 2026: Challenges and Strategic Outlook

Looking ahead to the remainder of 2026, several critical challenges remain (Figure 6):

 Stenberg warns that early-stage biotech financing is on pace for its "worst year this decade," which could lead to a thin manufacturing pipeline in the future.

 Garg predicts that as the stabilization period ends, organizations should expect greater operational scrutiny from trading partners regarding data accuracy and interoperability.

 Johanning argues the biggest challenge is "turning risk-based intent into executable control strategies" without falling into the trap of over-control.

 Davuluri emphasizes the need for CDMOs to be more agile and responsive, utilizing flexible manufacturing lines to meet crunched development timelines.

 Sinha predicts that the "connective tissue" between functions must be built now to survive the pace that AI-native discovery is about to create.

: Munnik identifies the core challenge as "digitalization with consistency," warning that digitalization only works when "underlying data are stable, governed, and consistent across regulatory, quality, and manufacturing systems."

: Bunce highlights the pressure to offer "innovative ways of rapidly developing molecules" through "high-throughput sort of design" to help biotechs reach critical patient data as quickly as possible.

The first half of 2026 has demonstrated that the pharmaceutical industry is no longer limited by its technology, but by its organizational readiness and data integrity. As Sinha aptly summarizes, "Strategy moves at the speed of boardroom. Execution has moved at the speed of a spreadsheet.” The choice, she says, is whether to wire operations into one auditable backbone now or remain fragmented.

The winners in the second half of 2026 will be those who treat digitalization as a data consistency challenge rather than a technology project, ensuring that their manufacturing, regulatory, and quality systems are truly aligned. As the industry moves toward 2030, the shift from "point solutions" to integrated, data-driven operational backbones has become a requirement for survival in a rapidly evolving global market.

Geopolitical tension and tariffs are accelerating multi-region redundancy and onshoring, making real-time traceability and serialization central to resilience across global networks. Agentic AI is already reducing investigation cycle times in validated GxP operations, yet adoption is constrained by auditability and quality-system governance. Data governance now differentiates winners, especially as NDC-12 forces enterprise-wide identity remapping akin to DSCSA. Annex 1 capital upgrades, uneven FDA inspection growth, and persistent GMP findings add pressure. Skills gaps and cross-functional integration will define H2 2026 execution.

Six months in, pharma manufacturing and development experts reassess their 2026 outlooks and predict what comes next.

Six Months In: A 2026 Progress Check on Pharma Manufacturing, AI, and Regulatory Shifts

PharmTech recently caught up with Mike Stenberg, vice president of business development at LGM Pharma, to follow up on predictions he made back in December on what the pharma manufacturing industry would face this year. Check out all three parts of the 2025 interview with Stenberg:

Strategies for Building Pharmaceutical Supply Chain Resilience in a Shifting Market

How GLP-1s, Digital Tech, and 505(b)(2) Strategies Are Reshaping the CDMO Landscape

Navigating Financial and Opportunity Risks in Accelerated Drug Launches

In this three-part interview, Stenberg predicted that inspections in China and India—already at or above pre-COVID levels—would continue to climb in 2026. At the time, he described the 

 (CNPV) program as shifting the bottleneck from FDA approval to the production floor, and said companies have to onshore manufacturing to the US to take advantage of it. Stenberg also predicted that the GLP-1 boom would push real advances in transdermal microneedles, subdermal delivery, and oral solid doses with enhanced GI uptake. Additionally, he said AI adoption on the production floor and in supply-chain vetting would be real but slowed by a lack of structured datasets and the need to rewrite SOPs and retrain staff in a highly regulated industry.

Now that 2026 is half over, Stenberg offers his thoughts on what predictions he made came to fruition, which didn't, and why, as well as what's in store for the second half of the year.

PharmTech: Have inspections in China and India continued to climb as you predicted?

Stenberg: It's still too early to know where we stand as an industry with 2026 inspection data, but FDA released its 

FY2025 Report on the State of Pharmaceutical Quality

 in June, and it complicates the story a bit. Inspections did increase, but growth was almost entirely domestic, with foreign inspections in countries like China and India seeing far more modest growth despite the number of registered facilities there continuing to increase. Citations per inspection actually ticked down year-over-year, so there are more visits happening, just not necessarily more citations found per visit.

What hasn't budged is what they're finding when they do show up. FDA data show that the same handful of core issues keep topping the list: written procedures and documentation, investigations of discrepancies and failures, and equipment and quality control lapses.

Have you seen clients make the onshoring move and commit to “day one” commercial-scale planning in response to CNPV?

It's still too early to speak to the voucher program specifically, since it's still in pilot phase. What we are seeing more broadly is real client interest in onshoring drug product manufacturing, closer to the end market. For the majority of products supplying the US market, APIs and raw materials tend to stay globally sourced, but finished dose is where the domestic investment makes the most sense, offering greater operational, regulatory, and economic control in that last mile.

Which of the alternate GLP-1 delivery formats has progressed furthest?

The biggest story for me is what's spilling over into how people access these drugs. Direct-to-consumer platforms have gone from a novelty to nearly universal in under two years, and it's not just Lilly and Novo. Telehealth providers and other manufacturers are building similar access models around GLP-1 demand that is expanding access to other drugs as well. Meanwhile, we continue to see new routes of dosage administration being explored, but the development of these dosage forms is still in early phases. The approval of the first oral solid dose forms of GLP-1s is the first new route of administration, but I doubt it will be the last.

Has the AI adoption curve moved faster or slower than you expected?

first warning letter that specifically cites improper use of AI in manufacturing

 with a major oversight related to specifications and procedures. In most industries, you can plug in a tool and move quickly with minimal repercussions, but the pharmaceutical industry proceeds more carefully given the regulatory scrutiny and what's at stake for patients if it gets this wrong. The pace will keep looking slow next to tech or even other regulated industries, and that's the system working as intended.

What's the most unexpected development in pharma manufacturing and development so far in 2026?

With the volatility we've witnessed in this decade, it would be more of a surprise to not have an unexpected development in 2026. Tariffs continue to shift, we've seen more regulatory turnover, and geopolitics can sometimes seem like a month-to-month calculation. It is our job to remain well-positioned and proactive for the next disruption with second sourcing lined up, safety stocks negotiated, and onshore production where it matters. We've learned as an organization to remain focused on what's in our sphere of influence and expect the unexpected.

What do you see as the biggest challenge facing pharma manufacturing and development for the remainder of 2026?

The challenge I'd point to is what's not getting funded. Early-stage biotech financing is on pace for its worst year this decade, while the capital that is moving chases assets that are already de-risked. We see a growing share of US and European investment and licensing deals flowing toward China instead of new companies in the US. The pipeline we'll all be manufacturing in a few years depends on what gets seeded today, and right now a lot of that isn't happening.

Mid-2026 signals mixed validation of prior pharma-manufacturing forecasts. FDA quality reporting shows inspection growth driven largely by US sites, with modest increases abroad and fewer citations per inspection, yet persistent repeat deficiencies in documentation, investigations, and equipment/QC. Interest in US-based drug-product finishing is rising, even as APIs remain globally sourced, and CNPV implications remain uncertain. GLP-1 demand is accelerating direct-to-consumer/telehealth access models; novel delivery routes are early, with oral solids emerging first. AI adoption remains cautious after an FDA warning letter. Funding contraction in early biotech threatens future pipelines.

Checking in at 2026's midyear mark, LGM Pharma's Mike Stenberg revisits his 2025 predictions on inspections, onshoring, GLP-1 delivery, and AI adoption.