2026 predictions: what are the operational priorities for late-stage pharma R&D?

It may look as though pharma companies are spinning plates, but when it comes to strategic investments in supporting services and solutions, three common themes emerge for the year ahead, according to those helping to transform operational delivery.

Post-experimental AI proliferation: opportunities to transform drug safety

Lucinda Smith
Chief Safety Product Officer, ArisGlobal

With considerable AI piloting now completed, 2026 is set to see a shift from proofs of concept (PoCs) to enterprise-scale implementation. In drug safety, one opportunity for AI to add next-level value is in enabling predictive pharmacovigilance. Lucinda Smith, chief safety product officer at ArisGlobal, believes this will be a significant theme in 2026, along with the use of AI to support early signal detection through use of advanced analytics, AI and RDE (insights/evidence generated from real-world data using analytics or AI/machine learning), and integrating data from electronic health records, wearables etc.

“This will be a big step forward for PV and for patients – but will also take a significant effort to deliver,” she says. Among the challenges that departments face are sourcing the right technology skills, building AI literacy and honing governance around AI. “Typically, PV departments are very experienced in governance and oversight, but in the era of AI the way they achieve that has to evolve; increasingly team members will need a balance of both PV and AI skills.”

Jean Redmond
Chief Operating Officer, Biologit

For Jean Redmond, chief operating officer at Biologit, which specialises in AI-powered literature monitoring platform for drug safety surveillance, regulators have a significant role to play in guiding pharma companies in their adaptation to using AI. “2025 saw interesting draft guidance being released and initial AI programmes being adopted by regulators,” she notes. “This year we can expect to see regulatory authorities drive further frameworks, guidance and expectations for the compliant use of AI, giving organisations the confidence to move from pilot projects into production.”

Solving the intra-function integration problem

The proliferation of function-specific solutions including RIM, PLM, QMS and workflow tools has too often resulted in integration challenges. Addressing these should be a priority in the coming year, as orchestration options advance.

Megha Sinha
Managing partner and CEO, Kamet Consulting Group

Says Megha Sinha, managing partner and CEO at Kamet Consulting Group, which advises on advanced product lifecycle management spanning multiple functions, “Life sciences companies now have plenty of point solutions, but the real struggle is how work actually flows between them. The differentiator in 2026 will be the ability to see the end-to-end work “graph” (products, SKUs, markets, tasks, owners); apply consistent, codified business rules; and coordinate execution across regulatory, manufacturing, quality, supply and commercial.

“Instead of treating a re-brand, site transfer or marketing authorisation holder change as dozens of disconnected projects, for instance, organizations will move towards a single orchestration layer that sequences tasks, manages dependencies and continuously re-plans as constraints change. AI will be critical, but as an engine within a work-orchestration fabric,” she clarifies.

Biologit’s Redmond agrees that bridging departmental divides, and enabling stronger cross-functional collaboration, is pivotal now. “Too often, challenges in areas like safety, operations or technology are approached in silos, slowing progress and limiting impact,” she says. “If teams across PV, regulatory, medical, data and engineering worked together from the start – sharing goals, data and ownership – problems would be solved sooner.”

John Cogan
Chief Operating Officer, Qinecsa Solutions

With fewer boundaries, workload management could be reviewed on a grander scale, according to John Cogan, chief operating officer at Qinecsa Solutions, which specialises in pharmacovigilance optimisation. He advocates that life sciences organisations, in a PV context in particular, should “stand back from their global end-to-end operating models, and do a full reanalysis on how their operations need to look beyond 2030,” he says. But this will mean breaking down entrenched structural silos, he acknowledges, which could prove more difficult than any technical integration.

Next-level data considerations

The way companies handle data will have a significant bearing on inter-departmental fluidity and process agility. It is here that regulatory operations greatest opportunity, and challenge, reemerges.

Encouragingly, there are signs that structured data may now properly evolve from a compliance requirement to strategic infrastructure, driven by EMA’s Network Data Strategy; agreed specifications under IDMP and SPOR; and the reality that AI/automation capabilities depend on high-quality, interoperable data foundations.

Remco Munnik
Founder and consultant, Arcana Life Science Consulting

Says Remco Munnik, founder and consultant at Arcana Life Science Consulting, which specialises in regulatory data strategy and IDMP implementation, “The strategic priority in regulatory operations in 2026 will be the full-scale implementation of structured data across regulatory and interconnected functions.
This shift is being driven by the publication of the EU Network Data Strategy and the tangible progress of EMA’s IDMP and SPOR initiatives, now embedded in core regulatory processes such as PLM eAF for product lifecycle management, and ESMP for shortage reporting.”

Equally important, and often underestimated, he says, is the EU Network’s evolving direction. “PMS is set to become the central source of product data across both the entire product lifecycle and the full regulatory network,” he notes. In practice, this means the scope will expand beyond authorised medicinal products to include investigational products under evaluation and for all national competent agencies (NCAs). “This shift demands proactive planning from both industry and regulators,” Munnik says, adding that this is ultimately a ‘people and process’ challenge, since the technical standards are now there to be harnessed.

Sharpening the patient-first perspective

Michelle Bridenbaker
Chief Operating Officer, Unbiased Science

From all of this, it should be patients who stand to benefit most. Says Michelle Bridenbaker, chief operating officer at Unbiased Science, a medical affairs and scientific communications consultancy, “In 2026, we need to further transform the way we engage with and reach our time-poor target audiences (particularly healthcare providers, but patients as well).

“Whether it is for disease-state awareness, or to ensure that patients use medications correctly, we are still struggling in the attention economy in Medical Affairs. Although we have made significant progress over the last five years, there is still so much to be done within the sea of mis- and disinformation, the explosion of social media – and now competition with large language models [LLMs] like ChatGPT and CoPilot – which almost half of clinicians now say they are using (1).

“We need to find ways to operate compliantly in the right social media channels, update our codes of practice, and other legal/compliance barriers to define a robust framework for industry to operate in this space,” she urges. “We also need to find a way to partner with or leverage LLMs to ensure our own content is more visible,” she adds – “as presently much is behind walls which the algorithms, and sometimes HCPs, cannot access. As an industry we must overcome these logistical and legal challenges to ensure that robust, unbiased, and complaint content is being served to audiences, wherever they are.”

References and notes

1. Elsevier‘s Clinician of the Future 2025 survey: Clinicians‘ AI usage and optimism grows despite concerns around trust and reliability, July 2025: https://www.prnewswire.com/news-releases/elseviers-clinician-of-the-future-2025-survey-clinicians-ai-usage-and-optimism-grows-despite-concerns-around-trust-and-reliability-302504230.html