As is custom at the end of each calendar year, The Pathologist team is excited to look ahead at what is to come in 2026. Many of our articles this year explored the future of pathology and laboratory medicine, but what do industry leaders expect to see in the next twelve months? From new applications for long-read sequencing, to digital twins in clinical studies, here’s what our panel predicts will hit the mainstream in 2026…
An R&D evolution approaches
In 2026, creative AI usage in research and development (R&D) will explode. Currently, 44 percent of corporate researchers would not use AI to write or draft papers, 47 percent would not use it to generate hypotheses, and 49 percent would not use it to design experiments. Meanwhile, only 27 percent say that AI tools are trustworthy. But with the development of new research-specific AI platforms with rigorous safeguards, 2026 will be the year when AI becomes more than just a time-saving tool for researchers – evolving to support hypothesis generation, experiment design and drafting with traceable sources.
Huntington’s milestone sets stage for wider genetic disease breakthroughs
2025’s success in slowing Huntington’s disease represents one of the first major advances for a group of genetic conditions known as repeat expansion disorders. In 2026, we can expect this achievement to drive increased research and investment into tackling other disorders caused by the abnormal repetition of DNA sequences beyond a safe threshold.
However, Huntington’s is among the more straightforward repeat expansion disorders to analyze. Others – such as those associated with ALS or frontotemporal dementia – carry longer, more complex repeats that current technologies struggle to resolve. Meaningful progress in 2026 and beyond will require broader adoption of long-read sequencing, the only approach capable of accurately analyzing these challenging repeats in a single test. With the right technology and partnerships, the coming years could bring steps toward treating conditions once considered untreatable.
More nations to invest in inclusive genomics
In 2026, more countries are expected to follow the example set by the Arab and South Korean pangenome initiatives by investing in their own population-specific genomic projects. These efforts marked an important shift in global precision medicine, revealing just how much genetic diversity is missing from the reference data that underpins modern healthcare. The Arab pangenome alone identified 8.94 million small variants and 235,000 structural variants unique to Arab individuals – illustrating the extent of genetic variation not captured in standard references.
Yet more than 90 percent of genome-wide association data still comes from people of European ancestry, who make up less than one-fifth of the world’s population. With long-read sequencing becoming faster and more affordable, inclusive pangenomes are poised to move from scientific aspiration to national priority.
AI-guided target ID will transform early biologics pipelines
In 2026, disease target identification will increasingly begin with in silico exploration before any wet-lab validation occurs. AI-guided platforms integrated with laboratory information management systems (LIMS) will merge genomic, proteomic, and transcriptomic datasets to uncover molecular patterns and disease mechanisms that were previously hidden within siloed data. These insights will allow scientists to define more precise starting points for biologics discovery, selecting targets with stronger biological rationale and clearer therapeutic pathways supported by disease associations and molecular evidence.
This shift will give research teams greater ability to connect target biology with candidate design, reducing the number of projects that stall during preclinical development. As AI becomes a consistent feature of early-stage research, target discovery will move from a manual search process to a continuous analytical workflow.
Biological modeling will embed in early discovery
In 2026, biological modeling will become a core component of early discovery rather than a specialized task.
Scientists will soon be able to access structure-prediction and binding-simulation tools directly within AI-native LIMS and electronic lab notebooks. These platforms will make it easier to evaluate complex therapeutic formats – such as multispecifics and fusion proteins – for affinity and specificity before any wet-lab work begins. By integrating modeling into routine workflows, teams can reduce trial and error, improve candidate selection, and shorten discovery timelines.
This shift represents a significant evolution in the scientific process, where computational prediction and experimental validation converge into a unified, iterative approach that accelerates the translation of molecular insights into therapeutic potential.
Digital twins will hit the mainstream
After years of experimentation, 2026 is expected to be the year digital twins move from pilot projects into routine use in clinical development. Throughout 2025, sponsors increasingly explored how digital twin technology could optimize protocol design, reduce costly amendments, and accelerate trial timelines. However, uncertainty around regulatory expectations for digital trial arms has slowed broader adoption.
That landscape is now shifting. Regulators, including the FDA, are expanding their AI frameworks and finalizing risk-based guidance and credibility assessments to ensure these tools are safe and effective for clinical development. This will open new opportunities to incorporate digital twins into both trial design and operational workflows.
To realize the full value of digital twins, sponsors will need to build regulatory confidence through rigorous validation, strong ethical data governance, and clear documentation. Continued collaboration among regulators, sponsors, and technology partners will be essential to ensure digital twins support what matters most: faster, more patient-centric, and more equitable clinical trials.
Unified AI will transform R&D
In 2026, AI silos in research will start to come down, and R&D organizations will embrace unified AI. There is currently a rapid move from AI point solutions in R&D to unified AI tools that bring together models and data to answer any question a researcher has. Although 33 percent of researchers have not yet used AI for work, the rise of trusted purpose-built tools will make it a more integral part of R&D workflows than ever.
The age of the agent is nigh
2026 will be the true ‘Year of the Agent’. Agentic AI was talked up in 2025, but didn’t have a huge impact on R&D processes like drug development. But now that is changing, as examples from Lilly (Kernel Lilly), the EPFL (ChemCrow), and others show that agents are making the difference in life sciences. With this enthusiasm, the sector is likely to beat pessimistic adoption estimates for agentic AI from other industries.
Digital technologies will enhance integrated diagnostics
Digital pathology maturity will accelerate in 2026, driven by a momentum of progress and by a critical urgency of demand and policy mandates facing healthcare systems. AI will come to the fore to enhance diagnostic accuracy, boost productivity, and augment capacity, but only if system-wide deployment can take place. Healthcare providers faced with finite capacity cannot trial algorithms ad infinitum – they need the right mechanisms to remove deployment burdens, ensure confidence, and focus evaluation on clinical efficacy for populations that will benefit. Adding AI to pathologists’ workflows won’t solve everything, however.
Maximum impact from pathology modernization now depends on strategic cross-diagnostic development. Where genuine integrated diagnostics is already being done at scale, providers, systems, and entire regions are achieving hugely. Cross-disciplinary insight at the point of reporting is enhancing clinical decisions. MDT meetings – one of healthcare’s most crucial and costly gatherings – are being transformed. And technology burdens facing providers are condensed. Maturity, but not in isolation, is the direction: one that is already delivering and that will hasten into 2026, setting the pace for realization of strategic priorities across enterprises and even nationally.
Teaser Credit: Background sourced from Adobe Stock
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