Here are the full trends and predictions, including more on AI, data management and collection, precision diagnostics, new testing, and more. -- the Editors
Stacey Gilbert, Director of Precision Medicine, ADVI Health
I believe 2026 could be the year of perfect pairings: Abbott's acquisition of Exact Sciences is just the beginning! I see a wave of strategic lab acquisitions by pharmaceutical companies that have the focus and vision to jump into the oncology diagnostics market. Highly precise MRD and MCED tests are exploding onto the scene and building a groundswell for broader coverage because they are directly changing the way certain cancers are monitored and treated. It can be a smart, highly strategic move for pharma power players with the resources to innovate precision drug therapies in parallel with diagnostics companies to more fully suit the complex needs of patients living with cancer.
Mike Banville, CEO and President, ALZpath
In the coming year, blood-based testing will move from promise to practice, redefining how we detect and manage Alzheimer’s disease: With proven efficacy of lifestyle interventions, at-home options for therapeutics like Leqembi, and prevention data continuing to build, individuals will increasingly demand access to testing that allows them to understand their risk early, long before symptoms appear. Blood-based diagnostics will become the foundation of a new care model, one that brings precision testing into homes, clinics, and health systems globally. I expect to see a pivotal shift from reactive care to proactive prevention, powered by accessible, high-performance testing.
Russ Lebovitz, CEO and Founder, Amprion
As our understanding of neurodegenerative disease biology grows, 2026 will bring a much-needed shift toward precision, mechanism-based diagnostics: Emerging research suggests that mixed misfolded-protein pathologies are common, with each protein type, such as alpha-synuclein or tau, spreading through the brain differently via unique pathways. These differences help explain the heterogeneous symptom profiles and progression seen across disorders. Capturing this complexity will require multifactorial diagnostic frameworks that combine blood biomarkers, CSF analyses, and imaging. By mapping both the presence and the spread of pathological proteins, clinicians will gain clearer insight into disease mechanisms, enabling earlier detection and informing the development of targeted interventions.
The real power of a data-driven life sciences world is in bringing diagnostics, analytics, and evidence together in real time: Diagnostic intelligence helps us make sense of all that data by turning it into insights that make care more innovative, more equitable, and more sustainable. In 2026, success will depend on turning the data deluge into actionable insight that accelerates discovery and delivers the right therapy to the right patient at the right time.
In 2026, we'll see a definitive shift in solid tumor oncology toward protein-based diagnostics: Proteins yield real-time tumor biology, capturing clinically meaningful changes that can reveal whether the disease is active, responding, or returning (often earlier than imaging or genomics alone). At the same time, cancer diagnostics are moving beyond standalone screening to use diagnostic tools that help inform what happens next, such as follow-up testing, monitoring, surveillance, or personalized treatment. Together these trends signal a bigger pivot toward proactive, long-term patient care where clinicians can accurately diagnose, track progression, and evolve treatment over time. The result is a safer, more precise approach to disease management that reduces overtreatment and improves outcomes.
FDA scrutiny of marketing claims, particularly challenges to the line between general wellness claims and clinical claims, will continue (and possibly increase) into 2026: In 2025, we saw an uptick of FDA enforcement activity targeting products’ intended uses based on statements on the companies’ websites and social media platforms, including not only public Warning Letters but also more private direct inquiries. In the device and diagnostics space, this enforcement largely hit companies marketing mobile applications and testing kits for lifestyle and wellness-related purposes. Similarly, many dietary supplement businesses fielded questions from FDA as to whether their promotional activity crossed the regulatory line into drug claims. The promulgation and wide adoption of digital marketing, coupled with the social pressures to promote accessible general wellness practices to the public, promises to draw more attention from FDA in its efforts to ensure these products are in line with its safety and effectiveness pillars.
Campbell Rogers, Chief Medical Officer, Heartflow
AI is redefining how we detect and manage disease: In 2026, AI is set to play an even greater role in transforming healthcare. Through advanced imaging and data, AI is giving clinicians deeper, more personalized insights into patient health, catching life-threatening diseases early so they can be treated and monitored. As AI becomes fully integrated into clinical workflows it will accelerate diagnostics, improve outcomes, and change the way we manage disease.
Diagnostics succeed when they change decisions, not just generate data: Whole genome sequencing (WGS) changes decisions because it sees what panels miss—complex rearrangements, genome-wide copy changes, and mutational signatures that influence targeted therapy, IO eligibility, and trial options, often with comparable turnaround and cost once you avoid reflex testing. In a CLIA/CAP setting with clinician-friendly reporting, WGS is shifting from ‘send-out specialty’ to a standard element of the diagnostic workup.
In order to advance diagnostic processes and outcomes for patients, digitizing site-to-lab data collection is critical: Unlike how trial master files, patient-reported outcomes and case report forms have all found digital forms, for various reasons, site-based electronic data capture for clinical laboratory testing activities has been slower to adopt electronic data. Real-time EDC is ensuring seamless transfer of patient and sample information from collection sites to labs, reducing delays and errors common in paper-based systems. Immediate access to accurate data accelerates analysis for diagnostic insights, supports biomarker validation and enables adaptive trial designs critical for precision medicine. Advanced platforms are showing to unify e-Requisition, sample tracking and inventory management with automated validation and guided entry, minimizing transcription errors. This real-time visibility strengthens chain-of-custody integrity and compliance while cutting query resolution from days to hours. Use cases are showing query rates can drop from 25% to 1%, with closure times shrinking from 3–7 days to under 2 days.
The near-term success measure for innovation in diagnostics won’t be new tests: Rather, it will be efficiently and systematically surfacing the right patients for the tests we already have. When you can couple precise, population-level identification with standardized, disease-specific pathways, you transform reactive systems into a more proactive diagnostic processes that ultimately shorten the time to treatment.
Smarter diagnostics are helping clinical research move at the speed of innovation: Molecular tools now let teams confirm eligibility, monitor safety, and track therapeutic impact earlier in the study process. As a result, data is cleaner, AI-powered decisions are made faster, and trials can adjust protocols and goals more quickly as new scientific information emerges.
Precision and speed are quickly becoming the standard expectation in diagnostics, not the exception: Rapid, multiplex PCR testing is helping clinicians act sooner and tailor therapies before resistance escalates. Combined with stronger stewardship programs and seamless lab-clinician communication, diagnostics are delivering on their promise of faster, more confident care decisions.
In 2026, the next major shift in diagnostics will come from the arrival of a truly affordable long-read genome: As AI shifts the diagnostics landscape, high quality genomes are required to power the large population studies and AI model development that will unlock new genomic-based diagnostic tools. With high-quality HiFi genomes inclusive of methylation data now available for less than $300, PacBio has made the economics of accessing these data more favorable than ever. At this price point, we envision researchers turning to HiFi data to deliver deeper insights that power the next wave of genomic discovery, enabling the development of new diagnostics for neonatal testing and rare disease diagnosis, infectious disease diagnosis, cancer genotyping, and more.
Denise Heaney, Chief Medical Partner of Molecular Lab and Infectious Diseases Network, VP of Medical and Scientific Affairs, Roche Diagnostics
In 2026, diagnostics will continue to move toward flexible, multiplex molecular testing that enables clinicians to rapidly distinguish among co-circulating syndromic pathogens, such as SARS-CoV-2, influenza A/B, RSV, and beyond: As viral activity becomes less seasonal and more unpredictable, we will see expanded adoption of customizable PCR panels across both laboratory and point-of-care settings, enabling tailored testing strategies, more efficient workflows, and better use of limited resources. Early real-world data already suggest that point-of-care molecular multiplex testing can support faster time to diagnosis and treatment compared with traditional lab-based approaches. Multiplex offerings in traditional and diverse healthcare settings have also been shown to optimize diagnostics stewardship throughout the continuum of care. This increased precision will likely play a growing role in antimicrobial stewardship, helping clinicians avoid unnecessary antibiotics and make more targeted treatment decisions earlier. As laboratories continue streamlining their diagnostic algorithms, digital reflex testing—which automates predefined follow-up testing from a single run—will help reduce waste, maximize diagnostic yield, and ensure that clinicians receive the most relevant insights from each sample.
As larger, richer sequencing datasets accumulate, AI improves diagnostic assay design, and those better assays, in turn, generate even more informative data: This feedback loop accelerates performance gains in applications like oncology, rare disease, and population health. In 2026, diagnostic development pipelines will increasingly be built around continuous data-to-model-to-assay iteration, shortening cycles from discovery to clinical impact.