Biotechnology Industry Trends & Innovations to Watch in 2026

Introduction: Biotechnology Industry Outlook for 2026 Biotech enters 2026 with momentum, as new modalities mature…

Tim Bernard
Pivotal Scientific
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Introduction: Biotechnology Industry Outlook for 2026

Biotech enters 2026 with momentum, as new modalities mature and technological capabilities broaden, with breakthroughs accumulating across oncology, metabolic diseases and neuroscience. More broadly, the biopharmaceutical industry is balancing rapid scientific progress with geopolitical tensions, pricing pressures and regulatory changes that complicate growth strategies (1).

Following a stronger second half of 2025, sentiment for 2026 improved globally, with 90% of European and Asian biopharma leaders optimistic about the year ahead, compared with 56% of US leaders, according to Deloitte’s survey of 280 biopharma executives (1).

Nonetheless, big pharma is experiencing a structural problem as the patent cliff emerges as a core pressure point, with a reported 40% of revenue approaching loss of exclusivity in the next six years (2). This helps explain the increased dealmaking in the second half of 2025, which is expected to continue into 2026 as large pharmaceutical companies prioritise late-stage, scalable assets with clear revenue replacement potential (3).

As big pharma reshapes its pipelines, adoption of breakthrough technologies is accelerating in 2026, from spatial multi-omics to Artificial Intelligence (AI). So, let’s explore what the year has in store for biotech.

AI Innovation in Biotechnology

In 2026, the question shifts from who is using AI to where it is truly driving impact. Generative, predictive and agentic AI are accelerating discovery, improving R&D efficiency and enabling data-driven decisions.

Adoption is now formalising at both regulatory and organisational levels. In December 2025, FDA guidance supports AI as a transparent decision-making tool (4). Moreover, a 2025 ICON survey found that 76% of biotech leaders expect AI to accelerate R&D within two years, underscoring the shift from hype to operational impact (5).

AI is moving beyond workflow optimisation into core biologics design, enabling the in-silico creation of antibodies and proteins. In January 2026, Absci deployed its Origin-1 AI model for de novo antibody design, targeting previously unaddressed “zero prior epitope” interfaces and advancing hard-to-drug biologics into the clinic with accelerated timelines (6). Additionally, companies like Cradle Bio are leveraging protein language models to engineer enzymes and receptor-binding proteins (7).

Moreover, AI is increasingly being paired with quantum computing to tackle biological problems beyond the reach of classical methods. Early last year, the University of Toronto, in collaboration with Insilico Medicine, demonstrated this approach by designing small-molecule candidates targeting cancer-related proteins (8).

Together, these advances suggest AI is shifting from a support tool to a primary engine of biological innovation, fundamentally changing how new biological products are discovered and designed.

Neurodegenerative Disease Research Advances

In 2026, neurodegenerative research is being reshaped by advances in multiplex immunoassays and spatial proteomics, accelerating both discovery and translational research.

As multiplex panels expand, researchers are placing greater emphasis on quantifying low-abundance biomarkers with high sensitivity and reproducible precision within complex matrices such as cerebrospinal fluid.

Over recent years, companies such as Quanterix have advanced multiplex immunoassays, capable of ultra-sensitive detection of key AD biomarkers including Aβ40, Aβ42, NfL and brain-derived tau (9). These tools are enabling earlier-stage Alzheimer’s research and supporting more refined biomarker-driven study design. Portfolios expanded in late 2025, to include newly approved AD biomarkers such as p-Tau 217, alongside emerging ones such as p-Tau 205, and APOE ε4, with providers rapidly translating new discoveries into scalable assays (10) (11). Nonetheless, growing evidence of intra-assay variability is driving demand for technologies that deliver more reproducible, standardised biomarker measurements.

On the spatial side, neurobiology panel design is being driven by demand to map disease-relevant cell states and interactions within intact brain microenvironments that bulk approaches cannot resolve. For example, Akoya Biosciences recently released the PhenoCode Neurobiology Panel, enabling the visualisation of 42 biomarkers associated with neurodegeneration, neuroinflammation and neuroplasticity within brain tissue (12).

Together, these advances indicate a shift towards high-resolution, biomarker-driven investigation of disease mechanisms, where reproducible measurement of low-abundance proteins is becoming essential.

Spatial Multi-Omics & Systems Biology

In 2026, spatial multi-omics is driving insights from basic biology to translational research. By integrating proteomics, transcriptomics, lipidomics and metabolomics, with advanced imaging, researchers are generating multidimensional data in immuno-oncology, neurobiology and metabolic research.

Recent strategic activity reinforced this trend. In 2025, Takara Bio acquired Curio Biosciences to strengthen its spatial genomics capabilities, while Thermo Fisher Scientific launched the EVOS S1000 to expand imaging capacity (13) (14). In early 2026, Illumina released its cloud-based multi-omics software and 10x Genomics partnered with PharosAI to advance AI-driven spatial oncology research. (15) (16). Together, these moves reflect intensifying competition and continued investment in integrated platforms.

Recent studies illustrate the impact. Spatial multi-omics approaches have identified immunosuppressive tumour microenvironments linked to therapeutic resistance (17). Moreover, integrated RNA and high-plex protein mapping has revealed molecular heterogeneity surrounding pathological plaques in Alzheimer’s Disease (18).

Looking ahead, mass spectrometry imaging (MSI) is emerging as a key spatial multi-omics modality, offering high multiplex capabilities, specificity and dynamic range. Instrument vendors such as Bruker and Waters are advancing label-free MSI methods, enabling comprehensive, high-resolution molecular mapping at speed (19) (20).

This year, spatial biology platforms face growing pressure to demonstrate clear translational value, particularly for personalised medicine. Beyond generating high-resolution datasets, stakeholders increasingly expect evidence that these technologies can inform biomarker discovery and treatment decisions (21).

Obesity and metabolic diseases

2026 marks a new phase in obesity and metabolic disease care, defined by scale, competition and strategic differentiation. Following the consolidation of GLP-1 therapies in 2025, the market is entering a more mature and commercially complex era (22).

Acceleration is evident across modalities and routes of administration. Off-patent semaglutide and the anticipated launch of oral GLP-1 therapies are poised to reshape pricing and broaden treatment options, intensifying competition (22).

High-profile dealmaking underscores the strategic value of next-generation assets. Pfizer’s $10 billion Metsera acquisition, Roche’s partnership with Zealand Pharma on petrelintide and AstraZeneca’s $1.2 billion upfront deal with CSPC Pharmaceuticals, collectively reflect fierce competition for differentiated metabolic therapies (23).

Moreover, pipeline innovation remains robust. GIP/GLP-1 dual agonists, amylin analogues and small molecules such as orforglipron, are expanding the mechanistic landscape, while ultra-long-acting injectables and alternative oral formulations diversify delivery (3).

For research reagent providers and service partners, 2026 presents major growth opportunities, as expanding metabolic pipelines drive demand for high-throughput screening assays, biomarker analysis and manufacturing support in an increasingly competitive obesity market.

Precision Medicine & Targeted Therapies

2026 marks a pivotal year for precision medicine as antibody-drug conjugates (ADCs), cell and gene therapies (CGTs) and next-generation sequencing (NGS) transition from breakthrough science to commercial maturity.

ADCs, which combine cytotoxic payloads with tumour-specific antibodies, are resurging as safer, more targeted oncology therapies. Bain reported in 2026 that ADCs account for approximately 40% of antibody transactions, underscoring their growing strategic importance (24). Deal activity is rising, exemplified by Roche’s $570 million agreement with Medlink in January 2026 and InduPro announcing early this year a strategic with Eli Lilly to develop first-in-class multispecific oncology therapeutics (25).

CGTs are shifting towards operational scale and commercial execution rather than pure pipeline expansion. Advances in allogeneic CAR-T, CAR-NK, induced pluripotent stem cell platforms, and bioprocess automation are supporting scalability and cost efficiency (26). Moreover, expansion into autoimmune diseases is further increasing demand for robust T-cell engineering, activation and immunophenotyping capabilities (26).

NGS remains central to precision medicine, with rare diseases emerging as a key 2026 growth driver beyond oncology. Illumina’s mapped-read technology for NovaSeq X enhances short-read sequencing with long-range information, improving detection of complex structural variants and enabling more genome sequencing (27).

Together, these advances signal a shift from innovation to implementation, where success will depend not only on therapeutic breakthroughs but on scalable manufacturing, advanced analytics and data infrastructure that enable real-world deployment.

Gene Editing & Next-Generation Therapies

Gene editing is moving from experimental promise to clinically validated modality. The 2023 approval of the CRISPR therapy Casgevy for sickle cell disease demonstrated real-world feasibility and commercial potential, accelerating investment and innovation (28).

Next-generation approaches, including base and prime editing, enable precise nucleotide changes without double-strand DNA breaks, indicating continued innovation (26). Reflecting growing commercial confidence, Seamless Therapeutics announced a $1.1 billion partnership with Eli Lilly in January 2026 to develop recombinase-based gene editing therapies for genetic hearing loss (29).

Viral delivery technologies are also advancing, with vectors such as AAV and lentivirus being re-engineered to improve safety and tissue targeting. In February 2026, OXB expanded its partnership with Bristol Myers Squibb to supply lentiviral vectors for CAR-T programmes, highlighting growing demand for scalable delivery platforms (30).

Likewise, non-viral systems, particularly lipid nanoparticles (LNPs), are gaining traction as flexible delivery platforms. New formulations using alternative structural lipids enhance stability and delivery efficiency, expanding the toolkit for nucleic acid delivery in research settings (31).

In 2026, gene editing’s bottleneck is no longer the ability to edit DNA, but the ability to deliver those edits safely, precisely and at scale.

Bioinformatics & Big Data in Biotech

Bioinformatics is being transformed by AI integration and advanced computational tools enabling advancements in genomic sequencing and drug discovery.

In January 2026, AlphaGenome was described in a peer-reviewed paper as a deep learning model that predicts how genetic mutations disrupt gene regulation, particularly within the “dark genome” (32). Analysing up to one million DNA bases at once, such models are expected to accelerate oncology studies, rare-disease diagnosis and understanding of gene regulation.

AI-driven bioinformatics is accelerating drug discovery through detailed modelling of molecular interactions and predictive optimisation of candidates. A 2026 collaboration between Iambic AI and Takeda illustrates this shift, using advanced models to design small molecules, predict protein–ligand interactions and accelerate progression from discovery to clinical development (33).

Morever, growing data complexity is driving advances in cloud and high-performance computing. Managed platforms such as Google Cloud Life Sciences enable scalable, secure workflows, reducing infrastructure burden, lowering costs and expanding access for smaller research organisations (32).

Together, these advances position bioinformatics as a core engine of modern life sciences, transforming vast biological data into actionable insights that increasingly guide discovery, diagnosis and therapeutic development.

Concluding remarks

In 2026, the biotechnology sector is being reshaped by the convergence of AI, spatial multi-omics, advanced gene therapies and personalised medicine. As the patent cliff approaches, pharmaceutical companies are prioritising commercially viable, late-stage assets. Innovation is advancing across immunology, inflammation, oncology and neuroscience, supported by tools that generate deeper biological insight. Crucially, success will favour integration over novelty: platforms that demonstrate translational value and compatibility within real-world workflows will outperform standalone innovations, shifting the industry from technological promise to practical impact.

As biotechnology innovation accelerates, companies must align scientific progress with a clear commercial strategy. If your organisation is preparing for 2026 and beyond, our life science strategy consultancy supports leadership teams navigating growth and positioning decisions.

Bibliography

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