As drug developers look toward 2026, they may see that industry is contending with tighter capital, shifting regulatory expectations, and rising pressure to make better decisions earlier in development. At the same time, advances in data, automation, and therapeutic design are continuing to disrupt how drugs are discovered, tested, and scaled.
To understand where momentum is building, and where real inflection points may emerge, DDN asked industry leaders across drug discovery, clinical development, manufacturing, and strategy to share their expectations for the year ahead. Their perspectives reflect a sector recalibrating how it manages risk, defines success, and translates science into viable therapies.
Taken together, these predictions point to a more disciplined development model in 2026. Novel technologies are moving out of pilot phases and into routine use, clinical trials are becoming more precise and patient-reflective, and safety and manufacturing decisions are being revisited through a more human-relevant lens.
Rather than signaling a slowdown, the outlook for 2026 suggests a narrowing of focus, on data that matters, development paths that can withstand scrutiny, and operating models built for resilience as much as innovation.
What biopharma leaders expect in 2026
Discovery is becoming more predictive, more integrated, and less tolerant of open-ended experimentation. Across AI, analytics, and engineered biology, the emphasis is on narrowing uncertainty earlier by embedding intelligence directly into scientific workflows. In 2026, discovery success increasingly depends on how well data, tools, and biology are orchestrated as a system.
“In 2026, life-science R&D will cross a meaningful inflection point as AI-augmented molecular design becomes not just a promising capability but the default mode of early discovery. The winners will be the organizations that deliver the predictive power of models directly into scientific context—embedded into electronic notebooks, analysis platforms, and design workflows—so chemists and biologists can act on high-confidence insights without leaving their workspace. At the same time, the industry will increasingly recognize that the true competitive advantage lies not in algorithms but in the training data behind them. As the benefits of collaborative model improvement begin to outweigh long-held concerns over data sovereignty, the industry will shift toward Federated Learning: a framework where pharma companies can benefit from collective intelligence without ever sharing raw data. By the end of 2026, federated approaches will move from pilots to standard practice, enabling secure cross-company model refinement and accelerating how the industry innovates.” — David Gosalvez, PhD, Chief Strategy Officer, Revvity Signals
Analytical tools or applications
“Analytical equipment and tools are key to advancing modern medicines, from drug discovery to development to commercial use. In-depth analysis allows deeper product and process understanding, facilitating the evaluation of innovative approaches on a molecular level. Yet the application of many new analytical tools and methods remains challenging. I am optimistic that in 2026 we will see further advances in analytical methods, such as using biophysical tools for GMP applications including identity testing.” — Hanns-Christian Mahler, CEO, ten23 health
“We're observing several convergent trends that may define near-term progress in biotechnology. Xenotransplantation is advancing from isolated compassionate-use cases toward more systematic clinical evaluation, supported by improved immunological compatibility in gene-edited porcine models. Concurrently, bioprinted vascular networks are addressing a critical scalability barrier for engineered tissues. In gene therapy, progress in vector engineering — particularly capsid evolution for ocular and CNS targeting — combined with reversible epigenetic modulation systems, is enabling more precise, compartmentalized interventions with improved safety margins for repeat dosing. In reproductive technology, in-vitro gametogenesis shows incremental progress in mammalian models, while early-stage artificial gestation systems are demonstrating improved endothelial and placental interface fidelity. Demographic pressures are beginning to accelerate both funding and regulatory pathways. The integration of AI-driven closed-loop experimentation and digital twin modeling for metabolic and immune systems is compressing R&D cycles significantly, potentially shifting biology toward a more predictable, engineering-like discipline.” — Boyang Wang, founder of longevity fund Immortal Dragons
“In the five years since the pioneers of CRISPR/Cas9 received the Nobel Prize in Chemistry, the field of cell and gene editing has made remarkable progress. Among these advances is the ongoing evolution of base editing, a technology that enables precise, single-base modifications to correct disease-causing mutations or silence genes without inducing the double-stranded DNA breaks characteristic of CRISPR/Cas9. This significantly reduces DNA damage, leading to a higher yield of healthier cells. Contemporary base editing platforms are highly flexible and modular, allowing for fine-tuning, simultaneous multi-gene edits, and even concurrent knock-ins, supporting complex, multiplexed genetic engineering. Recently, Revvity partnered with Profluent to incorporate AI-designed enzymes into base editors, vastly expanding the potential for optimizing these tools. The future promises base editing as a versatile toolbox for tackling both simple and complex genetic disorders.” — Michelle Fraser, Head of Cell and Gene Therapy, Revvity
Clinical development
Clinical development is shifting from scale-driven execution to precision-led design. Sponsors are using real-world data, modeling, and behavioral insight to better define patient populations and trial structures before the first subject is enrolled. In 2026, the cost of getting trial design wrong is simply too high.
“We must ensure our trials reflect real-world populations — particularly as the FDA may soon support new drug applications based on a single pivotal efficacy trial instead of two. Identifying and enrolling the right patients for the right trials and improving data interpretability will be crucial. Diversity will not only remain an ethical obligation but will also become essential for accurately representing real-world outcomes. However, greater diversity may also introduce new challenges, such as increasing data heterogeneity, requiring different patient engagement strategies. Applying behavioral science to understand our patients, interpret data variability, and understand the type of support they need will be more important than ever.” — Dominique Demolle, CEO, Cognivia
“After years of experimentation, 2026 will mark the year digital twins move from pilot to practice in clinical development. Regulators including the FDA are expanding their AI frameworks, finalizing risk-based guidance and credibility assessments to ensure tools are safe and effective in clinical development. This will create new opportunities to integrate digital twins into trial design and execution.Continued collaboration and feedback loops between regulators, sponsors and technology partners will be essential to ensure digital twins deliver on what matters most: faster, more patient-centric and more equitable clinical trials.” — Dr. Gen Li, Founder and President, Phesi
“The volume of real-world data available for cancer indications has boomed in recent years. This opens up the potential for sponsors to be far more precise in designing and running oncology clinical trials in 2026. With the right data meeting the right science, 2026 will be the year when precision oncology trials finally come into their own, eventually leading to lower patient burden and better, more targeted treatments.” — Dr. Gen Li, Founder and President, Phesi
Safety, risk, and regulatory science
Safety assessment is moving away from legacy convention toward biological relevance. New methodologies are challenging how risk is identified, justified, and communicated across development stages. In 2026, safety strategy is increasingly inseparable from regulatory credibility.
“In 2026, we will see changes with how drugs are developed as pharmaceutical companies increasingly embrace new approach methodologies (NAMs) to manage toxicology risk. NAMs will continue to play a key role in the nonregulated space, helping identify the most promising drug candidates with the highest potential for clinical success before advancing animal studies. In the regulated space, NAMs will be used to justify the need or elimination of various animal studies based on pharmacology and mechanisms of action. Additionally, instead of writing off drug candidates based solely on animal toxicology data, companies will continue to use NAMs as investigational tools to generate safety signals that prove or disprove human relevance — breathing new life into compounds previously shelved as “too risky.” This shift will redefine what constitutes safety for patients, as the industry moves beyond animal models and adopts more human-centric standards. Expect new regulatory scrutiny and a wave of thoughtfully reconsidered assets re-entering the pipeline, as developers leverage NAMs to make more science-driven, patient-focused decisions about safety.” — Steve Bulera, Corporate Vice President, Chief Scientific Officer: Discovery and Safety Assessment, Charles River Labs
Therapeutic modalities
Across therapeutic areas, progress is being measured by durability and deliverability rather than scientific novelty alone. Incremental improvements in modality performance are reshaping feasibility at scale. In 2026, therapies succeed by fitting into real clinical and operational constraints.
“Looking ahead to 2026, atopic dermatitis (AD) care will focus less on treating short flare-ups and more on controlling skin disease long-term. From a clinical and development lens, I see real momentum behind steroid-free options built for chronic use, including in young children. As we learn more about skin barrier dysfunction, immune signaling, and oxidative stress, more targeted topicals are entering clinical practice. What’s changing just as quickly is how we define success. Through the introduction of different modalities – such as first-in-class aryl hydrocarbon receptor agonists – durability, treatment-free days, adherence, and quality of life matter as much as complete skin clearance. The future of AD will be guided by a patient-first perspective.” — Juan Camilo Arjona Ferreira, Head of Research & Development and Chief Medical Officer, Organon
“The field of immunotherapy is rich with strategies for leveraging the natural capability of a person’s immune system to fight disease. The efficacy, scalability, cost and safety of these strategies, however, isn’t always certain, particularly as the complexity of therapeutic payloads increases and the range of target cell types expands. To improve the therapeutic response of certain cell therapies and to lower costs, drug development teams are increasingly turning to solutions that can boost lentiviral transduction efficiency – i.e., to improve gene delivery and expression. This can be the difference between a therapy making it to the clinic or not. When successfully integrated into clinical trials, these solutions could result in more effective cell therapies for a wide range of diseases.” — Chris Lowe, LentiBOOST business leader, Revvity
“In the year ahead, we anticipate more targeted and personalized therapies being used to treat chronic and rare conditions, due in part to the proliferation of multiomics in companion diagnostics (CDx) and the need for diagnostic assays for newer FDA approved therapeutics. By integrating various omics disciplines (e.g., genomics, proteomics, metabolomics), researchers are able to develop a more comprehensive approach to understand the molecular basis of disease – moving beyond single biomarker models to more robust, multi-layered systems. This integrated approach can lead to improvements in target validation, patient selection and reduce attrition in clinical trials. It’s also encouraging to see that regulators are seemingly more open to accelerating the approval process for new drugs that address major public health issues or treat large, unmet medical needs. For example, Sanofi’s Tzield is one of the first recipients of a national priority voucher from the US FDA, which could expedite its approval for use in stage 3 T1D individuals. Our team expects continued technological advances in 2026 and collaboration between pharma companies working on the same therapeutic approaches spanning oncology, immunology, rare and chronic diseases and complex neurological disorders like ALS and Alzheimer’s.”— Madhuri Hegde, SVP and Chief Scientific Officer, Revvity
Lab automation
Scientific productivity is increasingly driven by how well labs integrate tools, data, and workflows. Automation is shifting effort away from manual execution and toward interpretation and design. In 2026, the lab itself becomes an enabling platform rather than a bottleneck.
“We’re witnessing a decisive industry shift toward the automated digital lab, moving away from isolated instruments and manual workflows toward intelligently orchestrated environments that treat hardware, software and data as a single, integrated system. This will be our new normal and a driver of how science gets done. AI will also play a bigger role at the bench. It will amplify scientists and help them make faster, smarter, more confident decisions that accelerate drug discovery across modalities. In parallel, automation will take over the routine, manual tasks, allowing scientists to focus on high-value analysis, experiment design and innovation. In the coming years, the automated digital lab will determine the next stage of scientific productivity in pharma, biotech and beyond – and it will be led by humans and powered by automation.” — Mark Fish, VP & GM of Digital Science and Automation Solutions, Thermo Fisher Scientific
Manufacturing, outsourcing, and scale
Manufacturing decisions are increasingly made in parallel with scientific ones. CDMOs are becoming strategic partners in managing development risk, not just production capacity. In 2026, scale readiness is a filter for which programs advance.
“The industry’s longstanding tolerance for high failure rates and lengthy timelines is no longer sustainable, and those who fail to proactively derisk their development strategies risk being left behind. Outsourcing, which was once seen primarily as a cost-saving lever, will rapidly become a key piece of biopharma’s risk management playbook. Companies will strategically partner with external experts for both R&D and manufacturing, shifting toward centralized resources that deliver speed, flexibility, expert knowledge, and a path to commercial-scale production. This pivot will empower organizations to better anticipate market swings, adapt to risk-appropriate manufacturing, and avoid missteps that cost time.” — Matt Hewitt, Vice President and CTO of the Manufacturing Business Division, Charles River Labs
“In 2026, we anticipate a continued shift toward off-the-shelf, in vivo therapies, with increased demand for scalable, flexible manufacturing solutions. Advanced modalities such as allogeneic cell and gene therapies, and next-generation viral vectors, will drive the need for end-to-end CDMO partnerships that can support rapid translation from discovery to clinic. Automation and AI-driven process monitoring are expected to mature, enabling faster, more consistent production and data-driven process optimization. Researchers and sponsors should prepare for tighter integration between upstream development, analytics, and manufacturing, as bottlenecks in scale-out and supply chain reliability are increasingly addressed. From our perspective, CDMOs will play a central role not just in production, but in de-risking complex development paths and accelerating access to transformative therapies.” — Janet Hoogstraate, CEO, NorthX Biologics
Business strategy and organizational resilience
Economic pressure is forcing sharper strategic choices. Execution, alignment, and speed of reallocation are becoming decisive factors. In 2026, organizational coherence matters as much as scientific ambition.
“The data heading into 2026 points to a structural shift rather than a cyclical downturn. Record layoffs in 2025, combined with policy volatility and tightening capital, are forcing biopharma to operate with fewer people, fewer bets, and far less tolerance for ambiguity. Commercialization will increasingly be judged by early, observable customer behavior rather than long-term aspiration.Strategies built around sheer scale, spare capacity, and the luxury of slow course-correction will be increasingly hard to sustain. Instead, companies will need to be explicit about where they compete, what they are willing to resource properly, and which assumptions truly underpin value creation. Geographic diversification, tighter alignment across functions, and faster reallocation of resources will become core resilience mechanisms, not optional enhancements. At the same time, as automation reshapes talent models, there is a growing risk that strategic intent becomes fragmented or lost during restructurings. The organisations that navigate 2026 most effectively will be those that empower their teams to move as one and make their thinking visible, adaptable, and shared - so strategy survives even when teams change.” — Janice MacLennan, senior strategy consultant & founder of Nmblr
