Bioanalysis sits at the intersection of science, regulation, and application. As therapeutic modalities grow more complex and development timelines compress, the role of bioanalysis continues to expand beyond data generation into strategic enablement.
To better understand what lies ahead, we asked a diverse group of leaders across KCAS Bio, representing multiple functional disciplines and each of our locations, the same two questions:
1. What scientific, technological, or industry shift will most impact bioanalysis in 2026, and
2. What additional trends do you expect to unfold?
By posing identical questions across teams and geographies, we aimed to surface both shared signals and informed differences in perspective. What emerged was a remarkably consistent view of where bioanalysis is headed, and how bioanalytical organizations must evolve to keep pace.
Shared Signals for 2026
While each perspective reflects a distinct area of expertise, several themes appeared repeatedly across roles and sites, pointing to broad based change rather than isolated innovation.
AI Becomes Operational, Not Experimental
Artificial intelligence is moving beyond exploratory pilots and into routine bioanalytical workflows. Practical applications are accelerating timelines by reducing administrative burden, improving data review, and enabling earlier identification of trends across complex datasets. Rather than replacing scientific expertise, AI functions as an enabling layer that supports more informed experimental design and data interpretation.
At the same time, regulated environments continue to impose necessary constraints. System validation and data reliability remain central considerations as AI supported analysis becomes more deeply integrated into clinical and bioanalytical programs.
Modalities are Becoming More Complex
Biologics, PROTACs, and cell and gene therapies are redefining analytical requirements. Traditional small molecule approaches are being stretched, driving demand for hybrid strategies, advanced instrumentation, and deeper modality specific expertise.
Data Governance and Quality Underpin Progress
As bioanalytical datasets grow in size and complexity, strong data governance is becoming foundational. Clear frameworks for data integrity, sharing, and protection are essential to maintaining regulatory confidence and sponsor trust. The ability to responsibly manage and interpret data is emerging as a core capability, particularly as advanced analytics and AI driven tools become more widely adopted.
Sustainability Becomes Embedded in Laboratory Operations
Sustainability is increasingly shaping how laboratories operate. Efforts to reduce environmental footprint are driving changes in material usage, energy consumption, and reagent selection. These initiatives extend beyond environmental responsibility, influencing risk management, operational resilience, and long-term laboratory planning as expectations around sustainable practices continue to rise.
Individual Perspectives from Across KCAS Bio
With these shared signals as context, individual viewpoints provide depth into how these shifts are manifesting across different areas of expertise.
Brian Wile, PhD – General Manager, KCAS Bio-Philadelphia
Impactful shift for 2026
“I believe the AI transition will continue to reshape sponsor and CRO expectations of the speed at which bioanalytical testing and reporting can move. Multiple groups have now shown that applying AI in non-decision-making capacities can reduce administrative burdens and identify signals for additional human review.”
Additional trends
“I expect in vivo cell therapy techniques to remain a significant bright spot within the wider CGT sector, likely leading to multiple new clinical trial launches and outsized impact on the M&A activity in the field.”
Mouhssin Oufir, PhD – General Manager, KCAS Bio-Lyon
Impactful shift for 2026
“In this tsunami of AI initiatives and tools, data governance is becoming key. CROs that implement strong frameworks for data sharing and protection will build trust and gain a competitive edge”.
Additional trends
“As business partners for our clients, we need to manage and mitigate sustainability-related risks, including human rights, the labor environment, and environmental issues to ensure business continuity. Our recent EcoVadis scorecard for all 3 sites clearly showed this commitment”.
Cheikh Kane, PhD – Vice President, Biopharma Sciences
Impactful shift for 2026
“Industry adoption of FDA guidance on streamlined nonclinical safety studies is expected to significantly influence outsourced preclinical work and bioanalytical strategies.” (Reference FDA Guidance Document: CDER/Office of New Drugs Streamlined Nonclinical Studies and Acceptable New Approach Methodologies-NAMs)
Additional trends
“The need for confirmatory assessment during human anti-drug antibody testing will be reexamined, particularly whether it is required across all scaffolds and indications.”
Todd Pankratz, PhD – Vice President, Mass Spectrometry Bioanalysis
Impactful shift for 2026
“The maturation of AI-enabled bioanalysis will have the most meaningful impact in 2026. In 2026, we will see broader adoption of AI-assisted tools that improve data analysis.
Importantly, the value of AI in bioanalysis will not be about replacing scientists, but about amplifying scientific judgment. By automating time-intensive, low-value tasks and highlighting subtle trends that may be missed by manual review, these tools allow bioanalytical scientists to focus more on experimental design and data interpretation.
This shift will also accelerate bioanalytical timelines. Faster method development and optimization, enhanced data review, and earlier identification of assay performance issues will directly support shorter development cycles—an increasingly critical competitive advantage as sponsors push for faster clinical progression. “
Additional trends
“The continued expansion of complex therapeutic modalities; including biologics, oligonucleotides, PROTACs, and cell and gene therapies will redefine bioanalytical demands and increasingly strain approaches originally developed for small-molecule programs.
In response, hybrid analytical strategies are becoming essential to balance sensitivity, specificity, and molecular coverage across development stages. Adoption of higher-resolution mass spectrometry and improved sample preparation techniques will enable confident characterization and quantitation of structurally complex, low-abundance analytes in challenging matrices.
This evolution will require deeper modality-specific expertise, advanced instrument proficiency, and more sophisticated data interpretation to maintain assay robustness and regulatory confidence. Organizations that proactively invest in these capabilities will be better positioned to support next-generation therapeutics as modality innovation continues to outpace traditional bioanalytical models.”
Tracy Clark-Stovall – Vice President, Quality Assurance
Impactful shift for 2026
“Statistical methodologies may affect the need for testing in clinical trials, particularly through application of Bayesian approaches as outlined in recent FDA draft guidance for drugs and biologics.” (Reference FDA Draft Guidance Document: Use of Bayesian Methodology in Clinical Trials of Drugs and Biologics Products)
Additional trends
“AI/ML and other software programs will increasingly support data review and QA auditing. This can help quickly flag errors, decrease time in data review and audits, improve quality, and increase available time for continuous improvement.”
Todd Forsyth – Director, Quality Assurance, KCAS Bio-Philadelphia
Impactful shift for 2026
“The implementation of AI has been far reaching over the last few years. While the benefits of having AI in litterboxes and refrigerators may still be debated, the use of AI to mine a patient’s complete bioanalytical data across platforms to trend drug effects and disease progression is now possible with AI-supported analysis. There are still constraints of using AI in regulated spaces, specifically in the areas of AI system validation, data reliability, and patient privacy. 2026 will bring improvements and innovations in these areas bringing the benefits of AI-lead clinical data analysis closer to mainstream use. “
Additional trends
“A larger focus from laboratories on ensuring that science remains sustainable and their environmental footprint is reduced. Demand from laboratories will drive the reduction of plasticware, energy efficient instrumentation, and replacement of chemicals with environmentally friendly options.”
Looking Ahead
Together, these perspectives reflect a bioanalytical landscape defined by integration. AI, data governance, sustainability, and modality complexity are not independent trends. They are interconnected forces reshaping how bioanalysis supports drug development. At KCAS Bio, these shifts are being met through intentional investment in technology, data infrastructure, scientific expertise, and responsible laboratory practices.
In 2026, partnership with sponsors will become even more central to successful bioanalysis, as teams collaborate to anticipate challenges and adapt strategies in real time to facilitate more informed decisions throughout development. KCAS Bio is excited to partner with sponsors as these expectations grow, applying scientific depth and operational rigor to help programs navigate an increasingly complex landscape.