NextGen Biomed 2026 – London: Highlights and Event Recap

NextGen Biomed 2026 was held in London from March 24-25, featuring discussions across the entire value chain, from antibody engineering advancements to sustainable practices in TIDES chemistry. The event united over 30,000 R&D experts with the common mission of bringing life-saving medicines to patients, sustainably and at scale. 

→ Biointron’s Highlighted Points:

1. AI-native antibody discovery is maturing: integration of generative design, high-throughput data, and closed-loop learning systems. 

2. Next-generation antibody formats are expanding rapidly: multispecifics, T-cell engagers, FDCs, and degrader-antibody conjugates. 

3. Developability and CMC considerations are shifting earlier: analytics, QC, and manufacturability embedded into discovery. 

4. ADC innovation is moving beyond payload/linker basics: focus on toxicity mitigation, site-specific conjugation, and novel mechanisms. 

5. Data infrastructure is now a bottleneck and differentiator: high-quality datasets and automated pipelines drive competitive advantage. 

1. AI-Driven Antibody Discovery & Engineering

• AI models are evolving beyond static structure prediction to capture antibody conformational dynamics, improving binding and function prediction

• Closed-loop ML platforms combine high-throughput experimentation with iterative model training to co-optimize potency, selectivity, and developability

• Generative AI enables de novo biologics design and exploration of sequence space, accelerating lead identification and optimization

• Advances in antibody sequence numbering and segmentation algorithms support scalable, automated property prediction pipelines

• High-throughput reagent generation and synthetic biology platforms are being integrated into Design–Make–Test–Learn cycles to improve model training fidelity

2. Expansion of Next-Generation Antibody Modalities 

• Multispecific and logic-gated T-cell engagers are engineered for enhanced tumor selectivity and reduced off-tumor toxicity

• Novel 3+1 architecture T-cell engagers demonstrate strong tumor killing with minimal activity in healthy tissues

• Antibody fragment-drug conjugates (FDCs) improve tumor penetration and clearance versus traditional ADCs

• Emergence of degrader-antibody conjugates introduces new mechanisms to overcome resistance and expand therapeutic scope  

• Fc-engineering strategies (e.g., FcRn targeting) enable selective depletion of pathogenic antibodies and extended half-life modulation

3. ADC Innovation: Design, Toxicity & Bioanalysis

• Focus shifting to novel payload mechanisms (e.g., degraders) to address resistance and broaden patient populations  

• Site-specific conjugation technologies enable precise drug-to-antibody ratio (DAR) control, improving safety and efficacy  

• Increasing emphasis on understanding and mitigating ADC toxicity, including translational mismatches between preclinical and clinical settings  

• Advanced LC-MS and hybrid immunocapture workflows allow detailed characterization of ADC stability, metabolism, and payload distribution  

• Bioanalytical innovation supports real-time monitoring of complex biologics in biological matrices

4. Early Integration of Developability & Analytical Sciences

• Developability is being embedded into discovery via QC-driven selection and early risk assessment frameworks  

• Affinity LC-MS and advanced analytical workflows enable rapid, high-resolution characterization of biologics and ADCs  

• New analytical tools (e.g., native fluorescence CE, high-resolution LC-MS) improve detection of low-level impurities and variants  

• Increasing regulatory pressure: ~75% of FDA rejections linked to CMC issues, driving adoption of data-driven purification and characterization strategies  

• Co-formulation challenges (e.g., aggregation) are addressed through systematic screening and physicochemical optimization

5. Manufacturing, Expression & Platform Optimization

• Recombinase-based targeted integration reduces clone variability, enabling standardized bioprocesses and faster development timelines  

• Advances in vector design, promoter engineering, and CHO systems improve expression yields and stability across modalities  

• Next-gen purification innovations include engineered Protein A resins with improved stability and binding capacity  

• High-throughput screening and automation enable rapid scale-up from discovery to manufacturing  

• Integration of AI with bioprocessing supports predictive cell line selection and process optimization

Overall takeaway:

Antibody R&D is transitioning to integrated, data-centric platforms where AI, advanced modalities, and early-stage developability converge. Competitive advantage is increasingly defined by the ability to generate high-quality data, iterate rapidly, and design complex antibody formats with manufacturability in mind.

Thank you to everyone who visited our booth at NextGen Biomed 2026 to learn about our services! We had a fantastic time chatting with you and how it can help you achieve antibody development. Our expert team would be happy to answer any follow-up questions. Feel free to email us at info@biointron.com or visit our website at www.biointron.com.