Biointron

A new study by researchers at Stanford University and Arc Institute introduces Germinal, a generative pipeline for designing antibodies against user-specified epitopes.

🔹 The method integrates a structure predictor with an antibody-specific protein language model.
🔹 These tools co-optimize antibody structure and sequence.
🔹 Germinal then performs de novo design of functional complementarity-determining regions onto a user-specified structural framework.

This study highlights how rapidly computational antibody design is advancing. But identifying which in silico candidates translate into functional antibodies still depends on fast, reliable wet-lab expression and validation, which you can do with RushData: https://www.biointron.com/rushdata

Find the paper in Nature 👉 https://www.nature.com/articles/s41587-026-03187-0

Efficient generation of epitope-targeted antibodies with Germinal - Nature Biotechnology Germinal achieves epitope-targeted, de novo complementarity-determining region design with high experimental success rates.

NEW: Introducing RushData 🚀
𝗕𝗶𝗼𝗶𝗻𝘁𝗿𝗼𝗻’𝘀 𝗶𝗻𝘁𝗲𝗴𝗿𝗮𝘁𝗲𝗱 𝗱𝗮𝘁𝗮-𝗴𝗲𝗻𝗲𝗿𝗮𝘁𝗶𝗼𝗻 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 𝗳𝗼𝗿 𝗔𝗜-𝗱𝗿𝗶𝘃𝗲𝗻 𝗮𝗻𝘁𝗶𝗯𝗼𝗱𝘆 𝗱𝗲𝘀𝗶𝗴𝗻.

RushData combines high-throughput CHO expression, binding analytics, and early developability profiling to generate structured, actionable datasets for antibody discovery and optimization, in days, not weeks!

• 1-day CHO expression for rapid, standardized data generation
• Parallel processing of 3,000+ molecules per batch
• Custom workflows for different targets and antibody modalities
• Early developability assessments to identify potential liabilities sooner

Choose the service level that fits your program:

𝗕𝗮𝘀𝗶𝗰 – 𝗥𝗮𝗽𝗶𝗱 𝗦𝗰𝗿𝗲𝗲𝗻𝗶𝗻𝗴
Expression, titer, and affinity

𝗦𝘁𝗮𝗻𝗱𝗮𝗿𝗱 – 𝗕𝗶𝗻𝗱𝗶𝗻𝗴 𝗖𝗵𝗮𝗿𝗮𝗰𝘁𝗲𝗿𝗶𝘇𝗮𝘁𝗶𝗼𝗻
Expression, concentration, cGE, and affinity

𝗣𝗿𝗲𝗺𝗶𝘂𝗺 – 𝗗𝗲𝘃𝗲𝗹𝗼𝗽𝗮𝗯𝗶𝗹𝗶𝘁𝘆 𝗣𝗿𝗼𝗳𝗶𝗹𝗶𝗻𝗴
Binding characterization plus early developability assessments

Learn more 👉 https://www.biointron.com/rushdata

𝗛𝗼𝘄 𝗰𝗮𝗻 𝗺𝗮𝗰𝗵𝗶𝗻𝗲 𝗹𝗲𝗮𝗿𝗻𝗶𝗻𝗴 𝗵𝗲𝗹𝗽 𝗼𝗽𝘁𝗶𝗺𝗶𝘇𝗲 𝗺𝘂𝗹𝘁𝗶𝗽𝗹𝗲 𝗮𝗻𝘁𝗶𝗯𝗼𝗱𝘆 𝗽𝗿𝗼𝗽𝗲𝗿𝘁𝗶𝗲𝘀 𝗮𝘁 𝗼𝗻𝗰𝗲? 🤖

A recent review by University of Michigan researchers examines the growing role of AI and machine learning in multi-objective antibody design and optimization.

Besides antibody affinity, successful antibody development involves balancing multiple properties like specificity, stability, aggregation, polyreactivity, immunogenicity, and developability. Optimizing one parameter can hinder the development of another, making the identification of clinically suitable candidates a time-consuming process.

The review highlights emerging approaches such as:
• AI/ML-guided co-optimization across multiple antibody properties
• Deep sequencing and antibody sub-libraries for broader sequence-space exploration
• Computational prediction of co-optimal variants without sub-library generation
• Energy-based and interpretable ML models for humanization and developability optimization
• Proof-of-concept strategies for de novo antibody design

Find the paper here 👉 https://www.nature.com/articles/s44222-026-00444-4

Multi-objective antibody design and optimization using machine learning - Nature Reviews Bioengineering Antibodies are among the best-selling drugs and are crucial for numerous therapeutic and diagnostic purposes. However, optimizing antibodies for desirable drug-like properties has long been a hurdle, delaying or preventing promising drugs from reaching patients. Advances in computational methods, es...

🚀 𝗣𝗿𝗲𝘀𝘀 𝗥𝗲𝗹𝗲𝗮𝘀𝗲: 𝗕𝗶𝗼𝗶𝗻𝘁𝗿𝗼𝗻 𝗟𝗮𝘂𝗻𝗰𝗵𝗲𝘀 𝗥𝘂𝘀𝗵𝗠𝗮𝗯™ 𝗣𝗮𝗰𝗸𝗮𝗴𝗲𝘀 𝘁𝗼 𝗗𝗲𝗹𝗶𝘃𝗲𝗿 𝗣𝘂𝗿𝗶𝗳𝗶𝗲𝗱 𝗔𝗻𝘁𝗶𝗯𝗼𝗱𝗶𝗲𝘀 𝗶𝗻 𝟭𝟬 𝗗𝗮𝘆𝘀

RushMab™ compresses the wait for antibody expression! 4 days for transfection-grade expression plasmids, and 10 days for purified, quality-controlled antibodies.

• RushMab™ - Gene: 100ug transfection grade expression plasmids
• RushMab™ - Super (24/96-well plate): 1ml supernatant, expression plasmids
• RushMab™ - Mini: ≥100ug purified antibody, expression plasmids
• RushMab™ - Standard: ≥1mg purified antibody, expression plasmids

Take a look at the press release here https://finance.yahoo.com/sectors/healthcare/articles/biointron-launches-rushmab-packages-deliver-151200469.html

Biointron Launches RushMab™ Packages to Deliver Purified Antibodies in 10 Days CAMBRIDGE, MA, May 29, 2026 (GLOBE NEWSWIRE) -- CAMBRIDGE, MA - May 29, 2026 - - Biointron, a Shanghai-based antibody contract research organization with offices in Cambridge, MA and Piscataway, NJ, has introduced RushMab™, a suite of small-scale antibody expression packages that deliver purified ...