· 1-day CHO expression and rapid characterization help close the gap between computational design and experimental validation
· 20,000+ molecules per week capacity supports large-scale screening of AI-generated antibody candidates
· Integrated binding and developability assessments generate standardized, multidimensional datasets for candidate selection and AI/ML workflows
CAMBRIDGE, Mass.--(BIOSPACE)-- Biointron Biological USA Inc. ("Biointron"), a leading contract research organization specializing in antibody discovery, expression, and optimization, announces the launch of RushDATA™, an integrated wet-lab data generation platform designed to support the growing demands of AI-driven antibody discovery. Combining rapid CHO expression, high-throughput screening, and comprehensive antibody characterization, RushDATA™ enables researchers to evaluate computationally designed antibodies and generate experimental feedback for iterative model-guided discovery.
As AI technologies advance, researchers can generate hundreds to thousands of in silico-designed antibody sequences for a single target. Computational approaches are increasingly applied to de novo antibody design, sequence optimization, structure prediction, and virtual screening, allowing researchers to explore broader sequence spaces. However, experimentally evaluating these candidates at comparable scale remains challenging.
In modern design-build-test-learn (DBTL) workflows, computational predictions guide candidate design, while experimental results provide the evidence needed to evaluate performance and inform subsequent iterations. The ability to rapidly generate consistent, multidimensional datasets is therefore becoming increasingly important for efficient AI-driven antibody discovery.
RushDATA™ was developed to address this growing need by connecting computational sequence design with scalable experimental evaluation.
From Large Candidate Pools to Rapid Experimental Validation
Built around Biointron's 1-day transient CHO expression technology, RushDATA™ enables rapid production and screening of recombinant antibodies, with a processing capacity exceeding 20,000 molecules per week.
The platform supports early screening directly from antibody-containing supernatants, providing initial expression and binding measurements before purification. This approach allows researchers to assess large candidate libraries, identify promising sequences, and prioritize selected antibodies for more detailed characterization without committing extensive resources to every candidate.
For candidates advancing beyond initial screening, RushDATA™ integrates antibody purification, analytical characterization, and developability assessment into a coordinated workflow.
Key capabilities include:
- Rapid antibody production: 1-day transient CHO expression to support shorter experimental turnaround times.
- High-throughput screening: Capacity for 20,000+ molecules per week, supporting parallel evaluation of large candidate libraries.
- Early-stage supernatant screening: Initial expression and binding assessments to facilitate efficient candidate triage.
- Binding characterization: Biolayer interferometry (BLI) and surface plasmon resonance (SPR) measurements to assess antibody–antigen interactions.
- Developability profiling: Assessment of properties including thermal stability, self-interaction, and polyreactivity to support early candidate selection.
Beyond Binding: Multidimensional Data for Antibody Selection
While binding affinity is an important consideration in antibody discovery, it is not sufficient on its own to determine whether a candidate is suitable for further development.
Antibodies with comparable binding affinity may exhibit substantial differences in expression yield, purity, thermal stability, self-interaction, and polyreactivity. Evaluating these properties earlier can help identify potential developability liabilities and provide a more comprehensive basis for candidate prioritization.
RushDATA™ addresses this need by combining binding measurements with physicochemical and developability data within standardized experimental workflows. Depending on the selected service package, analytical methods may include non-reducing capillary gel electrophoresis (cGE), differential scanning fluorimetry (DSF), polyspecificity reagent binding (PSR-BVP), and affinity-capture self-interaction nanoparticle spectroscopy (AC-SINS).
The resulting datasets allow researchers to compare antibody candidates across multiple parameters rather than relying solely on predicted binding performance.
For AI/ML research teams, these experimental measurements can also serve as feedback for evaluating model predictions, examining sequence–property relationships, and informing subsequent rounds of computational optimization.
Integrating Experimental Data into AI/ML Workflows
To support computational research environments, RushDATA™ provides standardized, structured experimental outputs designed for downstream data analysis and integration.
The platform also supports API-based order submission and data retrieval, facilitating the connection between computational design pipelines and laboratory testing.
By linking antibody sequences with experimental measurements, RushDATA™ helps research teams incorporate empirical data into model evaluation, candidate prioritization, and iterative sequence optimization.
Flexible Service Packages
RushDATA™ is available in three service packages tailored to different stages of antibody discovery:
- Basic - Rapid Screening: Antibody expression in supernatant, BLI-based titer measurement, and two-point affinity screening for high-throughput candidate evaluation.
- Standard - Binding Characterization: Antibody expression and purification, concentration measurement, non-reducing cGE, and multi-point affinity characterization using BLI or SPR.
- Premium - Developability Profiling: Comprehensive characterization with additional assessments of thermal stability, polyreactivity, and self-interaction.
These packages support a progressive screening strategy, allowing researchers to begin with broad candidate evaluation and advance selected antibodies to more detailed characterization.
With more than 14 years of experience supporting antibody discovery, expression, and characterization, Biointron continues to expand its high-throughput laboratory capabilities to meet the changing needs of biologics research. RushDATA™ extends these capabilities to AI-driven discovery workflows, providing the experimental data needed to evaluate computational designs and support informed antibody development decisions.
To learn more about RushDATA™, visit https://www.biointron.com/antibody-production/rushdata.html or contact Biointron at +1 (732) 790-8340.
Limited-Time RushDATA™ Launch Promotion
To celebrate the launch of RushDATA™, Biointron is offering special pricing for eligible new customers through December 31, 2026.
- Order one 96-well plate: Receive 50% off.
- Order two or more 96-well plates: Receive the first plate free.
The promotion is available to eligible new customers outside China and provides an opportunity to access high-throughput antibody expression and characterization at reduced pricing.
For full details and eligibility requirements, visit the RushDATA™
Launch Promotion.
About Biointron
Founded in 2012, Biointron is an ISO 9001:2015-certified contract research organization specializing in antibody discovery, expression, and optimization. With more than 700 employees, the company has delivered tens of thousands of recombinant antibodies to more than 3,000 biotech and pharmaceutical companies worldwide. Biointron’s platform takes projects from gene sequence to purified antibody in as little as two weeks, and its RushDATA™ service brings high-throughput wet-lab validation to AI-driven antibody discovery, turning computational designs into experimentally confirmed candidates. Learn more at www.biointron.com.
Media Contact:
Biointron
+1 (732) 790-8340
20 University Road, Suite 500, Cambridge, MA 02138
