· 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 BiologicalUSA Inc. ("Biointron"), a leading contract research organizationspecializing in antibody discovery, expression, and optimization, announces thelaunch of RushDATA™,an integrated wet-lab data generation platform designed to support the growingdemands of AI-driven antibody discovery. Combining rapid CHO expression,high-throughput screening, and comprehensive antibody characterization, RushDATA™enables researchers to evaluate computationally designed antibodies andgenerate experimental feedback for iterative model-guided discovery.
As AI technologies advance, researchers can generatehundreds to thousands of in silico-designed antibody sequences for asingle target. Computational approaches are increasingly applied to de novoantibody design, sequence optimization, structure prediction, and virtualscreening, allowing researchers to explore broader sequence spaces. However,experimentally evaluating these candidates at comparable scale remainschallenging.
In modern design-build-test-learn (DBTL) workflows,computational predictions guide candidate design, while experimental resultsprovide the evidence needed to evaluate performance and inform subsequentiterations. The ability to rapidly generate consistent, multidimensionaldatasets is therefore becoming increasingly important for efficient AI-drivenantibody discovery.
RushDATA™was developed to address this growing need by connecting computational sequencedesign with scalable experimental evaluation.
From Large Candidate Pools to Rapid ExperimentalValidation
Built around Biointron's 1-day transient CHO expressiontechnology, RushDATA™enables rapid production and screening of recombinant antibodies, with aprocessing capacity exceeding 20,000 molecules per week.
The platform supports early screening directly fromantibody-containing supernatants, providing initial expression and bindingmeasurements before purification. This approach allows researchers to assesslarge candidate libraries, identify promising sequences, and prioritize selectedantibodies for more detailed characterization without committing extensiveresources to every candidate.
For candidates advancing beyond initial screening, RushDATA™integrates antibody purification, analytical characterization, anddevelopability 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 AntibodySelection
While binding affinity is an important consideration inantibody discovery, it is not sufficient on its own to determine whether acandidate is suitable for further development.
Antibodies with comparable binding affinity may exhibitsubstantial differences in expression yield, purity, thermal stability,self-interaction, and polyreactivity. Evaluating these properties earlier canhelp identify potential developability liabilities and provide a morecomprehensive basis for candidate prioritization.
RushDATA™addresses this need by combining binding measurements with physicochemical anddevelopability data within standardized experimental workflows. Depending onthe selected service package, analytical methods may include non-reducingcapillary gel electrophoresis (cGE), differential scanning fluorimetry (DSF),polyspecificity reagent binding (PSR-BVP), and affinity-captureself-interaction nanoparticle spectroscopy (AC-SINS).
The resulting datasets allow researchers to compare antibodycandidates across multiple parameters rather than relying solely on predictedbinding performance.
For AI/ML research teams, these experimental measurementscan also serve as feedback for evaluating model predictions, examiningsequence–property relationships, and informing subsequent rounds ofcomputational optimization.
Integrating Experimental Data into AI/ML Workflows
To support computational research environments, RushDATA™provides standardized, structured experimental outputs designed for downstreamdata analysis and integration.
The platform also supports API-based order submission anddata retrieval, facilitating the connection between computational designpipelines and laboratory testing.
By linking antibody sequences with experimentalmeasurements, 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 todifferent 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 advanceselected antibodies to more detailed characterization.
With more than 14 years of experience supporting antibodydiscovery, expression, and characterization, Biointron continues to expand itshigh-throughput laboratory capabilities to meet the changing needs of biologicsresearch. RushDATA™ extends these capabilities to AI-driven discoveryworkflows, providing the experimental data needed to evaluate computationaldesigns and support informed antibody development decisions.
To learn more about RushDATA™, visit https://www.biointron.com/antibody-production/rushdata.htmlor contact Biointron at +1 (732) 790-8340.
Limited-Time RushDATA™ Launch Promotion
To celebrate the launch of RushDATA™, Biointron is offering specialpricing 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 outsideChina and provides an opportunity to access high-throughput antibody expressionand characterization at reduced pricing.
For full details and eligibility requirements, visit the RushDATA™Launch Promotion.
About Biointron
Founded in 2012, Biointron is an ISO9001:2015-certified contract research organization specializing in antibodydiscovery, expression, and optimization. With more than 700 employees, thecompany has delivered tens of thousands of recombinant antibodies to more than3,000 biotech and pharmaceutical companies worldwide. Biointron’s platform takesprojects from gene sequence to purified antibody in as little as two weeks, andits RushDATA™ service brings high-throughput wet-lab validation to AI-drivenantibody discovery, turning computational designs into experimentally confirmedcandidates. Learn more at www.biointron.com.
Media Contact:
Biointron
+1 (732) 790-8340
20 University Road, Suite 500, Cambridge, MA 02138