What it is
LabGenius's EVA platform uses machine learning plus fully-automated robotics to explore antibody design space, iteratively proposing and testing candidates — including complex multi-specific formats — to optimize several therapeutic properties at once.
Evidence trail
BioAtlas keeps the path from source to decision visible. A connection records provenance; it does not imply that evidence is sufficient for every context.
Model passport
How LabGenius — EVA represents biology
Category is navigation. These fields describe the model-specific computational transformation and deliberately override broad category defaults.
Biological scale
Modalities & tasks
Registry, claims and frontier intelligence
Version history not yet curated
1 version record · release year not yet normalized. Model-family identity remains separate from capability and access changes.
Explore version lineage →0 normalized claims
No task, dataset, split and metric claim has been normalized for this record yet.
Open claim intelligence →0 connected frontiers
No frontier-research record currently connects to this model.
Inspect research horizon →Inputs and outputs
Inputs
Antigen, sequence or desired propertiesOutputs
Antibody candidatesAffinity or developability estimatesScientific and technical profile
Scientific principles
Technology
Scientific lineage
These are transparent concept matches—not claims that one scientist alone caused this model. Each connection is based on the model’s recorded domain, scientific principles, technical terms or an explicit lineage link.
Hybridoma production of monoclonal antibodies
Georges J. F. Köhler & César MilsteinTherapeutic antibodies, diagnostic antibodies and antibody discovery platforms became scalable and reproducible.
Somatic gene rearrangement generates antibody diversity
Susumu TonegawaAntibody language models and repertoire design operate on the sequence space created by V(D)J recombination and somatic diversification.
Phage display and selection of binding proteins
George P. Smith & Sir Gregory P. WinterDisplay-based selection created an experimental search engine for protein binders and remains a core validation partner for computational antibody design.
Directed evolution of enzymes and proteins
Frances H. ArnoldGenerative protein design increasingly closes the loop with directed evolution and experimental selection to optimize function and manufacturability.
Selective toxicity and the ‘magic bullet’
Paul EhrlichTarget selectivity, therapeutic index and mechanism-based screening remain central goals of drug discovery.
Cooperative ligand binding
Archibald V. HillDose–response curves, receptor occupancy, multisite binding and systems pharmacology still use Hill-type models.
Evaluation evidence
BioAtlas has not yet extracted a structured benchmark claim for this record.
Known limitations
- Independent reproducibility is limited by proprietary access.
- A structured benchmark claim has not yet been extracted for this record.
- Outputs require task-specific scientific and experimental validation.
Milestones
Robotics-driven design–test loop.
Focus on next-gen multi-specific antibodies.