What’s New on Vecura | September 07–11, 2026

New antibody-property assessment modules, clearer validation for large model runs, more reliable research outputs, and six newly onboarded scientific tools.

Welcome to What’s New on Vecura, our regular recap of recent platform improvements and scientific capabilities.

This week, Vecura expands antibody assessment workflows, makes large model submissions easier to validate before a run begins, and improves the reliability of research results and artifact access. Six additional tools are also now available across enzyme kinetics, RNA analysis, molecular design, omics, and single-cell research.

Workflows

Assess antibody properties in your workflow

Two new modules support computational Antibody Property Prediction:

• FlashABB adds TAP developability scoring for antibody candidates.

• BioPhi adds OASis humanness scoring.

Together, these modules give researchers additional computational signals to consider when prioritising antibody candidates during early-stage research.

See run outcomes more accurately

Cancelled runs are no longer displayed as failed, making run status easier to interpret.

Models and Tools

Five additional tools now available

Vecura has also onboarded six tools spanning enzyme kinetics, RNA research, molecular design, omics analysis, and single-cell workflows:

• CatPred for predicting enzyme kinetic parameters from enzyme and substrate or inhibitor information.

• DeepBioisostere for bioisosteric molecular design.

• decoupler for inferring biological activities from omics data and prior knowledge.

• Palantir for trajectory analysis in single-cell data.

• kb-python for single-cell RNA-seq pre-processing with the kallisto | bustools workflow.

Validate large model inputs before a run begins

Vecura now checks input-size limits before dispatching runs across a range of folding and docking models.

When an input exceeds the supported size, researchers receive a clear validation message instead of reaching an incomplete or blocked run state. This creates a more predictable setup experience for computationally intensive workflows.

Additional reliability improvements

Citation DOI links now resolve correctly, and Mermaid diagrams render only once they are complete.

Large artifacts can also be downloaded more reliably, helping researchers access complete output files from longer or more data-intensive runs.

Follow What’s New on Vecura for regular updates on new models, scientific workflows, and platform capabilities.