We model and optimize a wide range of protein and antibody-based therapeutics, including:

- Monoclonal antibodies (mAbs)

- Bispecific and biparatopic antibodies

- Single-chain variable fragments (scFvs)

- T cell engagers and TCRs

Using machine learning tools we are able to: predict high-confidence protein structures, analyze epitope-paratope interactions, guide sequence optimization and affinity design

We specialize in reformatting antibodies for human use and downstream manufacturability.

- CDR grafting and sequence optimization

- Detection of immunogenic or unstable motifs

- Assessment of hydrophobic patches, charge clusters, and post-translational liabilities

We offer gene-level support to ensure your design is optimized from the start:

- Gene synthesis planning and codon optimization

- Construct design for bacterial or mammalian expression

- Molecular cloning strategy and vector engineering

- Stable cell line generation using lentiviral systems

We combine structure-guided design with practical construct development for efficient downstream expression.

We provide support and analysis for:

- Binding kinetics (BLI, SPR)

- Analytical SEC and SDS-PAGE

- Mass spectrometry characterization (native MS, intact mass)

- Data integration with structural and functional predictions

We help early-stage teams build or scale their biologics discovery engines.

- LIMS selection and setup

- Expression and purification workflows (in-house or CRO-managed)

- Assay design and QC method development