Platform

Conditionally active precision oncology therapeutics

9Bio’s approach focuses on re-engineering validated protein frameworks rather than de novo discovery. By modifying existing antibodies and biologics, we introduce new binding profiles and functional properties and functions while preserving developability and reducing technical risk.

Our platform, Ninera™, is a computational protein engineering platform that integrates structural modeling, molecular dynamics, and in silico developability assessment to precisely control protein–protein interactions.

Ninera™ is built around three independent but complementary engines.

Ninera™ Discovery

Testing better protein designs digitally

Testing better protein designs digitally

Models many possible changes to an existing antibody or protein to find variants with improved performance reducing experimental iteration and helping to de-risk candidate selection earlier in development.

  • Large-scale variant testing

    Screens many possible protein changes to identify rare, high-potential candidates.

  • Condition-aware analysis

    Compares how each variant performs across disease-relevant conditions.

  • Reference-guided optimization

    Measures each new design against the original protein to identify meaningful improvements.

  • Developability assessment

    Prioritizes candidates that are not only promising, but also stable and manufacturable.

Ninera™ Dynamics

Understanding how binding really happens

Understanding how binding really happens

Reveals how a biologic interacts with its target over time, enabling more efficient prioritization of candidates and focusing development resources on molecules with more stable, specific, and disease-selective bindings.

  • Dynamic candidate triage

    Compares shortlisted candidates to prioritize those with the most favorable binding behavior.

  • Binding behavior resolution

    Reveals how interactions change over time, including short-lived states that static models may miss.

  • Specificity refinement

    Identifies candidates that better distinguish the intended target from closely related off targets.

  • Conformational stability analysis

    Assesses how stable and flexible each candidate remains under relevant biological conditions.

Ninera™ Glycans (in development)

Designing with glycans in mind

Designing with glycans in mind

Explores how glycans shape protein behavior, enabling more informed design of glycosylated therapeutics and opening new opportunities to tune efficacy, stability, and selectivity than would be possible without considering glycosylation.

  • Glycan-aware dynamic modeling

    Simulates glycans as flexible parts of proteins that influence binding, stability, and recognition.

  • Integrated protein-glycan dynamics

    Models proteins and attached glycans together to better capture real biological behavior.

  • Glycoprotein interaction modeling

    Characterizes how glycan-driven structural effects can shape target engagement.

Additional Capabilities

Antibody discovery

Complementary discovery approaches, including immunization and phage and yeast display.

Protein production and purification

Small-scale expression, purification, and preparation of antibody and protein candidates for downstream testing.

Antibody engineering

Sequence and structure-based humanization, CDR optimization, bispecific and multispecific antibody engineering, and custom antibody fusion proteins.

Candidate characterization

Binding, kinetics, epitope binning, developability, purity, stability, and cell-based functional assessment.