Having trouble finding your antibody linker to the clinic?

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From immunization to nanobodies and beyond, the field of antibody development is a vast ocean.

Antibody Discovery Widget

Preclinical Antibody Development Lifecycle

From antigen selection to IND Filing

1
Antigen Selection
Choosing a target antigen that mimics the disease molecule, then purifying or synthesizing it for use.
2
Immunization
Injecting the antigen into a host or using in vitro methods to induce an immune response from B cells.
3
Screening
Using assays like ELISA, phage display, or hybridoma tech to identify candidates with high affinity and specificity.
4
Preclinical Studies
Conducting in vitro and in vivo studies to evaluate efficacy, safety, and toxicology profiles.
5
Production
Optimizing cell cultures, purification, and quality control (GMP) to manufacture the drug at scale.
6
IND Filing
Submission of the Investigational New Drug (IND) application to regulatory bodies to start clinical trials.

At Vivogenia, we bridge the gap between initial target identification and a validated clinical lead. Developing a therapeutic antibody is no longer just about finding a binder; it is about engineering a molecule that is potent, specific, stable, and ready for large-scale manufacturing.

The failure rate in biologics development is often tied to late-stage "developability" issues, lack of functional efficacy or adverse effects that weren’t picked up beforehand. Our approach integrates discovery and engineering to solve these problems early on.

Modern-day antibody development scales exponentially in complexity. From linker selection to payload configuration, the configurations for your asset can be mind-boggling. It is this same complexity that makes developing a best-in-class antibody a struggle as well.

Antibody Development & Optimization Platform

Antibody Simulator

Configure dual-affinity architectures and simulate development parameters.

1 Molecular Architecture
2 Effector & Partner Engagement
3 Antigen Target Selection
Candidate Architecture

IgG Bispecific

Heavy Chain
Light Chain
Payload
Antigen Target
T-Cell Partner
NK-Cell Partner
SafetyHigh
StabilityHigh
Half-LifeHigh
Bio-DistMed
ComplexityLow
Dev CostLow

The data and visual representations provided by this platform are based on predictive simulations and simplified pharmacokinetic models for research and educational purposes only. Results do not constitute clinical, medical, or legal advice. Antibody stability, developability, and therapeutic efficacy are subject to complex biological variables and must be validated through laboratory testing.

Antibody Discovery Widget
Potential Development Obstacles
Antigen Risks
  • Wrong Target: Antigen may not drive disease pathology.
  • Conformation: Synthetic antigen may not mimic natural structure.
Immunization Risks
  • Tolerance: Host recognizes antigen as "self".
  • Immunodominance: Response targets non-functional epitopes.
Screening Risks
  • Sensitivity: Assays miss low-abundance binders.
  • False Positives: Candidates bind non-specifically in vitro.
Preclinical Risks
  • Toxicity: Off-target binding damages healthy tissue.
  • Immunogenicity: Body attacks the drug (ADA).
  • Poor PK: Rapid clearance reduces efficacy.
Manufacturing Risks
  • Aggregation: Antibodies clump, causing safety risks.
  • Low Yield: Cell lines fail to produce commercially viable amounts.
  • Instability: Degradation during storage.
Regulatory Risks
  • Rejection: Incomplete safety data or study flaws.
  • Compliance: Failure to meet GMP standards.

With near-endless antibody (and nanobody) configurations, targets and epitopes, comes near-endless obstacles that can impede your antibody development program.

There is nothing quite like the frustration of watching a promising project stall because your Antibody-Drug Conjugate (ADC) just isn’t behaving.

Maybe your antibody lost its binding affinity the moment you attached the linker. Or perhaps your "magic bullet" is falling apart in systemic circulation, releasing the payload way too early and hitting everything except the tumor. Maybe there’s an anti-drug antibody response to your lead candidate, which didn’t pop up in your in vivo studies, but suddenly it’s in the clinic.

We’ve seen these challenges, so you don’t have to figure out what’s going to be the next problem to solve.

Ready to link your antibody to the clinic?