From Antibody Lead to Better-Informed Candidates.
Explore a structured approach to evaluating antibody candidates, comparing potential improvements, and prioritizing variants for further investigation.
Conceptual workflow. The dashed stages happen before this service: the leads are produced in your own programme or by another service, not here.
Evaluates. The antibody leads you bring, however you obtained them: your own programme, NGS data, known antibodies or earlier design work.
Why it matters. This service starts from candidates that already exist. A clear set of them focuses everything that follows.
May produce. A defined set of leads to compare.
- 1
Objective first
Decisions follow the goal you define, not a fixed ranking.
- 2
Stages that connect
Evaluate, examine the evidence, compare, then prioritize.
- 3
Scoped to your data
Not every stage applies to every project.
Which service is this? Lead Optimization compares and prioritises across several leads or a dataset. It does not generate variants of one lead (Single Lead Optimization) or new sequences (De Novo).
The optimization workflow
Select a stage. Not every stage is included in every project. Scope is agreed from your objective and data.
Define objective
Agree what you want to decide and which criteria matter.
- Information required
- Your goal, constraints, and any measurements you already hold.
- Analysis that may apply
- None. This is a scoping conversation.
- Output
- A written objective and criteria.
Working on one antibody? Explore Single Lead Optimization.
From Inputs to Insights
- Candidate sequences, with chain information
- Identifiers and metadata
- A structure or complex, if you have one (optional)
- Experimental results, if available (optional)
- Your objectives and criteria
None of these is mandatory except the candidate sequences. More data allows more of the workflow.
- Comparison is only as strong as the data supplied. Experimental results are used where you provide them.
- Prioritisation reflects your criteria and the stated metrics. It is not a prediction of which lead will succeed.
- Metrics available depend on the inputs, for example whether structures are supplied.
Read scientific limitations
Computed descriptors are not measurements, and no score here predicts binding, stability, expression or efficacy.
Structural and interaction observations depend on a structure being supplied and on how well it represents your antibody. A contact in a model is not a confirmed interaction.
Prioritization organizes follow-up against your criteria. Only experimental evaluation can establish how a candidate performs.
Have a set of leads to prioritize?
Share what you have measured and what you need to decide, and we will discuss how to organise it.