Discovery Program Strategy

A discovery program begins long before anyone builds a library or runs a screen. The most consequential decisions happen at the planning stage: target selection, antigen design, format choice, and screening strategy. Get these wrong and you'll spend months optimizing molecules against the wrong epitope or in a format that can't be developed.

Target validation is the first gate. Is the target biologically validated in your indication? Is the extracellular domain structurally characterized? Are there known epitopes that correlate with function, or are you exploring a novel surface? These questions determine how much structural and functional data you'll have to work with, which directly affects your screening strategy. A well-characterized target like PD-L1 allows epitope-focused design from day one. A novel GPCR extracellular domain may require exploratory screening before you can define functional epitopes.

Antigen preparation is equally critical. The protein you screen against must present the relevant epitopes in a native-like conformation. Truncations, tags, aggregation, and improper disulfide formation can all bias your screen toward binders that don't recognize the native target. Spending time upfront on antigen quality control—SEC-MALS, thermal stability, binding to known reference antibodies—prevents the most expensive failure mode in discovery: months of optimization on a hit that doesn't translate.

The choice between conventional antibodies, single-domain antibodies (nanobodies/VHHs), peptides, and engineered scaffolds depends on your application. Full-length IgGs offer long half-life and effector functions but are expensive to produce and difficult to engineer for multi-specificity. VHHs are small, stable, and modular—ideal for multi-specific constructs, intracellular targets, and diagnostics—but lack Fc-mediated effector functions unless reformatted. Peptides offer oral bioavailability potential and chemical synthesis but typically bind with lower affinity.

Screening strategy follows format choice. Phage display, yeast display, ribosome display, and computational design each have different throughput, hit-rate, and affinity profiles. A naive phage library might give you 10–50 unique binders per campaign. Computational design can generate thousands of candidates in silico but requires structural data and co-fold validation. The best programs often combine approaches—computational design to seed a focused library, then display-based affinity maturation to optimize leads.

Discovery programs fail for predictable reasons: poor antigen quality, wrong format for the application, insufficient diversity in the screening library, and inadequate counter-screening. A good strategy builds in decision gates and backup plans at each stage. If your primary screen yields no hits, do you have an alternative library or antigen variant ready? If your leads aggregate, do you have a developability assessment workflow in place?

Realistic timelines matter. A computational-first program can deliver ranked candidates in 2–4 weeks. Adding display-based screening extends the timeline to 3–6 months. Affinity maturation adds another 2–4 months. Building these timelines with explicit milestones and go/no-go criteria keeps the program on track and prevents the drift that turns a 6-month discovery into an 18-month ordeal.