Designing for Developability: A New Mindset for Antibody Discovery

Rethinking the Sequence of Antibody Discovery 

In the traditional antibody discovery paradigm, developability is often treated as a downstream quality control issue, as something to verify once a candidate has been selected for advancement. However, a shift in mindset is emerging within the biopharmaceutical industry: developability must be a design principle from the outset. This approach integrates manufacturability, stability, safety, and pharmacology into early-stage decision-making, reducing the risk of failure in later stages of development. 

This perspective supports a broader concept of biopharmaceutical informatics, which promotes data integration and experimental standardization to guide therapeutic development, as described by Bauer et al. (2023). While AI plays a supporting role, the emphasis is on the harmonization of computational and experimental workflows to produce reliable, reproducible data from discovery through to development.¹

Rising R&D Costs, Falling Success Rates

The need for a developability-first approach is underscored by current trends in biologic R&D. Over the past decade, the average cost of bringing a new biologic to market has more than doubled, exceeding $3 billion. At the same time, clinical success rates for biologics have declined from roughly 30% in the early 2000s to below 12% in recent years. While this can be due to therapeutic efficacy, many programs fail due to poor manufacturability, stability, or pharmacokinetics. 

Failures often occur late in development, when re-engineering the molecule becomes impractical due to prior investments in cell lines, toxicology studies, and clinical materials. As a result, there is growing recognition that selecting molecules with optimal biophysical and functional properties must be a priority at the earliest stages of discovery. 

Related: Why Use Developability Assessments Early in Your Discovery Workflow?

Defining Developability

Developability can be defined as the combination of attributes that allow a molecule to be manufactured at scale, remain stable throughout shelf-life, perform safely and predictably in vivo, and meet regulatory standards. These attributes can be put in four categories: 

1. Manufacturability: High expression yield, efficient purification, and compatibility with platform processes 

2. Stability: Resistance to degradation (e.g., deamidation, oxidation), aggregation, and denaturation under manufacturing and storage conditions 

3. Safety: Low immunogenicity, minimal off-target binding, and absence of problematic PTMs or sequence motifs 

4. Pharmacology: Appropriate serum half-life, low clearance, and target-specific biodistribution

Pre-Paying for Developability

One emerging concept is the idea of “pre-paying for developability.” Instead of attempting to fix biophysical liabilities after lead selection, developers can design screening libraries, selection workflows, and analytical panels to eliminate unstable or poorly expressed clones at the earliest stage.¹

This approach involves:

• Engineering antibody libraries with developability filters (e.g., removing NG motifs, minimizing surface hydrophobicity) 

• Selecting framework regions known to support chemical and colloidal stability 

• Screening hits not only for binding affinity but also for key physicochemical properties (e.g., Tm, kD, pI) 

• Prioritizing clones that are both functional and well-behaved under platform conditions 

The benefit of this strategy is not just risk mitigation—it also enables more reliable timelines, fewer formulation surprises, and faster advancement into clinical development. Importantly, the incremental cost of early profiling is far lower than the downstream cost of remediating a poorly behaved lead.

Standardizing Developability Assessment Panels

A major barrier to effective early-stage screening has been the lack of standardized, scalable experimental panels. Developability assessments vary widely across organizations, and methods are often difficult to compare due to differences in assay formats, expression systems, or buffer conditions. 

To implement a developability-first approach, experimental screening panels must become: 

• Standardized: Conducted under defined conditions, with consistent thresholds for pass/fail outcomes 

• High-throughput: Capable of screening dozens to hundreds of candidates with minimal material 

• Quantitative: Yielding interpretable metrics for comparative ranking and triaging 

Key assays in a standardized panel include: 

• Thermal stability: Using DSF or nanoDSF to determine melting temperature (Tm) as a proxy for conformational robustness 

• Aggregation propensity: Measured via DLS or SEC under accelerated stress conditions 

• Solubility: Evaluated through PEG precipitation or kD measurements to assess behavior at high concentrations 

• Charge heterogeneity: Assessed using icIEF or IEX to identify charge variants that may impact purity or efficacy 

• Viscosity risk: Inferred from hydrophobic and charge distribution modeling to anticipate formulation challenges 

These assays, when applied in a consistent manner, generate a biophysical profile that can be directly compared across candidates and linked to downstream manufacturability risks. 

Antibody Developability Assessment →

Biointron: Implementing the Developability-First Philosophy

Biointron’s antibody discovery services are built around this developability-first mindset. By combining high-throughput protein expression with a customizable panel of developability assays, Biointron allows clients to screen early candidates not only for function, but also for their readiness to enter development. 

The platform includes: 

• High-throughput transient expression of antibody candidates in mammalian systems in 2 weeks, up to gram-scale 

• Experimental screening for thermal stability, aggregation, solubility, and charge profile 

• Sequence-based risk prediction for PTMs, aggregation-prone regions, and unusual isoelectric profiles 

This approach supports decision-making at the hit-to-lead and lead optimization stages, ensuring that molecules with desirable functional profiles also possess acceptable biophysical characteristics. By identifying and eliminating unstable clones early, Biointron helps reduce the likelihood of late-stage attrition due to formulation incompatibility or manufacturing hurdles.

Developability Begins at Library Design

The concept of designing libraries for developability extends beyond screening. Framework and CDR choices made during antibody library construction can have long-term consequences for downstream manufacturability and stability. 

Optimized libraries should: 

• Avoid sequences with known PTM hotspots (e.g., NG, NS motifs) 

• Minimize regions of high hydrophobicity or high isoelectric point 

• Use scaffold frameworks with known expression and stability profiles 

• Include developability filters during diversity generation 

Integrating these considerations during library construction can reduce the need for extensive downstream optimization and enable smoother progression from discovery to preclinical development. 

Biointron’s services are designed to support this model, giving discovery teams the tools to select better candidates earlier, and development teams the data they need to plan with confidence. 

Antibody Developability Assessment →

References:

1. Bauer, J., Rajagopal, N., Gupta, P., Gupta, P., Nixon, A. E., & Kumar, S. (2023). How can we discover developable antibody-based biotherapeutics? Frontiers in Molecular Biosciences, 10, 1221626. https://doi.org/10.3389/fmolb.2023.1221626