What are the advantages of Specifica's NGS datasets?
- Customized to your needs: Apply Specifica’s discovery pipeline to your AI data needs with all aspects of antibody selection, and data, tailored to your specifications;
Significantly increase the size of your training datasets: Expand beyond public datasets with their minimal specific VH/VL paired reads; - AI-ready scale: The large data provided in each package is ideal for your foundation model training, in silico antibody engineering, and sequence-function mapping;
- Custom labeling & sorting: Binary labels (bind/no bind, competitive/non-competitive) and multi-category labels (affinity tiers, stringency levels, concentration gradients) for your precise AI fine-tuning and transfer learning;
- Massive diversity: Train your protein language models (PLMs) or other AI models on tens of thousands to millions of non-redundant antibody sequences from our drug-like Gen3 libraries, already optimized for therapeutic developability, affinity and stability;
- Optimized for multi-objective tasks: Specifica’s NGS antibody datasets are rich, discovery-driven, and positioned along the Pareto frontier, giving your AI teams a head start with optimal, developable drug-like antibodies — not suboptimal starting points;
- Active learning integration: Large well-labeled datasets and our model testing data package enable improvement of your AI models — design, test, retrain — accelerating hit-to-lead cycles;
- Developability profiling: Build models with data already enriched for highly developable, drug-like properties, ensuring better structure-guided design decisions.
How does Specifica's expertise in antibody discovery impact the quality of their delivered datasets?
- Extensive antibody discovery campaign success: We understand therapeutic antibodies, having carried out 100+ antibody discovery campaigns, each producing dozens to hundreds of unique antibody clusters binding distinct epitopes, some now in clinical trials;
- Proven antibody library technology: >200 individual naïve sub-libraries built using different scaffolds, formats, gene sources and diversity;
- NGS leadership: Recognized expertise with high-profile publications and deep experience in deep sequencing antibody discovery analytics;
- We understand AI: We know what’s important, including NGS enrichment statistics, diversity clustering, population frequencies, and annotations for label-rich datasets that support machine learning pipelines;
- Our libraries are highly diverse, and very functional, allowing us to provide scale and relevance: Tens to hundreds of thousands of condition-labeled antibody sequences from our high-throughput in vitro display platform purpose-built for AI/ML integration.
