Biologics developability and formulation are entering a new phase as more labs adopt AI- and ML-based analysis or lab-in-the-loop models. Fueling this shift requires large, reliable datasets on protein, antibody, and peptide stability. Collecting this data has become increasingly complex and often relies on slow, labor-intensive testing.

Aunty accelerates developability and formulation screening with high-throughput, multi-attribute characterization. By combining full-spectrum DSF with static and dynamic light scattering in a 96-well quartz plate, you can gather melting and aggregation data at blazing speeds. Test thermal gradients, long-term isothermal stability, or protein refolding in a single system. Or, integrate Aunty into automated workflows to keep wet and dry labs moving at the same pace.

Join this webinar to see Aunty tackle a protein formulation development pilot and a peptide preformulation proof-of-concept study. A DoE-based excipient screen of 3 antibodies and an enzyme identified major stability drivers, while the peptide study exposed formulation factors that increased the aggregation risk of liraglutide and semaglutide.

Key learning points:

• See how Aunty captures melting and aggregation data at blazing speed with full-spectrum DSF, SLS, and DLS.
• Discover how to fuel formulation and developability screening with high-throughput stability data from Aunty.
• Accelerate stability screening with Aunty’s 96-well quartz plates.
• Break through testing bottlenecks that slow dry lab analysis and wet lab validation.