How does target antigen expression correlate to patient response for a specific antibody-drug conjugate (ADC)? How do factors like target distribution and heterogeneity, linker chemistry, and tumor immunogenicity influence patient stratification and trial design? ADCs hold great promise in oncology, but the complex mechanism-of-action (MOA) of the drugs and evolving resistance mechanisms present a significant challenge for drug development.
In recent years, novel tools like multiplex immunofluorescence (mIF) and AI-powered computational pathology have enabled us to get deep, rich insights into tumor biology. However, we still face bottlenecks in extracting valuable biomarker signatures from these complex datasets and turning all this rich data into actionable insights for drug discovery and development.
In this webinar, we’ll present a novel analysis studio that will enable biopharmaceutical researchers to rapidly interpret computational pathology (e.g., from IHC and H&E) and spatial biomarker data (e.g., from mIF) to derisk ADC drug discovery and development.
In this webinar, attendees will learn:
- How Nucleai’s Analysis Studio can be a valuable part of a biopharma researchers toolkit to rapidly extract actionable insights for ADC development
- How optical density (OD)-based quantitative biomarker scoring of IHC assays can measure protein expression in the membrane, cytoplasm, and nucleus at a more sensitive, granular level, potentially enabling more accurate patient stratification
- How AI-augmented spatial proximity scoring methods can model a drug’s potential bystander effect
- How mIF-based analysis can be used for target identification, credentialing of bispecific targets and combination strategies, and MOA studies
Scheduling conflict? You can still participate!
All registrants will receive a link to view an on-demand recording of the event.
