8:45 am Morning Coffee & Networking
9:25 am Chair’s Opening Remarks
Overcoming Operational Challenges to Empower Data Analysis Efforts
9:30 am Fireside Chat: Best Practices in Spatial Omics Data Generation & Analytics to Empower Drug Development Across Disease Areas
Synopsis
- Exploring best practices and troubleshooting strategies to effectively leverage spatial technologies to enhance biomarker discovery
- Examining diverse applications of spatial omics to support research across oncology, inflammation, neurological disorders, and other disease areas
- Harnessing spatial and multi-omics datasets through AI and machine learning tools to derive superior insights in target identification and patient stratification
Moderated by Angela Hadjipanayis, Head of Disease Profiling Genomics & Flow Cytometry, PMCB, Sanofi
10:15 am Proteomap: A Discovery-Focused Multiplexed Imaging Approach
Synopsis
- Multiplexed imaging approaches are ideal to probe for multiple markers on the same tissue to support target ID and validation in the exploratory space
- Proteomap is a flexible, affordable and universal multiplexed imaging method that has been utilized on many tissue types across species
- Examples will demonstrate how this technology is utilized to address and refine common research questions within the drug discovery process
10:45 am Morning Break
Leveraging Computational Tools to Support Targeted Drug Development
11:30 am Building a Machine Learning Model on Spatial Transcriptomic Data to Support Targeted Immuno-Oncology Drug Development
Synopsis
- Uncovering strategies to train a machine learning model on limited high-cost Xenium data to enhance drug development
- Applying this model to H&E data to annotate cell types and observe patterns, maximizing the utility of currently available datasets
- Investigating the spatial patterns in these annotated images to identify potential correlations between spatial distributions of cells and clinical prognosis, offering new insights into disease progression and outcomes
12:00 pm Optimizing Imaging Acquisition Techniques to Gain Better Insights From Your Data to Inform Oncology Drug Development
Synopsis
- Applying spatial biology to understand drug mechanisms of action and efficacy, with multi-tiered analysis from cell density quantification to cell interaction dynamics within the tumor microenvironment
- Utilizing these tools to identify biomarkers that can predict patient outcomes, enhancing treatment approaches
- Focusing on improving imaging acquisition techniques to obtain higher quality data, leading to more precise biomarker development and insightful analysis in spatial biology studies
12:30 pm Lunch Break & Networking
Applications of Spatial Biology to Empower Better Image Analysis & Assessing the Future of the Field
1:30 pm Fireside chat: Mapping Out the Future of Spatial Biology in Biopharma
Synopsis
- Re-iterating the importance of cross-collaboration and knowledge transfer between biopharma, academics, vendors, regulators and other key stakeholders
- Evaluating the growing question: can we use spatial data to support clinical trials at scale
- Discussing the immediate next steps the field needs to take to overcome barriers
2:15 pm Afternoon Break & Networking
Uncovering the Latest Applications of Single-Cell Technology & Understanding the Next Steps for Spatial Biology in Clinical Use
2:45 pm A Payor’s Perspective on Spatial Biology: Evidence Requirements for Novel Technologies
Synopsis
- Understanding the evidence requirements and approval criteria for novel technologies in drug development, with a focus on the U.S. regulatory environment
- Identifying the current state of research, future directions, and key emphasis areas for demonstrating drug efficacy, including addressing unmet clinical needs and assessing alternatives
- Guiding R&D and commercialization efforts by highlighting critical clinical questions, necessary outcomes, and criteria for demonstrating clinical equivalence or superiority to ensure successful acceptance for reimbursement
3:15 pm Spotlighting Lessons Learned from Adopting & Leveraging Deep Visual Proteomics in Translational Research
Synopsis
- Exploring best practices and troubleshooting strategies to effectively leverage deep visual proteomics across drug development
- Uncovering the different applications of this tool across multiple tissue types to gain better throughput
- Sharing the future applications and hopes for this technology to gain better disease insights