Present

Present a session or a poster at the SLAS Data Sciences and AI Symposium to get instant feedback on your research from a diverse audience of industry professionals, academics, scientists, engineers, entrepreneurs and researchers from the global life sciences and laboratory technology community.

Abstracts are no longer being accepted.

This year's topics:

Data Pipelines, Models and Analytics in the Life Sciences
Chair: Ian Kerman, M.S. (Certera)
In this session, tailored for life sciences and pharmaceutical industry scientists, we will dive into data pipelines, modeling and analytics. From initial data collection at the bench and laboratory instrumentation, discover how our expert speakers engineer robust pipelines, streamlining the data life cycle to allow more time for scientific inquiry. Topics include the construction of efficient pipelines, the development of predictive models and the analysis of data providing crucial insights for informed decision-making.

Image Analytics to Connect Genes to Physiology
Chairs: Rajarshi Guha, Ph.D. (Vertex Pharmaceuticals) and Adam Bleckert, Ph.D. (Vertex Pharmaceuticals)
The session aims to highlight approaches employing imaging and image analytics to study systems ranging in scale from the gene to the tissue or organ level. In particular, studies that integrate results from the two ends of the scale allow us to understand how genetic components drive disease phenotypes as observed in histopathological data will be of interest. All imaging modalities will be considered, and approaches that highlight automatic and high-throughput techniques will be considered, potentially applying modern M/L and AI methods. 

AI, Robotics and Automation: Crafting the Next Wave of Intelligent Systems
Chair: Mohit Goel, M.S. (Moderna)
This session delves into the impact of automation, robotics and AI across various sectors, emphasizing their role in streamlining laboratory workflows and material transport to boost efficiency. We'll explore integration challenges, opportunities for innovation, ethical considerations in AI and changes in work dynamics. Participants will discover practical applications and strategies for using these technologies to create smarter, autonomous systems, enhancing overall operations and value.

Biomarker Detection Using Omics and Clinical Translation
Chair: Anupama Reddy, Ph.D. (Vindhya Data Science)
Biomarkers are critical to enabling precision medicine for patients. However, multiple challenges exist, including patient/sample heterogeneity, integration of multiple omics data types and clinical translation. This session will discuss these aspects of biomarker detection and the considerations for successful translation to the clinic.

Merging AI with Experimentation for Modern Discovery
Chair: Jeremy Jenkins, Ph.D. (Novartis BioMedical Research)
Increasingly, machine learning and ML models are seen less as one-offs for analyzing experiments and more as iterative partnerships between wet and dry labs. Session presentations will focus on how AI drives experimental inquiry and changes how we ask discovery questions.