Conference Day 1

8:25 am Chair’s Opening Remarks

Improve Histopathological Image Analysis: Navigating Machine Learning & AI Algorithim Development for Sample Analysis

8:30 am Understanding the Required Applications of ML to Train Algorithm of Specific Tissue Samples

  • Ulysses Balis Professor & Director, Pathology Informatics, The Regents of the University of Michigan


  • Identifying key techniques currently used to train algorithms for machine learning
  • Discussing AI and machine learning applications for given tissue samples

9:00 am Delve Into The Automation of The Marsh Histology Endpoint For Celiac Disease


  • Endpoints with large observer variability hurt drug development
  • Machine-reading can be accurate, is more reproducible, and may provide additional insights
  • Celiac disease can serve as a model for other disease states

9:30 am Panel Discussion: Showcasing the Advantages of Abundant Imaging to Inform Future AI Development


  • Examining current state of sample sets and navigating current methods to obtain them 
  • Exploring how samples can be used for training, analysis and future development to create more successful data sets 


10:00 am Speed Networking


This session is the ideal opportunity to take advantage of face-to-face networking time and prioritize overcoming challenges associated to elucidating pathogenesis, standardizing understanding of endpoints and algorithm development in the fibrotic, GI and renal disease space

10:45 am Morning Break & Networking

11:15 am Exploring Patient-Derived Models to Test Novel Therapies in a High Throughput Manner

  • Pinaki Sarder Associate Director for Imaging, University of Florida


  • Using fibrotic models of multiplexing several readouts for a holistic overview
  • Assessing high content imaging to improve assay sensitivit

11:45 am Semi-quantifiable to Quantifiable: Applying Digital Pathology & AI Across Patient Cohorts to Enhance Endpoint Efficacy

  • Jerome Rossert Vice President, Head of Clinical Renal, Late CVRM, AstraZeneca


  • Enhancing disease prognosis in patient subpopulations by observing fibrosis progression in specific individuals
  • Obtaining more reproducible, consistent, and quantifiable endpoints as a key standard to resolving how patients are being evaluated

12:15 pm Panel Discussion: Comparing Evolving AI Algorithms in Digital Pathology Against Conventional Pathology to Identify Patient Subpopulations and Predict Disease Progression

  • Jerome Rossert Vice President, Head of Clinical Renal, Late CVRM, AstraZeneca
  • Tania Kamphaus Director - Metabolic Disorders, Foundation for the National Institutes of Health
  • Pinaki Sarder Associate Director for Imaging, University of Florida


  • Opening up possibilities in pathology progression to understand disease heterogeneity & execute precision medicine
  • Compare and contrast fibrosis against GI, cardiovascular and other disease targets.

1:00 pm Lunch & Networking

Expediating Regulatory Approval Through Application of Digital Pathology in Fibrotic Studies

2:00 pm Roundtable Discussions: Integrating Digital Pathology with Advanced Technologies to Complement Existing Evaluations of Disease Progression


  • A session dedicated to crowdsourcing and troubleshooting challenges faced by pathologists and technical experts alike to understand how peers are integrating, utilizing and advancing technologies for their pipelines.

Table 1 – Integrating NGS and Bioinformatics with Existing Evaluations of Disease Progression

Table 2 – The Use of Machine Learning with Multi-Omics to Predict Therapy Response

Table 3 – Discussing A-Zs of Cloud Computing, Storage Solutions, Pathology PACS and Informatics

2:45 pm Panel Discussion: Approaching Diseases from a Digital Pathology Perspective


  • Uniting ideas, challenges and solutions discussed during the roundtables
  • Identifying key takeaways from the discussions and next steps in driving innovation

3:45 pm Afternoon Break & Scientific Poster Session


Not ready to present? Showcase your latest developments and present the next-generation therapies for digital pathology and AI/ML algorithms in a relaxed atmosphere. This is your opportunity to continue to forge new and existing relationships, get feedback from key players in the field on your latest developments and connect with other stakeholders showcasing their posters alongside you

Coupling Digital Microscopy With Artificial Intelligence Analysis to Uncover Greater Insights Into Treatment-Induced Fibrosis Regression

4:30 pm Recapitulating the Commonalities Observed by Pathologists to Advance Digital Understanding of Neural Fibrosis Progression & Regression

  • Uptal Patel Exec Group Dir | Adjunct Prof, AstraZeneca


  • Understanding the levels of progression and regression pathologists are able to detect
  • Building an awareness of the requirements needed for therapeutic efficacy 

5:00 pm Leveraging Digital Pathology with Artificial Intelligence Analysis in NASH to Improve the Gold Standard for Fibrotic Diseases


  • Building a learning algorithm by imaging biopsies to define what profiles speak to disease progression
  • Utilizing AI in repeated longitudinal methods for numerous patients in combination with clinical data to develop an extensive database
  • Utilizing different levels of sensitivity of devices to observe pathogenesis

5:30 pm Chair’s Closing Remark