HALO® User Group Meeting: Harnessing the Power of AI in Digital Pathology

Date: 6 December 2022
Time: 8:00 – 9:00 PST | 11:00 – 12:00 EST | 16:00 – 17:00 GMT
Location: Webinar

Learn how Indica Labs’ customers employ AI for advanced tumor cell detection, clinical trials, drug development, and to address clinical needs



Indica Labs is pleased to announce our 8th Annual HALO® User Group Meeting to be held in conjunction with the Digital Pathology & AI Congress in London on Tuesday, 6 December from 12:00 to 16:00. A lunch will be provided to all pre-registered attendees.


Our program this year features four outstanding guest speakers representing leading universities, NHS sites, biotech, and pharma companies who will discuss how they use AI products from Indica Labs to achieve their research objectives and to implement clinical digital pathology with the CE-IVD marked HALO AP® platform. In addition to our guest speakers, Indica Labs will present the latest features in our latest life science and clinical digital pathology software and will present an overview of our collaborations with external industrial, clinical, and academic partners in order to develop AI products designed to be taken through regulatory approvals for clinical use. We welcome anyone who is interested in learning more about Indica Labs’ quantitative digital pathology solutions to register for the meeting. You do not need to be a current Indica Labs customer to attend.



Time Topic Presenters

11:30 - 12:00

Registration and Lunch

12:00 – 12:10

Welcome Address

Dr. Kate Lillard Tunstall

Chief Scientific Officer, Indica Labs

12:10 – 12:25

Live Demonstration of the New Microglial Activation and Object Colocalization Modules in HALO

Emily Gamble

Product Specialist, Indica Labs

Abstract: Learn about the new features of the new FL Microglial Activation module and updates to the BF Microglial Activation module as well as the BF and FL Object Colocalization 2.1 modules in this live demonstration. New features for the Microglial Activation modules include an interactive markup image option, inclusion of maximum cell body size parameter, inclusion of branch point and end point counts, and summary results are now divided into activated and inactivated microglia counts. The BF Object Colocalization module can now detect up to 5 chromogenic stains, the FL module can detect an unlimited number of channels, and an analysis tile padding parameter improves analysis markups. ​

12:25 – 12:55

Automation and Artificial Intelligence in the Pharmaceutical Histology Lab ​

Dr. Elena de Miguel

Associate Director of Histology and Imaging , uniQure​

Abstract: Histology is a key component of drug development which goes through massive transformation. There are several elements that are used by mid-size pharmaceutical histology labs. Elena will talk about how her lab utilizes HALO to get more accurate and reliable data from histological samples in a way that is scalable, quantitative and repeatable. She will put forward several examples from brain and liver research in order to substantiate her work. Further to that, she will also address the current challenges in the field. ​

12:55 – 13:15

Demonstration of New Features in HALO AI 3.6

Dr. Natasha Carmell

Manager, Life Science Applications (EMEA), Indica Labs

Abstract: Natasha will be discussing and demonstrating new features and functionality of HALO AI 3.6, due for release in early 2023. Learn about our new AI Membrane Segmentation module which can be embedded into analysis modules, interactive HALO AI classifier mark-ups and the importing of additional object data into the HALO results tab.

13:15 – 13:30

Refreshment Break

13:30 – 14:00

Advanced Tumor Cell Detection Using HALO AI

Dr. Marwan Chami

Translational Pathology Image Analysis Lead, AstraZenecaSubject Matter Expert Digital Pathology – Clinical Biomarkers & Companion Diagnostics, Merck KGaA

Abstract: Standard pathology approaches play a crucial role in diagnosis, assessment of protein expression and classification of disease. With the recent technological advances and the increased focus on precision medicine, digital pathology-based approaches had gained momentum for quantitative assessments of biomarker expression through the deployment of artificial intelligence (AI)- based solutions. The use of trained AI algorithms in drug development and translational research can significantly benefit the immune-oncology field in the discovery of novel biomarkers and drug targets. As different biomarkers have different expression patterns, we saw a need for more advanced tools to accurately detect and quantify biomarker immunoreactivity in different tumor cell compartments. In this presentation, we describe a project aiming at developing Tumor-Stroma classifiers for different cancer indications on IHC scanned slides. And on the cell level, the deployment of novel tumor cell quantification tools enabling us to robustly quantify marker expression in cellular compartments. We believe that with these robust AI-powered analysis tools assessing biomarkers tumor cells will be enhanced in precision, reproducibility, and scale.

14:00 – 14:30

HALO as a Central Platform for the Comparison of Orthogonal Methods of Pharmacodynamic Protein Quantification in Formalin Fixed Paraffin Embedded (FFPE) Clinical Trial Samples

Dr. Jack Robertson

Translational Pathology Image Analysis Lead, AstraZeneca

Abstract: Immunohistochemistry (IHC) has long been used as a pharmacodynamic endpoint in clinical trials, but this indirect measurement of protein levels is only linear in a limited range and does not measure protein concentrations in the cells. Traditionally IHC has been score by percentage of positive cells or H-Score, however the advent of digital pathology and image analysis has enabled much more granular scoring of differences in staining intensities. With this increase in measurement sensitivity how do we know what constitutes a meaningful change in protein concentration as measured by IHC? Newer orthogonal methods for tissue protein quantification from formalin fixed paraffin embedded tissue, such as protein mass spectrometry, are now available and have led to the ability for comparisons to be made between the techniques to fully understand the protein levels that relate to a certain staining intensity for an IHC assay. Here I present a workflow using HALO/HALO AI as a central platform to allow comparison of immunohistochemistry results with tissue region specific laser capture protein mass spectrometry results in clinical trial samples. In this I show how we aligned the two workflows to enable accurate comparison of the outputs of each technique in measuring the pharmacodynamic changes in clinical trial samples.

14:30 – 14:50

Customer Collaborations and the Development of Algorithms Approved for Clinical Use ​

Dr. Peter Caie

Principal Scientist of AI Collaborations, Indica labs

Abstract: Peter will cover how and why Indica Labs collaborate with external industrial, clinical and academic partners. He will give an overview of what these collaborations entail and what kind of advantages they can bring to both parties when developing AI products designed to be taken through regulatory approval for clinical use. He will also give examples of current projects which apply diverse levels of collaborator involvement with external partners.

14:50 – 15:05

Refreshment Break

15:05 – 15:35

Collaborative Working: Development of Pathology-based AI Tools for the Diagnosis and Treatment of Lung Cancer

Dr. David Dorward

Consultant Thoracic Pathologist, Royal Infirmary of Edinburgh, Honorary Senior Clinical Lecturer, University of Edinburgh

Abstract: With the rapid development of new targeted, personalised treatments for lung cancer there are many emerging challenges in the delivery of pathology services to ensure that patients receive both an accurate diagnosis and access to the correct therapies as quickly as possible. Currently within pathology laboratories much of this work is both labour and time intensive but the advent of digital pathology and artificial intelligence provides a number of opportunities to explore alternative ways of addressing some of these issues. This talk will focus on the development of a collaboration between Indica Labs and NHS Lothian to create clinically relevant AI tools to tackle some of the key "pinch points" in delivery of lung cancer pathology services. The aim is to highlight the unique opportunities that are available through clinical / industry collaborations in order to ensure that AI is integrated in a way that is tailored to clinical needs and can be fast-tracked through regulatory approval. In particular, this talk will focus on the development of AI tools to assess tumour percentage within biopsy samples to guide molecular testing and scoring of the predictive biomarker PD-L1.

15:35 – 15:55

Live Demonstration of the HALO Prostate AI and QC Algorithms Deployed in HALO AP

Katie McKinley

Director, Clinical Applications - Americas & Europe, Indica Labs

Abstract: Indica Labs provides ready-to-use AI algorithms to deliver operational efficiency and support diagnostic confidence. Katie will demonstrate our artificial intelligence based QC algorithm deployed in HALO AP. This tool drives the effective and efficient sign-out of cases from the lab to the pathologist by automating slide screening process and alerting staff only when necessary, minimizing the time required by lab staff to quality check each slide. Katie will also demonstrate the recently CE-marked HALO Prostate AI algorithm running within HALO AP. Learn how this deep-learning based screening tool assists pathologists in the identification and grading of prostate cancer in core needle biopsies.

15:55 – 16:00

Closing Remarks

Dr. Kate Lillard Tunstall

Chief Scientific Officer, Indica Labs

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