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Life Sciences Imaging
Mega Webinar

Date: Wednesday, September 27th 

Time: 11:00 AM EDT

Scientific Imaging is dramatically changing today's drug and therapy R&D and clinical landscape. Come learn and participate in this event which will include top partner-vendors and industry talks.
 

  • High-Content Screening (HCS)

  • ​Imaging Mass Spectrometry

  • In Vivo Imaging

  • Single-Cell Imaging

  • 3D Imaging and Organ-on-a-Chip Models

  • Machine Learning and Image Analysis

  • Personalized Medicine

Join us for a knowledge-packed session where experts will share their insights and advancements in life sciences imaging. From microscopy to medical imaging, we'll explore the latest breakthroughs shaping the future of research and diagnostics.
 

There will be something for everyone as we will have a well-rounded set of talks.
 

Thank you to our top sponsor Revvity Signals (formerly PerkinElmer Informatics)!

Premium Sponsor

rev_signals_logo_rgb_black.png

Sponsors & Speakers

Zeiss Logo.png
Qmetrics Tech_Logo.jpeg
eliyahu.ai logo.jpeg

Speakers

Zev Wisotsky, PhD_Headshot.jpeg

Talk Title:

Harnessing Machine Learning in Cell Painting and CRISPR Integration: An Evolving Paradigm in Drug Discovery

Abstract:

The utilization of machine learning in conjunction with cell painting, as proposed by Revvity Signals, is a promising development in identifying new therapeutics and studying mechanisms of action via cellular phenotypic changes. Revvity's end-to-end (reagents, instrument, and informatics) integrated approach enables an improved understanding of in vitro disease models, which can streamline therapeutic evaluations, minimize animal testing, and consolidate data collection through data analysis. The persistent challenge of bias in high-content screening calls for a strategic use of AI and machine learning to reduce these effects. Cell painting is a premier technique in phenotypic screening and with Signals’ approach integrates AI via machine learning to handle the large-scale data generated. This allows for refining our understanding of mechanisms of action and facilitating the discovery of therapeutic pathways from unknown perturbagens. The further incorporation of CRISPR-engineered cell lines, allowing precise genetic modifications, enhances the potential of cell painting in drug discovery, positioning Revvity as a leader in this transformative landscape.

Zev Wisotsky, PhD
Senior Principal Marketing Manager
Revvity Sig
nals 
 11:10 am - 11:40 am ET

Felix Baldauf-Lenschen

Talk Title:

Predictive Imaging Insights

Abstract:

Radiological imaging is by far the richest clinical data modality, but reductionist interpretation guidelines have historically limited what conclusions one could draw in both patient care and research settings. For example, imaging endpoints that rely on simplistic tumor measurements are known to significantly over- and underestimate true treatment effect. Trained on over 200 million images with associated clinical information, our end-to-end AI models can predict patient outcomes accurately and automatically. Tune in to learn how sponsors like AstraZeneca and Bayer harness these models in their phase 1-3 trials to reduce the time, cost, and failure rate in getting their most efficacious drugs to market.

Felix Baldauf-Lenschen
CEO
Altis Labs
 11:40 am - 12:10 pm ET

Schueller.jpg

Talk Title:

Harnessing Machine Learning in Cell Painting and CRISPR Integration: An Evolving Paradigm in Drug Discovery

Abstract:

The utilization of machine learning in conjunction with cell painting, as proposed by Revvity Signals, is a promising development in identifying new therapeutics and studying mechanisms of action via cellular phenotypic changes. Revvity's end-to-end (reagents, instrument, and informatics) integrated approach enables an improved understanding of in vitro disease models, which can streamline therapeutic evaluations, minimize animal testing, and consolidate data collection through data analysis. The persistent challenge of bias in high-content screening calls for a strategic use of AI and machine learning to reduce these effects. Cell painting is a premier technique in phenotypic screening and with Signals’ approach integrates AI via machine learning to handle the large-scale data generated. This allows for refining our understanding of mechanisms of action and facilitating the discovery of therapeutic pathways from unknown perturbagens. The further incorporation of CRISPR-engineered cell lines, allowing precise genetic modifications, enhances the potential of cell painting in drug discovery, positioning Revvity as a leader in this transformative landscape. 

Christian Schueller, PhD
Senior Field Application Scientist
Revvity Sig
nals
 
11:10 am - 11:40 am ET

kevin.jpg

Talk Title:

Advancing Science with AI: Automation in 3D Imaging and Analysis

Abstract:

The FDA Modernization Act 2.0 has introduced new opportunities for alternatives to animal testing, particularly in cell-based microscopy assays like organoids and organ-on-chip models. This field is still evolving, lacking well-established workflows, especially in 3D imaging and analysis. Researchers are experimenting with various assays, with the potential for standardization. To make experiments more efficient, from image capture to analysis, artificial intelligence (AI) plays a crucial role. For example, machine learning enables automatic segmentation of important areas, such as lumens and cell layers in organoids. When combined with standard techniques AI streamlines the analysis of whole organoids. This talk emphasizes the importance of automation, using organoids as an example. It also provides a brief overview of ZEISS tools, illustrating how AI streamlines workflows, from image acquisition to advanced analysis and scaling.

Kevin O'Keefe, PhD
Sr. Software Sales Biotech Pharma
ZEISS Microscopy 

 12:10 pm - 12:40 pm ET

Elliot Greenblatt_Headshot.jpeg

Talk Title:

Revolutionizing Medical Imaging: From Deep Segmentation to Analysis with Generative AI

Abstract:

In a healthcare landscape increasingly shaped by data-driven technologies, this talk delves into the transformative potential of Artificial Intelligence (AI) in medical image analysis. We'll explore cutting-edge techniques that quantify to segment regions in multi-modal medical images.  Furthermore, we'll examine how large language models like GPT-4 can be integrated into medical image analysis. Attendees will gain a holistic understanding of these advanced technologies and their promise to revolutionize diagnostics, patient care, and medical research.

Elliot Greenblatt, PhD
Founder
Eliyahu.ai
 12:40 pm - 1:10 pm ET

Edward Schreyer_Headshot.jpeg

Talk Title:

Applying Radiomics to Develop Personalized Imaging Solutions

Abstract:

Qmetrics Technologies is a boutique medical image analysis CRO that improves data analyses using artificial intelligence (AI) and machine learning (ML). Our founders are driven to discern more data from MRI, CT scans and X-Rays than traditional radiological review allows by using cutting edge technologies. Qmetrics was issued a US patent which covers the use of radiomics and artificial intelligence (AI) to discover a disease or injury specific signal and display that signal on a medical image. Our data mining platform includes proprietary software and a growing catalogue of machine learning-based signatures.

 

Qmetrics patented technology has been used to guide solutions for:

· mTBI Visualization in MRI

· Stratification of Mild Cognitive Impairment (MCI) Patients Regarding Alzheimer’s Disease Risk

· Determining Risk of Recurrence of Breast Cancer Using Mammography

 

Currently, the company is exploring Thermography Image Analysis as an exploratory endpoint for a TKA study. Qmetrics expertise lies in helping clients design unique image analysis solutions to extract data informative to their therapy or product.

Edward Schreyer
CEO & Chairman
Qmetrics Technologies
 1:10 pm - 1:40 pm ET

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