High Content Imaging User Group Meeting 2024 — Watch On Demand
Unlock deeper biological insights with advanced imaging – accelerating early discovery, enhancing predictability, and reducing attrition rates.
Experience India’s First Dedicated HCI User Group Meeting, Now Available Anytime
High Content Imaging (HCI) is transforming modern biological research by merging high‑throughput microscopy with advanced image‑based analytics. From early‑stage drug discovery and phenotypic screening to organoid characterization and multi‑parametric toxicity profiling, HCI is redefining how scientists visualize, quantify, and interpret cellular systems at scale.
For the first time in India, Revvity and Syngene brought together leading researchers, technology experts, and data scientists for a two‑day virtual User Group Meeting focused on real‑world HCI workflows, AI‑powered analysis, and emerging multi‑omics integration. Now, you can access the entire experience on demand.
Who You’ll Meet
Chandan Mithra
Senior Product Specialist, Revvity
Dr. Bappaditya Dey
Scientist-F, NIAB Hyderabad
Dr. Lakshmi Balasubramanian
Application Scientist, C-CAMP
Dr. Donald Apanovitch
Senior Research Director, Syngene International Limited
Dr. G. Kumaresan
Professor and Head, Dept. of Genetics, School of Biological Sciences, Madurai Kamaraj University
Dr. Koelina Ganguly
Senior Scientist, Syngene International Limited
Dr. Deepak Modi
Scientist G and Head Molecular and Cellular Biology Laboratory, ICMR- NIRRCH
Dr. Mamta Jain Goyal
Assistant Director, Translational and Clinical Research, Syngene International Limited
Dr. Ravikumar Nutakk
Assistant Director, Biology, Syngene International Limited
Session | Talk Details | Speaker | Designation | Organization |
Session 1 | Phenologic.AI: Unlocking Brightfield Imaging with Artificial Intelligence | Chandan Mithra | Senior Product Specialist | Revvity |
Session 2 | Fast, Accurate, and Insightful: Using High Content Screening to Unravel Mycobacterial Growth Kinetics | Dr. Bappaditya Dey | Scientist-F | NIAB Hyderabad |
Session 3 | From Pixels to Phenotypes: Computational workflow strategies for High-Content Image Data Analytics | Dr. Lakshmi Balasubramanian | Application Scientist | C-CAMP |
Session 4 | Neurodegenerative Disease Drug Development: Applications Using Phenotypic High Content Imaging Morphological Profiling Assay Strategies | Dr. Donald Apanovitch | Senior Research Director | Syngene International Limited |
Session | Talk Details | Speaker | Designation | Organization |
Session 1 | High-Content Imaging & Integrative Genomics in Drug Screening for Targeted Cancer Therapeutics: From Phenotype to Pathways | Dr. G. Kumaresan | Professor and Head, Dept. of Genetics, School of Biological Sciences | Madurai Kamaraj University |
Session 2 | Tracking GPCR Internalization Using High-Content Imaging Platform | Dr. Koelina Ganguly | Senior Scientist | Syngene International Limited |
Session 3 | When Cells Tell Stories: High-Content Screening in Women’s Health | Dr. Deepak Modi | Scientist G and Head Molecular and Cellular Biology Laboratory | ICMR- NIRRCH |
Session 4 | Overview of High Content Applications using 3D Organoids for Drug Discovery and Development | Dr. Donald Apanovitch, Dr. Mamta Jain Goyal, Dr. Ravikumar Nutakki |
| Syngene International Limited |
Spotlight on Publications
Stay updated with some of the most impactful publications in High Content Imaging
- Cell Painting for cytotoxicity and mode-of-action analysis in primary human hepatocytes
Ewald JD et al., bioRxiv, 2025 - Cell morphological representations of genes enhance prediction of drug targets
Iyer NS et al., bioRxiv, 2024 - A Decade in a Systematic Review: The Evolution and Impact of Cell Painting
Seal S et al., bioRxiv, 2024 - Predicting cell health phenotypes using image-based morphology profiling
Way GP et al., Molecular Biology of the Cell, 2021
- High-throughput deconvolution of 3D organoid dynamics at cellular resolution for cancer pharmacology with Cellos
Mukashyaka P et al., Nature Communications, 2023
- Data-analysis strategies for image-based cell profiling
Caicedo JC et al., Nature Methods, 2017 - Capturing single-cell heterogeneity via data fusion improves image-based profiling
Rohban MH et al., Nature Communications, 2019 - Weakly Supervised Learning of Single-Cell Feature Embeddings
Caicedo JC et al., CVPR Conference, 2018
- Open-source deep-learning software for bioimage segmentation
Lucas AM et al., Molecular Biology of the Cell, 2021 - Opportunities and obstacles for deep learning in biology and medicine
Ching T et al., Journal of the Royal Society Interface, 2018 - Evaluation of Deep Learning Strategies for Nucleus Segmentation in Fluorescence Images
Caicedo JC et al., Cytometry, 2019 - Learning representations for image-based profiling of perturbations
Moshkov N et al., Nature Communications, 2024 - From pixels to phenotypes: Integrating image-based profiling with cell health data as BioMorph features improves interpretability
Seal S et al., Molecular Biology of the Cell, 2024 - Bringing computation to biology by bridging the last mile
Carpenter AE & Singh S, Nature Cell Biology, 2024
Blogs & Case Studies
Unlock Deeper Insights with High Content Imaging at SynVent
At SynVent, our integrated drug discovery platform, High Content Imaging plays a pivotal role in accelerating target validation and phenotypic screening. By combining advanced imaging technologies with AI-driven analytics, we deliver richer biological insights that drive smarter decision-making across the discovery pipeline.
Want to explore how SynVent can transform your discovery strategy?
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