Ginkgo Datapoints

Don’t miss us at #PEGSBoston! We’ll be sharing how our datasets are powering AI/ML pipelines in antibody development. (Stay tuned for new data sets coming soon…) Presentation: ▪️ A High-Throughput Antibody Developability Data Generation Platform for AI/ML Model Training and Drug Discovery - May 14, 2025 at 3:30 PM Posters: ▪️ Predicting and generating developable antibodies with Protein Language Models  ▪️ A High-Throughput Antibody Developability Data Generation Platform for AI/ML Model Training and Drug Discovery Let us know if you’ll be there — better yet, grab time to meet with us! https://lnkd.in/eWFhTRYm #AntibodyDevelopability #AIforBiologics

Most CROs support drug discovery. We built one specifically for AI. At Ginkgo Datapoints, we generate antibody characterization datasets that are: ➡️ Large-scale ➡️ High quality  ➡️ Machine learning–ready Let’s talk at #PEGSBoston about how we can support your discovery efforts. #CRO #BiotechInnovation #AIModels #PEGS2025 http://bit.ly/3YI3w6c

“Data is our currency” - want to learn more about our work at Ginkgo Datapoints? Listen in to a conversation between our General Manager, John Androsavich and Jonah Comstock from pharmaphorum. How are data and AI reshaping pharma and accelerating scientific discovery? Why is data - not models or architecture - the biggest bottleneck in pharma AI? Tune in and share your thoughts in the comments section below. https://lnkd.in/enMYbUYT

A cellular masterpiece! 🎨 Can you guess the cell type? Take a closer look at this Cell Painting image. By using fluorescent dyes to illuminate key cellular structures, cell painting offers a window into complex cell morphology. Capturing thousands of features, Cell Painting helps decipher drug effects on cell morphologies.  Now, imagine this power scaled up. Our upcoming GDPx3 dataset does exactly that! It features dose-response profiles for small molecules across multiple cell types and 2 timepoints – including challenging primary cells.   Ginkgo Datapoints' high-throughput automation and cell engineering expertise make this possible, delivering AI-ready data to accelerate your drug discovery.  Get ready to unlock novel insights with GDPx3! Share your cell type guess below! 👇and be on the lookout for GDPx3 in the coming weeks! Learn more: https://lnkd.in/eBf5r2V9

We agree! Download our datasets here and get in touch: Functional Genomics: https://lnkd.in/ezBivx_G Antibody Developability: https://lnkd.in/egUR_Xu7

How to make the most of our datasets? We published our GDPx2 transcriptomic dataset, capturing dose-dependent drug responses for 85 compounds across four human primary cell types: - Human melanocyte cells - Aortic smooth muscle cells - Dermal fibroblast - Skeletal muscle myoblasts From seasoned computational biologists in the industry to excited researchers who want to play around with the data, many of you have downloaded our GDPx2 transcriptomic dataset. Here’s how to make the most of the dataset: 1. Download the dataset for free 2. Follow our DRUG-seq data analysis pipeline steps to convert fastq files to UMI counts here: https://hubs.ly/Q03gj1Dj0 3. Reach out to our team and discuss any questions GDPx3 is already in the making. What type of datasets would you like to see us put out in the future?

We are working with the Plex Research team to combine AI-driven reasoning and analysis with large scale data generation. Download our GDPx2 transcriptomic dataset now and be on the lookout for more datasets (including imaging data) coming up soon! https://lnkd.in/e_5MJDAF

Here’s why we love DRUG-seq: It is one of our core assays to generate transcriptomic data at scale. Drug-seq technology offers unprecedented efficiency in gene expression analysis — measuring 10,000+ genes per sample at less than 1/10th the cost of traditional bulk RNA-seq with 10x more measurements than L1000. The bottleneck? Scaling the upstream perturbations to match sequencing capabilities. That's why, despite being available for years, public DRUG-seq data remains scarce, and limited to cancer cell lines. We are changing this. At Ginkgo Datapoints, we combine DRUG-seq with automated high-throughput perturbations in biologically relevant models, including iPSC-derived and primary cells. Our recently released GDPx2 dataset captures dose-dependent drug responses across four human primary cell types - a perfect starting point for ML model training and novel insights: https://lnkd.in/ezBivx_G

At Ginkgo Datapoints, we generate vast datasets to unlock insights in functional genomics—managing thousands of small molecule compounds per campaign. That’s why we’re excited to partner with Tangible Scientific, experts in sample management, to ensure speed and quality in our workflows. With Tangible Scientific's Massachusetts-based facilities, we benefit from rapid turnaround times and impeccable sample integrity, helping us push the boundaries of discovery even faster. 🔬 Learn more about Ginkgo Datapoints: https://lnkd.in/exSXDF5F 📦 Explore Tangible Scientific’s services: https://lnkd.in/e4rRUN8r