Parse Bio GigaLab and Vevo Therapeutics Tahoe-100 experiment
100 million cells assayed over 60,000 conditions and 1,200 drug treatments across 50 different tumor models
Parse Bio, one of the single-cell omics companies out there competing for 10X Genomics big piece of the pie, has published a press release on their collaboration with Vevo Therapeutics to advance the AI-based drug discovery efforts using Parse’s GigaLab technology.
Parse Biosciences, founded in 2018 by Alex Rosenberg and Charles Roco, is a biotechnology company specializing in scalable single-cell sequencing solutions. As of December 6, 2024, the company has raised over $100 million in funding, including a $50 million Series C round in December 2023.
To compete with 10x Genomics' Chromium line, Parse Biosciences offers the Evercode™ Whole Transcriptome (WT) v3 platform. This technology enables high-throughput single-cell RNA sequencing without the need for custom instrumentation, allowing researchers to profile up to 1,000,000 cells across multiple samples simultaneously. Parse Bio has shown comparative analyses demonstrating that Evercode WT v3 provides increased gene detection and higher sensitivity compared to 10x Genomics' Chromium Nex-GEM Single Cell 3’ Kit v3.1. At the same time, 10X Genomics has recently released an updated version of their Chromium technology, labelled GEM-X, which increases gene detection rates and offers higher sensitivity compared to their Next-GEM equivalent.
By providing a flexible and scalable alternative, Parse Biosciences aims to democratize single-cell sequencing, making it more accessible to a broader range of researchers and applications. One of these applications is in the area of drug discovery, and the partnership announcement with Vevo Therapeutics wants to exemplify this to other potential Parse clients.
The announcement is to describe the completion of this new dataset, named Tahoe-100, comprising 100 million cells and 60,000 conditions with 1,200 drug treatments across 50 different tumor models. This was performed using Parse’s GigaLab, which seems to be Parse’s way of running Evercode WT Mega (up to 1,000,000 cells) with the aid of automation, so that the pipetting across the Evercode plates doesn’t need to be done manually by a lab scientist alone. In addition to the AI drug discovery dataset generated with Vevo, the Parse GigaLab is currently working on large-scale projects for a variety of applications including additional perturbation screens, data for generative AI models, and atlasing for population studies.
Vevo Therapeutics is an example of a small group of new start-ups appearing in the new era of Cell Atlases, such as the Human Cell Atlas Project project. The common premise is that one would pool cells from 10s to 100s of diverse patients or conditions and assay them via single-cell RNA profiling. Before getting the readout from scRNAseq, one can also “perturb” the cells with some sort of treatment, which can be drugs or CRISPR guide RNAs that knocks out or activates certain genes. Given this experimental setup, one can determine drug action across patients or conditions.
An important aspect of these type of high-throughput screening assays is to remain true to the conditions of the disease. For example, creating cell lines in vitro and assaying them changes the conditions “in vivo”. Thus, there has been a lot of work done in attempting to stay close to “in vivo” conditions, or recreate them in a way that is still relevant as a model for disease.
High-throughput scRNASeq
Several companies, including Fluent BioSciences, Scale Biosciences, and CS Genetics, are developing and commercialize instrument-free single-cell RNA sequencing (scRNA-seq) technologies to analyze (very) large numbers of cells simultaneously. These advancements aim to provide scalable and cost-effective alternatives to existing platforms like 10x Genomics' Chromium.
Fluent BioSciences offers the PIPseq™ V T100 3’ Single Cell RNA Kit, which enables the capture of up to 100,000 cells per sample without requiring microfluidics or expensive instrumentation. This flexibility allows researchers to scale their experiments according to specific needs, facilitating high-throughput single-cell analysis. Fluent Bio was recently acquired by Illumina ILMN 0.00%↑ , and the rumours point to future developments of the NextSeq/NovaSeq instruments to streamline the process of performing PIPseq assays that then go to SBS short-read sequencing into the Illumina NGS instrument.
Scale Biosciences provides a Single Cell RNA Sequencing Kit that utilizes combinatorial indexing technology, allowing for the processing of up to 500,000 cells in a single experiment. This approach enhances scalability and reduces costs, making it suitable for large-scale studies requiring extensive cell profiling. Their newly announced ScalePlex 2M method is aiming at assaying up to 2,000,000 cells per experiment.
CS Genetics is also active in the single-cell genomics field, focusing on developing innovative solutions for scRNAseq applications. Their technology has recently started shipping, the company's efforts are directed toward providing scalable single-cell analysis tools for many samples, but aiming at the 4,000-5,000 cell range per sample.
In contrast, 10x Genomics' Chromium platform is designed for high-throughput single-cell analysis through the Chromium instrument. Each experiment typically processes ten or twenty thousand of cells per sample, with between 8 and 16 samples per run. The platform employs microfluidics to partition individual cells, which can be more complex and costly compared to the combinatorial indexing methods used by some emerging competitors.
10x Genomics has long been a dominant player in the single-cell RNA sequencing (scRNA-seq) market, but the emergence of high-throughput competitors like Parse Biosciences with their Evercode WT Mega and Scale Biosciences with their 500,000-2,000,000 cell experiments posed a clear challenge. Recognizing this competitive threat, 10x Genomics recently introduced their GEM-X Flex technology, which is designed to meet the demands of the high-throughput market.
The GEM-X Flex represents 10x Genomics’ first system capable of processing up to 2.56 million cells in a single experiment, directly competing with Parse Bio and Scale Bio’s offerings. For the first time, 10x Genomics has achieved a cost of less than 1 cent per cell, a significant reduction compared to previous technologies. This makes high-throughput single-cell experiments more affordable and accessible for large-scale projects. By scaling up the number of cells per experiment while driving down costs, GEM-X Flex positions 10x Genomics to retain its dominance in the scRNA-seq market. This move directly addresses the strengths of Parse Biosciences and Scale Biosciences, whose technologies were designed for cost-effective, ultra-high-throughput studies.
