ELEM Puts US$1M Behind Open Virtual Cell Data: Name the Cells, Genes and Perturbations Before Counting Samples
Synopsis
ELEM Biotech plans to invest US$1 million in generating and openly sharing perturbation data for training and validating virtual cell models, and is asking researchers worldwide which experiments should be measured first. Submissions must name concrete cell, gene and perturbation combinations along with sampling times, readouts, controls and independent biological replicates, building on the already open-source ELEM-1200RS and the upcoming ELEM-600PR. Its automated platform can prepare up to 100,000 arrayed genetically perturbed cell samples per month, but that is sample production capacity, not 100,000 distinct genes measured monthly.
Interpretation
The composition of the next public perturbation dataset is no longer decided only by what the data producer can make: ELEM Biotech is handing experimental priorities for its next open dataset to researchers worldwide. Previously the makeup of public datasets was set by the producer, whereas this call asks for a ranked list of concrete cell, gene and perturbation combinations rather than a broad wish list. The call builds on the already released open-source bulk RNA-seq dataset ELEM-1200RS and the upcoming open-source ELEM-600PR, which contains more than 1,200 bulk RNA-seq and 600 proteomics samples across multiple human cell backgrounds.
Submissions must specify perturbation type, sampling times, readouts, controls and independent biological replicates so that results are interpretable and models can be tested against them. The call explicitly separates essential experiments from optional ones and asks how the data would support a real biological or modeling task. ELEM's automated platform can prepare up to 100,000 arrayed genetically perturbed cell samples per month, supports combined genetic and drug perturbations and multi-time-point sampling, and its samples are compatible with single-cell RNA sequencing, bulk RNA sequencing, quantitative proteomics and cell imaging.
The data are intended to be free and non-exclusive worldwide under CC BY 4.0, including commercial use, with no application gate and no preferential access for contributors. A first public release is proposed within six months of program launch and all completed, shareable data within twelve months, with failed and excluded experiments documented as well. Data temporarily withheld for blinded model evaluation will have an advance-announced release date and become public by the same final deadline, while funding approval, scope, exact release dates and license terms will be confirmed publicly before experiments begin.
Perspective
The item is aimed at researchers working on perturbation data production, virtual cell modeling and open data governance, and it describes a US$1 million data-generation plan and a call for experimental designs rather than generated data or model results; submissions are due December 25, 2026, at 23:59 UTC.
Funding approval, program scope, exact release dates and license terms will all be confirmed publicly before experiments begin, so the amount, timeline and CC BY 4.0 terms remain proposed arrangements; the up-to-100,000 samples per month figure is cell-sample production capacity, and final coverage depends on the chosen cells, perturbation feasibility, controls, replication, quality requirements and measurement costs.