GENOMETRY, INC. is a life-science technology company dedicated to L1000 Expression Profiling, a revolutionary high-throughput low-cost gene-expression profiling method. L1000 produces high-dimensional gene-expression profiles direct from cells, at a rate of thousands a day, and at only a fraction of the cost of conventional methods. This enables the use of expression profiling at a scale never before possible, and makes L1000 the method-of-choice for the creation of datasets for machine learning and artificial intelligence (AI) guided drug discovery. GENOMETRY is the sole and exclusive provider of commercial gene-expression profiling services using L1000, and provides data-generation and involved expert support to the pharmaceutical, biotechnology, personal care, cosmetics, consumer products, specialty chemical, and agrichemical industries from headquarters in Cambridge Massachusetts, USA.
Full-genome expression profiles can be faithfully recreated from the levels of just 5% of the transcripts. Measuring only these special landmark genes makes high-dimensional gene-expression profiling faster and cheaper than ever before.
L1000 Expression Profiling measures 978 validated landmark genes in crude cell lysate in 384-well plate format then calculates the levels of the remaining transcripts using an algorithm trained on tens-of-thousands of historical gene-expression profiles.
Library characterization, primary screening, hit prioritization, lead selection, novelty biasing, MOA elucidation, target deconvolution, safety alerts, indication discovery, and direct and seamless comparison with public L1000 data from the LINCS Program.
L1000 Expression Profiling is a patented whole-genome gene-expression assay based on the direct measurement of a reduced representation of the transcriptome and computational inference of the portion of the transcriptome not explicitly measured. The number of landmark transcripts whose abundance is measured is 978. An additional 80 invariant genes are also explicitly measured to enable scaling and normalization. The input for L1000 is crude lysates of human cells in 384-well plates. The output is tab-delimited text files of log-transformed expression values for 22,000 genes × 380 samples.
While working at the Broad Institute of MIT and Harvard University, GENOMETRY’s founders discovered that by measuring the expression levels of approximately one thousand specially-selected genes and using a computational model trained on more than one hundred thousand microarray experiments to infer the activity of the other genes, it was possible to produce close approximations of gene-expression profiles in which the levels of all twenty thousand transcripts are explicitly measured.
Our team then developed a multiplex ligation-mediated amplification assay to monitor landmark-gene expression and collaborated with Luminex Corporation in the creation of its FLEXMAP 3D® system, an instrument specifically designed to quantitate these analytes quickly and cost-effectively in 384-well plate format. The resulting L1000 Expression Profiling method delivers 80% of the information of a whole-genome assay for about 5% of the cost, with a throughput of tens-of-thousands of samples a week. Data produced using L1000 has the same format and is on the same scale as conventional microarray data.
L1000 has been extensively validated at the individual gene and full profile level, for both technical and operational performance, in hundreds of diseased and normal cell types. The technology has been in continuous operation at GENOMETRY since 2012, and at the Broad Institute since 2010 where it has been used to create a public reference collection of one million gene-expression profiles under the NIH-funded LINCS Program.
GENOMETRY holds worldwide licenses to patents covering L1000 owned by the Broad Institute, the Massachusetts Institute of Technology and the Dana-Farber Cancer Institute, and has rights to additional intellectual property required to practice the assay commercially.
GENOMETRY is the sole and exclusive provider of commercial gene-expression profiling services using L1000 Expression Profiling. We offer fee-for-service data generation and tailored expert support from dedicated facilities in Cambridge MA with solutions for one compound to one million.
GENOMETRY’s typical client is a large pharmaceutical company or research institute using L1000 to characterize novel chemical matter tens- or hundreds-of-thousands of compounds at a time, or to study the effects of a few hundreds or thousands of compounds across large panels of patient-derived or engineered cells. The client will treat cells and prepare crude lysates in their own laboratories. We provide lysis buffer, simple automation-friendly protocols for sample preparation, and advice on experimental design. Lysates are then shipped* to our facility in 384-well plates for processing. Throughput is 24 plates / week / client and turnaround time is 2 weeks. Volume discounts are available for library-scale projects. Contact us here for a quote.
GENOMETRY also has a solution for clients with only a few compounds. In this small-scale format the client provides compound rather than cell lysate, and we treat cells (selected from an expanding panel) using a fixed experimental design. This standardized format allows us to deliver genuine L1000 Expression Profiling data from one compound at 8 concentrations on one cell line for 6 hours with 3 replicates including all vehicle and positive controls for a flat fee of US$5,000. Turnaround time is approximately 4 weeks. Request more information and an order form for GENOMETRY’s OnlyOne option from here.
*Lysates are routinely sent to Genometry’s facilities in the United States from across Europe and throughout Asia.
Lilly and Mount Sinai Screen Drugs in Patient-Derived Cells Using L1000 from Genometry
New York NY, United States and Erl Wood Manor, United Kingdom—24 October 2018—Scientists from Icahn School of Medicine at Mount Sinai and Eli Lilly and Company today reported on a first-of-its-kind gene-expression based small-molecule screen conducted in a panel of patient-derived neural progenitor cells. Using induced pluripotent stem cells from twelve individuals with schizophrenia and twelve matched controls plus eight established cell lines the researchers were able to generate a matrix of nearly four-and-a-half thousand drug-induced gene-expression profiles, and thereby identify agents able to reverse schizophrenia-associated signatures in a cell type- and diagnosis- dependent manner. Kristen Brennand, the senior author of the paper, said in a statement: “There is tremendous value in gene expression-based drug screening using patient-derived cells because it can generate results that are more reflective of disease biology.” Corresponding author Radoslav Savic added, “For diseases in which high-throughput phenotypic screening is challenging, transcriptomic-based screening can be highly informative and help accelerate the drug discovery process.” The study was uniquely enabled by Genometry‘s L1000 high-throughput gene-expression profiling technology. It is published in Nature Communications.
AbbVie Reveals New Strategies for Target Identification Using L1000 from Genometry
North Chicago IL, United States—2 May 2018—Scientists from AbbVie’s Target Enabling Science and Technology Group today published a “Practitioners’ Perspective” on emerging approaches for identifying the protein targets of small molecules. Using real-world examples from both target-based and phenotypic discovery campaigns, the authors illustrate how L1000 gene-expression data from dense concentration ranges can disambiguate multiple admixed activities and distinguish on- and off- target effects of screening hits quickly and cheaply, and thereby provide unprecedented resolution for compound characterization and target deconvolution earlier in the development pipeline than ever before. The authors also disclose refined technology integration strategies. In one case study the combination of L1000 with gene ablation, acquired resistance, and cellular thermal shift analysis is shown to identify, validate, and confirm engagement of a novel oncology target by a hit from a primary phenotypic screen. The paper appears in the Journal of Medicinal Chemistry.
Janssen Improves Hit Rate by 300-fold by Combining L1000 and Machine Learning
Beerse, Belgium—1 April 2018—Scientists from Janssen Pharmaceutica today reported how the combination of L1000 gene-expression profiling with machine learning led to a 300-fold improvement in hit rate over conventional screening approaches for the identification of potent and selective chemical matter against a therapeutically-relevant target. This case study—using L1000 data generated by Genometry from an initial set of 31,000 compounds from the Janssen primary screening collection—identified 22 new and confirmed HSP90-independent NR3C1 inhibitors from multiple chemotypes, and illustrates how high-throughput gene-expression profiling can form the basis of a highly efficient target-agnostic in silico screening system to rival classical HTS. The work is published in Assay and Drug Development Technologies.
Development and Validation of L1000 with Applications in LINCS Published in Cell
Cambridge MA, United States—30 November 2017—Scientists from from the Broad Institute, Harvard Medical School, Dana-Farber Cancer Institute, Massachusetts General Hospital, Harvard University, and Howard Hughes Medical Institute today published a description of the development and validation of L1000 gene-expression profiling technology, and its use to create more than one million reference profiles under the NIH-funded Library of Integrated Network-Based Cellular Signatures (LINCS) Program. The paper appears in Cell and the associated L1000 data are freely publicly available through Gene Expression Omnibus (GEO). Genometry scientists are co-authors of the paper.
GlaxoSmithKline Reports Using L1000 from Genometry for Hit Characterization
San Diego CA, United States—10 October 2017—GlaxoSmithKline (GSK) today reported on their use of L1000 Expression Profiling to the Fourth Annual Drug Discovery USA Congress. In a presentation entitled “From Phenotype to Target Engagement: Increasing Confidence in Mechanism,” GSK’s Director of Protein and Cellular Sciences described how Genometry’s high-throughput gene-expression profiling technology had been combined with BioMAP® primary cell disease models to provide effective and scalable solutions for applications including series differentiation, identification of off-target effects, hit selection and prioritization, and drug repositioning. More than two hundred drug-discovery professionals attended the meeting.
Merck Uses L1000 Data from Genometry to Deorphanize “Dark Chemical Matter”
Boston MA, United States—27 February 2017—A paper published in Drug Discovery Today describes the strategies used by Merck Research Laboratories to understand and exploit so-called Dark Chemical Matter (DCM). DCM is the subset of a small-molecule library that has never shown any activity despite being tested in hundreds of assays. However, rather than simply being inert, these compounds may instead be exquisitely selective for unappreciated bioactivities, and thus highly desirable as novel leads or as tools with which to find new drug targets. Two complementary high-throughput linker-free technologies—Automated Ligand Identification System (ALIS) and L1000 Expression Profiling—have both the performance attributes and the broad and unbiased biological coverage required for efficient deorphanization of DCM, and are Merck’s methods-of-choice for this emerging discovery opportunity.
Merck Applies Innovative “Deep Learning” Methods to L1000 Data from Genometry
West Point PA, United States—9 February 2017—Scientists from Merck Research Laboratories today reported the application of deep learning techniques to the analysis and interpretation of L1000 Expression Profiling data. Using an illustrative set of 3,699 compounds from multiple active discovery campaigns the Merck researchers demonstrate that their new methods reveal chemical structure, protein target and promiscuity information encoded in the data, and outperform existing approaches for assigning functions to unknown compounds. The computational efficiency of the methods reported is of particular significance as gene-expression profiling becomes an increasingly important tool for small-molecule characterization, and the size and scope of the associated datasets get ever larger. The work is published in PLOS Computational Biology.
Expression-Based Drug Screening in 3D Cultures Uniquely Enabled by Genometry
Uppsala, Sweden—27 October 2016—Scientists from the Department of Medical Sciences at Uppsala University today published a paper entitled “Large-Scale Gene Expression Profiling Platform for Identification of Context-Dependent Drug Responses in Multicellular Tumor Spheroids” in the journal Cell Chemical Biology. The study used L1000 Expression Profiling to characterize the effects of small molecules at multiple doses on various types of multicellular spheroids in 384-well plate format, and revealed profound and therapeutically-relevant differences in transcriptional responses as a function of cellular disposition. It also demonstrated that L1000 is a powerful and practical universal assay technology for high-throughput screening in complex cellular systems.
Genometry Generates Data for Harvard Study Published in Nature Chemical Biology
Cambridge MA, United States—14 March 2016—Researchers from Massachusetts General Hospital and Harvard Medical School today published a paper entitled “Light-Controlled Modulation of Gene Expression by Chemical Optoepigenetic Probes” in the journal Nature Chemical Biology. L1000 Expression Profiling was used in the study to characterize the effects of a series of novel photochromic histone-deacetylase inhibitors across a large matrix of conditions, thereby demonstrating a powerful and generalizable new technique for chemical biology named Chemo-Optical Modulation of Epigenetically-regulated Transcription (COMET). Genometry scientists are co-authors of the paper.
Novartis To Use L1000 from Genometry for Large-Scale Gene-Expression Profiling
Cambridge MA, United States—1 March 2016—Genometry announced today that scientists from the Novartis Institutes for Biomedical Research (NIBR) are the winners of the company’s inaugural Leap Day Giveaway. This unique contest—open to Genometry’s current and prospective big-pharma clients—offered a prize of 29 plates (more than 11,000 samples) of L1000 Expression Profiling to explore the utility of the method for important drug-discovery applications not accessible to conventional gene-expression profiling approaches because of low throughput and high unit cost. The NIBR proposal, which contemplates profiling compounds in dense concentration ranges in a large panel of cell lines for pharmacodynamic biomarker discovery, was selected at random from dozens of entries.
Genometry Announces Deal with Janssen for Library-Scale Gene-Expression Profiling
Cambridge MA, United States—8 October 2015—GENOMETRY, INC. today announced entering into a service agreement with JANSSEN PHARMACEUTICA NV of Beerse, Belgium under the terms of which Genometry will generate gene-expression profiles from 250,000 compounds from Janssen’s small-molecule screening library using its proprietary L1000 Expression Profiling technology. This is the first time gene-expression profiling has been applied at this scale, and this multi-year contract showcases a commitment to high-throughput gene-expression profiling for multiple drug discovery and development applications. The data will be used for primary screening and library characterization as well as to improve the selection of candidate drugs prior to clinical studies. “L1000 was developed to make gene-expression profiling experiments of unprecedented scale and scope possible, and Genometry was founded to get this transformative technology into the hands of professional drug developers,” said Justin Lamb, Ph.D., Genometry’s President and CEO. “We are therefore thrilled to see Janssen engage in a true library-scale profiling effort uniquely enabled by Genometry’s capabilities.”