OmicsChart

23,884 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐂𝐚𝐬𝐞𝐬 - Real-world data with at least one omics modality directly from clinical patient cases. Standardised, integrated and harmonised for use. 4 𝐎𝐦𝐢𝐜𝐬 𝐃𝐚𝐭𝐚 𝐓𝐲𝐩𝐞𝐬 - RNA-seq, genomics, MS proteomics, and sc-RNAseq, capturing comprehensive molecular insights from actual patient tumours. 26 𝐏𝐫𝐨𝐯𝐢𝐝𝐞𝐫𝐬, 37 𝐏𝐫𝐢𝐦𝐚𝐫𝐲 𝐒𝐢𝐭𝐞𝐬, 𝐚𝐧𝐝 65 𝐒𝐭𝐮𝐝𝐢𝐞𝐬 - Broad data network providing unique perspectives on patient biology. We are experts in supporting drug development with data scouting, bespoke solutions, and tailored insights. Our team collaborates with you to identify and interpret the precise data needed to drive impactful oncology research. For partnership inquiries, contact info@omicschart.com for enquiries. #OncologyData #CancerResearch #BiomarkerDiscovery #DrugDevelopment #OmicsData #OmicsChart

𝗧𝗵𝗲 𝗵𝗶𝗴𝗵𝗲𝘀𝘁 𝗽𝗼𝗶𝗻𝘁 𝗼𝗳 𝗳𝗮𝗶𝗹𝘂𝗿𝗲 𝗼𝗳 #𝗼𝗻𝗰𝗼𝗹𝗼𝗴𝘆 (𝗮𝗻𝗱 𝗼𝘁𝗵𝗲𝗿) 𝗱𝗿𝘂𝗴𝘀 𝗶𝗻 𝗰𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗱𝗲𝘃𝗲𝗹𝗼𝗽𝗺𝗲𝗻𝘁 𝗶𝘀 𝗳𝗿𝗼𝗺 𝗣𝗵𝗮𝘀𝗲 𝗜𝗜 𝘁𝗼 𝗣𝗵𝗮𝘀𝗲 𝗜𝗜𝗜! We got really good at identifying molecules that seem to work wonders in cell lines and mice, that are also safe (hence, are able to move from Phase I to Phase II), but ultimately fail to actually do anything in patients. That's why it's so important to look for as much evidence as possible from patient-derived data, to understand how the drug might interact not only with tumor cells, but with the whole tumor microenvironment and even the body. We 𝘩𝘦𝘭𝘱 𝘱𝘩𝘢𝘳𝘮𝘢 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘵𝘰 𝘪𝘯𝘵𝘦𝘨𝘳𝘢𝘵𝘦 𝘣𝘪𝘰𝘮𝘢𝘳𝘬𝘦𝘳 𝘢𝘯𝘥 𝘰𝘮𝘪𝘤𝘴 𝘥𝘢𝘵𝘢 𝘪𝘯𝘵𝘰 𝘵𝘩𝘦𝘪𝘳 𝘤𝘭𝘪𝘯𝘪𝘤𝘢𝘭 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘺. #clinicaltrials #rwe #realworldevidence #drugdevelopment #biomarkers #omics Prepared by Tanya Aneichyk

𝗘𝘃𝗲𝗿𝘆𝗼𝗻𝗲 𝗹𝗼𝘃𝗲𝘀 #𝘀𝗰𝗥𝗡𝗔𝘀𝗲𝗾 𝗨𝗠𝗔𝗣 𝘄𝗶𝘁𝗵 𝗰𝗹𝘂𝘀𝘁𝗲𝗿𝘀 𝗮𝗻𝗱 𝗰𝗼𝗹𝗼𝗿𝘀! The idea of pulling many samples to increase the detection power is appealing, but 𝗶𝘁 𝗼𝗯𝗳𝘂𝘀𝗰𝗮𝘁𝗲𝘀 𝗰𝗲𝗹𝗹𝘀' 𝗼𝗿𝗶𝗴𝗶𝗻 𝗮𝗻𝗱 𝗹𝗲𝗮𝗱𝘀 𝘁𝗼 𝗱𝗮𝗻𝗴𝗲𝗿𝗼𝘂𝘀 𝗺𝗶𝘀𝗶𝗻𝘁𝗲𝗿𝗽𝗿𝗲𝘁𝗮𝘁𝗶𝗼𝗻𝘀!👇 It often happens that all the cells of interest come from just a handful of samples (and at times even just one single sample), therefore capturing an effect in a single individual. So when you are interpreting the results of a scRNASeq experiment, make sure you understand very well sample composition in your cells, and you exclude any confounding effects from mere under-/over-representation. 𝘞𝘦 𝘴𝘱𝘦𝘤𝘪𝘢𝘭𝘪𝘻𝘦 𝘪𝘯 𝘰𝘮𝘪𝘤𝘴 𝘢𝘯𝘥 𝘣𝘪𝘰𝘮𝘢𝘳𝘬𝘦𝘳 𝘥𝘢𝘵𝘢 𝘢𝘯𝘢𝘭𝘺𝘵𝘪𝘤𝘴 𝘧𝘰𝘳 𝘰𝘯𝘤𝘰𝘭𝘰𝘨𝘺 𝘥𝘳𝘶𝘨 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵. 𝘋𝘔 𝘶𝘴 𝘪𝘧 𝘺𝘰𝘶 𝘯𝘦𝘦𝘥 𝘩𝘦𝘭𝘱! Posted by Tanya Aneichyk #cancerresearch #singlecell #rnaseq #biomarkers #oncology #bioinformatics

Delivering actionable insights should be a number 1 priority in data analytics. We thrive to hear from our users and clients: "Now I know what the data is telling me and what I need to do next!"

🧪 𝗦𝗮𝗺𝗽𝗹𝗲𝘀 𝗺𝗶𝘅-𝘂𝗽𝘀 𝗼𝗿 𝘁𝗲𝗰𝗵𝗻𝗶𝗰𝗮𝗹 𝗮𝗿𝘁𝗶𝗳𝗮𝗰𝘁𝘀 𝗵𝗮𝗽𝗽𝗲𝗻 𝗮𝗹𝗹 𝘁𝗵𝗲 𝘁𝗶𝗺𝗲! And if you are leading translational and clinical #drugdevelopment, dedicate time to rigorously track samples and associated data. The very first step I suggest to companies working with highly valuable samples is to 𝗱𝗲𝘃𝗲𝗹𝗼𝗽 𝗮𝗻 𝗶𝗻𝘁𝗲𝗿𝗻𝗮𝗹 𝗻𝗮𝗺𝗶𝗻𝗴 𝗰𝗼𝗻𝘃𝗲𝗻𝘁𝗶𝗼𝗻 𝘁𝗵𝗮𝘁 𝗰𝗼𝗻𝘁𝗮𝗶𝗻𝘀 𝘀𝗮𝗺𝗽𝗹𝗲 𝗺𝗲𝘁𝗮𝗱𝗮𝘁𝗮. This simple step would allow you to track samples and associated outputs across many service providers and CROs, easily establish which samples got lost or failed QC, and establish which outputs correspond to which sample (for example, which WGS raw file belongs to which program). #oncology #omics #bioinformatics #translationalresearch #cancerresearch

Hey, Tanya here! 🧫 #CancerCellLines, one of the 1st in vitro models in preclinical #Oncology #DrugDevelopment, are often a karyotypic mess. 𝗧𝗵𝗲𝗿𝗲'𝘀 𝗮 𝗵𝗶𝗴𝗵 𝗰𝗵𝗮𝗻𝗰𝗲 𝘁𝗵𝗮𝘁 𝘆𝗼𝘂𝗿 𝗰𝗲𝗹𝗹 𝗹𝗶𝗻𝗲𝘀 𝗵𝗮𝘃𝗲 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟮 𝗰𝗼𝗽𝗶𝗲𝘀 𝗼𝗳 𝘆𝗼𝘂𝗿 𝘁𝗮𝗿𝗴𝗲𝘁 𝗴𝗲𝗻𝗲! The Cancer Cell Line Encyclopedia (CCLE) provides genomic data for over 1,400 cancer cell lines, along with computationally derived copy numbers for each gene in the genome. 𝗔𝗻𝗱 𝘁𝗵𝗲 𝗺𝗮𝗷𝗼𝗿𝗶𝘁𝘆 𝗼𝗳 𝗰𝗮𝗻𝗰𝗲𝗿 𝗰𝗲𝗹𝗹 𝗹𝗶𝗻𝗲𝘀 𝘀𝗵𝗼𝘄 𝗮𝗺𝗽𝗹𝗶𝗳𝗶𝗰𝗮𝘁𝗶𝗼𝗻 𝗶𝗻 𝗺𝗼𝗿𝗲 𝘁𝗵𝗮𝗻 𝟱𝟬% 𝗼𝗳 𝘁𝗵𝗲𝗶𝗿 𝗴𝗲𝗻𝗲𝘀! That makes the translation of the cell lines results to patients all the harder. 𝘈𝘵 𝘖𝘮𝘪𝘤𝘴𝘊𝘩𝘢𝘳𝘵 𝘸𝘦 𝘩𝘦𝘭𝘱 𝘰𝘯𝘤𝘰𝘭𝘰𝘨𝘺 𝘥𝘳𝘶𝘨 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 𝘤𝘰𝘮𝘱𝘢𝘯𝘪𝘦𝘴 𝘵𝘰 𝘪𝘯𝘵𝘦𝘨𝘳𝘢𝘵𝘦 𝘰𝘮𝘪𝘤𝘴 𝘥𝘢𝘵𝘢 𝘪𝘯𝘵𝘰 𝘤𝘭𝘪𝘯𝘪𝘤𝘢𝘭 𝘴𝘵𝘳𝘢𝘵𝘦𝘨𝘺 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵. 𝘋𝘰𝘯'𝘵 𝘮𝘪𝘴𝘴 𝘪𝘮𝘱𝘰𝘳𝘵𝘢𝘯𝘵 𝘤𝘰𝘯𝘴𝘪𝘥𝘦𝘳𝘢𝘵𝘪𝘰𝘯𝘴 𝘪𝘯 𝘱𝘳𝘦𝘤𝘭𝘪𝘯𝘪𝘤𝘢𝘭 𝘳𝘦𝘴𝘶𝘭𝘵𝘴 𝘸𝘩𝘦𝘯 𝘱𝘭𝘢𝘯𝘯𝘪𝘯𝘨 𝘧𝘰𝘳 𝘵𝘳𝘪𝘢𝘭𝘴! Message me or drop me an email at tanya@omicschart.com.

OmicsChart is not just a company, it's us. It's me, Tanya, and my co-founder Asta, and our network of experts that I have build during my years with Independent Data Lab. In the last year we have helped over a dozen of #oncology drug development companies to make decisions based on omics data, and we have build a platform with over 20,000 cancer patient omics records from 26 providers and 65 studies. And we make this data available to our clients! As a domain expert, I discuss with clients the best strategy for making the data useful for decision making, whether it's in-house generated, or from public studies, and then my team and I get to coding and data science! #oncology #drugdevelopment #bioinformatics #omics

Thank you for warm welcome at Festival of Biologics in Basel this week, and opportunity to showcase OmicsChart's innovation in omics data for #oncology translational research. Great to meet my former colleague Christine Rothe, who is now leading the development at iOmx Therapeutics AG and presented at FoB the amazing progress of IOMX-0675! Looks like my mini-reunions with Pieris days continue :) looking forward to continue discussions with OmicsChart's new friends as well! Now we are back to building! Building clients and investors relationships, building the team, and building PREON!

OmicsChart will be exhibiting at Biotech X Europe in Basel next week! This is a great opportunity to connect with industry leaders, explore innovations in biotechnology, and showcase how our cutting-edge data solutions are driving advancements in the oncology. 🔬 If you're attending, don't miss the chance to meet our team! Please reach out to our founders for a chat – we would love to discuss how OmicsChart can accelerate your drug development efforts. Looking forward to seeing you there! 🙌 #BiotechX #OmicsChart #BiotechInnovation #Basel #Networking #Omics #DataAnalytics #Biotechnology #LifeSciences

🧬 𝙊𝙢𝙞𝙘𝙨 𝙀𝙭𝙥𝙚𝙧𝙞𝙢𝙚𝙣𝙩𝙨 & 𝘼𝙣𝙖𝙡𝙮𝙨𝙞𝙨 🧬 𝙞𝙣 💊𝘾𝙖𝙣𝙘𝙚𝙧 𝘿𝙧𝙪𝙜 𝘿𝙚𝙫𝙚𝙡𝙤𝙥𝙢𝙚𝙣𝙩 💊 - 𝙬𝙝𝙖𝙩 𝙮𝙤𝙪 𝙣𝙚𝙚𝙙 𝙩𝙤 𝙠𝙣𝙤𝙬 𝙖𝙗𝙤𝙪𝙩 ... 🩺 𝙌𝙪𝙖𝙡𝙞𝙩𝙮 𝙤𝙛 𝙎𝙖𝙢𝙥𝙡𝙚𝙨 𝙖𝙣𝙙 𝘿𝙖𝙩𝙖 🩺 : Two most important factors that must be considered in the analysis of omics data from cancer patients: 𝗧𝘂𝗺𝗼𝗿 𝗰𝗼𝗻𝘁𝗲𝗻𝘁 𝗼𝗳 𝗮 𝗯𝗶𝗼𝗽𝘀𝘆. Genomics and transcriptomics generate a readout based on all the molecules present in the sample: from tumor or infiltrating immune cells or surrounding stromal or tumor-adjacent healthy tissue. Make sure this information is included in the analysis and is presented alongside the results to exclude variability associated with variable tumor content 𝗣𝗿𝗲𝘀𝗲𝗿𝘃𝗮𝘁𝗶𝗼𝗻 𝗼𝗳 𝘁𝗵𝗲 𝘀𝗮𝗺𝗽𝗹𝗲. Some of the omics technologies can only be applied to fresh-frozen samples, but fresh-frozen samples are challenging to collect and divide for multiple omics technologies, especially when multiple people are involved in sample collection, preservation and transport. Preservation quality can be a confounding factor, and shall be included in the analysis. 𝘕𝘦𝘹𝘵 𝘸𝘦𝘦𝘬: 𝘖𝘮𝘪𝘤𝘴 𝘦𝘹𝘱𝘦𝘳𝘪𝘮𝘦𝘯𝘵𝘴 & 𝘢𝘯𝘢𝘭𝘺𝘴𝘪𝘴 𝘪𝘯 𝘥𝘳𝘶𝘨 𝘥𝘦𝘷𝘦𝘭𝘰𝘱𝘮𝘦𝘯𝘵 - 𝘸𝘩𝘢𝘵 𝘺𝘰𝘶 𝘯𝘦𝘦𝘥 𝘵𝘰 𝘬𝘯𝘰𝘸 𝘢𝘣𝘰𝘶𝘵 ✅ 𝘊𝘰𝘮𝘱𝘶𝘵𝘢𝘵𝘪𝘰𝘯𝘢𝘭 𝘳𝘦𝘲𝘶𝘪𝘳𝘦𝘮𝘦𝘯𝘵𝘴 ✅ #omics #biomarkers #drugdevelopment #transcriptomics #genomics #cancer #proteomics #GCP