Case Studies

Case Study: Developing an MVP for Autoimmune Disease Research Using AI & Imaging Data

We developed a Minimum Viable Product (MVP) for a biotech platform company focused on autoimmune disease therapeutics. Their approach combines high-throughput biological imaging and data analysis to uncover novel therapeutic targets within the immune system. This MVP, leveraging advanced AI and multiplex immunofluorescence technology and Amazon Web Services (AWS), was designed to enhance the client’s […]

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Case Study: Enhancing Genomic Data Compression & Analysis for Cancer Research

Client Background A cancer therapeutics company approached us with the need to manage vast amounts of genomic data generated from their research, which was proving to be costly and time-consuming to store and analyze. Our goal was to enhance data compression ratios, accelerate analytical workflows, and ensure robust data security, thereby enabling more efficient research

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Case Study: Machine Learning Integration for Proteomic Data Analysis in Liver Fibrosis Research

In this case study, we explore our partnership with a biotech firm dedicated to advancing liver fibrosis research. We developed a comprehensive AWS infrastructure that efficiently manages and analyzes high-throughput proteomics data from mass spectrometry. By incorporating machine learning (ML) and artificial intelligence (AI), our solution aimed to identify biomarkers and therapeutic targets, driving significant

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Case Study: AI-Driven Drug Repurposing for Enhanced Therapeutic Discovery

This case study dives into our collaborative journey with a life sciences company fueled by a quest for drug repurposing. Armed with a diverse arsenal of data streams including transcriptomics, drug-response profiles, clinical records, literature insights, and drug interaction databases, we embarked on a transformative mission. This narrative unfolds how the synthesis of advanced analytics

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Case Study: Empowering Precision Medicine through Multiplexed PCR-based Diagnostics

This case study outlines our collaboration with a diagnostics instrumentation company on a mission to redefine patient care through precision medicine. The endeavor was fueled by the creation of a multiplexed PCR-based diagnostic system, a powerful tool designed to identify specific mutations in genes linked to drug response. Here, we dive into the pragmatic approach

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Case Study: Leveraging Microbiome Interactions for Enhanced Crop Nutrient Uptake

This case study illuminates our collaboration with an agriculture tech company poised to harness the intricate dance of microbiome interactions to enhance nutrient uptake in crops. With shotgun microbiome sequence data, metabolomic sequence data, and plant health metrics as our compass, we attempted to decode the synergy between soil microbes, metabolites, and plant vitality. In

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Case Study: AWS Setup and Streamlined Genomic and Proteomic Data Analysis for Neurological Disease Research

This case study provides insight into our partnership with a biotech company dedicated to untangling the complexities of neurological diseases. Central to our collaboration was the establishment of a secure AWS infrastructure, integration of genomics and proteomics data from diverse sources, and the subsequent pursuit of pathway analysis. Through a pragmatic approach, we delve into

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Case Study: Identifying a Drug Target for Autoimmune Disease Using Integrated Genomic Analysis

This case study delves into our partnership with a forward-thinking biotech company dedicated to addressing autoimmune diseases. Anchored in practicality, our collaboration revolves around utilizing the client’s genomic and transcriptomics data to identify potential drug targets. Through a strategic blend of in-house data analysis and cross-validation with publicly available genomic data, we showcase how this

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Case Study: Discovering a Potential Biomarker for Cancer Treatment Using Single-Cell RNA Sequencing

Our client aimed to discover biomarkers for a novel cancer drug to enhance patient stratification and treatment efficacy. They required a robust technological solution to handle complex biological data and uncover treatment-responsive biomarkers from the heterogeneous tumor microenvironment. Challenge The complexity and variability of tumor cells at the single-cell level demanded a high-throughput, precise method

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