Top 50 Ai For Genomics in Europe

SeqOne provides a clinical decision support platform that utilizes AI-driven bioinformatics to analyze next-generation sequencing (NGS) data for germline and somatic variants. The platform enhances diagnostic accuracy and efficiency by identifying complex genomic events that standard pipelines often overlook, thereby improving patient outcomes in precision medicine.

Genomate Health develops a computational platform that utilizes artificial intelligence to analyze the unique molecular profiles of cancer patients' tumors, enabling oncologists to identify the most effective targeted therapies. This approach improves treatment outcomes by providing data-backed recommendations that consider multiple genetic alterations, significantly increasing the likelihood of positive patient responses.

Ingenix provides a multimodal generative AI platform that builds digital twins of drug candidates by integrating genomics, proteomics, imaging, literature, and electronic health records across molecular to population scales. The system delivers detailed, interpretable predictions of clinical efficacy, safety endpoints, and adverse events, and supports natural‑language “what‑if” queries for trial design and candidate prioritization. It is aimed at pre‑clinical, strategic R&D, and clinical development teams in pharmaceutical and biotechnology companies.

The startup employs AI algorithms to analyze genetic data for identifying mutations associated with hereditary diseases. This technology enables healthcare providers to deliver accurate diagnoses and tailored treatment plans for patients with genetic disorders.

Healx provides an AI‑powered platform that integrates genomics, phenotypic and clinical data to identify and prioritize repurposed or optimized compounds for rare disease indications. The system automates in silico screening, predictive efficacy and safety modeling, and workflow orchestration to move candidates from computational prediction to preclinical validation, lowering discovery costs and timelines. It is offered to pharmaceutical, biotech and research consortium partners seeking to expand rare‑disease pipelines.

The startup develops gene therapies using artificial intelligence to enhance the design and optimization of genetic constructs. Their technology enables researchers to create more predictable and controllable gene therapies, facilitating faster development for various applications.

Rayca Precision utilizes AI-driven bioinformatics platforms, OncoCrest™ and RSA2™, to analyze genomic and transcriptomic data for personalized cancer treatment strategies. The technology addresses the challenge of cancer heterogeneity by providing precise predictions of drug responses and patient outcomes, enabling tailored therapeutic interventions.

WhiteLab Genomics utilizes a proprietary platform that combines graph knowledge technology and machine learning to optimize the design of payloads and vectors for gene and cell therapies. This technology accelerates the development process, reducing costs and time to market for genomic medicines, making them more accessible to patients.

Curenetics utilizes an AI-powered platform that integrates genomics, imaging, and clinical data to predict individual patient responses to cancer therapies. This technology addresses the high variability in treatment effectiveness, enabling personalized treatment plans that improve patient outcomes and reduce unnecessary healthcare costs.

The startup has developed an artificial intelligence platform for biomarker discovery and sequencing analysis, focusing on extracting biosignatures from single-cell and multi-omics data. This platform enables physicians to efficiently analyze complex disease patterns, reducing data processing time and costs while enhancing insights for patient stratification.

The startup has developed a digital diagnostics platform that utilizes artificial intelligence for genetic analysis and clinical decision support, enhancing the traceability and interoperability of bioinformatics data. This technology enables researchers and clinicians to efficiently access and reuse critical information, thereby expediting the diagnosis process for various diseases.

Ensocell utilizes single-cell genomics, AI-driven computational tools, and advanced cell models to identify intervention points for autoimmune, inflammatory, and fibrotic diseases. The company focuses on discovering novel therapeutics to improve treatment outcomes in these challenging health conditions.

Tailwind Biotech provides artificial DNA design services using proprietary artificial intelligence to optimize DNA sequences for bioproduction companies. This technology enhances gene expression and reduces development costs, enabling more efficient and effective genetic engineering processes.

TrueYouOmics utilizes DNA, RNA, and protein analyses, combined with AI-driven algorithms, to extract up to 3 billion datapoints from blood samples for personalized health risk assessments. The platform provides users with specific disease risk evaluations and tailored prevention plans, empowering them to make informed health decisions.

Nygen Analytics offers a cloud-based platform for the analysis of single-cell genomic data, utilizing bioinformatics techniques to enable researchers to visualize and interpret complex datasets without requiring coding skills. The platform addresses the challenges of data complexity and collaboration in single-cell studies, facilitating efficient data management and accelerating research insights.

MultiOmic Health utilizes AI-driven multi-omics analysis and computational systems biology to identify distinct molecular drivers of metabolic syndrome-related diseases. The company develops precision therapeutics and companion diagnostics, enabling shorter clinical trials with higher success rates for conditions such as type 2 diabetes and chronic kidney disease.

Novigenix utilizes an AI-driven RNA sequencing platform to profile immune responses, enabling precise risk assessment and treatment predictions for cancer patients. The company addresses the challenge of heterogeneity in cancer treatment by providing actionable data for drug target discovery and early detection, particularly in colorectal cancer.

One Biosciences utilizes single-cell technologies and AI-driven analysis to create high-resolution omics profiles of tumors, enabling precise patient selection and treatment strategies. This approach addresses the complexity of advanced cancer biology, facilitating the development of targeted therapeutics for difficult-to-treat diseases.

Causaly is a generative AI platform that automates knowledge extraction from vast biomedical literature, enabling researchers to identify validated targets and novel biomarkers with high precision. By reducing research time from months to minutes, it enhances productivity by up to 90%, allowing scientists to focus on innovative drug discovery.

Enhanc3D Genomics utilizes its GenLink3D platform to analyze the 3D organization of DNA, focusing on the impact of genetic variations in non-coding regions on disease progression. This approach enables the identification of new biomarkers and treatment targets for complex conditions such as cancer, aging, and autoimmune diseases.

Bioptimus is developing a universal AI foundation model specifically for biological research, enabling researchers to leverage large-scale data analysis and predictive modeling. This technology addresses the challenge of slow and fragmented discovery processes in biomedicine by providing a cohesive platform for accelerating insights and innovations.

Dyno Therapeutics utilizes artificial intelligence to design novel adeno-associated virus (AAV) vectors for gene therapy, enhancing delivery efficiency for a wide range of human diseases. The company aims to increase patient access to effective treatments while significantly reducing the cost of in vivo gene delivery.

SilicoGene offers a no-code platform for health-tech teams to manage the entire AI lifecycle in drug discovery, enabling users to prepare bioinformatics data, train models, and deploy them efficiently. The platform provides on-demand access to cost-effective GPUs and ensures data security through HIPAA-compliant infrastructure, facilitating rapid deployment of AI solutions in real-world applications.

Automata provides an integrated lab automation platform that combines modular LINQ hardware with a no‑code Workflow Canvas and a Python SDK for designing and executing genomics, cell biology, and screening protocols. The cloud‑native system offers real‑time run monitoring, version‑controlled workflow management, and REST APIs for LIMS and AI pipeline integration, enabling high‑throughput, reproducible experiments.

AIVIVO LTD develops artificial intelligence systems that generate multi-modal omics data to create OrganoMaps, which connect disease biology with treatment interventions at the organ level. This approach enables the development of targeted medicines for patients by providing insights into organ-specific disease mechanisms.

The startup offers a microbial bioinformatics and data management platform that enables researchers to analyze and interpret microbial genomic data effectively. By providing software licensing, consulting, and training, the platform enhances the understanding of microbial genomes and their biological functions, facilitating advancements in genomics research.

Watershed provides a platform for biological data analysis that integrates secure data management, customizable workflows, and supercomputing resources to enable rapid, large-scale analyses across various omics disciplines. By offering a dedicated bioinformatics team and ready-to-use AI tools, Watershed enhances productivity and collaboration for researchers facing the challenges of complex data interpretation.

The startup has developed a genome-analysis platform that facilitates the acquisition, analysis, and storage of genomic data without the need for repeated sequencing of the same genome for different tests. This technology enables healthcare providers to efficiently manage genetic data and deliver precise DNA sequencing services, enhancing the overall effectiveness of genomic research and patient care.

Exazyme is an AI-driven protein design tool that utilizes advanced algorithms to predict protein evolutions, enabling biotech companies to achieve superior outcomes with up to 100 times fewer experiments than traditional screening methods. The platform addresses the inefficiencies in protein optimization by allowing users to evaluate multiple protein properties simultaneously while ensuring data security through on-site deployment or API connections.

The startup develops a drug discovery platform that combines artificial intelligence and synthetic biology to digitize natural diversity and identify potential drug candidates based on their functions. This approach aims to make the discovery of new therapeutics for cancer, metabolic diseases, and infectious diseases more predictable and cost-effective.

Saphetor provides the VarSome Suite, a set of bioinformatics solutions that processes Next Generation Sequencing (NGS) data to generate clinically relevant genetic variation information. This technology enables healthcare professionals and researchers to access a comprehensive knowledge base and automated classification tools, enhancing the accuracy and efficiency of genomic analysis.

CoSyne Therapeutics utilizes polymathic AI and genetic computational systems analysis to expedite the development of pharmaceuticals targeting high-risk brain cancer. By digitizing cellular responses, the company enables medical researchers to create a new class of drugs more efficiently and at a lower cost than traditional methods.

Akkure is a digital platform utilizing AI and genomics to enhance clinical trial recruitment for oncology by providing precise patient-trial matching and personalized trial recommendations. The platform ensures GDPR and HIPAA compliance, facilitating secure access and ownership of clinical data while streamlining the enrollment process for patients and healthcare providers.

The startup develops analytics software that integrates multi-omic data with AI analytics to enhance drug candidate identification and biomarker discovery. This technology enables precision medicine organizations to streamline research processes and significantly reduce time-to-market for new treatments.

Nested Therapeutics utilizes a proprietary drug discovery platform that employs genomics, computational biophysics, and machine learning to identify novel driver mutations and druggable pockets in cancer pathways. This approach addresses the challenge of developing targeted therapies for the vast majority of recurrent cancer-associated mutations that currently lack FDA-approved treatments.

Ophiomics develops in vitro diagnostic devices that utilize artificial intelligence and genomics to enhance early cancer detection and optimize treatment selection. Their technology integrates machine learning algorithms with clinical and biomarker data to improve decision-making for clinicians, ultimately aiming to enhance patient outcomes in oncology.

TwinEdge Bioscience provides a cloud‑based platform that creates high‑fidelity digital twins of individual patient tumors by integrating genomics, transcriptomics, proteomics and histopathology data. Its AI‑augmented simulation engine predicts drug response, resistance mechanisms and biomarker associations across a library of over 10,000 validated tumor avatars, enabling pharmaceutical and CRO teams to prioritize candidates, design trials and stratify patients before human enrollment.

Provides an AI-powered platform for analyzing complex medical data, including transcriptomics, epigenomics, and proteomics, using modular machine learning techniques. This system accelerates research by delivering fast, high-quality insights for identifying therapeutic targets, biomarkers, and disease mechanisms, reducing time and cost compared to traditional methods.

ScienTek accelerates aptamer discovery for challenging protein targets using an AI-powered platform. Their technology combines in silico screening with in vitro validation to identify and optimize nucleic acid sequences with high binding affinity for next-generation therapeutics.

ions.bio provides an all-in-one solution for biomarker development, utilizing mass spectrometry and AI-driven bioinformatics to transform clinical samples into validated multi-omics datasets. This approach streamlines the biomarker discovery process, reducing the time and risk associated with drug and diagnostics development for biotech and pharmaceutical companies.

Imperagen has developed a fully automated platform that integrates AI-driven hotspot identification, precision DNA editing, and laboratory automation to enhance enzyme engineering. This technology significantly reduces the time and resources required for enzyme development, enabling rapid creation and optimization of enzyme variants across diverse applications.

The startup develops AI-powered precision medicine technology that utilizes multi-omics analysis to decode cellular health and identify molecular causes of diseases. This approach enhances early disease detection and enables targeted therapies for non-invasive prenatal and oncology testing.

Biographica utilizes biology-aware machine learning and high-throughput sequencing to identify and prioritize genetic targets for crop gene-editing, addressing the challenge of inefficient gene selection that often results in high costs and low success rates. By combining in silico modeling with in vivo validation, the platform enhances the precision of genomic modifications, enabling the development of more productive and climate-resilient crops.

Breed Bio provides a specialized Laboratory Information Management System (LIMS) for high-throughput agrigenomics laboratories. The platform automates data capture and standardization from laboratory instruments, managing millions of genetic data points and enabling AI-driven analysis for optimized breeding programs.

Datum develops AI-powered clinical decision support tools that utilize large language models trained on validated clinical guidelines and peer-reviewed publications. By integrating diverse evidence sources within a graph database, Datum provides clinicians with precise pharmacogenomics recommendations that are clinically validated and easily integrated into existing electronic health record systems.

Syngens AS has developed an AI-powered DNA Design Platform that enables precise and predictable DNA engineering for biomanufacturing applications. By optimizing gene expression and constructing novel biological pathways, the platform addresses the limitations of scalability and engineering precision in current biological methods, significantly reducing trial-and-error in experimental processes.

GeneSys Bio offers a portable, battery‑operated molecular diagnostics system that automates nucleic‑acid extraction, rapid PCR or isothermal amplification, and AI‑driven data interpretation to deliver results in under 60 minutes. The modular cartridge platform supports multiplex detection of bacteria, viruses, fungi and antibiotic‑resistance genes across human, animal and environmental samples, with secure cloud reporting for integration with laboratory information systems. It is designed for point‑of‑care clinical labs, veterinary diagnostics and field epidemiology teams that need fast, laboratory‑grade testing without centralized facilities.

The startup develops bioinformatics tools that utilize artificial intelligence for the identification of drug targets and the evolutionary analysis of protein sequences. By enabling the modeling and computational screening of mutant libraries, the company provides pharmaceutical firms with the capability to discover novel drug candidates in previously unexplored areas.

DATABIOMIX offers end-to-end microbiota analysis and microbial genomics services, providing researchers and healthcare providers with comprehensive reports and expert interpretation. Their AI-based platform facilitates microbiota biomarker discovery for personalized medicine and the development of microbiome-derived companion diagnostics.

NonExomics utilizes a proprietary platform that integrates genomics, transcriptomics, proteomics, and machine learning to identify druggable noncanonical proteins across the entire human genome. This approach addresses the limitation of current therapies that target only 1-2% of the genome, enabling the discovery of novel therapeutic targets associated with over 1,300 human diseases.