Alternatives to Recursion

Eidogen-Sertanty's Target Informatics Platform (TIP) stands out as the pioneering structural informatics system and knowledgebase that empowers researchers to explore the druggable genome through a structural lens. By harnessing the burgeoning wealth of experimental protein structure data, TIP revolutionizes structure-based drug discovery, shifting it from a limited, low-throughput field to a dynamic and data-rich scientific discipline. It is specifically designed to connect the realms of bioinformatics and cheminformatics, providing drug discovery scientists with a repository of insights that are not only unique but also highly synergistic with the information available from traditional bio- and cheminformatics tools. The platform's innovative combination of structural data management with advanced target-to-lead calculation and analytical capabilities significantly enhances every phase of the drug discovery process. With TIP, researchers are better equipped to navigate the complexities of drug development and make informed decisions.

Clara provides specialized tools and pre-trained AI models that are driving significant advancements across various sectors, such as healthcare technologies, medical imaging, pharmaceutical development, and genomic research. Delve into the comprehensive process of developing and implementing medical devices through the Holoscan platform. Create containerized AI applications using the Holoscan SDK in conjunction with MONAI, and enhance deployment efficiency in next-gen AI devices utilizing the NVIDIA IGX developer kits. Moreover, the NVIDIA Holoscan SDK is equipped with acceleration libraries tailored for healthcare, alongside pre-trained AI models and sample applications designed for computational medical devices. This combination of resources fosters innovation and efficiency, positioning developers to tackle complex challenges in the medical field.

DNAnexus Apollo™ enhances the efficiency of precision drug discovery by fostering collaboration that extracts valuable insights from omics data. The process of precision drug discovery involves the aggregation and examination of vast amounts of omics and clinical information. These extensive datasets serve as valuable assets; however, many traditional and custom-built informatics tools struggle to manage their intricacies and scale. Additionally, the effectiveness of precision medicine initiatives can be hindered by fragmented data sources, inadequate collaboration tools, and the challenges posed by complex, evolving regulatory and security demands. By enabling scientists and clinicians to jointly investigate and interpret omics and clinical data within a unified framework, DNAnexus Apollo™ bolsters precision drug discovery efforts. This platform, which is powered by a resilient and scalable cloud infrastructure, facilitates the seamless and secure sharing of data, tools, and analyses among peers and collaborators, regardless of whether they are nearby or across the globe. Ultimately, Apollo not only streamlines the data-sharing process but also enhances the overall collaborative experience in the pursuit of innovative drug discoveries.

Pharmaceutical companies require extensive genomic data to effectively implement precision medicine initiatives; however, they frequently rely on merely 10% of the available information for their decisions. Genomenon provides access to the complete dataset. Their Prodigy™ Patient Landscapes offer a streamlined and economical solution for natural history research, aiding the creation of therapies for rare diseases by deepening understanding of both retrospective and prospective health data. Utilizing an advanced AI-driven methodology, Genomenon conducts a thorough evaluation of each patient documented in the medical literature in a significantly reduced timeframe. Ensure you capture all relevant insights by exploring every genomic biomarker featured in published studies. Each scientific claim is substantiated by concrete evidence drawn from the medical literature, allowing researchers to uncover all genetic drivers and identify variants recognized as pathogenic in accordance with ACMG clinical standards, thereby enhancing the development process of targeted therapies. By leveraging this comprehensive approach, pharma companies can enhance their research effectiveness and ultimately improve patient outcomes.

AIDDISON™ is an innovative drug discovery software that harnesses the capabilities of artificial intelligence (AI), machine learning (ML), and advanced 3D computer-aided drug design (CADD) techniques, serving as an essential resource for medicinal chemistry applications. This comprehensive platform streamlines both ligand-based and structure-based drug design, effectively merging all components necessary for virtual screening while also facilitating in-silico lead discovery and optimization processes. By leveraging these cutting-edge technologies, AIDDISON™ significantly enhances the efficiency and effectiveness of the drug development pipeline.

Harnessing RNA sequencing (RNA-seq) data alongside Artificial Intelligence presents both a crucial necessity and a significant opportunity for creating therapies aimed at correcting splicing errors. By leveraging machine learning, we can uncover novel splicing errors and swiftly formulate therapeutic compounds to address them. Our AI platform, SpliceCore, is specifically designed for discovering RNA therapeutics. This cutting-edge technology focuses on analyzing RNA sequencing data with unparalleled efficiency. It can swiftly identify, evaluate, and validate potential drug targets, outpacing traditional methodologies. Central to SpliceCore is our unique repository containing over 5 million potential RNA splicing errors, making it the largest of its kind globally and instrumental for testing any RNA sequencing dataset submitted for analysis. The integration of scalable cloud computing allows us to handle vast quantities of RNA sequencing data in a way that is not only efficient but also cost-effective, significantly speeding up the pace of therapeutic advancements. This innovative approach promises to revolutionize the landscape of RNA therapeutics.

Harness the capabilities of artificial intelligence to accelerate the transition from laboratory research and experimental findings to the introduction of transformative therapies. Achieve a remarkable increase in research efficiency, potentially improving productivity by as much as 90% by cutting down your literature review time from several months to mere minutes. Eliminate distractions and enhance your search capabilities with a precise and accurate tool that simplifies the navigation of the expanding landscape of scientific publications. This approach not only saves time but also minimizes bias and enhances the likelihood of discovering groundbreaking insights. Delve deeply into the intricacies of disease biology and engage in sophisticated target identification. Causaly's advanced knowledge graph integrates data from countless publications, enabling thorough and objective scientific investigations. Effortlessly explore the intricate biological cause-and-effect dynamics without requiring extensive expertise. Access a comprehensive array of scientific documents and reveal previously overlooked connections. Causaly’s robust AI system processes millions of biomedical articles, facilitating improved decision-making and enhancing research outcomes, ultimately leading to a more informed and innovative scientific community. By utilizing such tools, researchers can significantly transform their methodologies and enhance their contributions to medicine.

Our innovative AI engine is revolutionizing the drug discovery process, enabling the creation of superior medications at an accelerated pace. The breakthroughs we achieve contribute to the development of medicines more efficiently and effectively. Our portfolio of AI-driven discoveries encompasses entirely owned and collaboratively developed pipeline assets, supported by leading investors in the industry. Atomwise has engineered a cutting-edge machine-learning discovery platform that merges the capabilities of convolutional neural networks with extensive chemical libraries to identify new small-molecule treatments. The key to transforming drug discovery through AI lies in our talented team. We are committed to enhancing our AI platform and leveraging it to revolutionize the discovery of small molecule drugs. It is essential that we confront the most daunting and seemingly insurmountable targets, streamlining the entire drug discovery process to provide developers with increased opportunities for success. Enhanced computational efficiency allows us to screen trillions of compounds virtually, significantly boosting the chances of finding viable solutions. Our impressive model accuracy has successfully addressed the persistent issue of false positives, underscoring the reliability of our approach. Ultimately, our dedication to innovation and excellence sets us apart in the quest for breakthrough therapies.

The Kanteron Platform assimilated a wide array of medical images, digital pathology slides, genomic sequences, and patient information from various modalities, scanners, sequencers, and databases, delivering a comprehensive data toolkit to all teams within hospital networks. It emphasizes pharmacogenomics to avert adverse medication events and facilitates the application of precision medicine at the point of care by integrating data sources on drug-gene interactions that were formerly only accessible in less user-friendly formats, such as tables found in PDF documents. By incorporating major pharmacogenomic databases like PharmGKB, CGI, DGIdb, and OpenTargets, it enables users to customize their queries according to specific gene families, types of interactions, and drug classifications. Additionally, its adaptable AI allows users to select the dataset that best aligns with their specific use case, applying it effectively to pertinent medical images. This robust functionality not only enhances the accuracy of medical insights but also fosters a more personalized approach to patient care.

BioNeMo is a cloud service and framework for drug discovery that leverages AI, built on NVIDIA NeMo Megatron, which enables the training and deployment of large-scale biomolecular transformer models. This service features pre-trained large language models (LLMs) and offers comprehensive support for standard file formats related to proteins, DNA, RNA, and chemistry, including data loaders for SMILES molecular structures and FASTA sequences for amino acids and nucleotides. Additionally, users can download the BioNeMo framework for use on their own systems. Among the tools provided are ESM-1 and ProtT5, both transformer-based protein language models that facilitate the generation of learned embeddings for predicting protein structures and properties. Furthermore, the BioNeMo service will include OpenFold, an advanced deep learning model designed for predicting the 3D structures of novel protein sequences, enhancing its utility for researchers in the field. This comprehensive offering positions BioNeMo as a pivotal resource in modern drug discovery efforts.

At Genospace, we recognize that the evolution of precision medicine is being propelled by advancements in genomics, yet the challenge of effectively scaling its implementation remains unresolved. Our mission is to bridge this gap. Our innovative platform aims to transform biomedical data into valuable insights that are easily accessible for all, particularly for those actively involved in delivering care. Equip your clinicians and researchers with essential information that empowers them to make well-informed choices while participating in our goal of utilizing intricate molecular data to enhance patient outcomes and speed up the processes of drug development and research. In this context, the significance of large-scale population data for drug discovery and research cannot be overstated. Utilize cohort-driven analyses through the Genospace platform to support your research initiatives. We have a strong focus on clinical trial research, enabling the Genospace platform to seamlessly align fragmented patient information with intricate trial requirements, thus facilitating quicker patient recruitment. Furthermore, our platform is designed to integrate genomic medicine into standard clinical care practices, making it easier than ever to harness the power of genomics in everyday healthcare. Together, we can push the boundaries of what’s possible in patient care and research.

Aspect Analytics provides a spatial multi-omics platform designed for collaborative and interdisciplinary data analysis and management, catering to research teams engaged in drug development, biomarker discovery, pathology analysis, and more. This innovative platform empowers transformative research and enhances collaboration by aggregating multi-omics data into a unified, interactive interface. Users can overlay various spatial omics measurements in a single visualization, allowing for simultaneous insights. Our solution integrates data from all spatial multi-omics assays, ensuring that you derive the necessary insights efficiently. You can securely store and manage vast amounts of data, with the ability to access it from anywhere at any time. The platform is designed for scalability, enabling you to customize your data infrastructure based on specific requirements. It supports the integration of spatial biology data from a variety of technologies and vendors, regardless of the format of the data. Furthermore, you can establish automated workflows to conduct comprehensive analyses on extensive datasets concurrently, thus enhancing the efficiency and effectiveness of your research endeavors. This capability not only streamlines the research process but also fosters innovation across disciplines.

Founded in 2000, VeraChem LLC aims to enhance the field of computer-aided drug discovery and molecular design by creating advanced computational chemistry techniques that merge innovative basic science with practical applications in research. A key aspect of the company's strategy for product development lies in delivering efficient, high-performance software solutions along with extensive user support. Among the current capabilities of VeraChem's software are predictions for protein-ligand and host-guest binding affinities, rapid and precise calculations of partial atomic charges for drug-like molecules, and the computation of energies and forces utilizing widely-used empirical force fields. Additionally, the software features automatic generation of alternate resonance forms for drug-like compounds, a robust conformational search enabled by the Tork algorithm, and the automatic identification of topological and three-dimensional molecular symmetries. The modular code base of VeraChem’s software packages allows for flexibility and adaptability in meeting diverse research needs, ensuring that users can leverage these tools effectively for their specific applications.

Rare diseases often lack comprehensive research, resulting in insufficient knowledge about essential elements for an effective drug discovery initiative. Our innovative AI platform, Healnet, addresses these issues by scrutinizing vast amounts of drug and disease data to uncover new connections that may lead to potential treatments. Utilizing cutting-edge technologies throughout the discovery and development process allows us to operate multiple phases simultaneously and on a large scale. The conventional approach of focusing on a single disease, target, and drug is overly simplistic, yet it remains the standard for most pharmaceutical companies. The future of drug discovery is driven by AI, characterized by parallel processes and an absence of rigid hypotheses, fundamentally integrating the three core paradigms of drug discovery into a cohesive strategy. This new paradigm not only enhances efficiency but also fosters creativity in developing solutions for complex health challenges.

Genedata Biologics® enhances the development of biotherapeutics, including bispecifics, ADCs, TCRs, CAR-Ts, and AAVs, providing a comprehensive solution for the industry. Recognized as the leading platform in the field, it seamlessly unifies all discovery workflows, allowing researchers to prioritize genuine innovation. By utilizing a pioneering platform that was purposefully created to digitalize the biotherapeutic discovery process, research can be accelerated significantly. The platform simplifies intricate R&D tasks by facilitating the design, tracking, testing, and evaluation of novel biotherapeutic drugs. It is compatible with various formats, such as antibodies, bi- or multi-specifics, ADCs, innovative scaffolds, and therapeutic proteins, as well as engineered therapeutic cell lines like TCRs and CAR-T cells. Functioning as a comprehensive end-to-end data backbone, Genedata Biologics connects all R&D processes, including library design, immunization, selection and panning, molecular biology, screening, protein engineering, expression, purification, and protein analytics, ultimately leading to thorough assessments of candidate developability and manufacturability. This holistic integration ensures that researchers can make informed decisions and push the boundaries of biotherapeutic innovation effectively.

Cytel stands out as a prominent global innovator in software for clinical trial design, biometrics, and advanced analytics, focusing on maximizing the efficiency of clinical trials while aiding pharmaceutical companies in harnessing the full scope of both clinical and real-world data. Established in 1987 by renowned statisticians Cyrus Mehta and Nitin Patel, Cytel has consistently been a leader in adaptive clinical trial technology and the field of biostatistics. Its software solutions, notably the East Horizon platform, facilitate accurate trial design and simulation, employing adaptive and Bayesian methodologies to enhance protocols and expedite the drug development process. The East Horizon platform serves as a comprehensive integration of Cytel's reliable software offerings, featuring R integration that significantly improves trial design functions. Furthermore, Cytel provides the Xact software suite, which is an all-encompassing toolkit designed for statistical analysis of small datasets, including those with sparse and missing data. By continuously innovating and expanding its product offerings, Cytel remains committed to providing cutting-edge solutions that meet the evolving needs of clinical research.

BIOiSIMTM represents a groundbreaking 'virtual drug development engine' that significantly enhances the drug development sector by effectively identifying drug compounds that are most likely to provide meaningful therapeutic benefits for various diseases or conditions. We provide an array of translational solutions that are tailored to meet the specific needs of your pre-clinical and clinical initiatives. Central to our offerings is the highly validated BIOiSIMTM platform, which supports the development of small molecules, large molecules, and viruses. This innovative platform is underpinned by extensive data derived from thousands of compounds across seven different species, resulting in a level of robustness that is uncommon in the field. Emphasizing human health outcomes, the heart of the platform features a translatability engine that seamlessly converts insights gained from different species. Importantly, the BIOiSIMTM platform can be deployed prior to the initiation of preclinical animal trials, facilitating earlier insights and potentially reducing the costs associated with outsourced experimentation. By integrating these advanced capabilities, we aim to streamline the drug development process and accelerate the journey from discovery to market.

We combine clinical and experimental data through machine learning techniques to explore human disease biology and promote the development of precision medicine. Our innovative Contingent AI™ technology comprehends the intricate relationships present in the data, yielding advanced insights. To combat data bias, we refine our machine learning models based on decisions made during the pre-processing and feature engineering phases. We utilize zebrafish, cellular, and various phenotypic animal models to test and confirm in silico predictions through in vivo experiments, along with genetic modifications conducted both in vitro and in vivo to enhance translation. By employing active learning and computer vision on validated models that focus on cardiac, central nervous system, and rare disorders, we swiftly integrate new data into our machine learning frameworks, allowing for continuous improvement and adaptation in our methodologies. This iterative process not only enhances the accuracy of our predictions but also enables us to stay at the forefront of research in precision medicine.

Our worldwide data-sharing network produces actionable clinical insights from data aimed at enhancing patient outcomes on a global scale. SOPHiA GENETICS is dedicated to shaping the future of AI-enhanced medicine. By integrating various healthcare-omics data types, we are dismantling existing data barriers and creating machine learning models that yield insights capable of aiding healthcare professionals in elevating patient care. The updated interface, along with new features and advanced functionalities, will further expedite precision medicine workflows, bringing us closer to making data-driven healthcare accessible to all. Utilizing the power of AI and machine learning (ML), our cloud-based platform offers a secure and easily accessible space for the standardization, computation, and analysis of digital health data, which generates insights from intricate multimodal data sets that can significantly enhance diagnostic processes, therapy choices, analytical methods, and drug development initiatives. Moreover, our continuous evolution reflects our commitment to innovation in the healthcare sector.

Partek bioinformatics software offers robust statistical and visualization capabilities through a user-friendly interface that caters to researchers of varying expertise. This innovation allows users to navigate genomic data with unprecedented speed and ease, truly embodying our motto, "We turn data into discovery®." With pre-installed workflows and pipelines in a simple point-and-click format, even complex NGS and array analyses become accessible to all scientists. Our combination of custom and public statistical algorithms works seamlessly to transform NGS data into valuable biological insights. Engaging visual tools like genome browsers, Venn diagrams, and heat maps illuminate the intricacies of next-generation sequencing and array data with vibrant clarity. Additionally, our team of Ph.D. scientists is always available to provide support for NGS analyses whenever queries arise. Tailored to meet the demanding computational requirements of next-generation sequencing, the software also offers flexible options for installation and user management, ensuring a comprehensive solution for research needs. As a result, users can focus more on their research and less on technical challenges.

VIPER streamlines the process of screening by automating remote patient identification right at the diagnosis stage and ensuring qualified enrollment. By leveraging artificial intelligence, VIPER efficiently matches patients to precision trials during a critical enrollment period by utilizing lab-agnostic genomic data, electronic medical records (EMR), and pathology information tailored to both the patient and the research requirements. The system employs a specialized matching engine that searches for the most suitable clinical trials corresponding to a patient's specific diagnosis at the moment they receive it. Additionally, through seamless workflow integration, VIPER provides real-time alerts regarding a patient’s eligibility for available trials, ensuring the entire care team is informed during this narrow enrollment timeframe. Furthermore, VIPER features interactive dashboards that offer extensive data mining capabilities, allowing for the aggregation of site and study-level patient data to effectively meet study key performance indicators (KPIs). This comprehensive approach not only enhances trial recruitment efficiency but also supports researchers in achieving their goals more effectively.

NVIDIA® Parabricks® stands out as the sole suite of genomic analysis applications that harnesses GPU acceleration to provide rapid and precise genome and exome analysis for various stakeholders, including sequencing centers, clinical teams, genomics researchers, and developers of high-throughput sequencing instruments. This innovative platform offers GPU-optimized versions of commonly utilized tools by computational biologists and bioinformaticians, leading to notably improved runtimes, enhanced workflow scalability, and reduced computing expenses. Spanning from FastQ files to Variant Call Format (VCF), NVIDIA Parabricks significantly boosts performance across diverse hardware setups featuring NVIDIA A100 Tensor Core GPUs. Researchers in genomics can benefit from accelerated processing throughout their entire analysis workflows, which includes stages such as alignment, sorting, and variant calling. With the deployment of additional GPUs, users can observe nearly linear scaling in computational speed when compared to traditional CPU-only systems, achieving acceleration rates of up to 107X. This remarkable efficiency makes NVIDIA Parabricks an essential tool for anyone involved in genomic analysis.

Scitara DLX™ provides a swift connectivity framework suitable for any instrument found within life science laboratories, all while operating on a cloud-based platform that is both compliant and auditable. As a versatile digital data infrastructure, Scitara DLX™ facilitates connections between various instruments, resources, applications, and software utilized in the lab. The comprehensive cloud system ensures that all data sources are interconnected, promoting seamless data movement across numerous endpoints. Consequently, researchers can concentrate on their scientific endeavors instead of being bogged down by data-related challenges. Moreover, DLX intelligently curates and corrects data as it is processed, fostering the creation of accurate and well-organized data models that are essential for enhancing AI and ML systems. This robust approach plays a vital role in advancing digital transformation strategies within the pharmaceutical and biopharmaceutical sectors. By unlocking valuable insights from scientific data, the platform accelerates decision-making processes in drug discovery and development, ultimately aiding in the expedited launch of new medications into the market. Additionally, the integration of such a sophisticated infrastructure not only streamlines workflows but also enhances collaboration among researchers, paving the way for innovative solutions in the life sciences field.

The biopharmaceutical sector today is characterized by its intricacy, driven by increasing demands for enhanced specificity and safety, the emergence of new treatment classes, and the complexity of disease mechanisms. To navigate this intricate landscape, a profound comprehension of therapeutic dynamics is essential. Advanced modeling and simulation techniques offer a distinctive approach to investigate biological and physicochemical phenomena at the atomic scale. This methodology not only informs physical experimentation but also expedites the drug discovery and development phases. BIOVIA Discovery Studio integrates more than three decades of peer-reviewed research with cutting-edge in silico methodologies, including molecular mechanics, free energy assessments, and biotherapeutics developability, all within a unified framework. By equipping researchers with a comprehensive suite of tools, it facilitates a deeper examination of protein chemistry, thereby accelerating the discovery of both small and large molecule therapeutics, from Target Identification all the way through to Lead Optimization. Ultimately, this synergy of research and technology underscores the vital role of innovative tools in transforming biopharmaceutical advancements.

Amazon Neptune is an efficient and dependable graph database service that is fully managed, facilitating the development and operation of applications that handle intricate, interconnected datasets. At its heart, Amazon Neptune features a specialized, high-performance database engine tailored for the storage of billions of relationships while enabling rapid querying with latency measured in milliseconds. It accommodates widely-used graph models, including Property Graph and W3C's RDF, along with their associated query languages, Apache TinkerPop Gremlin and SPARQL, which simplifies the process of crafting queries for navigating complex datasets. This service supports various graph-based applications, including recommendation systems, fraud detection mechanisms, knowledge graphs, drug discovery initiatives, and enhanced network security protocols. With a proactive approach, it enables the detection and analysis of IT infrastructure threats through a multi-layered security framework. Furthermore, it allows users to visualize their entire infrastructure to effectively plan, forecast, and address potential risks, while also enabling the creation of graph queries for the near-real-time identification of fraudulent patterns in financial and purchasing activities, thereby enhancing overall security and efficiency.

Manage, store, and collaborate on multi-omic datasets effectively. The Illumina Connected Analytics platform serves as a secure environment for genomic data, facilitating the operationalization of informatics and the extraction of scientific insights. Users can effortlessly import, construct, and modify workflows utilizing tools such as CWL and Nextflow. The platform also incorporates DRAGEN bioinformatics pipelines for enhanced data processing. Securely organize your data within a protected workspace, enabling global sharing that adheres to compliance standards. Retain your data within your own cloud infrastructure while leveraging our robust platform. Utilize a versatile analysis environment, featuring JupyterLab Notebooks, to visualize and interpret your data. Aggregate, query, and analyze both sample and population data through a scalable data warehouse, which can adapt to your growing needs. Enhance your analysis operations by constructing, validating, automating, and deploying informatics pipelines with ease. This efficiency can significantly decrease the time needed for genomic data analysis, which is vital when rapid results are essential. Furthermore, the platform supports comprehensive profiling to uncover novel drug targets and identify biomarkers for drug response. Lastly, seamlessly integrate data from Illumina sequencing systems for a streamlined workflow experience.

BC platforms harnesses cutting-edge scientific advancements, innovative technological capabilities, and strategic alliances to transform drug discovery and tailor healthcare solutions. Our platform is modular and highly adaptable, designed for integrating healthcare data effectively. With an open analytics framework, we seamlessly merge the most recent innovative methods and technology advancements into a single, cohesive platform. We prioritize security, holding ISO 27001 certification alongside compliance with GDPR and HIPAA regulations. Our comprehensive product suite empowers a contemporary healthcare system to fully adopt personalized medicine approaches. Our scalable deployment options support everything from initial setups to expansive healthcare operations. By offering a unique end-to-end toolbox, we facilitate the expedited application of research findings in clinical settings. Moreover, we strive to minimize your risks, enhance the value of your pipeline, and advance your enterprise data strategy by overcoming data access challenges and enabling swift insights. In doing so, we aim to foster a health ecosystem that is both responsive and forward-thinking.

Efficiently merge the multiomic information of patients with their health records to provide more tailored care solutions. Implement specialized data repositories to facilitate extensive analyses and foster collaborative research initiatives on a population-wide scale. Expedite research processes by leveraging adaptable workflows and comprehensive computational tools. Ensure the safeguarding of patient privacy through adherence to HIPAA standards, complete with robust data access and logging mechanisms. AWS HealthOmics empowers healthcare and life science organizations, along with their software collaborators, to securely store, retrieve, and analyze diverse omics data, such as genomic and transcriptomic information, ultimately yielding valuable insights that enhance health outcomes and propel scientific advancements. Manage and evaluate omics data for extensive patient cohorts to discern how variations in omics relate to phenotypic expressions within the population. Develop consistent and accountable clinical multiomics workflows designed to minimize turnaround times while boosting efficiency. Seamlessly incorporate multiomic assessments into clinical trials aimed at evaluating new therapeutic candidates, thereby enhancing the overall drug development process. By harnessing these innovative approaches, organizations can ensure a deeper understanding of patient health and contribute to groundbreaking research findings.

Correlation Engine serves as an engaging omics knowledgebase designed to situate private omics data within a rich biological framework alongside meticulously curated public datasets. Recognized as one of the most extensive biological databases globally, it offers life science researchers unparalleled access to an immense collection of high-quality whole-genome analyses, complemented by powerful scientific tools. This knowledgebase fosters groundbreaking discoveries by enabling the exploration of billions of data points sourced from standardized whole genome study analyses. It features an array of applications tailored for discerning biological context, a continuously expanding library of curated datasets, and versatility across various species and multi-omic datasets. Users can navigate through an intuitive graphical user interface that facilitates guided workflows, one-click applications, and application programming interfaces (APIs). By streamlining the transition from omic data to actionable insights, researchers can tap into over 25,000 multi-omics studies derived from more than 250,000 unique signatures that have undergone reanalysis, thereby enhancing their research capabilities even further.

Genoox is revolutionizing the field of genomics through its dynamic and expanding community, which enables the accumulation of the most pertinent database and facilitates the delivery of actionable, real-world genomic insights that significantly affect lives, enhance clinical outcomes, and influence healthcare business practices. By harnessing community power, Genoox merges public data with community-generated information to optimize the journey from DNA sample to clinical report, thereby improving patient care through the accessibility and applicability of genomic data at critical moments. The company's innovative solutions are transforming the landscape of genomics, while also supporting research and life sciences enterprises with an insightful platform that leverages real-world data and evidence, bolstered by comprehensive genomic analytics, which assists researchers in simplifying intricate genomic information and achieving meaningful breakthroughs with cutting-edge genetic tools. Moreover, Genoox collaborates with biosystems firms like DNA sequencing companies to integrate its advanced genomic engine with specialized assays, further enhancing the capabilities of the entire genomics ecosystem. Ultimately, Genoox stands at the forefront of genomic innovation, consistently aiming to empower healthcare professionals and researchers alike.

Clarity LIMS serves as a sophisticated laboratory information management system specifically tailored for genomics laboratories to effectively monitor samples and streamline workflows for enhanced laboratory efficiency. Beyond mere sample tracking, Clarity LIMS acts as a vital digital infrastructure for laboratory operations, encompassing every aspect from data and sample management to the oversight of personnel, equipment, and supplies. By standardizing and automating workflows, it significantly reduces the time required for processes and minimizes the likelihood of human error. This platform is designed to grow with your laboratory's needs, easily integrating new technologies and methodologies. Clarity LIMS also facilitates quicker laboratory operations through its easy-to-use implementation, offering preconfigured workflows for Illumina sample and library preparation kits, alongside quality control mechanisms that identify subpar samples. In addition, it aids in maintaining compliance with features such as electronic signatures, audit trails, reagent tracking, and robust privacy and security measures. Lastly, Clarity LIMS enhances precision through automation, incorporating built-in business logic and error-checking systems to ensure reliable results.

Created within the Data Sciences Platform at the Broad Institute, this comprehensive toolkit provides an extensive array of features primarily aimed at variant discovery and genotyping. With its robust processing engine and high-performance computing capabilities, it is equipped to manage projects of any magnitude. The GATK has established itself as the industry benchmark for detecting SNPs and indels in both germline DNA and RNA sequencing data. Its functionalities are now broadening to encompass somatic short variant detection as well as addressing copy number variations (CNV) and structural variations (SV). Besides the core variant callers, the GATK incorporates numerous utilities for executing associated tasks, including the processing and quality assurance of high-throughput sequencing data, and it comes bundled with the well-known Picard toolkit. Originally designed for exome and whole genome data generated via Illumina sequencing technology, these tools are versatile enough to be modified for use with various other technologies and study designs. As research evolves, the adaptability of the GATK ensures it remains relevant in diverse genomic investigations.

Vytelle is revolutionizing the livestock industry by providing innovative solutions that assist cattle producers globally in optimizing their herds. Our offerings minimize uncertainties, empowering you to make critical decisions regarding mating and reproduction. At the core of our technology is Vytelle SENSE™, a unique system for capturing individual animal data. This system measures feed intake and weight gain within the pen, allowing you to pinpoint top-performing animals that exhibit traits vital for both economic success and environmental sustainability. Utilizing low-contact devices, we gather essential performance metrics without causing stress to the animals, ensuring seamless communication of this data for further processing and integration. With a legacy of 30 years in aiding producers to gather and utilize cattle data, our decision-making tools now leverage the power of the industry's only AI analytic engine. This advanced technology swiftly analyzes phenotypic, genomic, environmental, and performance data, presenting it in user-friendly dashboards and reports that facilitate informed decisions for your cattle operations. As a result, producers can not only enhance their herd management practices but also contribute to a more sustainable agricultural future.

Emedgene optimizes the workflows involved in tertiary analysis for rare disease genomics and various germline research endeavors. It is specifically built to enhance the speed and reliability of interpreting, prioritizing, curating, and generating research reports for user-defined variants. By incorporating explainable AI (XAI) and automation, Emedgene boosts efficiency across diverse analysis workflows, including genomes, exomes, virtual panels, and targeted panels. The platform facilitates the integration of laboratory processes and NGS instruments with IT systems, streamlining and securing the entire workflow. With continuous advancements in science, technology, and demand, Emedgene empowers users to stay current by offering cutting-edge knowledge graph features, curation tools, and expert support throughout their research journey. Furthermore, it allows laboratories to increase their throughput without the need for additional personnel, thanks to XAI and automated processes. Ultimately, Emedgene enables the deployment of high-throughput workflows for whole genome sequencing (WGS), whole exome sequencing (WES), virtual panels, or targeted panels that seamlessly fit into the digital framework of any lab. This comprehensive approach ensures that researchers can focus on their discoveries while relying on robust technological support.

Persistence container technology facilitates efficient operations with a lightweight approach, allowing users to pay for usage by the second instead of waiting for hours or months. The payment process, which will occur via credit card, is set for the following month. This technology offers high performance at a competitive price compared to alternative solutions. Furthermore, it is set to be deployed in the fastest supercomputer globally at Oak Ridge National Laboratory. Various machine learning applications, including deep learning, computational fluid dynamics, video encoding, 3D graphics workstations, 3D rendering, visual effects, computational finance, seismic analysis, molecular modeling, and genomics, will benefit from this technology, along with other GPU workloads in server environments. The versatility of these applications demonstrates the broad impact of persistence container technology across different scientific and computational fields.

Business intelligence in the global biopharmaceutical sector focuses on drug patent dynamics and the entry of generics. It is essential to forecast future budget needs and proactively seek out generic alternatives. Analyzing the achievements of past patent challengers provides insights into the competitive landscape and informs research directions. This analysis plays a crucial role in guiding portfolio management strategies for upcoming drug development projects. Additionally, anticipating the expiration of patents on branded drugs, pinpointing potential generic suppliers, and managing branded drug inventory effectively are vital. Furthermore, acquiring detailed formulation and manufacturing data helps in identifying key formulators, repackagers, and relabelers to streamline operations and enhance market positioning. Understanding these elements can significantly bolster strategic decision-making in the biopharmaceutical industry.

Efficiently address tissue heterogeneity and the intricacies of microenvironments using the GeoMx Digital Spatial Profiler (DSP), which stands out as the most versatile and powerful spatial multi-omic platform for examining both FFPE and fresh frozen tissue sections. Unique among spatial biology platforms, GeoMx allows for non-destructive profiling of RNA and protein expression across various tissue compartments and cell populations, supported by an automated and scalable workflow that seamlessly integrates with conventional histology staining. You can spatially profile the entire transcriptome along with over 570 protein targets, either separately or concurrently, utilizing sample inputs such as whole tissue sections, tissue microarrays (TMAs), or organoids. By choosing GeoMx DSP, you position yourself at the forefront of spatial biology for effective biomarker discovery and hypothesis validation. With the ability to determine the relevant boundaries, you can rely on biology-driven profiling that enables you to focus on the tissue microenvironments and cell types that hold the most significance for your research. This innovative approach ensures that your analyses are both comprehensive and tailored to the specific biological contexts of interest.

Combinatorial barcoding technology revolutionizes the outdated limitations of traditional single-cell methodologies. By eliminating the need for specialized instruments, it empowers researchers to make groundbreaking discoveries with ease. This innovation allows for the profiling of anywhere from 1,000 to 1 million cells or nuclei in a single experiment, driving forward unparalleled advancements in science. Evercode combinatorial barcoding technology significantly outperforms droplet-based methods, enabling researchers to increase the scale of their experiments without the constraints of previous technologies. Enjoy enhanced data quality while avoiding the complexities and requirements of outdated hardware. Conduct single-cell experiments using only a pipette and standard laboratory tools, simplifying the process and making it more accessible. The split-pool combinatorial barcoding technique facilitates scalable single-cell analysis without relying on any specialized instruments, making it easier than ever to achieve scalable sequencing. Each kit includes a comprehensive set of reagents and user-friendly analysis software, streamlining the entire workflow from start to finish for optimal efficiency. This technology not only enhances research capabilities but also fosters a new era of accessibility in scientific exploration.

Dotmatics is the global leader in R&D scientific software that connects science, data, and decision-making. More than 2 million scientists and 10,000 customers trust Dotmatics to accelerate research and help make the world a healthier, cleaner, and safer place to live.

We are at the forefront of precision medicine, alleviating the strain on healthcare systems through our innovative automated analysis, diagnosis, and treatment solutions that cater to healthcare providers and patients globally. Congenica emerged from groundbreaking research conducted at the Wellcome Sanger Institute and the UK's National Health Service. Our offerings integrate cutting-edge technology, top-tier automation, and artificial intelligence, allowing our distinct platform to be utilized across various human diseases where genomic information plays a crucial role in revealing actionable insights. As a digital health company, we specialize in software and solutions designed for the large-scale analysis and interpretation of genomic data. Our fully automated system, enhanced with robust APIs and machine learning capabilities, aims to lighten the load on specialist staff, improve case processing efficiency, speed up decision-making, and simplify reporting. Our platform is certified, accurate, and secure, empowering clinical decisions with the utmost confidence in the resulting clinical outcomes, and we continuously strive to innovate and expand our capabilities to meet the evolving needs of the healthcare landscape.

Revolutionize the fields of drug discovery and materials research through cutting-edge molecular modeling techniques. Our computational platform, grounded in physics, combines unique solutions for predictive modeling, data analysis, and collaboration, facilitating swift navigation of chemical space. This innovative platform is employed by leading industries globally, serving both drug discovery initiatives and materials science applications across various sectors including aerospace, energy, semiconductors, and electronic displays. It drives our internal drug discovery projects, overseeing processes from target identification through hit discovery and lead optimization. Additionally, it enhances our collaborative research efforts aimed at creating groundbreaking medicines to address significant public health challenges. With a dedicated team of over 150 Ph.D. scientists, we commit substantial resources to research and development. Our contributions to the scientific community include more than 400 peer-reviewed publications that validate the efficacy of our physics-based methodologies, and we remain at the forefront of advancing computational modeling techniques. We are steadfast in our mission to innovate and expand the possibilities within our field.

AI-powered drug discovery is a proven technology. Cerella extracts hidden insights from your drug discovery data to reveal the best compounds and most valuable experiment for your project. It can make confident predictions by accurately filling in the missing values. This is especially useful for expensive downstream experiments, which are impossible to predict using other methods. This allows you to do more with sparse and limited data sets.

Transform your single-cell RNA sequencing data into actionable insights using Cellenics software, which is hosted by Biomage as a community instance of this open-source analytics tool developed at Harvard Medical School. This platform empowers biologists to delve into single-cell datasets without the need for coding, while facilitating collaboration between scientists and bioinformaticians. Within just a few hours, it can convert count matrices into publication-ready figures, integrating effortlessly into your existing workflow. Cellenics is designed to be fast, interactive, and user-friendly, as well as being cloud-based, secure, and scalable to meet various research needs. The community instance provided by Biomage is available at no cost for academic researchers working with smaller to medium-sized datasets, accommodating up to 500,000 cells. Currently, over 3000 academic researchers engaged in studies related to cancer, cardiovascular health, and developmental biology are utilizing this powerful tool. This collaborative environment not only enhances research capabilities but also accelerates the discovery process in various scientific fields.

The process of introducing a new medication to the market, starting from initial development to the final launch, is both time-intensive and heavily regulated, often spanning over a decade or more. Achieving success in this endeavor hinges on the timely availability of precise analytical data, which is essential for making informed decisions during the early stages of development and reducing the likelihood of setbacks later on. Modern drug development primarily follows a systematic approach, with the crucial first step usually being the identification of a biological target to concentrate efforts on. This target identification demands a comprehensive understanding of the characteristics of the candidates, enabling swift and reliable identification of the most promising options. After establishing a biological target, the next significant hurdle is identifying the most advantageous lead molecules, which entails discovering potential drug candidates—these may include small organic compounds or biological constructs with therapeutic capabilities. Thus, the entire journey from concept to market is a complex interplay of scientific insight and strategic decision-making.

We have established ourselves as frontrunners in the fields of ADMET property prediction, physiologically-based pharmacokinetics (PBPK) modeling, pharmacometrics, and quantitative systems pharmacology/toxicology, a status achieved through the achievements our clients have experienced while partnering with us. Leveraging over two decades of expertise, our skilled team excels at transforming complex scientific concepts into accessible software solutions, while also offering specialized consulting services that bolster drug discovery, clinical development research, and regulatory submission processes. Our dedication to client success drives our continuous improvement and innovation in these critical areas.

CDD Vault allows you to intuitively organize chemical structures, biological study data, as well as collaborate with external or internal partners via a simple web interface. Start a free trial to see how easy it can be to manage drug discovery data. Tailored for You Affordable Scales with your project team Activity & Registration * Electronic Lab Notebook * Visualization * Inventory * APIs

BigOmics Analytics is an innovative startup focused on biodata analytics, creating platforms that empower biologists to effectively visualize and interpret their omics data. Our primary offering, Omics Playground, is a highly intuitive bioinformatics tool tailored for RNA-seq and proteomics, enabling users to store their experimental data and visualize it interactively. With more than 18 interactive analysis modules and over 150 dynamic plots, the platform supports co-analysis with a vast array of more than 6,000 public datasets, in addition to providing access to more than 50,000 public gene sets and pathways. Furthermore, it seamlessly incorporates drug connectivity and drug sensitivity databases, featuring an extensive collection of over 30,000 drug expression profiles. BigOmics Analytics is designed to promote collaboration between biologists and bioinformaticians, allowing users to uncover insights while minimizing the time spent on data analysis, all without the need for any programming knowledge. The platform's commitment to producing reliable and reproducible results is achieved through the implementation of state-of-the-art methodologies. Ultimately, BigOmics Analytics is revolutionizing the way biological data is analyzed and understood.

Cufflinks is a software tool that compiles transcripts, estimates their levels of abundance, and evaluates differential expression and regulation in RNA-Seq datasets. By accepting aligned RNA-Seq reads, it organizes these alignments into a streamlined representation of transcripts. The software then assesses the relative abundances of these transcripts based on the number of supporting reads, while also factoring in potential biases from library preparation methods. Initially created through a collaboration with the Laboratory for Mathematical and Computational Biology, Cufflinks aims to simplify the installation process by offering several binary packages that alleviate the often cumbersome task of building the software from source, which necessitates the installation of various libraries. This toolset encompasses multiple utilities tailored for analyzing RNA-Seq experiments, with some functionalities available independently and others designed to fit into a more comprehensive workflow. Overall, Cufflinks serves as a vital resource for researchers in the field of genomics, enhancing their ability to interpret RNA-Seq data effectively.

LiveDesign serves as an integrated informatics solution that empowers teams to accelerate their drug discovery initiatives through collaborative design, experimentation, analysis, tracking, and reporting on a unified platform. It allows for the collection of innovative ideas alongside experimental and modeling data seamlessly. Users can develop and archive new virtual compounds within a centralized repository, assess them with sophisticated models, and prioritize the most promising designs. By merging biological data and model outputs from various corporate databases, the platform leverages advanced cheminformatics to provide a comprehensive analysis of all information simultaneously, facilitating quicker compound development. The platform employs cutting-edge physics-based methodologies along with machine learning to enhance prediction accuracy significantly. Teams can collaborate in real-time, regardless of location, enabling them to share concepts, conduct tests, make revisions, and progress chemical series while maintaining a clear record of their work. This not only fosters innovation but also ensures that projects remain organized and efficient throughout the drug discovery process.

Evo 2 represents a cutting-edge genomic foundation model that excels in making predictions and designing tasks related to DNA, RNA, and proteins. It employs an advanced deep learning architecture that allows for the modeling of biological sequences with single-nucleotide accuracy, achieving impressive scaling of both compute and memory resources as the context length increases. With a robust training of 40 billion parameters and a context length of 1 megabase, Evo 2 has analyzed over 9 trillion nucleotides sourced from a variety of eukaryotic and prokaryotic genomes. This extensive dataset facilitates Evo 2's ability to conduct zero-shot function predictions across various biological types, including DNA, RNA, and proteins, while also being capable of generating innovative sequences that maintain a plausible genomic structure. The model's versatility has been showcased through its effectiveness in designing operational CRISPR systems and in the identification of mutations that could lead to diseases in human genes. Furthermore, Evo 2 is available to the public on Arc's GitHub repository, and it is also incorporated into the NVIDIA BioNeMo framework, enhancing its accessibility for researchers and developers alike. Its integration into existing platforms signifies a major step forward for genomic modeling and analysis.