Alternatives to Recursion
Compare Recursion alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to Recursion in 2026. Compare features, ratings, user reviews, pricing, and more from Recursion competitors and alternatives in order to make an informed decision for your business.
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SYNTHIA Retrosynthesis Software
Merck KGaA
Expert-coded by chemists and engineered by computer scientists, SYNTHIA™ Retrosynthesis Software enables scientists to quickly find and easily navigate innovative and novel pathways for novel and published target molecules. Quickly and efficiently scan hundreds of pathways to help you identify the best option according to your needs. Explore the most cost-effective routes to your target molecules with state of the art visualization and filtering options. Easily customize search parameters to eliminate or promote reactions, reagents or classes of molecules. Explore unique and innovative syntheses that may be unknown for building your desired molecule. Easily generate a list of commercially available starting materials for your synthesis. Benefit from ISO/IEC 27001 Information Security Certification to guarantee the confidentiality, integrity, and protection of your data.Starting Price: €0 / 30 days -
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ClinCapture
ClinCapture
At ClinCapture our mission is to build software that saves lives. Our technology lowers the cost of clinical trials by streamlining data capture processes while providing a platform that protects patient privacy. Clincapture advances the evaluation and development of drugs, biologics, and devices that demonstrate promise for the diagnosis and/or treatment of a wide range of diseases or medical conditions. -
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BenevolentAI
BenevolentAI
BenevolentAI is an AI-enabled drug discovery platform and scientific technology company that unites advanced artificial intelligence, machine learning, and domain-specific science to accelerate the discovery, design, and development of new medicines for complex diseases by making sense of vast, diverse biomedical data and generating actionable scientific insights faster than traditional methods. Its proprietary Benevolent Platform ingests and harmonizes structured and unstructured biomedical information, including literature, genomics, clinical information, and multi-omics data, into a comprehensive knowledge graph, enabling scientists to reason across biological systems, generate hypotheses, predict novel drug targets, and design candidate molecules with higher confidence and lower failure rates. -
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Causaly
Causaly
Leverage the power of AI to expedite the journey from bench research and laboratory insights to the launch of life-changing therapies. Gain up to 90% in research productivity by reducing your reading time from months to minutes. Cut through the noise with a high-precision, high-accuracy search to navigate the ever-growing volume of scientific literature with ease. Save time, reduce bias and increase odds of novel discoveries. Deeply explore disease biology and conduct advanced target discovery. Causaly’s high-precision knowledge graph consolidates evidence from millions of publications, making deep, unbiased scientific exploration possible. Rapidly navigate biological cause-and-effect relationships without being an expert. Get a view of all scientific documents and uncover hidden connections. Causaly’s powerful AI machine reads millions of published biomedical literature to support better decision-making and research outcomes. -
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NVIDIA Clara
NVIDIA
Clara’s domain-specific tools, AI pre-trained models, and accelerated applications are enabling AI breakthroughs in numerous fields, including medical devices, imaging, drug discovery, and genomics. Explore the end-to-end pipeline of medical device development and deployment with the Holoscan platform. Build containerized AI apps with the Holoscan SDK and MONAI, and streamline deployment in next-generation AI devices with the NVIDIA IGX developer kits. The NVIDIA Holoscan SDK includes healthcare-specific acceleration libraries, pre-trained AI models, and reference applications for computational medical devices. -
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Genedata Biologics
Genedata
Genedata Biologics® streamlines discovery of biotherapeutics including bispecifics, ADCs, TCRs, CAR-Ts, and AAVs. The most widely adopted platform across the industry, it integrates all discovery workflows so you can focus on true innovation. Accelerate research with a first-in-class platform uniquely designed from the start to digitalize biotherapeutic discovery. The platform facilitates complex R&D processes by designing, tracking, testing, and assessing novel biotherapeutics drugs. It works with any format, from antibodies, bi- or multi-specifics, ADCs, novel scaffolds, and therapeutic proteins, to engineered therapeutic cell lines such as TCRs and CAR-T cells. Acting as a central end-to-end data backbone, Genedata Biologics integrates all R&D processes, from library design and immunizations, selections and panning, molecular biology, screening, protein engineering, expression, purification, and protein analytics, to candidate developability and manufacturability assessments. -
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Healnet
Healx
Rare diseases are often not well studied and there is a limited understanding of many of the aspects necessary to support a drug discovery program. Our AI platform, Healnet, overcomes these challenges by analyzing millions of drug and disease data points to find novel connections that could be turned into new treatment opportunities. By applying frontier technologies across the discovery and development pipeline, we can run multiple stages in parallel and at scale. One disease, one target, one drug: it's an overly simple model, yet it's the one used by nearly all pharmaceutical companies. The next generation of drug discovery is AI-powered, parallel and hypothesis-free. Bringing together the key three drug discovery paradigms. -
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Evo 2
Arc Institute
Evo 2 is a genomic foundation model capable of generalist prediction and design tasks across DNA, RNA, and proteins. It utilizes a frontier deep learning architecture to model biological sequences at single-nucleotide resolution, achieving near-linear scaling of compute and memory relative to context length. Trained with 40 billion parameters and a 1 megabase context length, Evo 2 processes over 9 trillion nucleotides from diverse eukaryotic and prokaryotic genomes. This extensive training enables Evo 2 to perform zero-shot function prediction across multiple biological modalities, including DNA, RNA, and proteins, and to generate novel sequences with plausible genomic architecture. The model's capabilities have been demonstrated in tasks such as designing functional CRISPR systems and predicting disease-causing mutations in human genes. Evo 2 is publicly accessible via Arc's GitHub repository and is integrated into the NVIDIA BioNeMo framework. -
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Genomenon
Genomenon
Pharma companies need comprehensive genomic information to drive successful precision medicine programs, but decisions are often made using only a fraction of the data available, about 10%. Genomenon delivers 100% of the data. An efficient and cost-effective natural history research solution for pharma, ProdigyTM Patient Landscapes support the development of rare disease therapies by enhancing insights contained in retrospective and prospective health data. Using a powerful AI-driven approach, Genomenon delivers a comprehensive and expert assessment of every patient in the published medical literature, in a fraction of the time. Don’t miss anything, get insight into every genomic biomarker published in the medical literature. Every scientific assertion is supported by empirical evidence from the medical literature. Identify all genetic drivers and pinpoint which variants are known to be pathogenic according to ACMG clinical standards. -
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BIOiSIM
VERISIMLife
BIOiSIMTM is a first-in-class 'virtual drug development engine' that offers unprecedented value for the drug development industry by narrowing down the number of drug compounds that offer anticipated value for the treatment or cure of specific illnesses or diseases. We offer a range of translational-based solutions, customized for your pre-clinical and clinical programs. These offerings are all centered around our proven and validated BIOiSIMTM platform for small molecules, large molecules, and viruses. Our models are built on data from thousands of compounds across 7 species, leading to robustness rarely seen in the industry. With a focus on human outcomes, the platform has at its core a translatability engine that transforms insights across species. The BIOiSIMTM platform can be used before the preclinical animal trial start, allowing earlier insights and savings in expensive outsourced experimentation. -
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NVIDIA BioNeMo
NVIDIA
BioNeMo is an AI-powered drug discovery cloud service and framework built on NVIDIA NeMo Megatron for training and deploying large biomolecular transformer AI models at a supercomputing scale. The service includes pre-trained large language models (LLMs) and native support for common file formats for proteins, DNA, RNA, and chemistry, providing data loaders for SMILES for molecular structures and FASTA for amino acid and nucleotide sequences. The BioNeMo framework will also be available for download for running on your own infrastructure. ESM-1, based on Meta AI’s state-of-the-art ESM-1b, and ProtT5 are transformer-based protein language models that can be used to generate learned embeddings for tasks like protein structure and property prediction. OpenFold, a deep learning model for 3D structure prediction of novel protein sequences, will be available in BioNeMo service. -
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AlphaFold
DeepMind
These exquisite, intricate machines are proteins. They underpin not just the biological processes in your body but every biological process in every living thing. They’re the building blocks of life. Currently, there are around 100 million known distinct proteins, with many more found every year. Each one has a unique 3D shape that determines how it works and what it does. But figuring out the exact structure of a protein remains an expensive and often time-consuming process, meaning we only know the exact 3D structure of a tiny fraction of the proteins known to science. Finding a way to close this rapidly expanding gap and predict the structure of millions of unknown proteins could not only help us tackle disease and more quickly find new medicines but perhaps also unlock the mysteries of how life itself works. -
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BioSymetrics
BioSymetrics
We integrate clinical and experimental data using machine learning to navigate human disease biology and advance precision medicines. Our patent-pending Contingent AI™ understands relationships within the data to provide sophisticated insights. We address data bias by iterating on machine learning models based upon decisions made in the pre-processing and feature engineering stages. We leverage zebrafish, cellular and other phenotypic animal models to validate in silico predictions in vivo experiments and genetically modify them in vitro and in vivo, to improve translation. Using active learning and computer vision on validated models for cardiac, central nervous system and rare disorders, we rapidly incorporate new data into our machine learning models. -
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Atomwise
Atomwise
We use our AI engine to transform drug discovery. Our discoveries help create better medicines faster. Our AI-enabled discovery portfolio includes wholly-owned and co-developed pipeline assets, and is backed by prominent investors. Atomwise developed a machine-learning-based discovery engine that combines the power of convolutional neural networks with massive chemical libraries to discover new small-molecule medicines. The secret to reinventing drug discovery with AI is people. We are dedicated to developing the best AI platform and using it to transform small molecule drug discovery. We have to tackle the most challenging, seemingly impossible targets and streamline the drug discovery process to give drug developers more shots on goal. Computational efficiency enables screening of trillions of compounds in silico, increasing the likelihood of success. Demonstrated exquisite model accuracy, overcoming the challenge of false positives. -
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BIOVIA Discovery Studio
Dassault Systèmes
Today’s biopharmaceutical industry is marked by complexity: growing market demands for improved specificity and safety, novel treatment classes and more intricate mechanisms of disease. Keeping up with this complexity requires a deeper understanding of therapeutic behavior. Modeling and simulation methods provide a unique means to explore biological and physicochemical processes down to the atomic level. This can guide physical experimentation, accelerating the discovery and development process. BIOVIA Discovery Studio brings together over 30 years of peer-reviewed research and world-class in silico techniques such as molecular mechanics, free energy calculations, biotherapeutics developability and more into a common environment. It provides researchers with a complete toolset to explore the nuances of protein chemistry and catalyze discovery of small and large molecule therapeutics from Target ID to Lead Optimization. -
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Mass Dynamics
Mass Dynamics
Discover biological biomarkers, create insights into disease mechanisms, discover new drugs or identify changes in protein levels from a set of carefully designed experiments. We’ve made it easy to start unlocking the power of MS and Proteomics so you can focus on the biological complexity and move closer to the moment of discovery. Our automated and repeatable workflow allows for quicker experiment startup and turnaround times, giving you the control and flexibility to make and act on decisions in the moment. Allowing you to focus on biological insights and human-to-human collaboration, our proteomics data processing workflow is built to scale, repeatedly. We’ve pushed heavy and repetitive processing to the cloud, enabling a seamless and enjoyable experience. Our intelligent Proteomics workflow seamlessly integrates complex moving parts to enable larger experiments to be processed and analyzed with ease. -
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AIDDISON
Merck KGaA
AIDDISON™ drug discovery software combines the power of artificial intelligence (AI), machine learning (ML), and 3D computer-aided drug design (CADD) methods to act as a valuable toolkit for medicinal chemistry needs. As a unified platform for efficient and effective ligand-based and structure-based drug design, it integrates all the facets for virtual screening and supports methods for in-silico lead discovery and lead optimization. -
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DNAnexus Apollo
DNAnexus
DNAnexus Apollo™ accelerates precision drug discovery by unlocking the power of collaboration to draw critical insights from omics data. Precision drug discovery requires collecting and analyzing huge volumes of omics and clinical data. These datasets are incredibly rich resources, but most legacy and home-grown informatics tools can't cope with their size and complexity. Precision medicine programs can also be hampered by siloed data sources, underpowered collaboration tools, and the burden of complex and always changing regulatory and security requirements. DNAnexus Apollo™ supports precision drug discovery programs by empowering scientists and clinicians to explore and analyze omics and clinical data together, in a single environment, built on a robust, scalable cloud platform. Apollo lets them share data, tools, and analyses easily and securely with peers and collaborators everywhere - whether they're on another floor, or another continent. -
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Bruker Drug Discovery
Bruker
Bringing a new drug into the market, from the first step to the final market introduction, is a time-consuming, highly regulated, and expensive process, which can take a decade or more. Final success crucially depends on the early availability of accurate analytical results, fast enough for taking the right decisions at the beginning of the development and minimizing late attrition rates. Today’s drug development is mainly based on a rational approach where typically establishing the biological target to focus on is the first key step. This target identification requires a deep understanding of the candidates´ properties to identify the most promising ones as quickly and reliable as possible. Once a biological target has been established, finding the most promising lead molecules is often seen as the next challenge. Typically, lead discovery is the identification of potential drug candidates – either small organic molecules or biologic assemblies with therapeutic potential. -
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Eidogen-Sertanty Target Informatics Platform (TIP)
Eidogen-Sertanty
Eidogen-Sertanty's Target Informatics Platform (TIP) is the world's first structural informatics system and knowledgebase that enables researchers with the ability to interrogate the druggable genome from a structural perspective. TIP amplifies the rapidly expanding body of experimental protein structure information and transforms structure-based drug discovery from a low-throughput, data-scarce discipline into a high-throughput, data-rich science. Designed to help bridge the knowledge gap between bioinformatics and cheminformatics, TIP supplies drug discovery researchers with a knowledge base of information that is both distinct from and highly complementary to information furnished by existing bio- and cheminformatics platforms. TIP's seamless integration of structural data management technology with unique target-to-lead calculation and analysis capabilities enhances all stages of the discovery pipeline. -
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Kanteron
Kanteron Systems
Kanteron Platform ingested medical images, digital pathology slides, genomics sequences, and patient data from modalities, scanners, sequencers and databases, and provided a complete data toolkit to every team in hospital networks. Pharmacogenomics for adverse medication event prevention, and Precision Medicine application at the point of care: Incorporates sources of drug-gene interaction data that were previously only available in in accessible formats (e.g. tables in a PDF document), implementing the major Pharmacogenomic databases (like PharmGKB, CGI, DGIdb, OpenTargets...) Allows the user to refine their query to certain gene families, types of interactions, classes of drugs, etc. Flexible AI means you can choose the data set that best fits your use case, and apply it to your relevant medical images. -
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Scitara DLX
Scitara
Scitara DLX™ offers a rapid connectivity infrastructure for any instrument in the life science laboratory in a fully compliant and auditable cloud-based platform. Scitara DLX™ is a universal digital data infrastructure that connects any instrument, resource, app and software in the laboratory. The cloud-based, fully auditable platform connects all data sources across the lab, allowing the free flow of data across multiple end points. This allows scientists to devote their time to scientific research, not waste it solving data issues. DLX curates and corrects data in flight to support the development of accurate, properly structured data models that feed AI and ML systems. This supports a successful digital transformation strategy in the pharma and biopharma industries. Unlocking insights from scientific data enables faster decision-making in drug discovery and development, helping bring drugs to market more quickly. -
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SOPHiA GENETICS
SOPHiA GENETICS
Our global data-sharing network generates clinically actionable insights from data to improve patient outcomes worldwide. SOPHiA GENETICS’ mission is to build the future of AI-assisted medicine. We are integrating multimodal healthcare-omics data, unlocking the existing data silos, and developing machine learning models to produce actionable insights that could eventually support healthcare professionals to improve patient outcomes. The revamped interface, new features, and cutting-edge capabilities are set to further accelerate precision medicine workflows, bringing us another step closer to democratizing data-driven medicine. Powered by AI and machine learning (ML), our global cloud-based platform provides a safe, secure, and instantly accessible environment to standardize, compute, and analyze digital health data, generating insights from complex multimodal data sets that have the potential to improve diagnosis, therapy selection, analysis, and drug development. -
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Schrödinger
Schrödinger
Transform drug discovery and materials research with advanced molecular modeling. Our physics-based computational platform integrates differentiated solutions for predictive modeling, data analytics, and collaboration to enable rapid exploration of chemical space. Our platform is deployed by industry leaders worldwide for drug discovery, as well as for materials science in fields as diverse as aerospace, energy, semiconductors, and electronics displays. The platform powers our own drug discovery efforts, from target identification to hit discovery to lead optimization. It also drives our research collaborations to develop novel medicines for critical public health needs. With more than 150 Ph.D. scientists on our team, we invest heavily in R&D. We’ve published over 400 peer-reviewed papers that demonstrate the strength of our physics-based approaches, and we’re continually pushing the limits of computer modeling. -
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Genospace
Genospace
At Genospace, we understand that genomics is driving the development of precision medicine, yet scaling its delivery is an unsolved challenge. We’re here to help. Our platform is designed to make biomedical data meaningful and accessible to everyone, especially those on the front lines of care delivery. Arm your clinicians and researchers with the information they need to make informed decisions and join us in our mission of leveraging high-dimensional molecular data to improve individual patient outcomes and accelerate drug development and research. Large-scale population data is necessary for drug development and research. Conduct cohort-driven analyses to inform your research activities with the Genospace platform. We specialize in clinical trial research. Use the Genospace platform to match fragmented patient data to complex trial criteria and expedite patient accruals. Integrate genomic medicine into mainstream clinical care with the Genospace platform. -
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NVIDIA Parabricks
NVIDIA
NVIDIA® Parabricks® is the only GPU-accelerated suite of genomic analysis applications that delivers fast and accurate analysis of genomes and exomes for sequencing centers, clinical teams, genomics researchers, and high-throughput sequencing instrument developers. NVIDIA Parabricks provides GPU-accelerated versions of tools used every day by computational biologists and bioinformaticians—enabling significantly faster runtimes, workflow scalability, and lower compute costs. From FastQ to Variant Call Format (VCF), NVIDIA Parabricks accelerates runtimes across a series of hardware configurations with NVIDIA A100 Tensor Core GPUs. Genomic researchers can experience acceleration across every step of their analysis workflows, from alignment to sorting to variant calling. When more GPUs are used, a near-linear scaling in compute time is observed compared to CPU-only systems, allowing up to 107X acceleration. -
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BLooP
BLooP
Welcome to the Dictionary of Programming Languages, a compendium of computer coding methods assembled to provide information and aid your appreciation for computer science history. BLooP was a very simple recursive block structured language invented by Douglas Hofstadter for his book Godel, Escher, Bach. It features simple subroutine structure, very simple number and boolean handling, and recursion. The interesting aspect of BLooP was that it offered only bounded loop constructs, and was therefore incapable of expressing certain general recursive computations.Starting Price: Free -
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CDD Vault
Collaborative Drug Discovery
With CDD Vault, you can intuitively organize chemical structures and biological study data, and collaborate with internal or external partners through an easy to use web interface. Start your free trial and see first hand how easy it is to manage drug discovery data. Tailored for you Affordable Scales with your project team(s) Activity & Registration * Electronic Lab Notebook (ELN) * Visualization * Inventory * APIs * Secure Online Hosting -
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LiveDesign
Schrödinger
LiveDesign is an enterprise informatics platform that enables teams to rapidly advance drug discovery projects by collaborating, designing, experimenting, analyzing, tracking, and reporting in a centralized platform. Capture ideas alongside experimental and modeling data. Create and store new virtual compounds in a centralized database, evaluate through advanced models, and prioritize new designs. Integrate biological data and model results across federated corporate databases, apply sophisticated cheminformatics to analyze all data at once, and progress compounds faster. Drive predictions and designs using advanced physics-based methods paired with machine learning techniques to rapidly improve prediction accuracy. Work together with remote team members in real-time. Share ideas, test, revise, and advance chemical series without losing track of your work. -
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IPA can also be used for analysis of small-scale experiments that generate gene and chemical lists. IPA allows searches for targeted information on genes, proteins, chemicals, and drugs, and building of interactive models of experimental systems. Data analysis and search capabilities help in understanding the significance of data, specific targets, or candidate biomarkers in the context of larger biological or chemical systems. The software is backed by the Ingenuity Knowledge Base of highly structured, detail-rich biological and chemical findings. Learn more about QIAGEN Ingenuity Pathway Analysis (IPA). Comparison Analysis determines the most significant pathways, upstream regulators, diseases, biological functions, and more, across time points, dose, or other conditions.
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SpliceCore
Envisagenics
Using RNA sequencing (RNA-seq) data and Artificial Intelligence are both a necessity and an opportunity to develop therapeutics that target splicing errors. The use of machine learning enables us to discover new splicing errors and quickly design therapeutic compounds to correct them. SpliceCore is our dedicated AI platform for RNA therapeutics discovery. We developed this technology platform specifically for the analysis of RNA sequencing data. It can identify, test and validate hypothetical drug targets faster than traditional methods. At the heart of SpliceCore is our proprietary database of more than 5 million potential RNA splicing errors. It is the largest database of splicing errors in the world and it is used to test every RNA sequencing dataset that is input for analysis. Scalable cloud computing enables us to process massive amounts of RNA sequencing data efficiently, at higher speed and lower cost, exponentially accelerating therapeutic innovation. -
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3decision
Discngine
3decision® is a cloud-based protein structure repository designed for comprehensive structural data management and advanced analytics, enabling small molecule and biologics discovery teams to accelerate structure-based drug design. It centralizes and standardizes experimental and in-silico protein structures from public sources like RCSB PDB and AlphaFoldDB, as well as proprietary data, supporting formats like PDBx/mmCIF and ModelCIF. This ensures easy access to X-Ray, NMR, cryo-EM, and modeled structures, fostering collaboration and enhancing research efforts. Beyond storage, 3decision® enriches entries with metadata and sequence information, including protein-ligand interactions, antibody annotations, and binding site details. Advanced analytical tools identify druggable sites, assess off-target risks, and enable binding site comparisons, transforming vast structural data into actionable knowledge. Its cloud-based platform facilitates collaboration among research teams. -
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Owkin
Owkin
Patients from around the world suffer from complex diseases and a staggering variety of symptoms. However, they share one thing in common: Patients have a need for faster development of safer and more effective therapies. Owkin’s mission is to empower researchers in hospitals, universities, and pharmaceutical companies to: understand why drug efficacy varies from patient to patient, enhance the drug development process, and identify the best drug for the right patient to improve treatment outcomes. Owkin Loop is the foundation of Owkin’s research platform: it connects medical researchers with high-quality datasets from leading academic research centers around the world. Owkin Loop is powered by the two main components of Owkin’s Software Stack: Owkin Studio, our machine learning platform, and Owkin Connect, our federated learning framework. Owkin medical research collaborations are in Oncology, Immunology and Cardiovascular diseases. -
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Correlation Engine
Illumina
Correlation Engine is an interactive omics knowledgebase that puts private omics data in a biological context with highly curated public data. One of the largest biological databases in the world, Correlation Engine provides life science researchers with unprecedented access to vast numbers of high-quality whole-genome analyses and insightful scientific tools. The knowledgebase enables novel discoveries by interrogating billions of data points derived from standardized analyses of whole genome studies. A suite of applications to determine biological context, a continually growing library of curated data sets, and support for multiple species and multi-omic datasets. Utilize a simple graphical user interface to leverage guided workflows, push-button applications, and APIs. Accelerate your journey from omic data to decision and get access to over 25,000 multi-omics studies (from over 250,000 signatures) that have been reanalyzed. -
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Mesh Bio
Mesh Bio
Based on proven medical science and explainable systems biology, DARA enables and enhances clinical decision support and intervention guidance. We work with healthcare providers and stakeholders to provide digital solutions that transform health screening and chronic disease management. We enable digital transformation of care delivery through clinical workflow automation and predictive analytics, built on gold standard clinical guidelines and best practices. We help physicians engage with patients better by providing actionable health insights through personalized disease risk and adverse event predictions. We guide pharmaceutical development by revealing pharmacodynamics in complex biological processes and find novel therapeutic interventions. Predictive analytics on multidimensional patient data will enable personalized precision medicine in the management of cardiometabolic disease to prevent catastrophic patient outcomes. -
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Aiforia
Aiforia
Aiforia equips pathologists and scientists in preclinical and clinical labs with powerful deep learning and cloud-based technology to advance their image analysis tasks and workflows. From empowering researchers in the identification of novel biomarkers of disease, and supporting R&D scientists in speeding up the time-to-market of novel drugs, to helping pathologists enhance the accuracy of cancer diagnostics, Aiforia has the expertise and experience to transform healthcare all the way from discovery to diagnosis. For clinical pathology labs aiming to increase productivity and improve diagnostic accuracy, the Aiforia Clinical Suites offer a portfolio of tools for AI-supported diagnostics, intelligent visualization, QC, and automated pre- and post-screening. We are currently developing Suites for some of the world’s most prevalent cancers and have CE-IVD marking for AI models in lung and breast cancer. -
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VSClinical
Golden Helix
VSClinical allows for the clinical interpretation of variants based on ACMG & AMP guidelines. The VSClinical guided workflow enables following the American College of Medical Genetics (ACMG) guidelines used to identify and classify causal variants for inherited disease risk, cancer predisposition, and the diagnosis of rare diseases. The ACMG/AMP joint guidelines for variant interpretation provide a set of criteria to score variants and place them into one of five classification tiers. Following the guidelines requires deep diving into the annotations, genomic context, and existing clinical assertions about every variant. VSClinical provides a tailored workflow to score each relevant criterion while also providing all the bioinformatic, literature and evidence from clinical knowledgebases to assist in the scoring and interpretation process. VSClinical is designed to allow variant scientists to efficiently process variants. -
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Kaleido
Kaleido
The microbiome is implicated in numerous diseases and health conditions. Learn how Kaleido is leading a differentiated approach to translating the promise of the microbiome into solutions for patients. The human microbiome is a community of more than 30 trillion microbes, organisms that include bacteria, viruses, archaea and fungi, which reside on and inside the human body. Over the last decade, research has increased exponentially on the impact the microbiome has on human health, including cardiovascular disease, cancer, diabetes, Parkinson’s disease and allergies. This highly complex microbial ecosystem has been referred to as a “newly discovered organ.” Many other human organs command tens of billions of dollars for therapeutics that treat disease by modulating physiology. From a therapeutic perspective, the microbiome organ remains a largely untapped frontier in healthcare. -
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Reliant AI
Reliant AI
Accuracy, speed, confidence. Introducing generative AI to commercial biopharma. Simplify the labor-intensive process of collecting, organizing, and inspecting vast amounts of complex data. Get straight to decision-critical insights with 100% confidence, every time. With our AI-powered data manipulation and verification platform, you'll never lose track of your workstreams again. Gather, refine, and check your data, all in one place. Search public and private databases by key drug characteristics. Segment drugs and trials by detailed patient profiles. Extract the data you need in plain English. Support your findings by linking answers back to their source. Focus your time and energy on synthesizing high-quality outputs from data rather than menially sifting through it. Our specialized LLMs enable researchers to perform asset scans 4.8x faster than by hand. We index over 38M scientific publications, conference abstracts, and clinical trials. All the data you need, when you need it. -
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Ozette
Ozette
Our immune system drives our most important biological processes. It protects us from sickness and disease by defending against outside invaders like pathogens and keeping our internal systems in equilibrium. No two of us share exactly the same immune makeup, and each of our systems is constantly evolving. Mapping and studying this complexity in great detail unlock the insights that accelerate research and derive better therapies for all. For too long, single-cell data analysis has lagged behind the technology that generates these data. That’s because the standard manual workflows, limited in resolution and speed, only allow for a small amount of cellular information to be seen. Advances in medicine are driving us more and more toward highly targeted treatments, with many therapies at the forefront being constructed from the patient’s own immune cells. Our AI-driven computational analysis technology unlocks insights to discover therapies and advance their development. -
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Partek Flow
Partek
Partek bioinformatics software delivers powerful statistical and visualization tools in an easy-to-use interface. Researchers of all skill levels are empowered to explore genomic data quicker and easier than ever before. We turn data into discovery®. Pre-installed workflows and pipelines in our intuitive point-and-click interface make sophisticated NGS and array analysis attainable for any scientist. Custom and public statistical algorithms work in concert to easily and precisely distill NGS data into biological insights. Genome browser, Venn diagrams, heat maps, and other interactive visualizations reveal the biology of your next-generation sequencing and array data in brilliant color. Our Ph.D. scientists are always just a phone call away and ready to help with your NGS analysis any time you have questions. Designed specifically for the compute-intensive needs of next-generation sequencing applications with flexible installation and user management options. -
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Kray
Kray
Kray is a state of the art global illumination renderer that allows very fast and accurate rendering of scenes where indirect light plays important role. It includes the most advanced modern algorithms and optimizations to allow it to render full global illumination, reflections, refractions and caustics quickly on standard computers. Fast global illumination: light/photon mapping – biased, but very fast and not much dependent on number of ray recursions, path tracing – unbiased with serval sampling optimizations, irradiance caching – for fast, view independent, reusable GI solution storage, caustics. Light models: point/directional, line lights, area lights, background light, HDR image based lighting, lights pre sampling. Instancing: allows repeated re-use of the same geometry in multiply locations in the rendered scene with very low memory consumption, instanced geometry can be also instances, even self cloning is possible with user defined number of recursions.Starting Price: €70 per unit -
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FLooP
Ziring
FLooP was a very simple recursive block structured language invented by Douglas Hofstadter for his book Godel, Escher, Bach. It features a simple subroutine structure, very simple number and boolean handling, and recursion. Unlike its cousin BLooP, FLooP does support unbounded loops. This allows it to possess the full power of a Turing machine, thus making it fair game for various undecidability theorums. The syntax of FLooP is rather verbose but simple in structure. Though Hofstadter doesn't mention it in GEB, FLooP is similar to early exercises in exploring the computational model of "Random Access Machines". Note the use of 'CELL(0) <= 2' and similar constructs. Though FLooP was never intended to be more than an academic exercise, an implementation of FLooP in Perl was made. Unfortunately, I can't seem to find it. S - block-structured language type. -
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Edison Scientific
Edison Scientific
Edison Scientific is an AI platform designed to automate and accelerate scientific research, enabling users to move from hypothesis to validated results within a single environment. The platform integrates literature synthesis, data analysis, and molecular design workflows, allowing research teams to complete end-to-end scientific investigations at dramatically increased speed. At its core is Kosmos, an autonomous research system that performs hundreds of research tasks in parallel, transforming multimodal datasets into comprehensive reports with validated findings and publication-ready figures. Kosmos synthesizes scientific literature, public databases, and proprietary datasets, identifies novel therapeutic targets, uncovers biological mechanisms, and supports the iterative design and optimization of molecular candidates. Validated in real research settings, Kosmos has demonstrated the ability to achieve results that typically require months of human effort in a single day.Starting Price: $50 per month -
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DeLorean AI Medical AI
DeLorean AI
Medical AI is a true technology solution that comprehensively addresses chronic diseases. The hallmarks of this technology are its ability to predict, generate the next-best actions, and present the outputs in an easy-to-consume user experience. DeLorean Medical AI augments human capabilities and creates a future where we can trust both the machine and the human to make the best decisions. Our technology has been shown to improve outcomes and is the first AI to be biologically validated through third-party clinical tests. With the ability to better classify patient populations, assign risk, and predict disease state transitions, Medical AI directly leads to earlier detection and diagnosis of diseases. It can also reduce costs. Having been installed for 10+ clients, it has demonstrated both cost reductions and savings associated with real-time predictions to determine at-risk populations and next-best-action recommendations based on statistical probabilities. -
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ProxiTrak
ProxiTrak
Synchronizes data communications between assets, eliminating human error, and allowing faster and more efficient decision-making based on real-time data. Simplifying and improving the deployment and maintenance process of the Industrial IoT system cost-effectively. It allows businesses full creative control by allowing the creation, recursive modification, and optimization of a virtual RFID tracking infrastructure. The Computer-Aided Design (CAD) predictive modeling engine provides a visual representation of your RFID tracking domain. This serves as the backbone for your key RFID terrain that is rendered live to present real-time tag, data, events, actions, transitions, and metrics globally that are not point-in-time discovery (PITD). -
47
Cerella
Optibrium
Proven AI-powered drug discovery. Cerella creates new value from your drug discovery data, revealing hidden insights into the best compounds and most valuable experiments for your project. It makes confident predictions, accurately filling in missing values, especially for expensive downstream experiments that can’t be predicted by other methods. This enables you to do more, even with sparse, limited data sets. -
48
Pluto
Pluto Biosciences
Since its founding in 2021 from the Wyss Institute at Harvard University, Pluto has become a trusted partner of life sciences organizations around the country ranging from biotech start-ups to public biopharma companies. Our cloud-based platform gives scientists the ability to manage all of their data, run bioinformatics analyses, and create interactive and publication-quality visualizations. The platform is currently being used for a wide variety of biological applications, from preclinical / translational science research, to cell and gene therapies, drug discovery and development, to clinical research. -
49
CrossManager
Datakit
With Cross Manager, you just need to select one or several CAD files to translate them automatically in the format you want. So, you can order your custom configuration, according to your needs, and only buy the formats that you need. The Menus Add Directory and Add Directory (recursive) as well as Load a list of files to be converted are not available in the basic version. -
50
Iktos
Iktos
Makya is the first user-friendly SaaS platform for AI-driven de novo drug design focused on Multi-Parametric Optimization (MPO). It enables the design of novel and easy-to-make compounds in line with a multi-objective blueprint with unprecedented speed, performance, and diversity. Makya offers multiple generative algorithms covering different use cases from hit discovery to lead optimization: fine-tuning generator to find optimal solutions within your chemical space in line with your project blueprint; novelty generator to find new ideas with high novelty for re-scaffolding/hit discovery; forward generator to design a focused library of compounds easily accessible from commercial starting materials. The new Makya 3D module enhances the user experience and scientific utility of Makya. With an extensive set of 3D modeling features in both ligand-based and structure-based pipelines, with Makya 3D you can now calculate 3D scores and use these to guide generations natively in Makya.
