Alternatives to Recursion

SYNTHIA™ Retrosynthesis software, developed by computer scientists and coded by chemists, allows scientists to quickly and easily navigate novel and innovative pathways for novel and previously published target molecules. You can quickly and efficiently scan hundreds pathways to identify the best options for your needs. Discover the most cost-effective route to your target molecule with the latest visualization and filtering features. You can easily customize the search parameters to eliminate or highlight reactions, reagents, or classes of molecules. Explore innovative and unique syntheses to build your desired molecule. Easy to generate a list for starting materials that are commercially available for your synthesis. ISO/IEC 27001 Information Security Certification will guarantee the confidentiality, integrity and protection of your data.

AIDDISON™, a drug discovery software, combines the power and efficiency of artificial intelligence (AI), computer-aided design (CADD), and machine learning (ML) to provide a valuable toolkit that can be used for medicinal chemistry. It is a unified platform that integrates all aspects of virtual screening, including ligand-based design and structure-based design. It also supports methods for in silico lead optimization and discovery.

Artificial Intelligence and RNA sequencing (RNA–seq data) are both a necessity and a way to develop therapeutics that target splicing mistakes. Machine learning allows us to quickly identify new splicing mistakes and design therapeutic compounds to correct them. SpliceCore, our AI platform for RNA therapeutics research, is what we call SpliceCore. This technology platform was specifically designed for the analysis and interpretation of RNA sequencing data. It can identify, validate and test hypothetical drug targets quicker than traditional methods. Our proprietary database of over 5 million potential RNA-splicing errors is the heart of SpliceCore. It is the world's largest database of splicing mistakes and is used to test all RNA sequencing data that is submitted for analysis. Scalable cloud computing allows us to process large amounts of RNA sequencing data efficiently at a higher speed and lower cost, thereby exponentially accelerating therapeutic innovation.

BioNeMo, an AI-powered cloud service for drug discovery and framework, is built on NVIDIA NeMo Megatron. It is used to train and deploy large biomolecular Transformer AI models at supercomputing scale. The service provides pre-trained large language models (LLMs), native support for common file types for proteins, DNA, and chemistry, as well as data loaders for SMILES molecular structures and FASTA amino acid and nucleotide sequencings. You can also download the BioNeMo framework to run on your own infrastructure. ESM-1, which is based on Meta AI’s state-of the-art ESM-1b and ProtT5 respectively, are transformer-based protein-language models that can be used for learning embeddings for tasks such as property prediction and protein structure. BioNeMo will offer OpenFold, a deep-learning model for 3D structure prediction and novel protein sequences.

Our AI engine transforms drug discovery. Our discoveries help create better medicines faster. Our AI-enabled discovery portfolio is co-owned and owned 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. People are the key to redefining drug discovery using AI. We are committed to creating the best AI platform possible and using it to transform small-molecule drug discovery. To help drug developers achieve their goals, we have to tackle the most difficult and seemingly impossible targets. We also need to streamline the drug discovery process in order to make it more efficient. The ability to screen trillions of compounds in silica increases the chance of success. Demonstrates exceptional model accuracy, surpassing the challenge of false negatives.

Clara's domain specific tools, AI pretrained models, accelerated applications, and accelerated AI applications are enabling AI advances in many fields, including medical device, imaging, drug discovery and genomics. Holoscan allows you to explore the entire pipeline of medical device deployment and development. With the NVIDIA IGX Developer Kits, you can build containerized AI apps using the Holoscan SDK. The NVIDIA IGX SDK includes pre-trained AI model, healthcare-specific acceleration libraries and reference applications for medical devices.

Use AI to accelerate the journey from bench-research and laboratory insights to life-changing therapies. Reduce your reading time to minutes and gain up to 90% more research productivity. With a high-precision and high-accuracy research, you can cut through the noise to navigate the ever-growing amount of scientific literature. Save time, reduce bias, and increase the odds of discovering novel things. Explore disease biology in depth and discover advanced targets. Causaly’s high-precision graph of knowledge consolidates evidence from millions publications, allowing for unbiased, deep scientific exploration. You can navigate cause-and effect relationships in biology without being an expert. Discover hidden connections by viewing all scientific documents. Causaly’s powerful AI machine is able to read millions of published biomedical publications in order to support better research and decision-making.

To drive precision medicine programs that work, pharmaceutical companies require comprehensive genomic information. However, decisions are often made with only 10% of the data available. Genomenon provides 100% of the data. ProdigyTM Patient Landscapes are a cost-effective and efficient natural history research solution for pharmaceuticals. They enhance insights from retrospective and prospective health data to support the development rare disease therapies. Genomenon uses an AI-driven approach to deliver a thorough and expert assessment of all patients in the medical literature in a fraction time. Get a complete overview of every genomic biomarker in the medical literature. Every scientific assertion is supported with empirical evidence from medical literature. Identify all genetic drivers and determine which variants are pathogenic according ACMG clinical standards.

We combine clinical and experimental data with machine learning to improve precision medicine and navigate human disease biology. Contingent AI™, a patent-pending technology, understands data relationships to provide sophisticated insights. We tackle data bias by iterating upon machine learning models that are based on decisions made during the feature engineering and pre-processing stages. We use zebrafish, cell, and other phenotypic animals models to validate in-silico predictions in in vivo experiments. We also genetically modify them in vitro to improve translation. We quickly incorporate new data into machine learning models by using active learning and computer vision on validated models of cardiac, central nervous system, and rare disorders. We quickly incorporate new data into machine learning models by using active learning and computer vision with validated models of cardiac, central nervous system, and rare disorders.

Rare diseases are often poorly understood and only a small amount of information is available to support drug discovery programs. Healnet, an AI platform that analyzes millions of data points related to drug and disease, helps overcome these challenges. It identifies novel connections that could lead to new treatment options. We can simultaneously run multiple stages at scale by applying frontier technologies throughout the discovery and development process. It's a simple model that can be used by almost all pharmaceutical companies. One disease, one target and one drug. The next generation in drug discovery is AI-powered and parallel. The key three paradigms of drug discovery are combined.

Genedata Biologics®, streamlines the discovery of biotherapeutics. This includes bispecifics and ADCs as well as TCRs, CARs-Ts, CARs-Ts, CARs, and AAVs. It integrates all discovery workflows, making it the most popular platform in the industry. This allows you to focus on innovation and is the most widely used. A first-in-class platform that digitalizes biotherapeutic discovery accelerates research. The platform simplifies complex R&D processes by allowing for the creation, tracking, testing, and evaluation of novel biotherapeutics drugs. It can work with any format: antibodies, bi- and multi-specifics as well as ADCs, novel scaffolds, therapeutic proteins, and engineered therapeutic cell line such CAR-T cells and TCRs. Genedata Biologics acts as a central data backbone that integrates all R&D processes. This includes library design, immunizations, selections, panning, molecular Biology, screening, protein engineering and expression, as well as candidate development and manufacturability assessment.

Eidogen-Sertanty’s Target Informatics platform (TIP), is the first global structural informatics system. It enables researchers to examine the druggable genome from an structural perspective. TIP increases the rapidly expanding body experimental protein structure information and transforms structure based drug discovery from an inefficient, data-scarce discipline to a high-throughput science with rich data. TIP is a tool that bridges the knowledge gap between bioinformatics (bioinformatics) and cheminformatics. It provides drug discovery researchers with a knowledge bank of information that is both unique and highly complementary to existing bio- and cheminformatics platform information. TIP's seamless integration between structural data management technology and unique target-to-lead analysis capabilities enhances every stage of the discovery pipeline.

DNAnexus Apollo™, accelerates precision drug discovery through collaboration that draws critical insights from omics data. Precision drug discovery requires the collection and analysis of large volumes of clinical and omics data. These data sets are extremely rich, but many legacy and home-grown informatics tools cannot handle their complexity and size. Silos, insufficient collaboration tools, and complex regulatory and security requirements can all hinder precision medicine programs. DNAnexus Apollo™, which supports precision drug discovery programs, empowers scientists and clinicians to analyze and explore omics and clinical data in a single environment built on a robust and scalable cloud platform. Apollo allows them to share data, tools and analyses securely with peers and colleagues from all over the world, regardless of whether they are on another floor or another continent.

The biopharmaceutical market is complex today. There are growing demands for better specificity and safety, new treatment classes, and more complex mechanisms of disease. To keep up with this complexity, we need to have a better understanding of therapeutic behavior. Simulation and modeling provide unique opportunities to explore biological and physical processes down to the atomic levels. This can be used to guide physical experimentation and accelerate the discovery and development process. BIOVIA Discovery Studio brings together more than 30 years of peer reviewed research and world-class in-silico techniques like molecular mechanics and free energy calculations. It also allows for biotherapeutics developmentability and other related topics into one environment. It gives researchers a complete toolkit to explore the nuances in protein chemistry and to catalyze the discovery of small and big molecule therapeutics, from Target ID to Lead Optimizement.

VeraChem LLC was established in 2000 to advance computer-aided drug discovery. These methods are implemented in high-performance software and provide comprehensive support to users. This is a key strategy of VeraChem LLC for product development. Current VeraChem software capabilities include host-guest and protein-ligand binding affinity prediction, fast calculation and computation of partial atomic charges for druglike compounds, computation and force of energies and forces using all the most commonly used empirical force field, automatic generation and generation of alternate resonance forms for drug-like substances, conformational search using the powerful Tork algorithm and automatic detection and removal of topological and 3D-molecular symmetries. VeraChem's software packages were built from a modular code base.

BIOiSIMTM, a revolutionary 'virtual drug engine', is the first-in-class tool that allows drug developers to narrow down the number drugs that have potential value in treating or curing specific diseases or illnesses. We offer a variety of translational-based solutions that can be customized for your clinical and pre-clinical programs. All of these solutions are based on our BIOiSIMTM platform, which is a proven and validated platform for small molecules, large molecule, and viruses. Our models are built using data from thousands upon thousands of compounds across seven species, which gives them a robustness that is rare in the industry. The platform is focused on human outcomes and has at its core a translatability tool that transforms insights across species. The BIOiSIMTM platform is available before preclinical animal trials begin, which allows for earlier insights and saves on expensive outsourced experimentation.

Patients around the globe suffer from complex diseases and have a wide range of symptoms. They all share one thing: Patients need faster access to safer and more effective treatments. Owkin's mission empowers researchers at hospitals, universities, as well as pharmaceutical companies to understand why drug efficacy differs from patient to patient, improve the drug development process, identify the best drug for the patient to improve treatment outcomes, and provide support to patients. Owkin Loop, the core of Owkin’s research platform, connects medical researchers to high-quality datasets from top academic research centers around world. Owkin Studio, Owkin Connect and Owkin Studio are the two main components of Owkin Software Stack. They power Owkin Loop. Owkin medical research collaborations include oncology, immunology, and cardiovascular diseases.

Scitara DLX™ provides a fast connectivity infrastructure for any instrument used in life science laboratories. It is fully compliant and auditable, and can be accessed from any cloud-based platform. Scitara™, a universal digital data network, connects all instruments, resources, apps, and software within the laboratory. The cloud-based platform, which is fully auditable, connects all data sources in the lab, allowing data to flow freely across multiple endpoints. Scientists can now spend their time on scientific research and not waste it trying to solve data problems. DLX corrects and curates flight data to support the creation of precise, structured data models that feed AI/ML systems. This supports a successful digital transformation strategy for the pharma and biopharma sectors. The ability to access scientific data allows for faster decision-making and drug discovery, which helps bring drugs to market quicker.

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.

A series of carefully planned experiments can help you discover biological biomarkers, uncover disease mechanisms, find new drugs, or identify protein levels changes. It's easy to unlock the power of MS/Proteomics. This allows you to focus on the biological complexity and get closer to the moment for discovery. Our automated, repeatable workflow makes it easier to start experiments and reduce turnaround times. This gives you the flexibility and control to make decisions and act on them immediately. Our proteomics data processing workflow allows you to concentrate on biological insights and human to human collaboration. It is built to scale repeatedly. We have made repetitive and heavy processing easy to use the cloud, making it a seamless and enjoyable experience. Intelligent Proteomics seamlessly integrates complex moving parts to allow larger experiments to be processed, analyzed, and reported with ease.

Amazon Neptune is a fully managed graph database service that allows you to quickly and reliably build applications that can work with highly connected data sets. Amazon Neptune's core is a purpose-built graph database engine that can store billions of relationships and query the graph with only milliseconds latency. Amazon Neptune supports the popular graph models Property Graph, W3C's RDF, as well as their respective query languages Apache TinkerPop Gremlin, SPARQL. This allows you to quickly build queries that efficiently navigate large datasets. Neptune supports graph use cases like recommendation engines, fraud detection and knowledge graphs. It also powers network security and drug discovery.

LiveDesign is an enterprise information platform that allows teams to collaborate, design, experiment, analyze, track, and report in one central platform. You can capture ideas and model data. Create and store virtual compounds in a central database. Use advanced models to prioritize new designs. Integrate biological data and model results from federated corporate databases. Use sophisticated cheminformatics for faster analysis and development of compounds. Advanced physics-based methods are combined with machine learning techniques to quickly improve prediction accuracy. Remote team members can collaborate in real-time. You can collaborate with remote team members to share ideas, test, revise, or advance chemical series without losing sight of your work.

BC platforms uses the latest science, unique technology capabilities and strategic partnerships to accomplish our mission of revolutionizing drug discovery, personalizing care, and transforming medicine. Modular, flexible platform that integrates healthcare data. Open analytics framework seamlessly combines the most innovative methods, technology developments and analytics in one platform. Superior security: ISO 27001 certified and GDPR and HIPAA compliant. A complete product portfolio allows modern healthcare systems to fully embrace personalized medicine. Scalable deployments allow for a robust start and large-scale healthcare operation. Our unique toolbox enables faster translation of research insights into clinical practice. Our unique toolbox helps reduce risk, increase your pipeline value, and advance enterprise data strategy. We remove the barriers to data access and enable rapid insight generation.

Global biopharmaceutical drug patents and generic entry business intelligence. Anticipate future budget needs and proactively find generic sources. Examine past successes of patent challengers to identify research paths for competitors. Inform portfolio management decisions on future drug development. Predict brand drug patent expiration, identify generic supplier, and prevent overstocking of branded drugs. Get formulation and manufacturing information. Identify final formulators, repackagers and relabelled.

R&D and manufacturing labs must be able to change and reconfigure on the fly in order to accelerate new discoveries and bring products to market quickly. Data management shouldn't be a problem. Thermo Scientific™, Nautilus LIMS™, for Dynamic Discovery and R&D Environments was developed in partnership with customers. It is highly configurable and flexible. It increases workflow efficiency, throughput, data reliability, and simplifies administration, sample traceability, and regulatory compliance.

Genospace understands that genomics is driving precision medicine development, but scaling its delivery remains a challenge. We are here to help. Our platform makes biomedical data meaningful, accessible and easy to use for everyone, especially those at the frontlines of care delivery. Your clinicians and researchers will have the information they need in order to make informed decisions. Join us in our mission to leverage high-dimensional molecular data to improve patient outcomes and accelerate drug discovery and research. For drug development and research, large-scale population data is essential. Genospace platform allows you to conduct cohort-driven analyses that will inform your research activities. We are experts in clinical trial research. Genospace allows you to quickly accrue patients by matching fragmented patient data with complex trial criteria. The Genospace platform enables you to integrate genomic medicine into your mainstream clinical care.

Medgnosis, an innovative medical app, is designed to help radiologists interpret X-ray images. The application uses advanced machine learning algorithms in order to analyze and predict possible abnormalities within selected X-ray readings. This tool is a valuable tool that adds an extra layer of knowledge to the diagnostic process. Medgnosis, which uses deep learning and neural network training on large datasets, accurately identifies many conditions from X ray images. Its performance is comparable to or better than traditional methods. A system that is designed for continuous improvements keeps it at the forefront of diagnostic technology. Medgnosis produces comprehensive, instantly accessible diagnostic reports that combine detailed identification of health issues, severity assessments, as well as recommended next steps, into a clear and accessible format. This streamlined approach helps healthcare providers make informed decisions quickly.

The process of bringing a new drug to market, from the initial step to the final market introduction can be time-consuming, expensive, and highly regulated. It can take up to a decade. Final success depends on early access to accurate analytical results that are fast enough to make the right decisions during development and minimize late attrition. Today's drug development relies heavily on a rational approach. Typically, identifying the biological target is the first step. To identify the most promising candidates, it is necessary to have a deep understanding about their properties. Finding the most promising lead molecules can be a daunting task once a biological target is established. Lead discovery is typically the identification of potential drug candidates, either small organic molecules or biologic assembly with therapeutic potential.

Advanced molecular modeling can transform drug discovery and materials research. Our physics-based computational platform combines differentiated solutions for predictive modelling, data analytics, collaboration, and collaboration to allow rapid exploration of chemical space. Our platform is used by industry leaders around the world for drug discovery and materials science in fields such as aerospace, energy, semiconductors and electronics displays. The platform powers our drug discovery efforts, from target identification through hit discovery to lead optimization. It also powers our research collaborations to create novel medicines for critical public healthcare needs. Our team includes more than 150 Ph.D. scientists. This allows us to invest heavily in R&D.

Our reputation as thought leaders in the areas of ADMET property prediction, physiologically-based pharmacokinetics (PBPK) modeling, pharmacometrics, and quantitative systems pharmacology/toxicology is earned through the success our clients have found through their relationship with us. With over 20 years of experience, we have the ability to translate science into software that is easy to use. We also provide expert consulting support for drug discovery, clinical research, and regulatory submissions.

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

InSilicoTrials.com, a web-based platform that allows users to create and simulate computational models and simulations. There are many easy-to-use tools in silico. The platform is primarily for users in the medical device and pharmaceutical industries. In silico tools for medical devices allow computational testing in different biomedical areas such as radiology, orthopedics, and cardiovascular during product development, validation, and design. The platform offers access to in-silico tools for the pharmaceutical industry, which can be used at all stages of drug discovery and development. It also covers a variety of therapeutic areas. The only cloud-platform built on crowdscience makes it easy to access validated models and reduce your R&D expenses. There is a growing list of models that can be used on a pay-per-use basis.

Kanteron Platform ingested digital pathology slides, medical images, and patient data from modalities and sequencers. It then provided a complete data toolkit for all hospital network teams. Precision Medicine at the point-of-care: Pharmacogenomics is used to prevent adverse medication events. It also incorporates data sources that have drug-gene interactions that were not previously available in easily accessible formats (e.g. Tables in a PDF document) and implementing the major Pharmacogenomic Databases (like PharmGKB or DGIdb, OpenTargets ...). This allows the user to refine their query to specific gene families, types, interactions, etc. Flexible AI allows you to choose the data set that is most appropriate for your use case and then apply it to your relevant medical images.

Makya is a user-friendly SaaS-based platform for AI-driven drug design focusing on Multi-Parametric Optimization. It allows the design of novel compounds that are easy to make in accordance with a multiobjective blueprint at unprecedented speeds, performance and diversity. Makya has multiple generative algorithms that cover different use cases, from hit discovery to lead optimizing: fine-tuning to find optimal solutions in your chemical space according to your project blueprint; novelty to find new ideas of high novelty for rescaffolding/hit discoveries; forward to design a focused collection of compounds easily accessible using commercial starting materials. The new Makya 3D Module enhances the user-experience and scientific utility of Makya. Makya 3D offers a wide range of 3D modeling capabilities in both ligand and structure-based pipelines. You can now use these 3D scores to guide generation natively within Makya.

Augnito combines Speech Recognition AI power with mobility. With best-in-class accuracy, Augnito allows you to edit, format, or complete reports at the speed and ease of human speech. You can now access your personal templates and short forms from any computer, whether you're at work, at home, or on the road. This program is best suited for those who need to create detailed reports, such as radiology, histopathology, and surgical notes. You can also dictate your reports from anywhere around the world. Augnito can recognize different accents and pronunciations without any profile training. Augnito is built with the most advanced deep learning technology and has the entire language for medicine that covers 50+ sub-specialties and all the popular generic and drug names.

RetinAI's software discovery platform is used by healthcare professionals and pharmaceutical companies to manage their data and gain enhanced insights through automatic AI analysis. It also supercharges clinical and research workflows. A single data platform that allows you to access and manage your data from anywhere at any time. Compatible formats include DICOM compliant and proprietary formats. AI is used to harmonize, organize, aggregate & analyze data at scale in order to extract insights into disease progression, treatment outcome & progression prediction. Secure cloud-based data access allows for collaborative research across your organization. The central hub for data, digital, and medical teams. Perform AI-based analyses on your OCT volume for layer and fluid segmentation. Centralize your insights and provide immediate evaluation in a single platform. Invite collaborators instantly to access and work on datasets with different levels of permission.

AutoDock is a set of automated docking tools. It predicts how small molecules, such sub- or drug candidates, will bind to a receptor with a known 3D structure. It has been improved over the years to add new functionalities and multiple engines were developed. AutoDock 4 is the current version, and AutoDock Vina is the latest. AutoDock-GPU is an accelerated version that runs hundreds of times faster than the original single CPU docking code. AutoDock 4 is actually composed of two main programs. Autodock docks the ligand to a list of grids that describe the target protein. Autogrid pre-calculates the grids. The atomic affinity grids can also be visualized. This can be used to help organic synthetic chemists create better binders.

Cortellis™, a suite of life science intelligence software solutions, reveals hidden insights in data. This allows you to make better informed decisions throughout the R&D process. We have taken out the tedious work of finding, integrating and analysing data so that you can concentrate on the crucial decisions required to bring your products to market quicker. Cortellis provides unique data analysis that is rich in domain knowledge, industry insight, and therapeutic expertise. This allows you to unlock hidden insights that will allow you to make data-driven decisions that drive innovation. With the most comprehensive and deepest intelligence, you can get precise and actionable answers to specific questions throughout the R&D process. Cortellis is an indispensable part your daily work flow.

You can share clinical and pre-clinical knowledge easily across your organization using a single platform that integrates all the tools you need. Phoenix WinNonlin is the preferred choice for non-compartmental analysis, toxicokinetic modeling, pharmacokinetic, and pharmacokinetic (PK/PD), modeling by more than 6,000 researchers from biopharmaceutical companies and academic institutions. It also includes 11 global regulatory agencies including the US FDA (EMA), PMDA, and more. The Phoenix Platform features population PK/PD modeling using Phoenix NLME and Level 1 correlation via the Phoenix IIVC Toolkit. Validation Suites allow for quick and easy software validation in less than 30 minutes.

NoviSight 3D Cell Analysis Software advances your discovery by providing statistical information for spheroids, and other 3D objects in microplate based experiments. It allows you to quantify cell activity in three dimensions, capture rare events more easily, increase detection sensitivity, and obtain accurate cell counts. NoviSight software has a simple user interface that allows you to perform analysis, recognition, and statistical analyses. NoviSight software's True 3D technology allows you to easily check the morphology and size of your samples. To speed up your research, measure a variety of cell nuclei parameters such as volume and sphericity. You can also analyze 3D cell models that are physiologically relevant to your work. The software can be used to analyze objects of interest and provide spatiotemporal and morphological information in 3D space. You can detect objects from whole structures to subcellular details and analyze changes in spheroids.

StarDrop™, a comprehensive suite of integrated software, delivers the best in silico technology within a highly visual interface. StarDrop™, which allows seamless flow between the latest data, predictive modeling, and decision-making regarding the next round or synthesis, improves the speed, efficiency and productivity of the discovery process. A balance of different properties is essential for successful compounds. StarDrop™, which guides you through the multi-parameter optimization challenge, helps you target compounds with the highest chance of success. It also saves you time and resources by allowing you to synthesize fewer compounds and test them less often.

Healthcare needs can change quickly. Healthcare facilities must be able to adapt and respond quickly. Care.ai Smart Care Facility Opera Platform transforms healthcare facilities with AI-enabled automation. It improves healthcare processes, saves valuable times, reduces costs, and eases the burdens on care team members so they can concentrate on providing the best possible patient care. The care facility is monitored by a neural network of sensors that continuously learns from patient behaviors. The care facility becomes more intelligent and self-aware by collecting behavioral data over time. This allows it to automate many tedious tasks. Process improvements and optimization can be achieved by utilizing real-time operational and clinical insights into behavior and conditions.

InformAI is a healthcare company that focuses on AI solutions for medical diagnosis at the point of care and improving radiologist productivity. The Texas Medical Center is the largest medical center complex in the world. We developed our AI-enabled image classifications and patient outcome predictors. InformAI, along with its partners, is changing the way healthcare is delivered. InformAI partners with leading medical imaging companies, national physician groups, and renowned healthcare organizations to create solutions that improve patient outcomes. Our team includes leaders in healthcare, medicine, and artificial intelligence. InformAI Sinus Image Classifier was built using a 3D convolutional neural net (CNN), which is trained on radiology-validated 3D CT scan image libraries that contain 6 million images.

Our immunotherapy approach starts with our understanding of antigens. We also know which neoantigens will be present on cells by Human leukocyte antigen molecules. This will allow us to identify the ones that will be transcribed and translated. Gritstone EDGETM is our machine-learning-based platform that enables us to accomplish this. It is difficult to develop cancer immunotherapies that include tumor specific neoantigens. Tumors can have hundreds of mutations. However, only a small number of these mutations result in true tumor-specific antigens. We used EDGE's new integrated neural network architecture to train it with millions of data points from hundreds tumor and normal tissue samples taken from patients of different ancestries.

Genedata Imagence®, allows you to train a deep neural net to classify cellular characteristics in HCS images. This will give you objective, high-quality results. It automates your analysis to allow assay biologists to harness the power of deep learning algorithms. Genedata Imagence allows biologists to immediately and directly analyze HCS imaging data with sophisticated deep learning techniques using no specialized algorithmic knowledge. Don't hide your analysis behind abstract lines of code. Genedata Imagence's intuitive interface makes it easy to QC and explore data at every stage.

Our platform is regulatory compliant and allows clinical research to be done by analyzing unstructured EMR data in order to identify life-threatening conditions. We develop technologies that increase access to the most innovative healthcare through clinical trials. Our team is focused on saving lives and providing access to new healthcare therapeutic innovations that are still being investigated. We believe every patient should be informed about their options to participate in clinical trials that could offer therapies that significantly save or improve their lives. We are an AI-based healthcare research company that has developed a platform that uses computational technology to identify patients who meet a complex set criteria and allows them to participate in clinical trials.

To integrate with your diabetes management platform, plug'n play API. Personalized therapeutic education. Improved understanding of BGL fluctuations. Real-time prediction to predict risks. This allows for greater personalization and better regulation. Manage complex phases of life with rapid glucose changes. Telemedicine & retrospective analysis. Decision-support for patients. Hillo is currently working on the next versions of its AI technology, a therapeutic recommendation system to anticipate and prevent hypoglycemia and hyperglycemia, whose CE mark class IIB is planned for 2020, and the new generation of artificial pancreas(AP) for 2021, which will help overcome the main limitations of current AP systems thanks to the ultra-personalization provided by machine learning. The CE mark class IIB medical device will be the first self-learning artificial intelligence to predict blood glucose levels.

We are an artificial intelligence-enabled SaaS which diagnoses drug-resistant tuberculosis within a matter of hours. AarogyaAI aims at diagnosing drug-resistant tuberculosis using Artificial Intelligence within a few hours. We allow rapid and accurate diagnosis of DRTB so that patients can be prescribed the most effective drug combinations. Tuberculosis kills more people each year than AIDS. Because there are 19 anti-TB medications available, doctors don’t always know which one will work for whom. Even though tuberculosis may be curable, patients who are not diagnosed in time can end up on ineffective treatment for up to seven years. AarogyaAI is able to diagnose drug-resistant tuberculosis within a few hours, so that patients can be prescribed effective treatment immediately. Our SaaS uploads the patient's DNA sequence. The machine learning algorithm generates an output report that shows a complete drug susceptibility status.

Many diseases and conditions are linked to the microbiome. Discover how Kaleido is transforming the promise of microbiome into solutions that benefit patients. The human microbiome, which includes bacteria, viruses, archaea, fungi and other organisms, is a collection of over 30 trillion microbes. Research has increased exponentially over the past decade on the effects of the microbiome on human health, including diabetes, heart disease, Parkinson's disease, and cancer. This complex microbial ecosystem has been called a "newly discovered" organ. Many other human organs are worth tens to billions of dollars for therapeutics that modify physiology and treat disease. The microbiome organ is a promising therapeutic option.

Altis Labs launches Nota, a clinical information platform that accelerates R&D for therapeutics. AI predicts patient outcomes based on imaging data, so sponsors can prioritize their most promising treatments. Nota allows researchers to access imaging biomarkers and speed up R&D by operationalizing clinical trial imaging data. Altis' cloud software platform powered with deep learning allows biopharma to incorporate comprehensive outcomes predictions at the image level, patient level, and cohort-level in order to improve clinical trial designs and better anticipate clinical endpoints. These insights can accelerate drug development timelines and lower costs, while increasing the likelihood of success in clinical trials across therapeutic areas.