Alternatives to BIOiSIM

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.

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.

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.

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 are a biotechnology company in clinical stage. We decode biology by integrating technological innovations across biology and chemistry to industrialize drug discovery. CRISPR genome editing and synthetic Biology allow for greater control over biology. Advanced robotics allows for reliable automation of complex laboratory research on an unprecedented scale. Neural network architectures allow for iterative analysis and inference from large, complex, in-house data sets. Cloud solutions increase the flexibility of high-performance computation. To build a next-generation biopharmaceutical business, we are using new technology to create virtuous learning cycles around datasets. A synchronized combination hardware, software, and data that is used to industrialize drug discovery. Redefining the traditional drug discovery process. One of the most extensive, broadest, and deepest pipelines in any technology-enabled drug company.

Metabolon offers the largest Level 1 library available in the metabolomics field. Over 5,400 entries are contained in our proprietary library, which has been built over 20 years. The majority of entries are Level 1, accounting for approximately 85% of our library (4,600 entries). However, some are level 2 (approximately 15 % of the entries), due to a lack commercial standards to qualify for Level 1. Metabolon's unmatched library breadth, industry-leading annotation confidence level and unmatched library depth enable us to provide our clients with accurate, highly actionable insight for their scientific or clinical inquiries. Metabolomics is applicable to a wide variety of research, including soil health, food nutrition, preclinical research and clinical trials. Whether you are looking for trends within a group, or modifying an individual's treatment plan, metabolomics will help you find the answers you need.

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.

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.

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.

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.

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.

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.

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.

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.

Cleerly, a digital healthcare company, is changing the way that clinicians approach heart disease treatment. We create intelligent clinical technologies that help clinicians identify and define atherosclerosis sooner, so they can provide personalized, vital treatment plans for all patients. Atherosclerosis is plaque buildup in the heart's vessels. We do not use indirect markers like risk factors or symptoms to diagnose the disease. Our AI-enabled digital healthcare pathway makes it easier, faster, and more accurate to diagnose and report heart disease. This improves overall clinical and financial outcomes. Cleerly empowers providers by analyzing, characterizing and quantifying plaque types. This allows them to more accurately determine the risk of heart attacks and to develop a treatment plan for improving heart health.

Site-Identification by Ligand Competitive Saturation generates 3D maps (FragMaps), showing interaction patterns for chemical functional group with your target molecule. Site-Identification through Ligand Competitive Saturation generates 3D maps, (FragMaps), of interaction patterns for chemical functions groups with your target molecule. SILCS reveals the intricacies and provides tools to optimize ligand scaffolds through qualitative and quantitative binding pocket insights. This allows for faster and more effective drug design. SILCS employs multiple small molecule probes that have different functional groups and explicit solvent modeling to perform protein target mapping. Visualize positive interactions with the target macromolecule. Get insights to design better binding agents with the best functional groups.

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.

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.

Our AI products are designed for healthcare professionals to help them at critical moments in their medical journey. We enable seamless workflow optimization throughout the care continuum, including preventive screenings, early detection and emergency care. Our AI is built in collaboration with top healthcare professionals and training algorithms that process unprecedented amounts of data. Our solutions are backed by deep data science research to anticipate your care needs and assist you in limited circumstances. Our AI solutions can be deployed wherever and whenever needed. They are compatible with any device and can integrate with existing technological infrastructure. We offer easy deployment and scaling, as well as industry-certified data security. Our team is here to help you at every stage of your AI journey.

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.

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.

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.

Aurora uses quantum mechanics, thermodynamics and an advanced continuous-water model for solvation effects in order to calculate ligand binding affinities. This approach is significantly different from the binding affinity predictions that are often based on scoring functions. Aurora algorithms are able to produce more precise and reliable binding free energies values by including the entropy as well as the aqueous electrostatic contribution directly into the calculations. The binding free energy is the measure of interaction between a ligand and a protein. The free energy (F), which is a thermodynamic quantity directly related to the experimentally measurable value for inhibition constant (IC50), and depends on the statistical properties of interacting molecules as well as electrostatic, quantum, and aqueous solver forces, is a thermodynamic quantity. Two major contributors to F's non-additivity are 1) the electrostatic and the solvation energy, and 2) the entropy.

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.

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.

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.

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.

Automated surveillance of any source of data, fully integrated with a GVP IX-compliant signal management platform. GVP-IX compliant signal-management platform integrated into Evidex and ready-to-use off-the-shelf. Modernize and audit-proof all your management processes without the need to switch between platforms or services. Your safety data is worth more than you think. Automating signal detection and management allows you to focus on your organization's value, not just regulatory requirements. Safety signals can be identified from traditional sources such as ICSR databases, FDA Adverse Events Reporting System (FAERS), VigiBase, and clinical trial data. Incorporate new data sources like claims, EHR, or other unstructured data. These data sources can be combined seamlessly to improve signaling algorithms, increase validations and assessment efficiency, and provide faster answers for drug safety questions.

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.

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.

Oncoustics develops and deploys patented AI solutions that are low-cost and non-invasive for surveillance, diagnostics and treatment monitoring of high-unmet clinical needs. Oncoustics provides a range of anatomy-focused apps that can be used on any PoC ultrasound. They can also be used by any MD/nurse/tech to provide basic primary care office instruments, without the need for images. Oncoustics' AI solutions transform point-of-care ultrasounds into powerful diagnostic tools that can detect and monitor diseases such as those in the liver, prostate and kidney, breast, thyroid, and other organs. Our team includes experts in AI, signal processing and radiology. Point of care diagnosis and surveillance are cost-effective and improve outcomes. This results in better disease management.

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.

Our healthcare enablement system reduces the amount of work clinicians have to do and improves patient experience. We increase volume by ensuring that patients receive the right care at the correct time. With a platform that takes care of the admin, we reduce clinical work time and frustration. We can help you build a seamless integrated tech ecosystem to augment your existing EMR. Fabric, which uses conversational AI, intelligent adaptive interviews and workflow automation, unifies virtual and physical care across intake triage routing and treatment. Fabric's clinical engine is built on clinical guidelines and developed by a team clinicians. It offers omnichannel access to patients while maintaining excellence in care.

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.

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.

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.

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.

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.

Medical AI is an effective technology solution for chronic diseases. This technology is characterized by its ability to predict and generate the best actions. It also presents the outputs with an easy-to consume user experience. DeLorean Medical AI enhances human capabilities, and creates a world where we can both trust the machine and human to make the right decisions. Our technology has shown to improve outcomes, and is the first AI that has been biologically validated by third-party clinical testing. Medical AI can help diagnose and detect diseases earlier by predicting disease states, assigning risk and classifying patient populations. It can reduce costs. It has been installed by 10+ clients and has shown both cost reductions as well as savings.

VIPER automates screening from remote patient identification (at point of diagnosis) through to qualified enrollment. VIPER uses artificial intelligence to match patients to precision trials within a narrow window of opportunity. This is done through the ingestion of lab-agnostic genomic and pathology data. It is tailored to the patient and the researcher. VIPER searches the personalized matching engine to locate the best clinical trials available for a patient's specific diagnosis--at that time. VIPER integrates workflow to send real-time notifications to the entire care team about a patient's eligibility in available clinical trials. This is done within a very limited enrollment window. VIPER provides interactive dashboards that allow you to access real-time data mining capabilities to aggregate patient data from both study and site levels to help you reach your study KPIs.

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.

Traditional evidence generation methods are expensive, complex, and take too long to generate. This prevents agile research and the wider utilization of authentic patient insights in treatment development and commercial pipelines. Our HyperStream is the largest real-time data stream of patient experience on earth. It records the real-world digital history and symptoms of diseases as they are shared online by authentic patients. Pharos, a web-based evidence generator tool and research framework, uses its integrated data streaming technology and AI capabilities to efficiently capture online patients experience data and enables teams and individuals to quickly find evidence when they need it. The Pharos Suite has been successfully used to generate evidence and patient insight in multiple therapeutic areas and diseases.

adWATCH – AE assists pharmaceutical companies to report adverse events that may occur during clinical trials. adWATCH – AE provides a quick and efficient way for a reporter at a clinic or hospital to generate and manage Adverse Event Reports (AERs), and report to regulatory agencies and government agencies. A negative or dangerous effect is one that a patient experiences due to the use of drugs or medical devices. Adverse event reporting involves the tracking of all medical complaint cases. This allows for the generation of MedWatch reports, CIOMS and additional reports for management. adWATCH – AE allows researchers, physician-investigators, Contract Research Organizations, clinical trial specialists, and other healthcare professionals to create and file AERs in FDA mandated MedWatch or CIOMS format.

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.

Zebra's Imaging Analytics Engine automatically analyzes images from different modalities for clinical findings. It does this in a timely fashion and in full synergy to radiology workflow. Zebra-Med alerts providers of patients at high risk for cardiovascular, lung, bone, and other diseases. This allows for preventative care programs, proper risk adjustment and allocation, as also conformance to quality standards like MACRA. Zebra-Med allows for the right patient to be seen at the right time, saving money and improving care.

ClinicalWave.ai, built on AWS' cloud platform, is an integrated AI platform designed for life sciences companies. It uses cutting-edge NLP to extract valuable insights and automates the redaction and extraction sensitive data from clinical documents. It is made up of: 1. ClinRedact AI - Our Redaction Product that automatically identifies and removes sensitive information from clinical documents. This product saves time and ensures data integrity. 2. ClinExtract AI - The AI Data Extraction Product that uses NLP and Machine Learning to extract relevant data from clinical documents. This product provides valuable insights and streamlines workflows. 3. ClinDICOM AI - Experience the power and features of our DICOM data extraction product. It offers targeted redaction, customizable redaction rules, intelligent context analysis, audit trail compliance and a user friendly interface.

Through decades of collaboration with thought leaders, we have made significant progress in tissue data mining tools, precision and workflow. Learn more about image analysis and tissue mining in multi- and highplexed photos, mine your data to find clinically relevant patterns that lead you to disease insight, transform your research tissue images into information. Learn more about image analysis CE/IVD APPs and workflows. And shift the paradigm of standardization with AI-driven pathology products that provide diagnostic decision support. Our app center provides access to a wide range of AI-based apps, as well as APPs that can scale to your needs. Explore our collection of publications, guides and webinars to learn more about digital pathology.

Imagine what care management could look like. A mission-driven data platform powered with AI can reduce the cost of healthcare, reduce admissions and readmissions, increase star ratings and HEDIS measurement, and improve quality and outcomes. Health EM.AI is a new way to improve healthcare delivery and manage care. We simplify patient data at all points of care and use AI/ML-based predictive analysis to empower healthcare organizations with actionable insight to improve the quality of their care. Measurable impact at the patient level with palliative care management workflows. Unified 360 data from all points of care can have an impact on STAR and risk adjustment, closing gaps, and other measures. Localized healthcare models that analyze more then 1,000 clinical and non-clinical characteristics based on geography.

Computer vision-enabled clinical performance insight from the world's best AI-powered pathology detection engine. Pearl's computer vision system, which is trained on the largest collection in dental imagery expertly annotated worldwide, reads radiographs with precision and speed that a dentist can achieve and the consistency of a machine. Pearl's AI is put to use by Practice Intelligence®, which allows dental offices to access powerful clinical insights that can be used across all stages of their workflow. This will help improve patient care and practice performance. For more radiologic insight, you can automatically distinguish the parts of teeth and their supporting structures. Assess the size and extent of bone loss, as well as the progression of decay, to pinpoint the exact location. Accept/reject AI detections. Add additional findings to ensure patients see the same clinician's findings.

harrison.ai partners with top healthcare organizations to create AI-as a-medical-device solutions that have a global impact on the health care system and support clinical excellence. We believe that quality healthcare is a fundamental human rights. It should be available to everyone, regardless of where they are located in the world. We combine medical insight with data engineering to make this vision a reality. We also harness the potential of AI (artificial intelligence) to create a better, brighter future in healthcare. We are bringing together the best minds to create a culture that encourages exceptional work and bold, innovative ideas. We are a healthcare AI company led by clinicians that provides accessible and efficient solutions and services. We combine deep learning expertise and clinical experience to create healthcare AI solutions.