Alternatives to BIOiSIM
Compare BIOiSIM alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to BIOiSIM in 2024. Compare features, ratings, user reviews, pricing, and more from BIOiSIM 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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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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Recursion
Recursion
We are a clinical-stage biotechnology company decoding biology by integrating technological innovations across biology, chemistry, automation, machine learning and engineering to industrialize drug discovery. Increased control over biology with tools such as CRISPR genome editing and synthetic biology. Reliable automation of complex laboratory research at an unprecedented scale using advanced robotics. Iterative analysis of, and inference from, large, complex in-house datasets using neural network architectures. Increasing elasticity of high-performance computation using cloud solutions. We are leveraging new technology to create virtuous cycles of learning around datasets to build a next-generation biopharmaceutical company. A synchronized combination of hardware, software and data used to industrialize drug discovery. Reshaping the traditional drug discovery funnel. One of the largest, broadest and deepest pipelines of any technology-enabled drug discovery company. -
5
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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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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Metabolon
Metabolon
At Metabolon, we offer the largest Level 1 library in the metabolomics industry. Our proprietary library has been built and curated over 20 years and contains over 5,400 entries. The vast majority of entries in our library are Level 1 attributing approximately 85% (~4,600 entries); however, some are Level 2 (approximately 15% accounting for around 800 entries) due to a lack of commercial standards available to qualify for Level 1. Metabolon delivers accurate, highly actionable insights for our clients’ scientific or clinical inquiries due to our unmatched library breadth and industry-leading annotation confidence levels. Metabolomics applies to a wide range of research, from soil health to food nutrition and preclinical research to clinical trials. Whether you’re searching for trends in a group or refining an individual’s treatment, metabolomics can help you find answers to important questions. -
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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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BC Platforms
BC Platforms
BC platforms leverages latest science, unique technology capabilities, and strategic partnerships to achieve our mission of revolutionizing drug discovery and personalizing care. Modular, highly configurable platform for integrated healthcare data. Open analytics framework seamlessly combining latest innovative methods, analytics and technology developments in one single platform. Superior security: ISO 27001 certified, GDPR and HIPAA compliance. Complete product portfolio enabling a modern healthcare system to fully embrace personalized medicine. Scalable deployments enabling a robust start as well as large scale healthcare operation. Accelerated translation of research insights into clinical practice with our unique end to end toolbox. We help reduce your risk, enhance your pipeline value and advance your enterprise data strategy by solving the barriers of data access and enabling rapid insight generation. -
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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. -
11
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. -
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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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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. -
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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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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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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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Cleerly
Cleerly
Cleerly is a digital healthcare company transforming the way clinicians approach the treatment of heart disease. We design intelligent clinical technologies to help clinicians precisely identify and define atherosclerosis earlier, so they can provide personalized, life-saving treatment plans for all patients throughout their care continuum. We measure atherosclerosis, plaque build-up in the heart's arteries, not indirect markers such as risk factors and symptoms of the disease. Our AI-enabled digital care pathway offers simpler, faster, more accurate heart disease diagnostics and reporting that's tailored to each stakeholder, improving overall clinical and financial outcomes. Cleerly empowers providers to go beyond traditional measures of heart disease by analyzing, characterizing, and quantifying types of plaque, so they can more accurately determine a patient's risk of heart attack and develop a treatment plan to improve heart health. -
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SILCS
SilcsBio
Site-Identification by Ligand Competitive Saturation (SILCS) generates 3D maps (FragMaps) of interaction patterns for chemical functional groups with your target molecule. Site-Identification by Ligand Competitive Saturation (SILCS) generates 3D maps (FragMaps) of interaction patterns for chemical functional groups with your target molecule. SILCS reveals intricacies of dynamics and provides tools to optimize ligand scaffolds using qualitative and quantitative binding pockets insights allowing more rapid and effective drug design. SILCS uses multiple small molecule probes with various functional groups, explicit solvent modeling, and target molecule flexibility to perform protein target mapping. Visualize favorable interactions with the target macromolecule. Gain insights to design better ligands with optimally placed functional groups. -
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Qure.ai
Qure.ai
Our AI products are designed to empower healthcare professionals during key moments in the medical journey. From preventive screenings, early detection, emergency care, institutional disease response and treatment adherence; we're enabling seamless workflow optimization across the care continuum. Collaborating with world-renowned healthcare experts, and training algorithms on unprecedented volumes of data, our AI is developed to uphold the strictest global regulatory standards. Backed by deep data science research our solutions anticipate care needs to aid you in constrained circumstances. Our AI solutions are ready for deployment, whenever and wherever needed. Designed to integrate with existing technological infrastructure, they are configurable with your devices of choice. We offer convenient deployment and scaling procedures while assuring industry-certified data security. Our team is there to support you every step of your AI journey. -
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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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AutoDock
AutoDock
AutoDock is a suite of automated docking tools. It is designed to predict how small molecules, such as substrates or drug candidates, bind to a receptor of known 3D structure. Over the years, it has been modified and improved to add new functionalities, and multiple engines have been developed. Current distributions of AutoDock consist of two generations of software: AutoDock 4 and AutoDock Vina. More recently, we developed AutoDock-GPU, an accelerated version of AutoDock4 that is hundreds of times faster than the original single-CPU docking code. AutoDock 4 actually consists of two main programs: autodock performs the docking of the ligand to a set of grids describing the target protein; autogrid pre-calculates these grids. In addition to using them for docking, the atomic affinity grids can be visualized. This can help, for example, to guide organic synthetic chemists design better binders. -
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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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Aurora Drug Discovery
Aurora Fine Chemicals
Aurora employs quantum mechanics, thermodynamics, and an advanced continuous water model for solvation effects to calculate ligand´s binding affinities. This approach differs dramatically from scoring functions that are commonly used for binding affinity predictions. By including the entropy and aqueous electrostatic contributions in to the calculations directly, Aurora algorithms produce much more accurate and robust values of binding free energies. Interaction of a ligand with a protein is characterized by the value of binding free energy. The free energy (F) is the thermodynamic quantity that is directly related to experimentally measurable value of inhibition constant (IC50) and depends on electrostatic, quantum, aqueous solvation forces, as well as on statistical properties of interacting molecules. There are two major contributing quantities leading to non-additivity in F: 1) the electrostatic and solvation energy and 2) the entropy. -
24
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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Simulations Plus
Simulations Plus
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. We have the talent and 20+ years of experience to translate science into user-friendly software and provide expert consulting supporting drug discovery, clinical development research, and regulatory submissions. -
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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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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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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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Evidex
Advera Health Analytics
Automated surveillance of any data source, fully integrated with a GVP IX compliant signal management platform. GVP-IX compliant signal management platform integrated within Evidex and ready to use off-the-shelf. Modernize and audit-proof your management processes without having to move back and forth between platforms and services. Unlock the value of your safety data. When you automate signal detection and management, you can focus not just on regulatory requirements, but on driving value for your organization. Identify safety signals from traditional sources like ICSR databases, FDA Adverse Event Reporting System (FAERS), VigiBase and clinical trial data. Include new data sources such as claims, EHR, and other unstructured data. Bring these pools of information together seamlessly to enhance signaling algorithms, make validations and assessment more efficient, and provide faster answers to drug safety questions. -
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Altis Labs Nota
Altis Labs
Altis Labs announces launch of Nota – a clinical information platform to accelerate therapeutic R&D Nota leverages. AI to predict patient outcomes from imaging data so sponsors can better prioritize their most promising therapies. Nota enables researchers to operationalize clinical trial imaging data, access predictive imaging biomarkers, and accelerate R&D at scale. Using Altis’ cloud-based software platform powered by deep learning, biopharma can incorporate comprehensive outcome predictions at the image, patient, and cohort level to improve clinical trial design and more confidently anticipate clinical endpoints. Such insights have the potential to significantly accelerate development timelines, lower drug development costs, and improve the likelihood of trial success across therapeutic areas. -
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Oncoustics
Oncoustics
Oncoustics is creating and deploying advanced and patented AI solutions for low-cost, non-invasive surveillance, diagnostics, and treatment monitoring of diseases with high unmet clinical needs. Oncoustics offers a suite of disease and anatomy-focused apps that work on any PoC ultrasound and can be used by any MD/nurse/tech as a basic primary care office instrument, without the need to look at images. Oncoustics’ AI solutions turn the inexpensive point-of-care ultrasound devices into powerful diagnostic tools for faster, cost-effective detection and monitoring of diseases including diseases in the liver, prostate, kidney, breast, and thyroid. Our team is made up of experts in AI, signal processing, radiology, hepatology, digital health, and ultrasound. Inexpensive point of care diagnosis and surveillance improves outcomes through early detection and monitoring resulting in effective disease management. -
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RetinAI
RetinAI
Healthcare professionals & pharmaceutical companies use RetinAI's software platform discovery to manage their data, gain enhanced insights with automatic AI analysis, and supercharge clinical and research workflows. A single data platform to manage & access your data anytime from anywhere. Compatible formats include DICOM-compliant and proprietary formats. Data is harmonized, organized, aggregated & analyzed at scale using AI to extract insights about disease progression, treatment outcomes & progression prediction. Enable participative research across your organization with secured cloud-based access to data. The town square for data, medical, and digital teams. Perform AI-based analysis on your OCT volumes for layer & fluid segmentation. Provide immediate evaluation & centralize your insights in a single platform. Instantly invite collaborators to access and work with datasets with different permission levels. -
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Fabric
Fabric
Our healthcare enablement system eliminates busywork for clinicians and improves experiences for patients. We unlock more volume by getting patients more efficiently to the right care at the right time. We reduce clinical work time, frustration, and burnout with a platform that does the admin tasks for you. We help build a seamless, integrated tech ecosystem that augments your existing EMR. Leveraging conversational AI and intelligent adaptive interviews, Fabric unifies virtual and in-person care across intake, triage, routing, and treatment while automating workflows for staff. Built on clinical guidelines by a team of clinicians, Fabric’s clinical intelligence engine upholds excellence in care quality while offering omnichannel access for patients. -
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Semantic Health
Semantic Health
Next-generation medical coding & auditing with AI. Streamline your manual inpatient coding and auditing processes, improve coding and documentation quality, and unlock your team to focus on high-value work. Semantic Health drives improvement at leading hospitals. Semantic Health uses custom clinical AI and NLP algorithms, trained on millions of records by our world-class AI team, to parse through clinical and coded data which allows our coding and auditing engines to better understand nuanced clinical context, incorporate changing coding guidelines and rules, and suggest high-quality coding and auditing opportunities with clear evidence back to the clinical documentation. Save time and optimize your revenue cycle by adding AI to labor-intensive medical coding and auditing processes. Semantic Health offers hospitals and health systems a supercharged inpatient auditing platform for a 100% pre-bill review of claims data. -
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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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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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VeraChem
VeraChem
VeraChem LLC was founded in 2000 to advance the state of the art in computer-aided drug discovery and molecular design by developing computational chemistry methods that are based on cutting-edge basic science but are also applicable in applied science research settings. Efficient high-performance software implementations of these methods coupled with comprehensive user support are a central company strategy for product development. Current VeraChem software capabilities include protein-ligand and host-guest binding affinity prediction, fast calculation of accurate partial atomic charges for drug-like compounds, computation of energies and forces with all the commonly used empirical force fields, automatic generation of alternate resonance forms of drug-like compounds, conformational search with the powerful Tork algorithm, and automatic detection of topological and 3D molecular symmetries. VeraChem’s software packages are constructed from a modular code base. -
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DrugPatentWatch
DrugPatentWatch
Global biopharmaceutical drug patent and generic entry business intelligence. Anticipate future budget requirements and proactively identify generic sources. Assess past successes of patent challengers and elucidate research paths of competitors. Inform portfolio management decisions on future drug development. Predict branded drug patent expiration, identify generic suppliers, and prevent overstock of branded drugs. Obtain formulation and manufacturing information; identify final formulators, repackagers, and relabelled.Starting Price: $250 per month -
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Phoenix PK/PD Platform
Certara
With all the tools you need in a single, interoperable platform, effortlessly share pre-clinical and clinical knowledge across your organization through secure and consistent workflows using Phoenix-based tools and 3rd-party applications. Phoenix WinNonlin is the first choice for non-compartmental analysis (NCA), toxicokinetic modeling, and pharmacokinetic and pharmacodynamic (PK/PD) modeling by over 6,000 researchers at biopharmaceutical companies, academic institutions, and 11 global regulatory agencies, including the US FDA, EMA, PMDA and more. The Phoenix Platform also features population PK/PD (popPK) modeling with Phoenix NLME and Level A correlation via the Phoenix IVIVC Toolkit, Validation Suites provide fast and easy software validation in under 30 minutes. -
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Gritstone
Gritstone bio
The first pillar of our immunotherapy is our understanding of antigens and neoantigens, and specifically which ones will be transcribed, translated, processed and presented on a cell surface by Human leukocyte antigen (HLA) molecules; and therefore will be visible to T cells. We accomplish this through the use of Gritstone EDGETM, our proprietary machine learning-based platform. Developing cancer immunotherapies that include tumor-specific neoantigens presents a challenge due to their nature – tumors typically have hundreds of mutations, but only a small percentage of those mutations result in true tumor-specific neoantigens that are. To address this challenge, we trained EDGE’s novel integrated neural network model architecture with millions of data points from hundreds of tumor and normal tissue samples from patients of various ancestries. -
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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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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. -
43
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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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. -
45
adWATCH
Atlant Systems
adWATCH - AE helps pharmaceutical organizations manage and report adverse events that occur during clinical trials. adWATCH - AE gives the reporter at a clinic, hospital, or investigative site a fast and effective means of generating and managing Adverse Event Reports (AERs) and reporting to the regulatory departments and government agencies. An adverse effect is a negative or dangerous effect experienced by a patient and caused by drugs and/or medical devices. Adverse event reporting requires the tracking of all medical complaint case information, resulting in the generation of MedWatch reports, CIOMS reports and additional reports for management. adWATCH - AE allows researchers, physician investigators, Contract Research Organizations (CROs), clinical trial specialists, and other health professionals to produce and file AERs in the FDA mandated MedWatch and/or CIOMS format.2 -
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Deep Lens VIPER
Deep Lens
VIPER automates the screening process from remote patient identification (at the point of diagnosis) to qualified enrollment. Utilizing artificial intelligence, VIPER identifies and matches patients to precision trials in the narrow window of opportunity through lab-agnostic genomic data ingestion, EMR and pathology data in a way that is customized to both the patient and to the research. VIPER searches the customized matching engine to find the best available clinical trials for a patients’ specific diagnosis—at the time of diagnosis. Through workflow integration, VIPER sends real-time notifications of a patient's eligibility for available clinical trials to the entire care team in the narrow enrollment window. VIPER also provides real-time interactive dashboards with rich data mining capabilities to aggregate site and study level patient data to hit your study KPIs. -
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Amazon Neptune
Amazon
Amazon Neptune is a fast, reliable, fully managed graph database service that makes it easy to build and run applications that work with highly connected datasets. The core of Amazon Neptune is a purpose-built, high-performance graph database engine optimized for storing billions of relationships and querying the graph with milliseconds latency. Amazon Neptune supports popular graph models Property Graph and W3C's RDF, and their respective query languages Apache TinkerPop Gremlin and SPARQL, allowing you to easily build queries that efficiently navigate highly connected datasets. Neptune powers graph use cases such as recommendation engines, fraud detection, knowledge graphs, drug discovery, and network security. Proactively detect and investigate IT infrastructure using a layered security approach. Visualize all infrastructure to plan, predict and mitigate risk. Build graph queries for near-real-time identity fraud pattern detection in financial and purchase transactions. -
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Medical ChatBot
John Snow Labs
Chat with a medical generative AI that explains its answers, cites references, updates medical knowledge daily, and lets you add and choose knowledge bases. Pre-load the knowledge base and pre-train the model with 2,300+ reference datasets curated by medical domain experts, including hundreds of terminologies, medical research, clinical trials, patents, population health, cost, and public and regulatory data. Multiple sources of medical research and data sources indexed. Daily updates of new medical results, clinical trials, and terminologies. Ready to process millions or billions of documents. Scale the cluster to fit your needs. A medical chatbot is a type of conversational AI that uses natural language processing (NLP) to interact with users and provide them with medical information, advice, or support. They can be used for a variety of purposes. Answer general medical questions about diseases, health conditions, and treatment options. -
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Semalytix Pharos
Semalytix
The cost, complexity and long timeframes associated with evidence generation through traditional approaches prevent agile research and the broader utilization of authentic patient insights in the treatment development and commercial pipelines. Our HyperStream represents the largest real-time patient experience data stream on earth. It captures the real-world digital history of diseases, as they are shared by authentic patients online. Pharos is a web-based evidence generation tool and research framework that uses its integrated data streaming and AI capabilities to efficiently capture online patient experience data and enables teams to quickly discover evidence when they need it. To date, the Pharos Suite has successfully been used to generate evidence and patient insights in multiple therapy areas and diseases. -
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Zebra Imaging Analytics Engine
Zebra Medical Vision
Zebra’s Imaging Analytics Engine receives imaging scans from various modalities and automatically analyzes them for a number of different clinical findings, in a timely manner and full synergy with radiology workflow. Providers use Zebra-Med to alert them of patients at high risk of cardiovascular, lung, bone and other diseases. This facilitates preventative care programs, proper risk adjustments and allocation, as well as conformance with quality standards such as MACRA. With Zebra-Med – focus can be provided to the right patients, at the right time – saving overall costs while improving care.