SILCS Alternatives

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.

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.

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.

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.

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.

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.

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.

LigPlot+ is a successor to our original LIGPLOT program for the automatic generation of 2D ligand-protein interaction diagrams. It is run from an intuitive java interface that allows on-screen editing of the plots via mouse click-and-drag operations. In addition to the new interface, the program includes several major enhancements over the old version. When two or more ligand-protein complexes are sufficiently similar, LigPlot+ can automatically display their interaction diagrams either superposed or side by side. Any conserved interactions are highlighted. The LigPlot+ suite also now includes an update of the original DIMPLOT program for plotting protein-protein or domain-domain interactions. Users can flexibly select the interface of interest and DIMPLOT will then generate a diagram showing the residue-residue interactions across the interface. To assist in interpretation, the residues in one of the interfaces can be optionally displayed in sequence order.

Transform drug discovery and materials research with advanced molecular modeling. Our physics-based computational platform integrates differentiated solutions for predictive modeling, data analytics, and collaboration to enable rapid exploration of chemical space. Our platform is deployed by industry leaders worldwide for drug discovery, as well as for materials science in fields as diverse as aerospace, energy, semiconductors, and electronics displays. The platform powers our own drug discovery efforts, from target identification to hit discovery to lead optimization. It also drives our research collaborations to develop novel medicines for critical public health needs. With more than 150 Ph.D. scientists on our team, we invest heavily in R&D. We’ve published over 400 peer-reviewed papers that demonstrate the strength of our physics-based approaches, and we’re continually pushing the limits of computer modeling.

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.

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.

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.

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.

Kanteron Platform ingested medical images, digital pathology slides, genomics sequences, and patient data from modalities, scanners, sequencers and databases, and provided a complete data toolkit to every team in hospital networks. Pharmacogenomics for adverse medication event prevention, and Precision Medicine application at the point of care: Incorporates sources of drug-gene interaction data that were previously only available in in accessible formats (e.g. tables in a PDF document), implementing the major Pharmacogenomic databases (like PharmGKB, CGI, DGIdb, OpenTargets...) Allows the user to refine their query to certain gene families, types of interactions, classes of drugs, etc. Flexible AI means you can choose the data set that best fits your use case, and apply it to your relevant medical images.

BIOiSIMTM is a first-in-class 'virtual drug development engine' that offers unprecedented value for the drug development industry by narrowing down the number of drug compounds that offer anticipated value for the treatment or cure of specific illnesses or diseases. We offer a range of translational-based solutions, customized for your pre-clinical and clinical programs. These offerings are all centered around our proven and validated BIOiSIMTM platform for small molecules, large molecules, and viruses. Our models are built on data from thousands of compounds across 7 species, leading to robustness rarely seen in the industry. With a focus on human outcomes, the platform has at its core a translatability engine that transforms insights across species. The BIOiSIMTM platform can be used before the preclinical animal trial start, allowing earlier insights and savings in expensive outsourced experimentation.

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.

Dotmatics is the global leader in R&D scientific software that connects science, data, and decision-making. Combining a workflow and data platform with best-of-breed applications, we offer the first true end-to-end solutions for biology, chemistry, formulations, data management, flow cytometry, and more. Trusted by more than 2 million researchers from the world’s leading biopharma, chemicals and materials enterprises, and academic institutions, we are dedicated to working with the scientific community to help make the world a healthier, cleaner and safer place to live. Learn more about our platform and products, including GraphPad Prism, Geneious, SnapGene, Protein Metrics, LabArchives, and more.

With CDD Vault, you can intuitively organize chemical structures and biological study data, and collaborate with internal or external partners through an easy to use web interface. Start your free trial and see first hand how easy it is to manage drug discovery data. Tailored for you Affordable Scales with your project team(s) Activity & Registration * Electronic Lab Notebook (ELN) * Visualization * Inventory * APIs * Secure Online Hosting

Chemical Computing Group (CCG) has a strong reputation for collaborative scientific support. With offices in North America, Europe and Asia, our team of PhD-level scientists works closely with our clients, providing support, hands-on training and scientific advice on a wide range of projects. CCG continuously develops new technologies with its team of mathematicians, scientists and software engineers and through scientific collaborations with customers.

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.

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.

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.

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.

Chemia is a Browser-based & cloud-ready ELN platform. Chemia is conceived, designed and architected by scientists for scientists. A platform to drive, assign, manage and monitor all R&D activities and record capture from one dashboard. It enables you to automate your R&D set-up and make it a truly paperless operation. It saves time(approx. an hour saved per scientist) with Cross-functional collaboration; makes you audit-ready and manages data effectively. Quick retrieval, search, comparative study, and reconfigurability enable faster and appropriate decisions. An inventory management system that organizes, maintains and schedules relevant information for chemicals and equipment used inside the laboratory. A system that provides usage logs of equipment, maintenance logs and calibration logs, for effective management of labs and efficient working. A system that provides the protocol and adherence to it for compliance.

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.

When operating LC-MS/MS for research or routine workflows, you expect to achieve fast, accurate, and conclusive results. The SCIEX software suite helps you get the most out of your high-performance LC-MS/MS system. It includes specific workflow and application modules to supplement your operating system. As a result, your mass spectrometer runs with the ideal software combination, tailored to your needs. These are the core engines of SCIEX nominal mass and accurate mass LC-MS/MS systems. They are for rapid and reliable data acquisition, processing, and reporting, all with compliance readiness. Combine high performance and simplicity with add-on modules for optimized quantitative and qualitative workflows. Translate your data into conclusive results even faster with application-specific software modules.

InSilicoTrials.com is a web-based platform, which provides a user-friendly computational modeling and simulation environment where many integrated easy-to-use in silico tools are readily available. The platform targets primarily users from the medical devices and pharmaceutical sectors. The in silico tools available for medical devices enable computational testing in different biomedical areas like radiology, orthopedics and cardiovascular during product design, development and validation processes. For the pharmaceutical sector, the platform provides access to in silico tools developed at all stages of the drug discovery and development processes and for many different therapeutic areas. We have built the only cloud-platform based on the crowdscience concept that makes it easy to use validated models and cut your R&D costs now. A growing catalogue of models ready to be used, on a pay per use basis.

The software that will help you improve the safety, traceability, quality, agility and integration of your Pharmacotechnics and Medicines Manufacturing Unit. No two pharmacy services are the same, which is why we have divided PharmaSuite into functional modules that will help you manage the different units in the most efficient way. Management of the Pharmacotechnics and Drug Preparation unit (parenteral mixtures). Management of parenteral nutrition.

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.

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

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.

Calculate Abraham Solvation Parameters and various solvation-related properties of solutes, directly from chemical structure.

These exquisite, intricate machines are proteins. They underpin not just the biological processes in your body but every biological process in every living thing. They’re the building blocks of life. Currently, there are around 100 million known distinct proteins, with many more found every year. Each one has a unique 3D shape that determines how it works and what it does. But figuring out the exact structure of a protein remains an expensive and often time-consuming process, meaning we only know the exact 3D structure of a tiny fraction of the proteins known to science. Finding a way to close this rapidly expanding gap and predict the structure of millions of unknown proteins could not only help us tackle disease and more quickly find new medicines but perhaps also unlock the mysteries of how life itself works.

Since 1985 ChemDraw® solutions have provided powerful capabilities and integrations to help you quickly turn ideas and drawings into publications you can be proud of. A chemistry communication suite, ChemOffice+ Cloud transforms your chemical drawings into chemical knowledge by facilitating the management, reporting and presenting of your Chemistry research. ChemOffice+ Cloud, is a robust, comprehensive suite, purpose-built to simplify, facilitate, and accelerate chemistry communication. The cloud-native chemistry communication suite builds on the foundations of ChemDraw Professional and adds access to a powerful set of tools to enable scientific research. The mundane task of creating reports to communicate chemical research has become much more efficient with ChemOffice+ Cloud. With powerful capabilities to search, reuse, select, and organize chemical structures and data, chemists can use ChemOffice+ Cloud to create presentation-ready PowerPoint slides and manuscripts.

Predict absorption, distribution, metabolism, and excretion (ADME) properties from chemical structure. This collection of high-quality calculations of pharmacokinetic properties supports high-throughput screening of libraries, provides insights into pharmacological effects, and can help assure that products are safe for human use.

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.

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.

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.

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.

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.

With its comprehensive suite of integrated software, StarDrop™ delivers best-in-class in silico technologies within a highly visual and user-friendly interface. StarDrop™ enables a seamless flow from the latest data through predictive modeling to decision-making regarding the next round of synthesis and research, improving the speed, efficiency, and productivity of the discovery process. Successful compounds require a balance of many different properties. StarDrop™ guides you through this multi-parameter optimization challenge to target compounds with the best chance of success, saving you time and resources by enabling you to synthesize and test fewer compounds.

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.

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.

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.

ArgusLab is a molecular modeling, graphics, and drug design program for Windows operating systems. It’s getting a little dated by now, but remains surprisingly popular. To date, there are more than 20,000 downloads. ArgusLab is freely licensed. You don’t need to sign anything. You can use as many copies as you need if you are teaching a class where your students might benefit from using ArgusLab. You are not allowed to redistribute ArgusLab from other websites or sources. However, you may link to this website from your own websites if you like. A low-key effort is currently underway to port ArgusLab to the iPad. In addition, I’ve done some work with the Qt cross-platform development environment in an effort to support Mac, PC, and Linux.

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.

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.

metaphactory transforms your data into consumable, contextual & actionable knowledge and drives continuous decision intelligence. Out-of-the-box, intuitive interfaces for searching, browsing & exploring your Knowledge Graph. Low-code approach to building custom interfaces that enable business-user interaction with the Knowledge Graph. Start small, iterate often & add new use cases, new data and new users on the fly. Agile knowledge management & low-code platform for building applications.

Harness the power of biomedical data with Polly. The Polly Platform helps to scale batch jobs, workflows, coding environments and visualization applications. Polly allows resource pooling and provides optimal resource allocation based on your usage requirements and makes use of spot instances whenever possible. All this leads to optimization, efficiency, faster response time and lower costs for the resources. Get access to a dashboard to monitor resource usage and cost real time and minimize overhead of resource management by your IT team. Version control is integral to Polly’s infrastructure. Polly ensures version control for your workflows and analyses through a combination of dockers and interactive notebooks. We have built a mechanism that allows the data, code and the environment co-exist. This coupled with data storage on the cloud and the ability to share projects ensures reproducibility of every analysis you perform.

IPA can also be used for analysis of small-scale experiments that generate gene and chemical lists. IPA allows searches for targeted information on genes, proteins, chemicals, and drugs, and building of interactive models of experimental systems. Data analysis and search capabilities help in understanding the significance of data, specific targets, or candidate biomarkers in the context of larger biological or chemical systems. The software is backed by the Ingenuity Knowledge Base of highly structured, detail-rich biological and chemical findings. Learn more about QIAGEN Ingenuity Pathway Analysis (IPA). Comparison Analysis determines the most significant pathways, upstream regulators, diseases, biological functions, and more, across time points, dose, or other conditions.