Alternatives to LiveDesign
Compare LiveDesign alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to LiveDesign in 2026. Compare features, ratings, user reviews, pricing, and more from LiveDesign competitors and alternatives in order to make an informed decision for your business.
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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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Schrödinger
Schrödinger
Transform drug discovery and materials research with advanced molecular modeling. Our physics-based computational platform integrates differentiated solutions for predictive modeling, data analytics, and collaboration to enable rapid exploration of chemical space. Our platform is deployed by industry leaders worldwide for drug discovery, as well as for materials science in fields as diverse as aerospace, energy, semiconductors, and electronics displays. The platform powers our own drug discovery efforts, from target identification to hit discovery to lead optimization. It also drives our research collaborations to develop novel medicines for critical public health needs. With more than 150 Ph.D. scientists on our team, we invest heavily in R&D. We’ve published over 400 peer-reviewed papers that demonstrate the strength of our physics-based approaches, and we’re continually pushing the limits of computer modeling. -
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Chemaxon Design Hub
Chemaxon
A platform that connects scientific rationale, compound design, and computational resources. Chemaxon’s Design Hub for medicinal chemistry from analysis to prioritize ideas. Design Compounds and manage ideas within one platform. A single platform that connects scientific rationale, compound design, and computational resources. Switch from PowerPoint files to graphical and chemically searchable hypotheses that are an integral part of the compound design process. Easily work with your trusted phys-chem properties, computational models, novelty issues, or purchasable compound catalogs in a rich visual environment. Involve your CROs in the compound progression process using this secure online service. Analyze collected evidence from biological assays or experimental structural information, extract SAR, and make new hypotheses for the next optimization iteration. Store your scientific hypotheses in a “designer's ELN” (chemically aware drawing canvases). -
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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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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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BIOiSIM
VERISIMLife
BIOiSIMTM is a first-in-class 'virtual drug development engine' that offers unprecedented value for the drug development industry by narrowing down the number of drug compounds that offer anticipated value for the treatment or cure of specific illnesses or diseases. We offer a range of translational-based solutions, customized for your pre-clinical and clinical programs. These offerings are all centered around our proven and validated BIOiSIMTM platform for small molecules, large molecules, and viruses. Our models are built on data from thousands of compounds across 7 species, leading to robustness rarely seen in the industry. With a focus on human outcomes, the platform has at its core a translatability engine that transforms insights across species. The BIOiSIMTM platform can be used before the preclinical animal trial start, allowing earlier insights and savings in expensive outsourced experimentation. -
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GPT-Rosalind
OpenAI
GPT-Rosalind is a purpose-built frontier reasoning model developed by OpenAI to accelerate scientific research across biology, drug discovery, and translational medicine. It is designed specifically for life sciences workflows, where researchers must navigate large volumes of literature, experimental data, and specialized databases to generate and validate new ideas. It combines deep domain understanding in areas such as chemistry, genomics, protein engineering, and disease biology with advanced tool-use capabilities, allowing it to interact with scientific databases, analyze experimental outputs, and support complex, multi-step reasoning tasks. It can assist with evidence synthesis, hypothesis generation, literature review, sequence interpretation, and experimental planning, helping scientists move faster from raw data to actionable insights. GPT-Rosalind transforms complex, time-intensive research processes into more efficient AI-assisted workflows. -
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3decision
Discngine
3decision® is a cloud-based protein structure repository designed for comprehensive structural data management and advanced analytics, enabling small molecule and biologics discovery teams to accelerate structure-based drug design. It centralizes and standardizes experimental and in-silico protein structures from public sources like RCSB PDB and AlphaFoldDB, as well as proprietary data, supporting formats like PDBx/mmCIF and ModelCIF. This ensures easy access to X-Ray, NMR, cryo-EM, and modeled structures, fostering collaboration and enhancing research efforts. Beyond storage, 3decision® enriches entries with metadata and sequence information, including protein-ligand interactions, antibody annotations, and binding site details. Advanced analytical tools identify druggable sites, assess off-target risks, and enable binding site comparisons, transforming vast structural data into actionable knowledge. Its cloud-based platform facilitates collaboration among research teams. -
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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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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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StarDrop
Optibrium
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. -
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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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Amazon Bio Discovery
Amazon
Amazon Bio Discovery is an AI-powered application designed to accelerate early-stage drug discovery by combining computational biology models with real-world laboratory testing in a unified, “lab-in-the-loop” workflow. It provides scientists with direct access to a broad catalog of biological foundation models trained on large-scale biological datasets, enabling them to generate and evaluate potential drug candidates such as antibodies with greater speed and precision. Through an integrated AI agent, users can interact in natural language to select appropriate models, configure experiments, and optimize inputs without requiring advanced coding or infrastructure expertise. It allows researchers to build multi-step pipelines that combine different models, benchmark their performance, and reuse workflows across teams, improving collaboration between computational biologists and lab scientists. -
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Alchemite
Intellegens
Alchemite provides AI-augmented physical modeling and solutions that help organizations extract actionable insights from experimental and simulation data by combining machine learning with physics-informed models to improve prediction accuracy, reduce experimental costs, and optimize product and process development. Its solutions span materials discovery and design, predictive modelling of performance and reliability, multiscale modelling that connects atomistic to macroscopic behaviour, and automation of workflow tasks such as data integration, surrogate modelling, and model validation. It supports physics-aware neural networks and hybrid modelling approaches that respect underlying scientific laws while learning from data to enable faster and more accurate simulations, reduced reliance on expensive physical testing, and improved decision-making. Intellegens’ tools are applied in areas such as battery performance prediction, chemical process optimization, etc. -
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Recursion
Recursion
Recursion is a TechBio company focused on transforming drug discovery by combining biology, data, and artificial intelligence. Founded over a decade ago, the company pioneered the use of large-scale cellular imaging to train AI models that decode the biological drivers of disease. Recursion’s mission is to deliver better medicines through novel insights and precision design, reducing the high failure rates of traditional drug development. Its proprietary Recursion OS platform integrates massive biological datasets with machine learning to accelerate discovery from target identification to clinical development. The company has built an advanced pipeline of potential first-in-class and best-in-class therapies targeting aggressive cancers and rare diseases. Automated wet labs and robotics enable millions of experiments per week, feeding continuous learning into its AI models. -
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BenevolentAI
BenevolentAI
BenevolentAI is an AI-enabled drug discovery platform and scientific technology company that unites advanced artificial intelligence, machine learning, and domain-specific science to accelerate the discovery, design, and development of new medicines for complex diseases by making sense of vast, diverse biomedical data and generating actionable scientific insights faster than traditional methods. Its proprietary Benevolent Platform ingests and harmonizes structured and unstructured biomedical information, including literature, genomics, clinical information, and multi-omics data, into a comprehensive knowledge graph, enabling scientists to reason across biological systems, generate hypotheses, predict novel drug targets, and design candidate molecules with higher confidence and lower failure rates. -
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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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CDD Vault
Collaborative Drug Discovery
With CDD Vault, you can intuitively organize chemical structures and biological study data, and collaborate with internal or external partners through an easy to use web interface. Start your free trial and see first hand how easy it is to manage drug discovery data. Tailored for you Affordable Scales with your project team(s) Activity & Registration * Electronic Lab Notebook (ELN) * Visualization * Inventory * APIs * Secure Online Hosting -
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alvaMolecule
Alvascience
alvaMolecule is a no-code cheminformatics tool for visualizing, curating, and standardizing molecular datasets before analysis. It supports common molecular formats (SMILES, SDF/MOL2) and lets users explore collections in grid or spreadsheet views, with automatic import of associated data. The software provides structure verification and standardization using predefined standardizers and custom SMIRKS rules, helps detect and manage duplicates, and offers scaffold analysis to summarize core frameworks. Built-in filters and charting tools enable sorting by substructure, calculated molecular descriptors, and physicochemical properties. alvaMolecule calculates ~88 structural and physicochemical properties, including drug-like and lead-like scores such as LogP, TPSA, and the Lipinski alert index, helping prepare high-quality datasets for QSAR/QSPR modeling, descriptor calculation, and virtual screening workflows. -
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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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AQBioSim
SandboxAQ
AQBioSim is a cloud-native platform developed by SandboxAQ that leverages Large Quantitative Models (LQMs) grounded in physics and chemistry to revolutionize materials discovery and optimization. By integrating Density Functional Theory (DFT), Iterative Full Configuration Interaction (iFCI), Generative AI, Bayesian Optimization, and Chemical Foundation Models, AQBioSim enables high-fidelity simulations of molecular and material behaviors under real-world conditions. AQBioSim's capabilities include predicting performance under various stresses, accelerating formulation through in silico testing, and exploring sustainable chemical processes. Notably, AQBioSim has demonstrated significant advancements in battery technology by reducing lithium-ion battery end-of-life prediction time by 95%, achieving 35x greater accuracy with 50x less data. -
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DNAnexus Apollo
DNAnexus
DNAnexus Apollo™ accelerates precision drug discovery by unlocking the power of collaboration to draw critical insights from omics data. Precision drug discovery requires collecting and analyzing huge volumes of omics and clinical data. These datasets are incredibly rich resources, but most legacy and home-grown informatics tools can't cope with their size and complexity. Precision medicine programs can also be hampered by siloed data sources, underpowered collaboration tools, and the burden of complex and always changing regulatory and security requirements. DNAnexus Apollo™ supports precision drug discovery programs by empowering scientists and clinicians to explore and analyze omics and clinical data together, in a single environment, built on a robust, scalable cloud platform. Apollo lets them share data, tools, and analyses easily and securely with peers and collaborators everywhere - whether they're on another floor, or another continent. -
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InfoChem
DeepMatter
As part of the DeepMatter Group we continue to supply our platforms for Synthesis & Reaction Prediction, Information Extraction and Cheminformatics as well as DigitalGlassware®, the innovative cloud-based digital chemistry platform from DeepMatter™, that brings recordability, reproducibility and shareability to your lab at every stage of the discovery process, from planning your reaction to analyzing the outcome. We continue to work side-by-side with our clients and users developing cutting-edge software solutions to boost chemical research and inspire scientific workflows. DeepMatter has a differentiated portfolio of products that accelerate and optimize the hypothesis, design, and synthesis process. These products enable new compounds such as pharmaceuticals, agrichemicals, and performance chemicals to get to market faster.DigitalGlassware transforms your chemistry into code to improve your productivity in your laboratory. -
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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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AlphaFold
DeepMind
These exquisite, intricate machines are proteins. They underpin not just the biological processes in your body but every biological process in every living thing. They’re the building blocks of life. Currently, there are around 100 million known distinct proteins, with many more found every year. Each one has a unique 3D shape that determines how it works and what it does. But figuring out the exact structure of a protein remains an expensive and often time-consuming process, meaning we only know the exact 3D structure of a tiny fraction of the proteins known to science. Finding a way to close this rapidly expanding gap and predict the structure of millions of unknown proteins could not only help us tackle disease and more quickly find new medicines but perhaps also unlock the mysteries of how life itself works. -
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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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alvaBuilder
Alvascience
alvaBuilder is a no-code de novo molecular design software for generating novel chemical structures that satisfy user-defined structural, physicochemical, and modeling constraints. It enables the creation of new molecules starting from scratch or by evolving existing structures using fragment-based and rule-driven approaches. alvaBuilder integrates seamlessly with QSAR/QSPR workflows, allowing users to guide molecule generation using predictive models, descriptor ranges, and property targets. The software supports medicinal chemistry, lead optimization, and virtual screening tasks by efficiently exploring chemical space while maintaining chemical feasibility and interpretability. alvaBuilder is designed for research and industrial applications where transparent, controllable, and reproducible molecular generation is required. -
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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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Reaxys
Elsevier
Reaxys is a web-based tool developed by Elsevier for retrieving information about chemical compounds and data from published literature, including journals and patents. The platform provides access to chemical compounds, reactions, properties, related bibliographic data, substance data with synthesis planning information, and experimental procedures from selected journals and patents. Launched in 2009 as the successor to the CrossFire databases, Reaxys was designed to offer research chemists access to current and historical information in organic, inorganic, and organometallic chemistry through an intuitive interface. The platform covers over 200 years of chemistry, abstracted from thousands of journal titles, books, and patents. Its content includes data from selected journals and chemistry patents, focusing on entries that have a chemical structure, are supported by experimental facts, and have credible citations. -
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alvaDesc
Alvascience
alvaDesc is a cheminformatics software for the calculation and analysis of molecular descriptors, fingerprints, and structural patterns for QSAR, QSPR, read-across, and machine learning applications. It computes more than 5,000 molecular descriptors (0D–3D), including constitutional, topological, geometrical, electronic, physicochemical, and fragment-based descriptors. The software also generates molecular fingerprints and structural pattern counts for similarity analysis, clustering, and classification. Integrated tools support descriptor filtering and correlation analysis for robust and reproducible modeling. alvaDesc integrates seamlessly with KNIME and Python, enabling efficient connection to external data analysis and machine learning workflows. It is widely used in academic and industrial research and supported by extensive documentation and scientific publications. -
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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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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. -
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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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IPA can also be used for analysis of small-scale experiments that generate gene and chemical lists. IPA allows searches for targeted information on genes, proteins, chemicals, and drugs, and building of interactive models of experimental systems. Data analysis and search capabilities help in understanding the significance of data, specific targets, or candidate biomarkers in the context of larger biological or chemical systems. The software is backed by the Ingenuity Knowledge Base of highly structured, detail-rich biological and chemical findings. Learn more about QIAGEN Ingenuity Pathway Analysis (IPA). Comparison Analysis determines the most significant pathways, upstream regulators, diseases, biological functions, and more, across time points, dose, or other conditions.
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BIOVIA
Dassault Systèmes
BIOVIA solutions create an unmatched scientific management environment that can help science-based organizations create and connect biological, chemical and material innovations to improve the way we live. The industry-leading BIOVIA portfolio is focused on integrating the diversity of science, experimental processes and information requirements end-to-end across research, development, QA/QC and manufacturing. Capabilities over the areas of Scientific Informatics, Molecular Modeling/Simulation, Data Science, Laboratory Informatics, Formulation Design, BioPharma Quality & Compliance and Manufacturing Analytics. BIOVIA is committed to enhancing and speeding innovation, increasing productivity, improving quality and compliance, reducing costs and accelerating product development for customers in multiple industries. Manage and connect scientific innovation processes and information across the product lifecycle. -
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NVIDIA BioNeMo
NVIDIA
BioNeMo is an AI-powered drug discovery cloud service and framework built on NVIDIA NeMo Megatron for training and deploying large biomolecular transformer AI models at a supercomputing scale. The service includes pre-trained large language models (LLMs) and native support for common file formats for proteins, DNA, RNA, and chemistry, providing data loaders for SMILES for molecular structures and FASTA for amino acid and nucleotide sequences. The BioNeMo framework will also be available for download for running on your own infrastructure. ESM-1, based on Meta AI’s state-of-the-art ESM-1b, and ProtT5 are transformer-based protein language models that can be used to generate learned embeddings for tasks like protein structure and property prediction. OpenFold, a deep learning model for 3D structure prediction of novel protein sequences, will be available in BioNeMo service. -
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Healnet
Healx
Rare diseases are often not well studied and there is a limited understanding of many of the aspects necessary to support a drug discovery program. Our AI platform, Healnet, overcomes these challenges by analyzing millions of drug and disease data points to find novel connections that could be turned into new treatment opportunities. By applying frontier technologies across the discovery and development pipeline, we can run multiple stages in parallel and at scale. One disease, one target, one drug: it's an overly simple model, yet it's the one used by nearly all pharmaceutical companies. The next generation of drug discovery is AI-powered, parallel and hypothesis-free. Bringing together the key three drug discovery paradigms. -
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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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ChemOffice
PerkinElmer Informatics
ChemOffice enhances scientists’ personal productivity and helps them do better science by enabling them to organize and explore their compounds, reactions and associated properties so that data can be turned into actionable information, and decisions can be made with greater confidence. ChemDraw for Excel adds chemical intelligence to Excel spreadsheets so that chemists can use Excel’s analysis, sorting and organization tools to further manipulate and enrich sets of compounds and data and explore structure-activity relationships. Chem3D generates 3D models so that chemists can view their compounds in three dimensions to assess shape and properties to maximize activity or specificity. ChemFinder is a chemically-intelligent personal database system that scientists use to organize their compounds and to search for and correlate structures with properties. -
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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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BIOVIA COSMO-RS
Dassault Systèmes
BIOVIA COSMO-RS is a comprehensive toolbox for modeling and predicting fluid phase properties, enabling chemical engineers, chemists, formulation engineers, and materials scientists to research and develop new solutions faster and more efficiently than with test and experimentation alone, thus accelerating innovation and reducing costs. COSMO-RS simulations are based on a sound scientific theory, which ensures robust and reliable predictions over the whole range of chemistry in the liquid state. The first-principle approach allows for predictions of new, not yet synthesized compounds, reaching beyond the known chemical space. BIOVIA’s COSMO team consists of the original inventors of COSMO-RS, assuring timely support and prime expertise to help solve even the most challenging problems in solution thermodynamics. Key benefits include a robust scientific foundation combining quantum chemistry and thermodynamics to ensure accuracy and reliability. -
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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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ChemDraw
PerkinElmer
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. -
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alvaModel
Alvascience
alvaModel is a software tool for building, validating, comparing, and applying QSAR and QSPR models. It supports regression and classification workflows based on molecular descriptors and fingerprints, with a strong focus on model transparency, interpretability, and scientific robustness. The software includes multiple data splitting strategies, variable selection methods, modeling algorithms, and comprehensive internal and external validation procedures. alvaModel provides diagnostic plots, applicability domain analysis, and model comparison tools to support the identification of reliable and predictive models. Designed according to best practices in chemometrics, alvaModel facilitates the development of interpretable models consistent with the OECD principles for QSAR validation, making it suitable for research and regulatory-oriented applications. The graphical interface guides users through the entire modeling workflow while allowing full control over each modeling step. -
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ADME Suite
ACD/Labs
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. -
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Cytel
Cytel
Cytel is a leading global provider of clinical trial design software, biometric services, and advanced analytics, specializing in optimizing clinical trials and assisting pharmaceutical companies in unlocking the full potential of their clinical and real-world data. Founded in 1987 by distinguished statisticians Cyrus Mehta and Nitin Patel, Cytel has been at the forefront of adaptive clinical trial technology and biostatistical science. Our software solutions, including the East Horizon platform, empower precise trial design and simulation, utilizing adaptive and Bayesian tools to optimize protocols and accelerate drug development. The East Horizon platform integrates key components of Cytel's trusted software portfolio into a unified solution with R integration, enhancing trial design capabilities. Additionally, Cytel offers the Xact software suite, a comprehensive toolkit for statistical analyses of small datasets, and sparse, and missing data. -
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Discngine Assay
Discngine
Discngine Assay is a laboratory informatics platform that integrates every phase of plate-based assays into a cohesive, compliant, and efficient workflow, making it an essential tool for screening research labs. It enables scientists to streamline the entire High Throughput Screening workflow, from sample management and assay data analysis to data warehousing and liquid handling equipment qualification. With its intuitive interface and robust API, Discngine Assay integrates seamlessly with Lab equipments and existing IT environment, ensuring efficient data capture and processing. Designed to accelerate new molecule discovery, it addresses the needs of pharmaceutical, biotech, and CRO industries, enhancing collaboration and driving innovation in life science research. -
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Kanteron
Kanteron Systems
Kanteron Platform ingested medical images, digital pathology slides, genomics sequences, and patient data from modalities, scanners, sequencers and databases, and provided a complete data toolkit to every team in hospital networks. Pharmacogenomics for adverse medication event prevention, and Precision Medicine application at the point of care: Incorporates sources of drug-gene interaction data that were previously only available in in accessible formats (e.g. tables in a PDF document), implementing the major Pharmacogenomic databases (like PharmGKB, CGI, DGIdb, OpenTargets...) Allows the user to refine their query to certain gene families, types of interactions, classes of drugs, etc. Flexible AI means you can choose the data set that best fits your use case, and apply it to your relevant medical images. -
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Scitara DLX
Scitara
Scitara DLX™ offers a rapid connectivity infrastructure for any instrument in the life science laboratory in a fully compliant and auditable cloud-based platform. Scitara DLX™ is a universal digital data infrastructure that connects any instrument, resource, app and software in the laboratory. The cloud-based, fully auditable platform connects all data sources across the lab, allowing the free flow of data across multiple end points. This allows scientists to devote their time to scientific research, not waste it solving data issues. DLX curates and corrects data in flight to support the development of accurate, properly structured data models that feed AI and ML systems. This supports a successful digital transformation strategy in the pharma and biopharma industries. Unlocking insights from scientific data enables faster decision-making in drug discovery and development, helping bring drugs to market more quickly. -
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InSilicoTrials
InSilicoTrials
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.
