Alternatives to BIOiSIM
Compare BIOiSIM alternatives for your business or organization using the curated list below. SourceForge ranks the best alternatives to BIOiSIM in 2026. 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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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
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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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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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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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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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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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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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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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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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. -
13
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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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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PharmaPendium
Elsevier
PharmaPendium is a comprehensive resource that provides access to FDA and EMA drug approval documents, including pharmacokinetic, pharmacodynamic, and safety profiles. It offers detailed information on drug-drug interactions, adverse effects, and clinical study outcomes, facilitating informed decision-making in drug development and regulatory submissions. The platform's extensive data supports researchers and healthcare professionals in evaluating drug efficacy and safety, contributing to the advancement of pharmaceutical research and patient care. Find information about previous regulatory submissions and profit from precedents to predict agencies’ requirements. Seamlessly move from table view to interactive charts, graphs, and visual aids to easily interrogate and interpret data. Find information by adverse events (MedDRA), targets, indications, drug,s and endpoints using normalized data. Result pages bridge the preclinical to clinical divide. -
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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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Pristima
Xybion
In many laboratories, preclinical information resides in numerous internal systems and among several external partners. Without a unified solution, team members lack the necessary transparency of core business data to enable clear and informative decisions. Pristima is a fully integrated digital laboratory execution system with intelligent workflows, task automation, connected systems and facilities, and data and information management for the entire preclinical process. With a central data repository and standardized archive platform, Xybion has created a total preclinical solution platform to help you improve productivity and reduce costs. Gain visibility into information where it resides and initiate actions based on current business requirements with complete transparency across all platforms. Decrease end-of-study to final SEND submission timelines with effective data management. -
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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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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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Savante
Xybion Corporation
Consolidating and validating data sets is a highly challenging and business-critical effort for many Contract Research Organizations (CROs) and drug developers who perform toxicology studies either internally or outsourced with external partners. Savante provides a mechanism for your organization to create, merge, validate, and visualize preclinical study data regardless of source or format. Savante provides a vehicle for preclinical data aggregation, analysis, and visualization in SEND format to scientific staff and management. Preclinical data from Pristima XD is automatically synchronized into the Savante repository. Data from other sources can be aggregated through migration and import, including direct loads of sent data sets. The Savante toolkit handles the necessary consolidation, study merging, control terminology mapping, and data definition file preparation. -
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Pluto
Pluto Biosciences
Since its founding in 2021 from the Wyss Institute at Harvard University, Pluto has become a trusted partner of life sciences organizations around the country ranging from biotech start-ups to public biopharma companies. Our cloud-based platform gives scientists the ability to manage all of their data, run bioinformatics analyses, and create interactive and publication-quality visualizations. The platform is currently being used for a wide variety of biological applications, from preclinical / translational science research, to cell and gene therapies, drug discovery and development, to clinical research. -
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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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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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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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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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Aiforia
Aiforia
Aiforia equips pathologists and scientists in preclinical and clinical labs with powerful deep learning and cloud-based technology to advance their image analysis tasks and workflows. From empowering researchers in the identification of novel biomarkers of disease, and supporting R&D scientists in speeding up the time-to-market of novel drugs, to helping pathologists enhance the accuracy of cancer diagnostics, Aiforia has the expertise and experience to transform healthcare all the way from discovery to diagnosis. For clinical pathology labs aiming to increase productivity and improve diagnostic accuracy, the Aiforia Clinical Suites offer a portfolio of tools for AI-supported diagnostics, intelligent visualization, QC, and automated pre- and post-screening. We are currently developing Suites for some of the world’s most prevalent cancers and have CE-IVD marking for AI models in lung and breast cancer. -
27
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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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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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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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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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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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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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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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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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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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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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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Seralogix Study Manager
Seralogix
An integrated suite of professional products, enabling you to dynamically share pre-clinical study data across an enterprise and around the world, with cutting-edge functionality, and industry-embraced standards. Seralogix Study Manager™ is a new platform aiming to standardize and streamline pre-clinical studies via an elegant interface. Suitable for individual researchers and scalable to vast research enterprise, the platform employs sophisticated computing power to make your experimental design, data collection, and reporting a breeze. This suite of tools will enable you and your team to have confidence in your data quality and enjoy the benefits of instant reporting. Correctly planning your experimental design can be a daunting task. Seralogix Study Manager walks you through the process of experimental design to achieve the statistically rigor necessary to ensure your studies success. -
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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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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. -
41
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. -
42
Torx
Cresset Group
Make better design decisions and track compound synthesis from start to finish with ease. Torx is a visual, chemistry aware, web-based platform that inspires discovery chemistry teams to work together and deliver faster. Dedicated stand-alone modules for Design, Make, Test and Analyze that work in synergy to deliver a complete discovery cycle platform. Design molecules faster, capture and share knowledge, and manage resources with ease. Collaborative team working and information delivery for all roles in the DMTA cycle. However you refer to it, 'Design-Make-Test-Analyze' or 'Design-Synthesize-Test-Analyze', all small molecule chemistry teams go through a common process: design molecules, make or synthesize compounds, then test and analyze the results before the next iteration; it’s the mantra of chemistry teams all over the world. -
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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. -
44
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. -
45
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. -
46
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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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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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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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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Tox Suite
ACD/Labs
Calculate drug toxicity and safety endpoints to reduce attrition rates of molecular entities that are unlikely to succeed to nomination as a drug candidate, direct new compound synthesis, and focus animal testing requirements.
