Alternatives to Bruker Drug Discovery

The biopharmaceutical sector today is characterized by its intricate nature, driven by increasing demands for enhanced specificity and safety, the emergence of new treatment modalities, and a deeper understanding of complex disease mechanisms. To navigate this intricate landscape, a thorough grasp of therapeutic behavior is essential. Modeling and simulation techniques serve as a powerful method to investigate biological and physicochemical phenomena at the atomic scale, which can inform experimental work and expedite both discovery and development timelines. BIOVIA Discovery Studio consolidates over three decades of rigorously validated research alongside cutting-edge in silico methodologies, including molecular mechanics, free energy assessments, and the development of biotherapeutics, all within a unified platform. This comprehensive toolkit empowers researchers to delve into the subtleties of protein chemistry, facilitating the discovery and optimization of both small and large molecule therapeutics from the identification of targets through to lead optimization, thereby enhancing the overall efficiency of the drug development process. In an era where precision medicine is increasingly pivotal, such tools are indispensable for advancing therapeutic innovation.

SYNTHIA™ Retrosynthesis software, developed by computer scientists and coded by chemists, allows scientists to quickly and easily navigate novel and innovative pathways for novel and previously published target molecules. You can quickly and efficiently scan hundreds pathways to identify the best options for your needs. Discover the most cost-effective route to your target molecule with the latest visualization and filtering features. You can easily customize the search parameters to eliminate or highlight reactions, reagents, or classes of molecules. Explore innovative and unique syntheses to build your desired molecule. Easy to generate a list for starting materials that are commercially available for your synthesis. ISO/IEC 27001 Information Security Certification will guarantee the confidentiality, integrity and protection of your data.

BIOiSIMTM represents a groundbreaking 'virtual drug development engine' that delivers exceptional advantages to the pharmaceutical sector by efficiently identifying drug compounds with promising potential for treating or curing targeted diseases. Our suite of translational solutions is tailored to meet the specific needs of your pre-clinical and clinical initiatives. Central to these offerings is our validated and reliable BIOiSIMTM platform, which caters to small molecules, large molecules, and viruses. Our sophisticated models leverage data from thousands of compounds spanning seven different species, resulting in a level of robustness that is uncommon in the industry. With a strong emphasis on human outcomes, the platform features a translatability engine that effectively converts insights across various species. Notably, the BIOiSIMTM platform can be utilized prior to the commencement of preclinical animal trials, facilitating earlier insights and reducing the costs associated with outsourced testing. This innovative approach not only enhances efficiency but also accelerates the overall drug development process, ultimately benefiting the quest for effective treatments.

Genedata Biologics® enhances the development of biotherapeutics, including bispecifics, ADCs, TCRs, CAR-Ts, and AAVs, providing a comprehensive solution for the industry. Recognized as the leading platform in the field, it seamlessly unifies all discovery workflows, allowing researchers to prioritize genuine innovation. By utilizing a pioneering platform that was purposefully created to digitalize the biotherapeutic discovery process, research can be accelerated significantly. The platform simplifies intricate R&D tasks by facilitating the design, tracking, testing, and evaluation of novel biotherapeutic drugs. It is compatible with various formats, such as antibodies, bi- or multi-specifics, ADCs, innovative scaffolds, and therapeutic proteins, as well as engineered therapeutic cell lines like TCRs and CAR-T cells. Functioning as a comprehensive end-to-end data backbone, Genedata Biologics connects all R&D processes, including library design, immunization, selection and panning, molecular biology, screening, protein engineering, expression, purification, and protein analytics, ultimately leading to thorough assessments of candidate developability and manufacturability. This holistic integration ensures that researchers can make informed decisions and push the boundaries of biotherapeutic innovation effectively.

3decision® serves as an innovative cloud-based repository for protein structures, focusing on efficient structural data management and sophisticated analytics to expedite the discovery of small molecules and biologics through structure-based drug design. The platform consolidates and standardizes both experimental and computational protein structures sourced from public databases such as RCSB PDB and AlphaFoldDB, along with proprietary datasets, while supporting various formats like PDBx/mmCIF and ModelCIF. This approach guarantees straightforward access to a range of structural data, including X-Ray, NMR, cryo-EM, and modeled structures, which promotes teamwork and enhances scientific research endeavors. In addition to mere storage, 3decision® enriches its database entries with significant metadata and sequence details, covering aspects such as protein-ligand interactions, antibody annotations, and binding site characteristics. Its advanced analytical tools facilitate the identification of potential druggable sites, evaluation of off-target effects, and comparisons of binding sites, effectively converting extensive structural data into practical insights. Moreover, the cloud-based nature of this platform encourages seamless collaboration among research teams, making it an essential tool for advancing drug discovery initiatives.

Site-Identification by Ligand Competitive Saturation (SILCS) produces three-dimensional maps, known as FragMaps, that illustrate how different chemical functional groups interact with a specific target molecule. By revealing the complexities of molecular dynamics, SILCS offers tools that enhance the optimization of ligand scaffolds through both qualitative and quantitative insights into binding pockets, thereby streamlining the drug design process. This approach employs a range of small molecule probes, each featuring diverse functional groups, alongside explicit solvent modeling and accommodating the flexibility of the target molecule to effectively map protein targets. Furthermore, the technique allows researchers to visualize advantageous interactions with the target macromolecule. With these insights, scientists can strategically design improved ligands with functional groups situated in optimal positions for enhanced efficacy. The innovative nature of SILCS represents a significant advancement in the field of medicinal chemistry.

Harnessing RNA sequencing (RNA-seq) data alongside Artificial Intelligence presents both a crucial necessity and a significant opportunity for creating therapies aimed at correcting splicing errors. By leveraging machine learning, we can uncover novel splicing errors and swiftly formulate therapeutic compounds to address them. Our AI platform, SpliceCore, is specifically designed for discovering RNA therapeutics. This cutting-edge technology focuses on analyzing RNA sequencing data with unparalleled efficiency. It can swiftly identify, evaluate, and validate potential drug targets, outpacing traditional methodologies. Central to SpliceCore is our unique repository containing over 5 million potential RNA splicing errors, making it the largest of its kind globally and instrumental for testing any RNA sequencing dataset submitted for analysis. The integration of scalable cloud computing allows us to handle vast quantities of RNA sequencing data in a way that is not only efficient but also cost-effective, significantly speeding up the pace of therapeutic advancements. This innovative approach promises to revolutionize the landscape of RNA therapeutics.

AutoDock comprises a collection of automated docking tools aimed at forecasting the binding interactions of small molecules, like substrates or potential pharmaceuticals, with receptors that have a defined three-dimensional structure. Over time, the suite has undergone various modifications and enhancements to incorporate additional features, resulting in the development of several engines. The current versions of AutoDock include two primary iterations: AutoDock 4 and AutoDock Vina. Recently, an advanced version known as AutoDock-GPU was introduced, which accelerates the docking process of AutoDock 4 and achieves speeds that are hundreds of times greater than its original single-CPU counterpart. AutoDock 4 is fundamentally made up of two key applications: autodock, which facilitates the docking of ligands to a grid representation of the target protein, and autogrid, which computes these grids in advance. Besides their application in docking, the atomic affinity grids generated can also be visualized, providing valuable insights that can assist organic synthetic chemists in creating more effective binders for their projects. This capability helps bridge the gap between computational predictions and practical applications in drug design.

Eidogen-Sertanty's Target Informatics Platform (TIP) stands out as the pioneering structural informatics system and knowledgebase that empowers researchers to explore the druggable genome through a structural lens. By harnessing the burgeoning wealth of experimental protein structure data, TIP revolutionizes structure-based drug discovery, shifting it from a limited, low-throughput field to a dynamic and data-rich scientific discipline. It is specifically designed to connect the realms of bioinformatics and cheminformatics, providing drug discovery scientists with a repository of insights that are not only unique but also highly synergistic with the information available from traditional bio- and cheminformatics tools. The platform's innovative combination of structural data management with advanced target-to-lead calculation and analytical capabilities significantly enhances every phase of the drug discovery process. With TIP, researchers are better equipped to navigate the complexities of drug development and make informed decisions.

Revolutionize the fields of drug discovery and materials research through cutting-edge molecular modeling techniques. Our computational platform, grounded in physics, combines unique solutions for predictive modeling, data analysis, and collaboration, facilitating swift navigation of chemical space. This innovative platform is employed by leading industries globally, serving both drug discovery initiatives and materials science applications across various sectors including aerospace, energy, semiconductors, and electronic displays. It drives our internal drug discovery projects, overseeing processes from target identification through hit discovery and lead optimization. Additionally, it enhances our collaborative research efforts aimed at creating groundbreaking medicines to address significant public health challenges. With a dedicated team of over 150 Ph.D. scientists, we commit substantial resources to research and development. Our contributions to the scientific community include more than 400 peer-reviewed publications that validate the efficacy of our physics-based methodologies, and we remain at the forefront of advancing computational modeling techniques. We are steadfast in our mission to innovate and expand the possibilities within our field.

CDD Vault allows you to intuitively organize chemical structures, biological study data, as well as collaborate with external or internal partners via a simple web interface. Start a free trial to see how easy it can be to manage drug discovery data. Tailored for You Affordable Scales with your project team Activity & Registration * Electronic Lab Notebook * Visualization * Inventory * APIs

Our innovative AI platform revolutionizes the field of drug discovery, enabling us to develop superior medications at an accelerated pace. With a diverse portfolio of discovery assets—both fully owned and collaboratively developed—and the support of renowned investors, we are making significant strides in the industry. Atomwise has crafted a machine-learning discovery engine that leverages the capabilities of convolutional neural networks alongside extensive chemical libraries to identify novel small-molecule drugs. The key to transforming drug discovery through AI lies in the expertise and commitment of our team. We are focused on creating the most effective AI tools to enhance small molecule drug discovery, striving to address the toughest and seemingly insurmountable targets while streamlining the entire process for drug developers. By maximizing computational efficiency, we can screen trillions of compounds virtually, significantly boosting the chances of success. Our models have demonstrated remarkable accuracy, effectively mitigating the issue of false positives and paving the way for groundbreaking advancements in medicine. Ultimately, our mission is to empower researchers with the technology they need to drive innovation and achieve transformative results in drug discovery.

InSilicoTrials.com is an online platform that offers a user-friendly environment for computational modeling and simulation, featuring a range of integrated, easy-to-navigate in silico tools. It primarily serves professionals in the medical device and pharmaceutical industries. The in silico tools designed for medical devices facilitate computational testing across various biomedical fields, including radiology, orthopedics, and cardiovascular health, during the stages of product design, development, and validation. For the pharmaceutical industry, the platform grants access to in silico tools that support all phases of drug discovery and development across diverse therapeutic areas. We have developed a unique cloud-based platform grounded in crowdscience principles, allowing users to efficiently utilize validated models and reduce their R&D expenses. Additionally, users can explore a continuously expanding catalog of models available for use on a pay-per-use basis, ensuring flexibility and accessibility for their research needs.

The foundational aspect of our immunotherapy approach lies in our comprehension of antigens and neoantigens, particularly in identifying which variations will be transcribed, translated, processed, and subsequently displayed on the surface of cells via Human leukocyte antigen (HLA) molecules, thus making them recognizable to T cells. We achieve this by employing Gritstone EDGETM, a unique platform powered by machine learning. Creating cancer immunotherapies that incorporate tumor-specific neoantigens proves challenging, mainly because tumors consist of numerous mutations, yet only a fraction of these lead to genuine tumor-specific neoantigens. To tackle this complexity, we have developed EDGE's cutting-edge integrated neural network model, trained with millions of data points gathered from a diverse range of tumor and normal tissue samples across various patient ancestries. This extensive training allows us to enhance the accuracy of neoantigen identification and improve the effectiveness of our immunotherapy strategies.

Cytel stands out as a prominent global innovator in software for clinical trial design, biometrics, and advanced analytics, focusing on maximizing the efficiency of clinical trials while aiding pharmaceutical companies in harnessing the full scope of both clinical and real-world data. Established in 1987 by renowned statisticians Cyrus Mehta and Nitin Patel, Cytel has consistently been a leader in adaptive clinical trial technology and the field of biostatistics. Its software solutions, notably the East Horizon platform, facilitate accurate trial design and simulation, employing adaptive and Bayesian methodologies to enhance protocols and expedite the drug development process. The East Horizon platform serves as a comprehensive integration of Cytel's reliable software offerings, featuring R integration that significantly improves trial design functions. Furthermore, Cytel provides the Xact software suite, which is an all-encompassing toolkit designed for statistical analysis of small datasets, including those with sparse and missing data. By continuously innovating and expanding its product offerings, Cytel remains committed to providing cutting-edge solutions that meet the evolving needs of clinical research.

The microbiome plays a significant role in various diseases and health issues. Discover how Kaleido is pioneering a unique method to transform the potential of the microbiome into effective patient solutions. Comprising over 30 trillion microbes, the human microbiome includes a diverse array of organisms such as bacteria, viruses, archaea, and fungi that inhabit both the exterior and interior of the human body. In recent years, there has been a remarkable surge in research focusing on the microbiome's influence on human health, linking it to conditions such as cardiovascular disease, cancer, diabetes, Parkinson’s disease, and allergies. This intricate microbial community has been likened to a "newly discovered organ," highlighting its significance. Just as many human organs command substantial investments for therapies that modify physiology, the microbiome represents a largely unexplored territory in the realm of healthcare. Addressing this frontier could unlock new therapeutic avenues and enhance overall health outcomes.

Uncover biological markers, generate insights into the mechanisms of disease, identify novel pharmaceuticals, or detect variations in protein concentrations through a meticulously structured series of experiments. We have simplified the process of harnessing the potential of mass spectrometry and proteomics, enabling you to concentrate on the intricacies of biology and advance toward groundbreaking discoveries. Our automated and consistent workflow facilitates faster initiation and completion of experiments, granting you the authority and adaptability to make timely decisions. By prioritizing biological insights and fostering collaborative efforts, our scalable proteomics data processing system is designed for repeated use. We have delegated intensive and repetitive tasks to the cloud, ensuring a smooth and satisfying experience. Our sophisticated proteomics workflow effectively integrates numerous complex elements, allowing for the efficient analysis and processing of larger-scale experiments, ultimately enhancing the research journey. Thus, with our innovative approach, researchers can now delve deeper into the molecular landscape and achieve more significant breakthroughs than ever before.

Makya stands out as the pioneering user-centric SaaS platform dedicated to AI-enhanced de novo drug design, particularly emphasizing Multi-Parametric Optimization (MPO). This innovative tool empowers users to create novel and easily synthesize compounds based on a multi-objective framework, achieving unprecedented levels of speed, efficiency, and variety. Makya incorporates a range of generative algorithms tailored to various stages of drug development, from hit discovery to lead optimization; it includes a fine-tuning generator for pinpointing ideal solutions within your specified chemical landscape, a novelty generator designed to explore fresh concepts for re-scaffolding and hit discovery, and a forward generator to create a targeted library of compounds that can be readily synthesized from commercially available starting materials. The recently introduced Makya 3D module significantly improves both the user interface and the scientific capabilities of the platform. With a comprehensive array of 3D modeling functionalities available for both ligand-based and structure-based approaches, Makya 3D allows for the calculation of 3D scores, which can be seamlessly utilized to guide compound generation within the platform. This integration not only enhances the design process but also offers researchers deeper insights into their molecular designs.

LiveDesign serves as an integrated informatics solution that empowers teams to accelerate their drug discovery initiatives through collaborative design, experimentation, analysis, tracking, and reporting on a unified platform. It allows for the collection of innovative ideas alongside experimental and modeling data seamlessly. Users can develop and archive new virtual compounds within a centralized repository, assess them with sophisticated models, and prioritize the most promising designs. By merging biological data and model outputs from various corporate databases, the platform leverages advanced cheminformatics to provide a comprehensive analysis of all information simultaneously, facilitating quicker compound development. The platform employs cutting-edge physics-based methodologies along with machine learning to enhance prediction accuracy significantly. Teams can collaborate in real-time, regardless of location, enabling them to share concepts, conduct tests, make revisions, and progress chemical series while maintaining a clear record of their work. This not only fosters innovation but also ensures that projects remain organized and efficient throughout the drug discovery process.

Business intelligence in the global biopharmaceutical sector focuses on drug patent dynamics and the entry of generics. It is essential to forecast future budget needs and proactively seek out generic alternatives. Analyzing the achievements of past patent challengers provides insights into the competitive landscape and informs research directions. This analysis plays a crucial role in guiding portfolio management strategies for upcoming drug development projects. Additionally, anticipating the expiration of patents on branded drugs, pinpointing potential generic suppliers, and managing branded drug inventory effectively are vital. Furthermore, acquiring detailed formulation and manufacturing data helps in identifying key formulators, repackagers, and relabelers to streamline operations and enhance market positioning. Understanding these elements can significantly bolster strategic decision-making in the biopharmaceutical industry.

AIDDISON™, a drug discovery software, combines the power and efficiency of artificial intelligence (AI), computer-aided design (CADD), and machine learning (ML) to provide a valuable toolkit that can be used for medicinal chemistry. It is a unified platform that integrates all aspects of virtual screening, including ligand-based design and structure-based design. It also supports methods for in silico lead optimization and discovery.

Rare diseases often lack comprehensive research, resulting in insufficient knowledge about essential elements for an effective drug discovery initiative. Our innovative AI platform, Healnet, addresses these issues by scrutinizing vast amounts of drug and disease data to uncover new connections that may lead to potential treatments. Utilizing cutting-edge technologies throughout the discovery and development process allows us to operate multiple phases simultaneously and on a large scale. The conventional approach of focusing on a single disease, target, and drug is overly simplistic, yet it remains the standard for most pharmaceutical companies. The future of drug discovery is driven by AI, characterized by parallel processes and an absence of rigid hypotheses, fundamentally integrating the three core paradigms of drug discovery into a cohesive strategy. This new paradigm not only enhances efficiency but also fosters creativity in developing solutions for complex health challenges.

Aurora utilizes principles of quantum mechanics, thermodynamics, and a sophisticated continuous water model to assess the solvation effects when calculating the binding affinities of ligands. This methodology stands in stark contrast to traditional scoring functions typically employed in predicting binding affinities. By integrating entropy and aqueous electrostatic factors directly into their calculations, Aurora's algorithms yield significantly more precise and reliable estimates of binding free energies. The interaction between a ligand and a protein is fundamentally determined by the binding free energy, which is a thermodynamic measure linked directly to the experimentally observable inhibition constant (IC50). This free energy (F) is influenced by various factors, including electrostatic interactions, quantum effects, solvation dynamics, and the statistical behaviors of the molecules involved. Two primary components contribute to the non-additive nature of F: first, the combined effects of electrostatic and solvation energy, and second, the entropy involved in the system. Understanding these contributions allows for a deeper insight into the molecular interactions at play.

Harness the capabilities of artificial intelligence to accelerate the transition from laboratory research and experimental findings to the introduction of transformative therapies. Achieve a remarkable increase in research efficiency, potentially improving productivity by as much as 90% by cutting down your literature review time from several months to mere minutes. Eliminate distractions and enhance your search capabilities with a precise and accurate tool that simplifies the navigation of the expanding landscape of scientific publications. This approach not only saves time but also minimizes bias and enhances the likelihood of discovering groundbreaking insights. Delve deeply into the intricacies of disease biology and engage in sophisticated target identification. Causaly's advanced knowledge graph integrates data from countless publications, enabling thorough and objective scientific investigations. Effortlessly explore the intricate biological cause-and-effect dynamics without requiring extensive expertise. Access a comprehensive array of scientific documents and reveal previously overlooked connections. Causaly’s robust AI system processes millions of biomedical articles, facilitating improved decision-making and enhancing research outcomes, ultimately leading to a more informed and innovative scientific community. By utilizing such tools, researchers can significantly transform their methodologies and enhance their contributions to medicine.

Dotmatics is the global leader in R&D scientific software that connects science, data, and decision-making. More than 2 million scientists and 10,000 customers trust Dotmatics to accelerate research and help make the world a healthier, cleaner, and safer place to live.

The Kanteron Platform assimilated a wide array of medical images, digital pathology slides, genomic sequences, and patient information from various modalities, scanners, sequencers, and databases, delivering a comprehensive data toolkit to all teams within hospital networks. It emphasizes pharmacogenomics to avert adverse medication events and facilitates the application of precision medicine at the point of care by integrating data sources on drug-gene interactions that were formerly only accessible in less user-friendly formats, such as tables found in PDF documents. By incorporating major pharmacogenomic databases like PharmGKB, CGI, DGIdb, and OpenTargets, it enables users to customize their queries according to specific gene families, types of interactions, and drug classifications. Additionally, its adaptable AI allows users to select the dataset that best aligns with their specific use case, applying it effectively to pertinent medical images. This robust functionality not only enhances the accuracy of medical insights but also fosters a more personalized approach to patient care.

We are a biotechnology firm in the clinical stage, dedicated to unraveling biological complexities through the integration of cutting-edge innovations spanning biology, chemistry, automation, machine learning, and engineering, all aimed at revolutionizing drug discovery. Our approach allows for enhanced precision in biological manipulation with advanced techniques like CRISPR genome editing and synthetic biology. We also achieve reliable automation for intricate laboratory processes at an unprecedented scale through the use of sophisticated robotics. By employing neural network architectures, we conduct iterative analyses and draw insights from extensive, intricate datasets generated in-house. Furthermore, we are boosting the adaptability of high-performance computing capabilities through cloud-based solutions. Our initiative harnesses new technologies to foster continuous learning cycles around our datasets, establishing us as a next-generation biopharmaceutical enterprise. This is achieved through a harmonious integration of hardware, software, and data, all dedicated to the industrialization of drug discovery. We are transforming the conventional drug discovery pipeline and boast one of the most extensive, diverse, and in-depth pipelines among technology-driven drug discovery companies. Ultimately, our mission is to enhance the efficiency and effectiveness of drug development, paving the way for breakthrough therapies.

These remarkable and complex entities are proteins, serving as the foundation for not only the biological functions within your body but also for every living organism on Earth. They are fundamental components of life itself. At present, there are approximately 100 million recognized distinct proteins, with new discoveries emerging annually. Each protein possesses a specific three-dimensional configuration that dictates its function and role. However, determining the precise structure of a protein is often a costly and labor-intensive endeavor, resulting in only a small percentage of proteins having their exact 3D structures identified by scientists. Addressing this widening gap and developing methods to predict the structures of countless unknown proteins could significantly enhance our ability to combat diseases and expedite the discovery of novel medications, and it may also provide insights into the very essence of life. Such advancements could revolutionize our understanding of biological systems and lead to groundbreaking innovations in medicine and biotechnology.

Discngine Assay serves as a comprehensive laboratory informatics platform that unifies all stages of plate-based assays into a streamlined, compliant, and effective workflow, proving to be a vital resource for screening research laboratories. This platform empowers researchers to optimize their entire High Throughput Screening process, encompassing everything from managing samples and analyzing assay data to data storage and qualifying liquid handling instruments. With its user-friendly interface and powerful API, Discngine Assay integrates effortlessly with laboratory equipment and the existing IT infrastructure, facilitating effective data collection and processing. Tailored to expedite the discovery of new molecules, it meets the requirements of the pharmaceutical, biotech, and contract research organization sectors, thereby promoting collaboration and fostering innovation within life sciences research. Furthermore, its ability to adapt to various laboratory environments makes it a versatile solution for evolving research demands.

AI-powered drug discovery is a proven technology. Cerella extracts hidden insights from your drug discovery data to reveal the best compounds and most valuable experiment for your project. It can make confident predictions by accurately filling in the missing values. This is especially useful for expensive downstream experiments, which are impossible to predict using other methods. This allows you to do more with sparse and limited data sets.

Founded in 2000, VeraChem LLC aims to enhance the field of computer-aided drug discovery and molecular design by creating advanced computational chemistry techniques that merge innovative basic science with practical applications in research. A key aspect of the company's strategy for product development lies in delivering efficient, high-performance software solutions along with extensive user support. Among the current capabilities of VeraChem's software are predictions for protein-ligand and host-guest binding affinities, rapid and precise calculations of partial atomic charges for drug-like molecules, and the computation of energies and forces utilizing widely-used empirical force fields. Additionally, the software features automatic generation of alternate resonance forms for drug-like compounds, a robust conformational search enabled by the Tork algorithm, and the automatic identification of topological and three-dimensional molecular symmetries. The modular code base of VeraChem’s software packages allows for flexibility and adaptability in meeting diverse research needs, ensuring that users can leverage these tools effectively for their specific applications.

DNAnexus Apollo™ enhances the efficiency of precision drug discovery by fostering collaboration that extracts valuable insights from omics data. The process of precision drug discovery involves the aggregation and examination of vast amounts of omics and clinical information. These extensive datasets serve as valuable assets; however, many traditional and custom-built informatics tools struggle to manage their intricacies and scale. Additionally, the effectiveness of precision medicine initiatives can be hindered by fragmented data sources, inadequate collaboration tools, and the challenges posed by complex, evolving regulatory and security demands. By enabling scientists and clinicians to jointly investigate and interpret omics and clinical data within a unified framework, DNAnexus Apollo™ bolsters precision drug discovery efforts. This platform, which is powered by a resilient and scalable cloud infrastructure, facilitates the seamless and secure sharing of data, tools, and analyses among peers and collaborators, regardless of whether they are nearby or across the globe. Ultimately, Apollo not only streamlines the data-sharing process but also enhances the overall collaborative experience in the pursuit of innovative drug discoveries.

The software designed to enhance the safety, traceability, quality, agility, and integration of your Pharmacotechnics and Medicines Manufacturing Unit is essential. Recognizing that each pharmacy service has unique needs, we have organized PharmaSuite into specialized functional modules to optimize the management of various units effectively. This includes overseeing the Pharmacotechnics and Drug Preparation unit, particularly for parenteral mixtures, as well as the administration of parenteral nutrition. With these tailored modules, your operations can run more smoothly and efficiently.

Scitara DLX™ provides a swift connectivity framework suitable for any instrument found within life science laboratories, all while operating on a cloud-based platform that is both compliant and auditable. As a versatile digital data infrastructure, Scitara DLX™ facilitates connections between various instruments, resources, applications, and software utilized in the lab. The comprehensive cloud system ensures that all data sources are interconnected, promoting seamless data movement across numerous endpoints. Consequently, researchers can concentrate on their scientific endeavors instead of being bogged down by data-related challenges. Moreover, DLX intelligently curates and corrects data as it is processed, fostering the creation of accurate and well-organized data models that are essential for enhancing AI and ML systems. This robust approach plays a vital role in advancing digital transformation strategies within the pharmaceutical and biopharmaceutical sectors. By unlocking valuable insights from scientific data, the platform accelerates decision-making processes in drug discovery and development, ultimately aiding in the expedited launch of new medications into the market. Additionally, the integration of such a sophisticated infrastructure not only streamlines workflows but also enhances collaboration among researchers, paving the way for innovative solutions in the life sciences field.

Clara provides specialized tools and pre-trained AI models that are driving significant advancements across various sectors, such as healthcare technologies, medical imaging, pharmaceutical development, and genomic research. Delve into the comprehensive process of developing and implementing medical devices through the Holoscan platform. Create containerized AI applications using the Holoscan SDK in conjunction with MONAI, and enhance deployment efficiency in next-gen AI devices utilizing the NVIDIA IGX developer kits. Moreover, the NVIDIA Holoscan SDK is equipped with acceleration libraries tailored for healthcare, alongside pre-trained AI models and sample applications designed for computational medical devices. This combination of resources fosters innovation and efficiency, positioning developers to tackle complex challenges in the medical field.

We have established ourselves as frontrunners in the fields of ADMET property prediction, physiologically-based pharmacokinetics (PBPK) modeling, pharmacometrics, and quantitative systems pharmacology/toxicology, a status achieved through the achievements our clients have experienced while partnering with us. Leveraging over two decades of expertise, our skilled team excels at transforming complex scientific concepts into accessible software solutions, while also offering specialized consulting services that bolster drug discovery, clinical development research, and regulatory submission processes. Our dedication to client success drives our continuous improvement and innovation in these critical areas.

BC platforms harnesses cutting-edge scientific advancements, innovative technological capabilities, and strategic alliances to transform drug discovery and tailor healthcare solutions. Our platform is modular and highly adaptable, designed for integrating healthcare data effectively. With an open analytics framework, we seamlessly merge the most recent innovative methods and technology advancements into a single, cohesive platform. We prioritize security, holding ISO 27001 certification alongside compliance with GDPR and HIPAA regulations. Our comprehensive product suite empowers a contemporary healthcare system to fully adopt personalized medicine approaches. Our scalable deployment options support everything from initial setups to expansive healthcare operations. By offering a unique end-to-end toolbox, we facilitate the expedited application of research findings in clinical settings. Moreover, we strive to minimize your risks, enhance the value of your pipeline, and advance your enterprise data strategy by overcoming data access challenges and enabling swift insights. In doing so, we aim to foster a health ecosystem that is both responsive and forward-thinking.

BioNeMo is a cloud-based service for drug discovery that utilizes artificial intelligence, leveraging NVIDIA NeMo Megatron to facilitate the training and deployment of large biomolecular transformer models at an extensive computing scale. This platform offers pre-trained large language models (LLMs) along with inherent compatibility for various file formats related to proteins, DNA, RNA, and chemistry, and features data loaders for SMILES to represent molecular structures and FASTA for amino acid and nucleotide sequences. Users will also have the option to download the BioNeMo framework to run it on their own systems. Among its offerings are ESM-1, derived from Meta AI’s cutting-edge ESM-1b, and ProtT5, both of which are transformer models designed for protein language applications that aid in generating learned embeddings for tasks such as predicting protein structure and properties. Additionally, the service will include OpenFold, an advanced deep learning model dedicated to predicting the 3D structures of novel protein sequences, further enhancing its capabilities in the realm of biomolecular research. This comprehensive suite of tools positions BioNeMo as a valuable resource for researchers in the field of drug discovery.

ArgusLab is a program designed for molecular modeling, graphics, and drug design, specifically for Windows platforms. While it may be somewhat outdated, it continues to enjoy a surprising level of popularity with over 20,000 downloads recorded. This software is available under a free license, which means you don't have to fill out any forms to access it. Educators can utilize as many copies as necessary for their classes, allowing students to benefit from ArgusLab’s features. However, it is important to note that redistributing ArgusLab from external websites is prohibited, although linking to the official site from your own is permitted. Currently, there is a modest initiative in progress to adapt ArgusLab for use on the iPad. Additionally, efforts have been made to integrate the Qt cross-platform development environment to potentially expand compatibility across Mac, PC, and Linux systems, enhancing its accessibility for a wider audience. This commitment to adaptability underscores the software's ongoing relevance in the field of molecular modeling.

Amazon Neptune is a robust and efficient fully managed graph database service designed to facilitate the development and operation of applications that utilize intricately connected datasets. At its core lies a specially designed, high-performance graph database engine that excels in storing vast amounts of relational data and performing queries with minimal delay. Neptune accommodates widely recognized graph models, such as Property Graph and the W3C's RDF, alongside their corresponding query languages, Apache TinkerPop Gremlin and SPARQL, enabling seamless creation of queries that adeptly traverse complex datasets. This service is instrumental in various graph-related applications, including systems for recommendation, fraud detection, knowledge representation, drug research, and cybersecurity. It also empowers users to proactively recognize and examine IT infrastructure through a comprehensive security framework. Moreover, it allows for the visualization of all infrastructure components, aiding in the planning, forecasting, and risk mitigation processes. By utilizing Neptune, organizations can craft graph queries that detect identity fraud patterns in near-real-time, particularly in financial transactions and purchases, enhancing their overall security measures.

adWATCH - AE is a solution designed to aid pharmaceutical companies in handling and documenting adverse events that arise during clinical trials. It provides a quick and efficient way for reporters at clinics, hospitals, or investigative sites to create and oversee Adverse Event Reports (AERs), ensuring proper reporting to regulatory bodies and government organizations. An adverse effect refers to a harmful or undesirable reaction experienced by a patient due to medications or medical devices. The process of documenting adverse events necessitates thorough tracking of all medical complaint case details, which culminates in the creation of MedWatch reports, CIOMS reports, and other management documentation. With adWATCH - AE, researchers, physician investigators, Contract Research Organizations (CROs), clinical trial experts, and various health professionals can easily generate and submit AERs in compliance with FDA requirements, adhering to both MedWatch and CIOMS formats. This streamlined process not only enhances regulatory compliance but also improves patient safety oversight during clinical trials.

Streamlined surveillance of diverse data sources, seamlessly integrated with a GVP IX compliant signal management platform, can revolutionize your safety data handling. The Evidex platform offers a ready-to-go, GVP-IX compliant signal management solution that simplifies your operations without the hassle of switching between various services. By modernizing your management processes, you can ensure they are audit-proof and efficient. This automation not only helps meet regulatory standards but also enhances the overall value generated for your organization. With automated signal detection, you can identify safety signals from established sources such as ICSR databases, the FDA's Adverse Event Reporting System (FAERS), VigiBase, and clinical trial data. Furthermore, you can incorporate additional data sources, including claims, electronic health records (EHR), and other unstructured information. By aggregating these diverse data pools, you can significantly improve signaling algorithms, streamline validations and assessments, and accelerate responses to pressing drug safety inquiries. Ultimately, this approach transforms how organizations manage and leverage safety data for better outcomes.

Preclinical information is found in many laboratories. It can be stored in multiple systems within the laboratory and with several external partners. Team members are unable to have clear and informed decisions without a unified solution because they lack transparency in core business data. Pristima, a fully integrated digital laboratory execution platform, features intelligent workflows, task automation, and data and information management throughout the entire preclinical process. Xybion's preclinical platform provides a central data repository as well as a standard archive platform. This platform can help you increase productivity and lower costs. With complete transparency across all platforms, gain visibility into the information that is there and take actions based on your current business needs. Effective data management can reduce the time it takes to submit final SENDs from end-of-study.

Discover valuable insights within your data by utilizing the Cortellis™ suite of life science intelligence tools, enabling you to make more informed decisions throughout the entire R&D process. We have alleviated the burden of gathering, integrating, and analyzing data, allowing you to concentrate on the essential choices necessary for expediting your products' market entry. With a unique combination of extensive, high-quality data, fortified by profound domain knowledge, industry insight, and therapeutic expertise, Cortellis reveals crucial insights that facilitate data-driven decisions, ultimately speeding up innovation. Access tailored, actionable responses to your specific inquiries throughout the R&D lifecycle, drawing from the most comprehensive and in-depth intelligence sources available. By incorporating Cortellis into your daily routine, you can significantly enhance the pace of innovation and streamline your workflow. This makes Cortellis not just a tool, but a vital partner in your path to success.

Genedata Imagence® provides a platform for training deep neural networks that classify cellular phenotypes in high-content screening (HCS) images, ensuring that the results are both unbiased and of superior quality. By automating the analysis process, it enables assay biologists to harness the capabilities of deep learning algorithms effectively. With Genedata Imagence, biologists can analyze HCS imaging data in real-time using advanced deep learning methods, all without requiring extensive knowledge of the underlying algorithms. This eliminates the complexity often associated with data analysis, as the user-friendly interface of Genedata Imagence facilitates quality control and data exploration throughout the entire workflow. As a result, researchers can focus on deriving insights rather than getting lost in intricate coding.

StarDrop™, a comprehensive suite of integrated software, delivers the best in silico technology within a highly visual interface. StarDrop™, which allows seamless flow between the latest data, predictive modeling, and decision-making regarding the next round or synthesis, improves the speed, efficiency and productivity of the discovery process. A balance of different properties is essential for successful compounds. StarDrop™, which guides you through the multi-parameter optimization challenge, helps you target compounds with the highest chance of success. It also saves you time and resources by allowing you to synthesize fewer compounds and test them less often.

At Metabolon, we proudly provide the most extensive Level 1 library in the metabolomics field. Our unique library has been meticulously developed and refined over two decades, boasting more than 5,400 entries. The majority of these entries are classified as Level 1, comprising roughly 85% (around 4,600 entries); however, about 15% of the library consists of Level 2 entries (approximately 800 entries), which are categorized as such due to the unavailability of commercial standards necessary for Level 1 classification. Thanks to our unparalleled library size and exceptional annotation confidence, Metabolon offers precise and highly actionable insights tailored to our clients’ scientific or clinical needs. The applications of metabolomics span a broad spectrum of research areas, including soil health, nutritional studies, preclinical investigations, and clinical trials. Whether you're identifying trends within a population or fine-tuning an individual's treatment plan, metabolomics serves as a powerful tool to uncover crucial answers to pressing questions in various fields. With such extensive resources at your disposal, the potential for discovery is truly limitless.

Experience seamless collaboration and knowledge sharing across your organization with a comprehensive platform that integrates all essential tools, allowing for secure workflows and the use of Phoenix-based applications alongside third-party software. With more than 6,000 researchers relying on Phoenix WinNonlin for non-compartmental analysis (NCA), toxicokinetic modeling, and pharmacokinetic and pharmacodynamic (PK/PD) modeling, it has become the preferred choice among biopharmaceutical companies, academic institutions, and 11 international regulatory bodies, including the US FDA, EMA, and PMDA. Additionally, the Phoenix Platform offers advanced features like population PK/PD (popPK) modeling through Phoenix NLME and Level A correlation capabilities provided by the Phoenix IVIVC Toolkit, while its Validation Suites enable rapid software validation in less than half an hour, ensuring efficiency and compliance. This powerful suite not only enhances research productivity but also fosters innovation by enabling users to streamline their workflows effectively.

IPA can also help analyze small-scale experiments that produce gene and chemical lists. IPA allows for targeted searches on genes, chemicals, and drugs. It also allows the creation of interactive models of experimental system. Data analysis and search capabilities allow for the understanding of the significance of data, targets, or candidate biomarkers within larger biological or chemical systems. The Ingenuity Knowledge Base contains highly structured, detail-rich chemical and biological findings that backs the software. Learn more about QIAGEN Ingenuity Pathway Analysis. Comparison Analysis determines which pathways, upstream regulators and diseases are most important. It can also be used to identify biological functions across time, doses, and other conditions.

Leverage the capabilities of biomedical data through the Polly Platform, which is designed to enhance the scalability of batch jobs, workflows, coding environments, and visualization tools. By facilitating resource pooling, Polly optimally allocates resources according to your specific usage needs and leverages spot instances whenever feasible. This functionality contributes to increased optimization, improved efficiency, quicker response times, and reduced costs associated with resource utilization. Additionally, Polly provides a real-time dashboard for monitoring resource consumption and expenses, effectively reducing the burden of resource management on your IT department. An essential aspect of Polly's framework is its commitment to version control, ensuring that your workflows and analyses maintain consistency through a strategic combination of dockers and interactive notebooks. Furthermore, we've implemented a system that enables seamless co-existence of data, code, and the computing environment, enhancing collaboration and reproducibility. With cloud-based data storage and project sharing capabilities, Polly guarantees that every analysis you conduct can be reliably reproduced and verified. Thus, Polly not only optimizes your workflow but also fosters a collaborative environment for continuous improvement and innovation.