Best Drug Discovery Software in the Middle East

Eidogen-Sertanty’s Target Informatics platform (TIP), is the first global structural informatics system. It enables researchers to examine the druggable genome from an structural perspective. TIP increases the rapidly expanding body experimental protein structure information and transforms structure based drug discovery from an inefficient, data-scarce discipline to a high-throughput science with rich data. TIP is a tool that bridges the knowledge gap between bioinformatics (bioinformatics) and cheminformatics. It provides drug discovery researchers with a knowledge bank of information that is both unique and highly complementary to existing bio- and cheminformatics platform information. TIP's seamless integration between structural data management technology and unique target-to-lead analysis capabilities enhances every stage of the discovery pipeline.

VeraChem LLC was established in 2000 to advance computer-aided drug discovery. These methods are implemented in high-performance software and provide comprehensive support to users. This is a key strategy of VeraChem LLC for product development. Current VeraChem software capabilities include host-guest and protein-ligand binding affinity prediction, fast calculation and computation of partial atomic charges for druglike compounds, computation and force of energies and forces using all the most commonly used empirical force field, automatic generation and generation of alternate resonance forms for drug-like substances, conformational search using the powerful Tork algorithm and automatic detection and removal of topological and 3D-molecular symmetries. VeraChem's software packages were built from a modular code base.

The biopharmaceutical market is complex today. There are growing demands for better specificity and safety, new treatment classes, and more complex mechanisms of disease. To keep up with this complexity, we need to have a better understanding of therapeutic behavior. Simulation and modeling provide unique opportunities to explore biological and physical processes down to the atomic levels. This can be used to guide physical experimentation and accelerate the discovery and development process. BIOVIA Discovery Studio brings together more than 30 years of peer reviewed research and world-class in-silico techniques like molecular mechanics and free energy calculations. It also allows for biotherapeutics developmentability and other related topics into one environment. It gives researchers a complete toolkit to explore the nuances in protein chemistry and to catalyze the discovery of small and big molecule therapeutics, from Target ID to Lead Optimizement.

The process of bringing a new drug to market, from the initial step to the final market introduction can be time-consuming, expensive, and highly regulated. It can take up to a decade. Final success depends on early access to accurate analytical results that are fast enough to make the right decisions during development and minimize late attrition. Today's drug development relies heavily on a rational approach. Typically, identifying the biological target is the first step. To identify the most promising candidates, it is necessary to have a deep understanding about their properties. Finding the most promising lead molecules can be a daunting task once a biological target is established. Lead discovery is typically the identification of potential drug candidates, either small organic molecules or biologic assembly with therapeutic potential.

Chemical Computing Group (CCG), has a strong reputation in collaborative scientific support. Our team of PhD-level scientists has offices in North America and Europe. They work closely with clients to provide support, hands-on training, and scientific advice on a wide variety of projects. CCG continues to develop new technologies through its team of scientists, mathematicians and software engineers as well as scientific collaborations with customers.

You can share clinical and pre-clinical knowledge easily across your organization using a single platform that integrates all the tools you need. Phoenix WinNonlin is the preferred choice for non-compartmental analysis, toxicokinetic modeling, pharmacokinetic, and pharmacokinetic (PK/PD), modeling by more than 6,000 researchers from biopharmaceutical companies and academic institutions. It also includes 11 global regulatory agencies including the US FDA (EMA), PMDA, and more. The Phoenix Platform features population PK/PD modeling using Phoenix NLME and Level 1 correlation via the Phoenix IIVC Toolkit. Validation Suites allow for quick and easy software validation in less than 30 minutes.

Chemia is a browser-based & cloud-ready ELN platform. Chemia was designed, developed and architected by scientists. It is a platform that allows you to manage, assign, monitor, and track all R&D activities. It allows you to automate your R&D setup and makes it paperless. It saves time (approx. It saves time (approx. 1 hour per scientist) through Cross-functional collaboration. This makes it audit-ready and helps you manage data effectively. Fast retrieval, search, comparative studies, and reconfigurability allow for faster and more appropriate decisions. A system for managing inventory and scheduling information for chemicals and equipment within a laboratory. A system that tracks equipment usage, maintenance logs, and calibration logs. This is essential for efficient lab management and effective working. A system that provides the protocol, and ensures compliance.

Genedata Imagence®, allows you to train a deep neural net to classify cellular characteristics in HCS images. This will give you objective, high-quality results. It automates your analysis to allow assay biologists to harness the power of deep learning algorithms. Genedata Imagence allows biologists to immediately and directly analyze HCS imaging data with sophisticated deep learning techniques using no specialized algorithmic knowledge. Don't hide your analysis behind abstract lines of code. Genedata Imagence's intuitive interface makes it easy to QC and explore data at every stage.

Genedata Biologics®, streamlines the discovery of biotherapeutics. This includes bispecifics and ADCs as well as TCRs, CARs-Ts, CARs-Ts, CARs, and AAVs. It integrates all discovery workflows, making it the most popular platform in the industry. This allows you to focus on innovation and is the most widely used. A first-in-class platform that digitalizes biotherapeutic discovery accelerates research. The platform simplifies complex R&D processes by allowing for the creation, tracking, testing, and evaluation of novel biotherapeutics drugs. It can work with any format: antibodies, bi- and multi-specifics as well as ADCs, novel scaffolds, therapeutic proteins, and engineered therapeutic cell line such CAR-T cells and TCRs. Genedata Biologics acts as a central data backbone that integrates all R&D processes. This includes library design, immunizations, selections, panning, molecular Biology, screening, protein engineering and expression, as well as candidate development and manufacturability assessment.

You expect fast, accurate, and conclusive results when using LC-MS/MS in research or routine workflows. SCIEX software helps you get the most from your high-performance LC/MS/MS system. It provides specific workflow and application modules that can be used to complement your operating system. Your mass spectrometer will run with the right software combination that suits your needs. These are the core engines for SCIEX nominal mass systems and accurate mass LC/MS/MS systems. These modules are designed to quickly and reliably acquire, process, and report data, while remaining compliant. Add-on modules allow for simplified workflows and high performance. With application-specific software modules, you can convert your data into conclusive results faster.

Site-Identification by Ligand Competitive Saturation generates 3D maps (FragMaps), showing interaction patterns for chemical functional group with your target molecule. Site-Identification through Ligand Competitive Saturation generates 3D maps, (FragMaps), of interaction patterns for chemical functions groups with your target molecule. SILCS reveals the intricacies and provides tools to optimize ligand scaffolds through qualitative and quantitative binding pocket insights. This allows for faster and more effective drug design. SILCS employs multiple small molecule probes that have different functional groups and explicit solvent modeling to perform protein target mapping. Visualize positive interactions with the target macromolecule. Get insights to design better binding agents with the best functional groups.

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. With over 20 years of experience, we have the ability to translate science into software that is easy to use. We also provide expert consulting support for drug discovery, clinical research, and regulatory submissions.

AutoDock is a set of automated docking tools. It predicts how small molecules, such sub- or drug candidates, will bind to a receptor with a known 3D structure. It has been improved over the years to add new functionalities and multiple engines were developed. AutoDock 4 is the current version, and AutoDock Vina is the latest. AutoDock-GPU is an accelerated version that runs hundreds of times faster than the original single CPU docking code. AutoDock 4 is actually composed of two main programs. Autodock docks the ligand to a list of grids that describe the target protein. Autogrid pre-calculates the grids. The atomic affinity grids can also be visualized. This can be used to help organic synthetic chemists create better binders.

Cortellis™, a suite of life science intelligence software solutions, reveals hidden insights in data. This allows you to make better informed decisions throughout the R&D process. We have taken out the tedious work of finding, integrating and analysing data so that you can concentrate on the crucial decisions required to bring your products to market quicker. Cortellis provides unique data analysis that is rich in domain knowledge, industry insight, and therapeutic expertise. This allows you to unlock hidden insights that will allow you to make data-driven decisions that drive innovation. With the most comprehensive and deepest intelligence, you can get precise and actionable answers to specific questions throughout the R&D process. Cortellis is an indispensable part your daily work flow.

metaphactory converts your data into actionable, contextual and consumable knowledge. It also drives continuous decision intelligence. Intuitive interfaces that are intuitive and out-of-the box for searching, browsing, and exploring your Knowledge Graph. It is possible to create custom interfaces using low-code that allow business users to interact with the Knowledge Graph. Start small, iterate often, and add new use cases, data, and users as you go. Low-code platform for building applications and agile knowledge management.

To drive precision medicine programs that work, pharmaceutical companies require comprehensive genomic information. However, decisions are often made with only 10% of the data available. Genomenon provides 100% of the data. ProdigyTM Patient Landscapes are a cost-effective and efficient natural history research solution for pharmaceuticals. They enhance insights from retrospective and prospective health data to support the development rare disease therapies. Genomenon uses an AI-driven approach to deliver a thorough and expert assessment of all patients in the medical literature in a fraction time. Get a complete overview of every genomic biomarker in the medical literature. Every scientific assertion is supported with empirical evidence from medical literature. Identify all genetic drivers and determine which variants are pathogenic according ACMG clinical standards.

BioNeMo, an AI-powered cloud service for drug discovery and framework, is built on NVIDIA NeMo Megatron. It is used to train and deploy large biomolecular Transformer AI models at supercomputing scale. The service provides pre-trained large language models (LLMs), native support for common file types for proteins, DNA, and chemistry, as well as data loaders for SMILES molecular structures and FASTA amino acid and nucleotide sequencings. You can also download the BioNeMo framework to run on your own infrastructure. ESM-1, which is based on Meta AI’s state-of the-art ESM-1b and ProtT5 respectively, are transformer-based protein-language models that can be used for learning embeddings for tasks such as property prediction and protein structure. BioNeMo will offer OpenFold, a deep-learning model for 3D structure prediction and novel protein sequences.

Use AI to accelerate the journey from bench-research and laboratory insights to life-changing therapies. Reduce your reading time to minutes and gain up to 90% more research productivity. With a high-precision and high-accuracy research, you can cut through the noise to navigate the ever-growing amount of scientific literature. Save time, reduce bias, and increase the odds of discovering novel things. Explore disease biology in depth and discover advanced targets. Causaly’s high-precision graph of knowledge consolidates evidence from millions publications, allowing for unbiased, deep scientific exploration. You can navigate cause-and effect relationships in biology without being an expert. Discover hidden connections by viewing all scientific documents. Causaly’s powerful AI machine is able to read millions of published biomedical publications in order to support better research and decision-making.

Clara's domain specific tools, AI pretrained models, accelerated applications, and accelerated AI applications are enabling AI advances in many fields, including medical device, imaging, drug discovery and genomics. Holoscan allows you to explore the entire pipeline of medical device deployment and development. With the NVIDIA IGX Developer Kits, you can build containerized AI apps using the Holoscan SDK. The NVIDIA IGX SDK includes pre-trained AI model, healthcare-specific acceleration libraries and reference applications for medical devices.

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.

Makya is a user-friendly SaaS-based platform for AI-driven drug design focusing on Multi-Parametric Optimization. It allows the design of novel compounds that are easy to make in accordance with a multiobjective blueprint at unprecedented speeds, performance and diversity. Makya has multiple generative algorithms that cover different use cases, from hit discovery to lead optimizing: fine-tuning to find optimal solutions in your chemical space according to your project blueprint; novelty to find new ideas of high novelty for rescaffolding/hit discoveries; forward to design a focused collection of compounds easily accessible using commercial starting materials. The new Makya 3D Module enhances the user-experience and scientific utility of Makya. Makya 3D offers a wide range of 3D modeling capabilities in both ligand and structure-based pipelines. You can now use these 3D scores to guide generation natively within Makya.

Scitara DLX™ provides a fast connectivity infrastructure for any instrument used in life science laboratories. It is fully compliant and auditable, and can be accessed from any cloud-based platform. Scitara™, a universal digital data network, connects all instruments, resources, apps, and software within the laboratory. The cloud-based platform, which is fully auditable, connects all data sources in the lab, allowing data to flow freely across multiple endpoints. Scientists can now spend their time on scientific research and not waste it trying to solve data problems. DLX corrects and curates flight data to support the creation of precise, structured data models that feed AI/ML systems. This supports a successful digital transformation strategy for the pharma and biopharma sectors. The ability to access scientific data allows for faster decision-making and drug discovery, which helps bring drugs to market quicker.

We combine clinical and experimental data with machine learning to improve precision medicine and navigate human disease biology. Contingent AI™, a patent-pending technology, understands data relationships to provide sophisticated insights. We tackle data bias by iterating upon machine learning models that are based on decisions made during the feature engineering and pre-processing stages. We use zebrafish, cell, and other phenotypic animals models to validate in-silico predictions in in vivo experiments. We also genetically modify them in vitro to improve translation. We quickly incorporate new data into machine learning models by using active learning and computer vision on validated models of cardiac, central nervous system, and rare disorders. We quickly incorporate new data into machine learning models by using active learning and computer vision with validated models of cardiac, central nervous system, and rare disorders.

LiveDesign is an enterprise information platform that allows teams to collaborate, design, experiment, analyze, track, and report in one central platform. You can capture ideas and model data. Create and store virtual compounds in a central database. Use advanced models to prioritize new designs. Integrate biological data and model results from federated corporate databases. Use sophisticated cheminformatics for faster analysis and development of compounds. Advanced physics-based methods are combined with machine learning techniques to quickly improve prediction accuracy. Remote team members can collaborate in real-time. You can collaborate with remote team members to share ideas, test, revise, or advance chemical series without losing sight of your work.

Automated surveillance of any source of data, fully integrated with a GVP IX-compliant signal management platform. GVP-IX compliant signal-management platform integrated into Evidex and ready-to-use off-the-shelf. Modernize and audit-proof all your management processes without the need to switch between platforms or services. Your safety data is worth more than you think. Automating signal detection and management allows you to focus on your organization's value, not just regulatory requirements. Safety signals can be identified from traditional sources such as ICSR databases, FDA Adverse Events Reporting System (FAERS), VigiBase, and clinical trial data. Incorporate new data sources like claims, EHR, or other unstructured data. These data sources can be combined seamlessly to improve signaling algorithms, increase validations and assessment efficiency, and provide faster answers for drug safety questions.