Computational Modeling & Simulation

Display Application Development

ENSCO leverages its display application development experience with visualization expertise and the IData Human Machine Interface (HMI) tool suite, adopted and accredited by both commercial and military customers, for a display application advantage. ENSCO offers highly reliable, safety- and mission-critical system expertise for display application development for embedded, PC-based, and simulation applications. Our engineering capabilities span concept to development, including verification and certification for display development. Our HMI solutions are structured for high-performance embedded solutions and take advantage of propriety tools and processes to accelerate prototyping and design solutions, making them a cost-effective. ENSCO has an extensive partner network that offers a broad set of COTS hardware and software, including the most popular real-time operating systems, graphics drivers and board support packages. Our commercial and military industry standard experience includes ARINC 661, FACE™, DO-178C, and DO-254. > * Safety-critical knowledge and experience in avionics, space, medical, rail and security sectors > * IData HMI tool suite for visual design, customer in the loop prototyping and development > * Visualization and graphics expertise in instrumentation, synthetic reality and augmented reality > * Verification, validation and certification to formal, regulated standards, including ARINC 661, FACE™, DO-178C, and DO-254 > * Expansive partner network for integration ease with the most popular real-time operating systems, graphics drivers and board support packages ENSCO is a one-stop supplier for development of on-time, visually rich simulation, modeling, training and embedded display applications. System providers in safety-critical sectors, including avionics, military, space, medical and transportation require highly reliable, embedded software development and certification expertise. There is a critical need for embedded display graphical applications development, verification and certification from a single provider that offers a turnkey solution in an industry that requires extremely reliable, yet cost-effective solutions.

Finite Element Analysis (FEA)

This modeling technique simulates the stress and deformations that individual components undergo during railway operations. ENSCO uses various FEA simulation packages, including Ansys, ABAQUS, and LS-DYNA. Results of simulations can be used for: > * Investigation of rolling stock and track components failing from fatigue > * Evaluation of design changes to components > * Life-extension studies of rolling stock

FACE™ Application Development

Using the IData infrastructure, customers can easily create Portable Component Segments (PCS) that use the IData Runtime that resides in the Platform Specific Services Segment (PSSS) and will communicate over the Transport Services Segment (TSS) on a stack aligned with the FACE Technical Standard. Advantages > * Integrated Tool Set — One integrated toolset for creating mission- and safety-critical displays > * Data-driven Architecture — Does not rely on the need for code generators or the need for custom code for each target device > * Platform Independent — Runs on any RTOS, processor and GPU combination > * DO-178C Certifiable — Certification kit meets the highest Design Assurance Level defined by the FAA Features > * Superior Performance > * True Rapid Prototyping > * Verification Tools > * Behavior-based Animations > * Performance Enablers > * Aligned with the FACE™ Technical Standard > * Supports Khronos OpenGL® SC 1.0 and SC 2.0, DO-178C, AS9100 ENSCO Avionics has teamed up with industry leaders in processing hardware, graphics processing and real-time operating systems to put together a DO-178 certifiable hardware and software aligned to the FACE Technical Standard.

Railway Simulation Services

ENSCO has industry-leading railway experts to perform simulations on behalf of our customers, including vehicle/track interaction studies, train handling, and make-up analysis, and derailment investigations.

Track/Train Dynamics Simulation

Used to simulate an entire train over long stretches of track that includes elevation changes and curves. This type of simulation is often used to assess freight train make-up and handling. ENSCO uses the software program Train Energy and Dynamics Simulator (TEDS) provided by our partner Sharma and Associates. Results of simulations can be used to assess problems such as: > * Building operational rules for train make-up and train handling > * Evaluating larger freight train sizes for safety > * Assessing proposed designs of new track, industrial leads, and balloon loops for safety and expected use deterioration > * Investigating and predicting derailment risk and identifying mitigating strategies

Vehicle/Track Interaction Simulation

ENSCO uses VAMPIRE for vehicle/track interaction simulation to predict vehicle motions and wheel/rail interaction forces when interacting with measured track conditions. Results of simulations can be used for: > * Understanding premature wheel and rail wear or RCF generation > * Investigating and predicting derailment risk and identifying mitigating strategies > * Identifying root causes of rapid track deterioration conditions > * Evaluating new vehicle or suspension types

Data Analytics

ENSCO employs subject matter expert-driven data analysis of track measurement, instrumentation, simulation, and economic analysis data. ENSCO uses small and large data analytics tools and methodologies, including statistical, artificial intelligence and machine learning. Benefits of ENSCO Data Analytics - Root Cause Identification - Prediction - Optimization Case Study: Data Analytics Project: Ballast Fouling and Trending Study The Challenge: Determine criteria for class-based approach to fouled ballast safety enforcement. The ENSCO Approach: Collect and analyze pertinent information via track inspection vehicles, long-term wayside instrumentation and ground-penetrating radar. Result: Objective criteria for more consistent enforcement of fouled ballast safety. Case Study: Data Analytics Project: Track Feature Risk Assessment Using V/TI Data The Challenge: Assess track feature health/risk using Vehicle/Track Interaction monitors and determine if the approach can scale to fleet size and offers greater coverage than traditional systems. The ENSCO Approach: Use analytical models that can be trained and applied to a variety of track features to develop a risk assessment index algorithm to rank features and conditions, and identify/prioritize high-risk sites. Result: Track feature-specific Bridge Risk Index that provided health and derailment risk assessments for bridges to prioritize maintenance.

Pharmacokinetic / pharmacodynamic modeling (CFD modeling)

Our recirculating medium allows for complex pharmacokinetic profiles of compounds and metabolic products through absorption, distribution, metabolism, and elimination (ADME) depending on the organ systems incorporated. We have extensive experience coupling HPLC-MS data with modeling of these systems through computational fluid dynamics (CFD) and other numerical methods to produce pharmacokinetic profiles both in different medium compartments and accumulated in the cells. Coupled with our functional measurements, we have the capabilities to generate Pharmacokinetic-Pharmacodynamic (PK-PD) relationships [2].

Modeling, Simulation and Analysis

Modeling is the art of capturing physical and abstract phenomena into digital systems. Simulation is the science of computational interactions and data evolution. Leveraging M&S as part of the Digital Engineering process requires selecting the right framework for the purpose. From early concept ideation to high-TRL system testing, we can bring the right M&S solution to your digital ecosystem. Our team of simulation software engineers and operations research analysts can provide end-to-end M&S capabilities with complete data traceability.

C2 Concept Exploration and Optimization Toolset

Infinity Labs developed a toolset that enables the exploration and optimization of largescale C2 concepts, with particular emphasis on dual-use technologies and swarms that may be added to the battlespace. Our toolset is compatible with AFSIM (Advanced Framework for Simulation, Integration, and Modeling).

Missile Intercept Defense Assessment Suite (MIDAS)

The Missile Intercept Defense Assessment Suite (MIDAS) integrates analysis capabilities with the Advanced Framework for Simulation, Integration, and Modeling (AFSIM) for evaluation of missile defense system performance against multi-missile raid scenarios.

Target / Hit triage

Target Triage: In-Silico analysis of the Target (Protein) of interest. It includes analysis of target: Sequence, Pocket/s, Inhibitor landscape, etc., 3D structures, Ligandability. Hit Triage: In-silico compilation and analysis of screening (In-vitro / phenotypic) output including clustering, Phys-chem property space, Ligand efficiency indexes, catalog SAR, and predictive ADME properties to enable decision-making on the selection of Active / Hit series by the Project team.

Virtual Screening

Virtual screening at Jubilant Biosys encompasses use of multiple methods like 2D, 3D, structure-based and ligand-based approach for initial screening, followed by analyses of hits from each screening, consolidation, application of data-fusion techniques to ensure and enhance hit-enrichment. Using virtual screening, we can help restrict the list of compounds to those that are most likely to have the desired therapeutic effect by screening the compounds based on certain characteristics such as bioactivity, solubility, and toxicity; while drastically cutting down the time and expense associated with the drug development process. Get in touch with our experts to find out how we can assist you. Virtual screening of databases of drug-like compounds or target-class-focused libraries is a strategy to discover novel scaffold(s). Virtual screening is a powerful approach to find novel hits, using either structure-based approaches (protein structure or homology model with known/identified binding site) or ligand-based approaches (chemical structures of known modulators of the target). Structure-based approaches encompasses - Screening by docking the database of chemical structures into the known or identified binding site and selecting the hits by analyzing the top hits in terms of docking score, interactions & ligand internal strain. - Constructing a pharmacophore based on key interactions of known modulators with the residues in the binding site and then using it for virtual screening. Ligand-based approaches will include - Pharmacophore-based screening by constructing pharmacophore models using structures of known inhibitors and then screening the databases using these pharmacophore models. - Using the shape. - Two-dimensional chemical structures of the known potent modulators to screen the databases. The databases we routinely use for virtual screening are pre-filtered using various filters like REOS (Rapid Elimination Of Swill), PAINS (Pan-Assay INterfering compoundS), and physico-chemical properties to remove known toxicophores, potential promiscuous ligands, assay-interfering moieties and non-drug like compounds. Virtual screening can be employed to screen against known binding sites, protein-protein interaction sites or known or predicted allosteric sites. For virtual screening in case of specific targets like kinases, since the interactions of inhibitors with the hinge is important, those interactions can be constrained during screening, so that all the hits will have appropriate moieties for these interactions. The final selected hits from virtual screening can be procured from commercial vendors and tested in biological assays.

Approaches to Compound Library Design

Utilizing different in-silico methods, we design focused arrays of compounds for parallel synthesis. With curated sets of available reagents, we enumerate compounds accessible through current chemistry, subsequently prioritizing compounds for synthesis by deploying various CADD protocols: - Random - Single to multi-dimension - Focused: Various aspects of 2D to 3D CADD protocols: - Structure-based - Ligand-based - Target/pathway specific - Diversity oriented - Phys-Chem properties - R-group

Databases for Virtual Screening

At Jubilant Biosys, we have meticulously curated an extensive in-silico lead-like library (commercially purchasable) comprising over 5 million compounds, optimized for high-throughput virtual screening. On-demand databases (REAL / Galaxy) could also be considered. We utilize physicochemical property filters, fingerprint clustering, and diversity analysis to curate and enhance our fragment/lead-like library, elevating its quality for lead discovery.

Computational Chemistry

The Jubilant Biosys Computational Chemistry team excels in drug discovery design efforts in collaboration with the medicinal chemistry, biology and DMPK teams, by conducting molecular modeling studies – ligand-based drug design approaches (LBDD, pharmacophore and QSAR modeling), protein structure-based drug design (SBDD, homology modeling, docking and scoring), fragment-based drug design, chemoinformatic analysis and de novo design. The team providing these computational chemistry services extensively utilizes in-house expertise in software development, curation and structural biology for driving molecular design. Achievements: - The Jubilant modeling group is actively involved in over twenty integrated drug discovery projects and modeling collaborations. - Jubilant’s computational chemistry group played a critical role in the design and successful development of a multi-kinase inhibitor series for two different projects. - Molecular modeling (structure-based drug design) techniques have been employed in the development of two clinical candidates (GPCR and kinase targets) and a backup candidate (protease target) for clinical trials. Molecular Design Collaborations: Our team of computational chemists empowers drug discovery scientists to deploy ready-to-use models and make faster and wiser decisions. The Tools Used for Computational Drug Discovery: - Jubilant proprietary platforms for drug properties and shape-based searches. - Curated small molecule databases containing over 2 million molecules, covering all therapeutically significant target classes: kinases, GPCRs, ion channels, NHRs, PDEs, proteases and a known drug database. - Scaffold, bio-isostere and R-group databases. - Internal software tools to facilitate the execution of complex modeling tasks. - Extensive databases of drugs and leads from the literature. - Schrodinger molecular modeling and CIMPL chemoinformatics software platforms. - Multi-core, high-performance workstation with GPU card for molecular dynamics, virtual screening and quantum calculations. The People Providing Expertise in a Range of Computational Chemistry Solutions: - A strong and highly diverse modeling team, proficient in all relevant aspects of drug design. - Management with over thirty years of combined pharmaceutical industry experience. - Leadership with versatile skills in modeling, experienced in the development of drug candidates and marketed drugs. - Senior leaders with a strong publication and patent record, covering diverse therapeutic targets and computational methodologies.

Ligand-based Drug Discovery

In the field of drug discovery, very often, the target structure will not be available, but a few small molecules might be known to be modulating the target. In such a situation, the small molecules are used as the basis for discovery efforts. Ligand-based drug discovery (LBDD) refers to drug discovery efforts in absence of any target structures and in presence of chemical structures known to modulate the target. Ligand-based drug discovery starts with either a single compound or a set of compounds known to be potent against a target and based on the knowledge of structure-activity relationships (SAR), potency and other important properties are improved by designing appropriate analogs. Designing can be accomplished by Topliss method or simple analog design based on structural similarity or properties. Often, computational tools such as pharmacophore models or shape of the compounds can be useful for design purposes. Once a dataset of considerable size becomes available, with a good range of potency, a Quantitative Structure-Activity Relationships (QSAR) models can be attempted and used if the models are robust enough for prediction purposes. Similarly, if the target is well known with a lot of compounds already known in public literature or public databases, then machine-learning based models can also be attempted. If the machine-learning models are robust enough, they can be used for filtering design ideas or virtual screening or scaffold-hopping hits. Jubilant has been successful in delivering clinical candidate compounds for several targets for which the target structure was not known at the time. The computational chemistry team, along with the medicinal chemistry team, collaborates quite closely, to run the projects requiring LBDD efforts. Jubilant Biosys employs Schrodinger software suite as well as Cresset’s scaffold-hopping tool, Spark, for driving ligand-based drug discovery projects. The computational chemistry group of Jubilant Biosys also employs many machine-learning (ML) algorithms to build ML-based models, both regression and classification models, to assist LBDD efforts. If the target structure is not known, but structures of its closest homologues are known, then a homology-based model can be built using the experimental coordinates of the structure of the closest homologue. If the homology model is good enough, then a structure-based design strategy can be employed. Jubilant Biosys provides a wide variety of specialized support for drug discovery services. If you are looking for quality solutions incorporated with the best practices in the drug discovery domain, feel free to contact us.

Chemoinformatics

The chemoinformatics team at Jubilant Biosys is engaged in developing or deploying various CADD protocols for managing and analyzing data during the DMTA cycle, strengthening data-driven decision-making across preclinical discovery and broader drug development services. We deploy in-house developed and state-of-the-art tools: KNIME, Datawarrior, CDD vault, Canvas, Cresset, RDKit, etc. for various Chemoinformatics activities. Some of the key activities include: - Target / Hit triage - Databases for Virtual screening - Predictive modelling - QSAR - AI/ML - Library design - Similarity and diversity analysis Target / Hit triage Target Triage In-Silico analysis of the Target (Protein) of interest. It includes analysis of target: - Sequence - Pocket/s - Inhibitor landscape, etc. - 3D structures - Ligandability Hit Triage In-silico compilation and analysis of screening (In-vitro / phenotypic) output including clustering, Phys-chem property space, Ligand efficiency indexes, catalog SAR, and predictive ADME properties to enable decision-making on the selection of Active / Hit series by the Project team. Compound Library Design The availability of a good quality compound collection and library design expertise is an essential feature for the drug discovery DMTA cycle. At Jubilant Biosys, our expertise includes catering to different aspects of Compound Library Design (CLD) for developing project-specific libraries for screening in relevant biological assays or through Virtual screening. These libraries feature chemotypes enriched with diversity as well as compounds possessing desired properties and functionalities. Our strategic compilation of compound libraries ensures rapid synthesis and expediting Structure-Activity Relationship (SAR) or DMTA cycles across various discovery phases. Approaches to Compound Library Design Utilizing different in-silico methods, we design focused arrays of compounds for parallel synthesis. With curated sets of available reagents, we enumerate compounds accessible through current chemistry, subsequently prioritizing compounds for synthesis by deploying various CADD protocols: - Random - Single to multi-dimension - Focused: Various aspects of 2D to 3D CADD protocols: - Structure-based - Ligand-based - Target/pathway specific - Diversity oriented - Phys-Chem properties - R-group Databases for Virtual Screening At Jubilant Biosys, we have meticulously curated an extensive in-silico lead-like library (commercially purchasable) comprising over 5 million compounds, optimized for high-throughput virtual screening. On-demand databases (REAL / Galaxy) could also be considered. We utilize physicochemical property filters, fingerprint clustering, and diversity analysis to curate and enhance our fragment/lead-like library, elevating its quality for lead discovery.

Quantum Smart Grid

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Quantum Meteorological Prediction

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Smart Grid Solution

Combining quantum algorithms with grid operations to boost forecasting, efficiency, and resilience—advancing toward quantum-intelligent power systems. Industry Background Dual-Carbon Goals Driving Grid Upgrades Energy restructuring calls for smarter, greener computing. Growing Grid Complexity Rising demand and renewables increase computing pressure. Need for Breakthrough Technologies Classical limits emerge; quantum offers new solutions. Industry Pain Points Low Algorithm Efficiency Conventional methods are slow and fail to meet real-time demands like power flow and load forecasting. Limited Accuracy Struggle with complex, uncertain data, reducing decision precision. Data Overload Exploding data volumes expose classical computing limits, hindering analysis and application. Solution Architecture & Advantages Full-Stack Integration Covers applications, algorithms, frameworks, and hardware for end-to-end quantum-power grid integration. Multi-Algorithm Collaboration Utilizes QLSTM, QTransformer, QMLP, etc., for time series, stream, and large-model computing. Platform-Hardware Synergy Supports encryption, structuring, and simulation with flexible backend quantum and hybrid clusters. Application Scenarios Power Forecasting Quantum LSTM improves short-term PV prediction for better supply-demand balance. Load Forecasting Quantum attention models fuse multi-source data to enhance load accuracy. Power Flow Calculation Quantum algorithms speed up flow computations for real-time scheduling. Fault Diagnosis Quantum models boost fault detection accuracy and response speed. Collaboration Case State Grid Corporation of China Exploring quantum-based solutions for PV power forecasting, power flow calculation, and load prediction.

Weather Forecasting Solution

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