Execution Dynamics: Align to the Customer Quantum for the Best Possible Business Performance

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BIOVIA User Conference | Agenda

Do you know what is in the latest? Do you want to know what is coming in the next few years? Panel Discussion Efforts are well underway to digitalize processes and workflows in the Consumer Packaged Goods and Chemicals industries. However there is still progress to be made, and many companies still face challenges in implementations. In this interactive session, we will discuss topics such as digital solution deployments and user adoption, as well as the related IT challenges.

In this presentation we will discuss various aspects of the selection process, including workshops with QC units to get feedback on current system and how it was implemented, and discussions with Gartner, vendors and other pharma companies.

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We held focused sessions with two vendors including BIOVIA, looking at what the system can and cannot do, how fast AstraZeneca methods can be applied out-of-the-box, and how easy it is to get basic training for the core project team. After evaluating and scoring system usability with the wider AstraZeneca QC community, we looked at the proposed scope, timelines, and resource estimates, leading to the final proposal for a decision from the Steering Committee.

Mary Beth Finnegan , BIOVIA Product formulators have the daunting task of creating high quality formulas that are regulatory compliant, at the lowest cost, and delivered fast. Enginuity is a robust formula design and management solution that combines powerful ingredient-level calculations with real-time regulatory evaluation to the lowest substance level. Combined with performance test data and version-controlled dossier creation and management, it contains all the information that follows a formula in the product development life cycle.

In this talk we will detail how Enginuity can enhance your formulators' efficiency to accelerate product innovation and achieve regulatory compliance, while significantly reducing time-to-market and raw material costs to create better, faster products. Mats Khilen , BIOVIA This presentation will detail a number of significant changes for the end users in , like better editor performance, export of experiment lists to Excel, improved tables in body text section and better integration with MacOS.

System integration is a prioritized development area and more features are planned for the release. I have over methods, how can you help me?

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I have sites globally, how can I roll out to other sites quickly? Are these questions you have been asking? By utilizing templates, the deployment of methods and recipes could be streamlined and made easier. Despite that organized nature, surprisingly LIMS are often single sample centric, which makes it difficult to aggregate test data across multiple samples and connecting such test and performance data back to the sample source information like formulations and associated production process parameters.

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Ton van Daelen , BIOVIA The process of optimization of a molecular design can be improved through the use of appropriate modeling and simulation techniques. Execution of these techniques within a project constitutes virtual experimentation where hypothesis, method and outcomes must be tracked. The outputs of these virtual experiments must balance practical considerations and real world constraints with rapid evolution of design. Recently, a number of trends in machine learning, synthesis planning, rapid synthesis and high-throughput testing have begun to converge on effective methods for getting value from the integration of real and virtual experimentation.

This typically means that machine learning ML models built from such data have relatively weak predictive power and a narrow applicability domain. Here we discuss results of computational experiments we have done at BIOVIA which indicate that ""static"" models built only from initially available data yield poor results when used for optimization.

Additional computational experiments indicate that a superior approach is active learning, in which ML models are used to guide lab experiments in such a way as to alternate between providing data to improve the lead "exploitation and providing data to improve the model "exploration". The use of rapid in silico "pseudo-assays allows us to test and tune proposed active learning strategies much more rapidly than if we relied solely on lab experiments to provide new training data. It is crucial in DNA repair, clearly resulting in a major target of interest for cancer research. To date, although the understanding of ADP-ribosylation role in cellular functions has been greatly enhanced, molecular targets and their specific modification sites are partially understood.

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Identifying ADP-ribosylation sites is essential to clarify the molecular mechanisms regulated by this modification. To this purpose, we present ADPredict, the first dedicated computational tool for the prediction of ADP-ribosylated aspartic and glutamic acids. It is based on i physicochemical properties, ii in-house designed secondary structure-related descriptor, and iii three-dimensional features of a set of human ADP-ribosylated proteins reported in literature, developed using machine learning techniques.

ADPredict statistical robustness and predictive performance was evaluated both internally, via intensive bootstrapping, and in predicting two external experimental datasets.

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Thus, ADPredict represents a valuable tool for enriching the knowledge of the ADP-ribosylation, both in investigating pathways affected by ADP-ribosylation events, and more specifically when focusing the study on a given target protein. Moreover, the novel secondary structure descriptor introduced, HM-ratio, represents a promising tool for different kinds of chemo-bioinformatics studies, such as post-translational modification prediction.

ADPredict is freely available online, at www. The software Pipeline Pilot was crucial for the automation of each step of ADPredict development, from the early stages of data preparation and standardization to the conclusive predictive performance evaluations. The soap web service integration provides the predictions, calculated on the fly in a completely automated Pipeline Pilot workflow, to the ADPredict web server.

Indeed, by several blind challenges and benchmark studies, COSMO-RS in its COSMOtherm implementation, has been proven to be currently the most accurate method for predicting free energies in liquids, being about twice as accurate as force-field approaches. Even though the binding of ligands to enzyme receptors is somewhat different from solvation in liquids and therefore not directly available by COSMO-RS, it is governed by the same kinds of interactions, i.

The excellent performance of the COSMO surface polarities as interaction descriptors within COSMO-RS strongly suggests, that these surface polarities should also be valuable input for the quantification of ligand-receptor interactions. Both methods yield results, which are comparable or superior to state-of-the-art competing methods. Furthermore, COSMOsar3D does not require any cutoff parameters, and turns out to be far less sensitive to parameters as grid position, grid size and misalignment. Recent advances in machine learning methods have shown the ability to generate and optimize compounds in silico to meet a desired product profile.

SSA allows them to make better and more informed decisions by accelerating the conversion of scientific data into knowledge and action. Chemistry searching is a very important component of SSA as it allows scientists to search using chemical language.

However, with the evolution of storage technologies, chemical data sets that everyone can create are getting bigger and bigger and can easily exceed a billion or more chemical structures. Therefore the scalability of chemistry aware indexation and search engine is very important. This presentation will discuss how BIOVIA overcame the technical challenges encountered building its new Scientific Search and Analytics framework and show you the great new achievements that we made within a modern environment such as Cloud-based architecture.

As informatics goals and software needs evolve, so too must the informatics infrastructure needed to protect critical intellectual property in an agile and cost-effective IT environment. The system also needs to be highly configurable and extensible to accommodate your specific project needs. Jaroslaw Tomczak - Informatics Unlimited Ltd. Electronic laboratory notebooks have been in use in chemistry for almost 20 years. These are further individually defined by the underlying databases or chemical tools from which the data are exported.

But without a common language and structure shared by all users to describe experiments, data integration is unnecessarily expensive and a significant part of published data has not been readily available for processing or analysis. UDM is a collective effort of vendors and life science organizations to create an open, extendable and freely available reference model and data format for the exchange of experimental information about compound synthesis and testing.

Run under the umbrella of the Pistoia Alliance, the project team has published two releases of the UDM data format and it is expected that the model will continue to be improved as demand stipulates working with the Pistoia FAIR data implementation by industry community. Dana Honeycutt , BIOVIA Assuming we have available a large diverse set of real or virtual chemical compounds, multi-objective lead optimization involves ranking these compounds according to how they best meet a set of conflicting objectives.

The objectives may include activity against one or more targets, a lack of activity against anti-targets, suitable ADME properties, and low toxicity. Here we discuss methods for assessing these tradeoffs while maintaining diversity within the top-scoring subset of compounds and accounting for the applicability domain of machine learning models used to score the individual compounds. Within the context of evolutionary optimization, these methods make up the strategy for determining which subset of compounds survives to the next generation of the overall optimization cycle. Joe Bradley , Scitegrity Scitegrity take a new approach to chemical compliance.

We encode chemical legislation so it can be searched computationally via chemical structure. Highly accurate and reliable, it is used by major chemical and pharmaceutical companies around the world to ensure compliance. With the ability to automatically check inventories running into millions of compounds and legislation checked and updated weekly.

Sean O'Hare , BIOVIA In this session our experts will share a variety of customer stories of different areas and applications in Scientific Research decision-making detailing the applications and the realized value of the deployments. See how you can at the same time improve your material inventory operations, internally and externally and how to leverage over supplier catalogues via the Available Chemicals Directory to achieve streamlined lab processes across sites.

Providing a first principle based alternative to force-field driven molecular dynamics simulation methods on the one hand, and to empirical QSPR or group contribution methods on the other hand, COSMO-RS has become a versatile toolbox in various areas of application, from chemical engineering and pharmaceutical formulation to environmental properties and life science applications. Through its unique combination of a quantum chemical treatment of solutes and solvents with an efficient statistical thermodynamics procedure for the molecular surface interactions, it enables the efficient prediction of many thermodynamic equilibrium properties such as solubility, VLE, LLE, and SLE phase diagrams, vapor pressure, and Henry law constants.

References [1] A. Klamt, J. Eckert, A. Klamt, F.

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Eckert, W. Therefore, realistc modeling of such processes requires the inclusion of solvation effects. While COSMO-RS was restricted to homogeneous liquids, it has been extended to the self-consistent prediction of the structure and the free energies of molecules in complex, self-organizing inhomogeneous systems.

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It extends the application range to many new areas, such as the prediction of micellar structure and critical micelle concentrations, finite loading effects in micelles and biomembranes, free energies and structure of liquid interfaces, microemulsions, and similar applications. A series of application examples will be demonstrated. The applicability extends into the simulation of multiphase microemulsion systems in virtual testtubes, for example, the simulation of complex fish point diagrams.

In this workshop we provide a brief introduction how to use COSMOtherm to predict properties such as solubility or vapor liquid equilibria. In the hands-on part the participants will have the opportunity to predict a larger number of solvation free energies and to compare them with experimental results. Free energies of solvation are the key quantity to bring a quantum chemically calculated reaction into solution and thus indispensable in reaction chemistry.

In order to reconstruct this process, we performed a chondrule formation experiment aboard the International Space station. At conditions of long-term micro gravity synthetic forsterite Mg2SiO4 particles were repeatedly exposed to electrical discharges with the aim to observe if these particles melt and fuse under these conditions.