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Scientific Informatics: The Evolution of Scientific Business Intelligence to Drive Top Line Innovation GrowthImprove scientific data management across the global R&D Enterprise

One of the major challenges facing scientific and clinical research organizations is the inability to access, aggregate and mine scientific data across an R&D enterprise organization. Data remains locked in silos, causing productivity and decision making to suffer, and ultimately impeding an organization’s research efficiency. By successfully harnessing disparate data sources and software applications, organizations position themselves to apply their data in an intelligent, focused manner, thereby improving productivity, decision making and research efficiency. However, such efficiencies have eluded many scientific and engineering research organizations because traditional business intelligence (BI) technologies cannot handle advanced scientific data processing and analysis. As a result, organizations have been forced to make do with vendor-specific point solutions that drain in-house development resources to build customized solutions, or struggle with manually sharing data among incompatible point products. There is a clear need in today’s life, Consumer products, and materials sciences indus-tries for an open and standards-based scientifically-relevant BI solution that meet the needs of the scientific and engineering research communities.

Limitations of Traditional Business Intelligence in the Scientific Community

Business Intelligence technologies, including corporate dashboards, hyper-cubes and visualization systems, have been suc-cessfully applied in enterprise operations such as sales, marketing and finance to improve business productivity, competitive-ness and lower costs. Generally speaking, these BI tools have been used to satisfy the demands of executive-level decision makers who are looking for information about existing products, services and business operations. The information manage-ment needs of the business community continue to grow and drive vendors to improve analytics and information interfaces. Yet even with this mainstream business adoption, the use and relevance of traditional BI technologies within the research and development world has been limited, primarily because the BI platforms created for business are inadequate in their ability to handle anything other than structured numerical data, and they lack critical advanced scientific analysis and drill-down capabilities. In order to become more relevant to the scientific business community, BI technologies have been able to federate differing types of data more robustly across an enterprise’s operations, providing business knowledge workers with the information necessary to increase their productivity and effectiveness. However, the complexity of the data types and analysis methods used in the scientific community has left the scientific and clinical research markets with un-served needs.

Downfalls of Data Disparity and Point Products

Over a decade ago, scientific informatics was transformed with the advent of two new disciplines—bioinformatics and cheminformatics—which were created to change the way scientists mined data and how IT managed that data. After the advent of these two disciplines, the underlying concept widened into a more general notion of “omics”-based data mining (i.e. genomics, proteomics). These disciplines have developed organically since their genesis, and their associated data struc-tures, databases and analysis tools have grown exponentially both in size and disparity, resulting in often disconnected and isolated research silos of information. As such, software in the materials and pharmaceutical discovery arena has been sold as a series of point applications with several different interfaces. This not only requires users to write complicated scripts that are difficult to leverage between different types and levels of users, but it has also locked their data into software from one vendor or another, demanding that they write and read files of multiple standards to transfer data between applications.

Scientific Business Intelligence Solutions

In order to fully leverage the vast quantities and types of data within their organizations, scientific and engineering research organizations require a platform that encourages and enables exploration of data across many scientific disciplines. The platform must have the capability to access and aggregate both structured and unstructured data from mul-tiple research areas into a single environment. It must enable advanced scientific analytics and allow users to integrate the applications and algorithms that work best for them. It must empower all types and levels of users to rapidly and easily

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develop applications that meet their needs, limiting the burden on IT resources. It must offer flexibility for users to view results in the manner most effective for their needs, which may range from web portals to sophisticated 3D visualization. Finally, for users to realize the true value of their data, the platform must be able to deliver the precise information users seek—exactly when and how they need it—through interactive reports and dashboards.

Accelrys has developed technology solutions that meet these demands, enabling scientists, engineers, and managers to at-tain new insights and knowledge. The goal of these solutions is to formalize and institutionalize standard scientific research and decision-making tools for Scientific Business Intelligence (SBI) to the same degree that BI tools have become mainstream technologies. SBI solutions create foundational approaches and applications that can enable new and important initiatives such as translational medicine and formulation innovation into new markets.

Open Scientific Operating PlatformAt the heart of SBI and informatics technologies is an open and standards-based scientific operating platform (SOP) that enables the integration and aggregation of diverse scientific data and applications. The ability to aggregate disparate tools and data in a single environment is critical to enable users to readily leverage and combine their preferred technologies in a “plug and play” environment, thereby allowing them to meet their own individual needs without the burden of maintaining “home grown” applications. Users further benefit from a “plug and play” environment as they will no longer be locked into a single vendor relationship and they will be able to incorporate “best of breed” components—thereby challenging vendors to push the envelope of innovation.

As illustrated in Figure 1 and described in the following paragraphs, the power and openness of Accelrys’ SOP allows the delivery of true user-based solutions via:

1. The ability to select and configure best of breed methods into user-defined workflows 2. The freedom to choose a client interface for creating and deploying those workflows 3. The capacity to deliver data and analysis results in interactive reports and dashboards

BiologyChemistry

Reporting Statistics3rd Party/Internal

Apps

Materials Accord Isentris

Tools Databases

Webport(web access)

PipelinePilot

(Pro or Lite)

ThirdPartyClient

MaterialsStudioClient

DiscoveryStudioClient

AccordClients

Figure 1. A scientific operating platform based on an SOA model enables users to pick “best of breed” components from multiple vendors and configure the methods and interface to suit their needs. The new approach is highly customizable to the customer’s process, enabling the process to drive the informatics solution and not vice versa. This allows the customer to attain a competitive advantage by optimizing their process and then layering in the IT solutions.

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Service Oriented Architecture Ideally, the integrated SBI and Informatics platform is delivered via a Service Orientated Architecture (SOA), so it can stand on its own or dovetail into a larger, corporate SOA environment. The main advantage is that it moves beyond a proprietary backplane allowing component services to deliver advanced data aggregation, data mining and scientific analysis functionality from a variety of data and application sources, covering a range of capabilities across multiple scientific disciplines. These components can be joined together to enable workflows that are simple (e.g., a one-click check against molecular weight) to extremely complex (e.g., homology modeling or docking workflows).

SOA provides a true “plug and play” architecture that allows customers to decide what is “best of breed” science and let them choose from in-house, and third-party application technologies, data bases, including legacy.

Componentization of Best of Breed MethodsComponentization of a powerful and diverse range of functionalities on a single platform represents an industry breakthrough that improves research efficiency. Users will be able to improve efficiency and attain new insights by creating workflows that not only integrate functionalities previously disconnected due to vendor incompatibilities, but also transcend traditional scientific discipline barriers. On top of this, the ability to join and parameterize components within a graphical drag-and-drop environment empowers users to create new SBI applications without relying on already over-burdened IT groups.

With this new found flexibility, users will only be limited by their imaginations. The ability to rapidly configure components will also drive new science, such as what has been achieved through the development of new scoring methods for docking experiments. A workflow that connects the various steps in this extremely complex methodology is illustrated in Figure 2.

Flexible VisualizationIt is critical that the components of a Scientific Operating Platform can be developed independently from any specific client interface, because end users enjoy the freedom to deploy advanced scientific and engineering functionality in a variety of ways. As such, users can choose an interface that fits their needs. In some cases, this may be a web-based client that enables easy delivery and access to non-experts, and in other cases it will be a configured expert client.

For example, a company can configure the same interface into a tool for communicating the results of molecular modeling tasks performed by a Computer Aided Drug Design group to chemists and biologist. The interface can also be configured as

Figure 2: A workflow that configures complex science into a simple solution

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a simple modeling tool for chemists and biologists to use themselves. This type of flexibility has been requested for years and is now available. These two levels of flexibility and modular design allows for configurable innovative applications that offer greater ease of use and higher quality standards. This two dimensional configuration also allows the IT group to accommodate the exact needs of their users in a way that provides competitive advantage.

Interactive Reporting and DashboardsAnother advantage of an SOP is that it facilitates the creation of “dashboards”—customized interfaces that provide high level “views” into critical organizational information, which can range from information about the status of a company as a whole to information about a particular research site or project. Often delivered as browser- or PDF-based reports, dashboards give users and management alike the power to “drill-down” to the data behind the high-level reports in real-time, enabling them to immediately obtain the information they need to investigate questions or problems. Any analyses required to obtain the underlying information are set up to be automatically executed behind the scenes. As a result, end users don’t need to incur delays or productivity losses by calling on database administrators or scientists to obtain the information they need.

Financial Benefits of a Plug and Play Environment

The independence that customers can achieve from a “plug and play” environment is truly revolutionizing the way they will invest in software. Now, users can better align with any changes in a company’s process by modifying just a fraction of a system, instead of throwing out the entire system. No longer will investments be deemed “once and done,” thus increasing the return on investment (ROI) for companies that invest in the new environment. The ROI will not only come from faster, better and more cost effective solutions, but also from a more competitive assembly of the applications into workflows that facilitate creativity. In most R&D IT groups, the main goal is to enhance not just bottom line efficiencies, but also top line growth through IT strategies. Now, it is possible to quickly meet the ever changing demands of the scientific and engineering community through rapid delivery of applications that can be built at the speed of discovery, without excessive development or legacy support expense.

Examples of SBI Technologies in Action: Solutions for All Levels of Users

SBI solutions fully integrated with Informatics capabilities can be customized to provide the exact analytic and reporting functionalities a user needs. For example, as illustrated in the following examples, data from corporate scientific databases can be accessed and presented in one way for executives needing to assess the state of the company, and in a different way for managers or scientists or engineers looking to make specific research decisions. Moreover, customized solutions can be built with a low burden of time and cost because of the openness of the underlying technology architecture and the avail-ability of a drag-and-drop graphical interface that extends application development out to a wider audience, limiting the involvement of IT groups and database administrators. As such, SBI capabilities integrated with Scientific Informatics solu-tions are truly far-reaching and are capable of improving productivity, decision making, and efficiency for all types and levels of users—from executive to scientist.

Executive Example: Site Management DashboardExecutives, managers and other key decision makers rely on having accurate and up-to-date information at their disposal. However, this need is often unmet due to:

The difficulty of accessing necessary data •

The challenges of gathering complete data and achieving the ability to explore that data through different levels—• from high-level overview to very specific data

The high cost of manually creating reports•

The slow process of creating reports, which often results in out-of-date information •

A critical value of SBI tools is the ability to present diverse types of data and enable users to drill down (or up) through the data in order to

monitor project, site or company performance, or address emergent issues as they arise. Specifically, dashboards offer an interactive

means for providing both high-level summary data and drill down capabilities via graphical web or PDF pages. Figure 3 shows an example

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dashboard that could be used by decision makers at a global pharmaceutical company to monitor compound registration performance,

anywhere from the site to the individual level. After the initial set-up of this dashboard, end users are empowered to access current data,

without needing a database administrator to execute queries against the database. Updating the dashboard is easy, with negligible costs.

In Figure 3, the upper left pane shows the initial starting point of the dashboard deployed in a web browser. The user simply needs to click

a link from an email or web page to get this report. This example shows various graphical elements and tables that provide a high level

overview of the number and success rate for compound registration over a six-month period, across seven research sites. The use of

conditional color-coding on the bar chart and table highlight sites that do not meet a defined performance threshold. Such visual cues

are essential for effective information presentation. In this example, to access the most up-to-date information, a user would click the

“Click for six month update” link, which retrieves data for the most recently completed period and repopulates the page (Figure 3, upper

right panel). The use of a web browser environment and hyperlinks to perform actions means that there is no learning curve for users—it

is all completely familiar to them. In the updated report, the user can easily assess site performance, such as detecting that the Atlanta

site appears to be underperforming in terms of the success rate for compound registration (i.e. the bar is now red). To further investigate

this, the user can click the bar/pie slice/or table entry for Atlanta and drill down to view data for the Atlanta site (Figure 3, lower left

panel). In this case, the data shown at the site level is similar to the higher-level data that compared all sites (though this need not be the

case); however, in the Atlanta site view, the report compares individual scientists. The user can now assess the performance of the

individual scientists and drill down to see individual compounds that were registered, as well as additional information on these

compounds (Figure 3, lower right panel). Overall, the dashboard gives the user a means for quickly navigating from information at a

high-level (i.e. looking at overall research division performance) to detailed information (i.e. looking at data about individual

compounds)—all within a simple point-and-click interface.

Figure 3: Screen shots of various reports from an interactive site management dashboard. Top left: overview of compounds registered by site January to June. Top right: six-month update of site performance for July to December. Lower left: Atlanta site details. Bottom right: individual scientist report.

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Professional/Manager Example: Lead Management ToolWhen teams of scientists are working toward a common goal, the ability to gather information from multiple users and databases is imperative because it aids in decision making and helps prevent duplication of efforts. However, efficiency suffers when scientists on a discovery research team spend an inordinate amount of time gathering data and preparing presentation materials for review. As a result, less time is spent actually generating data—the primary role for the scientists. Figure 4 shows an example of a dashboard that could be used by a manager or research team to make decisions about lead candidates. The dashboard draws data from multiple databases (chemistry, biology, safety), as well as project documents containing property criteria and project metadata. It can be generated five minutes before a review session, without the involvement of any of the scientists, allowing them to work right up to meeting time. During the meeting, the team can assess each new candidate molecule with the help of conditional color-coding of values that quickly reveal molecular properties. With this information, decisions can be made on whether to keep a molecule (as a lead, second or third candidate) or discard it. Decisions on candidate molecules take immediate effect and the database is automatically updated. Values for the property criteria, and their priority, can also be altered at any time; the effects are also applied in real-time, allowing the molecules to be reassessed immediately. This means that all decisions are both made and acted on in real-time, so once decisions have been made, scientists can immediately return to work.

Scientist/Expert-User: Web-based Tool for the Design of New MaterialsMaterials science spans a tremendous domain that encompasses the automotive, aerospace, electronics, polymer, and catalysis sectors, to name just a few. Materials used by scientists and engineers in these sectors can include minerals, ceramics, metals, metal oxides, and alloys. SBI and Scientific Informatics solutions enable researchers to determine the properties of the materials in detail, search for materials with desired properties, and predict the properties of new, as of yet un-synthesized, materials..

Figure 4: Lead management dashboard that draws from multiple data sources and allows users to update property criteria and quickly review, prioritize or discard leads in real-time.

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Users need to be able to use a simple web-portal to enter a request for data and search available materials databases. If data are not available, users will be presented with an option to compute the properties using accurate “first principles” methods. Ultimately, as the databases become enriched, QSAR methods will allow users to “reverse engineer” a material to meet their specifications. This approach provides materials scientists with the ability to make rational, informed decisions through unprecedented access to materials properties; it enables instant sharing of the data across an organization and provide predictive methods that refine themselves as new data become available.

Scientist/Expert-User: Web-Based Pharmacophore Profiling ToolTo exemplify SBI solutions at the expert-user or scientist level, consider the life science area, where addressing new methods of innovation

for several processes, including target identification, hit identification, lead optimization, drugability, IP capture and reporting is a key

capability. When undertaking hit identification, lead optimization and drugability, molecular modelers and cheminformaticians employ a

combination of Structure Based Design (SBD), 3D Ligand Based Design (LBD) and QSAR methodologies, but they do so in very different ways

for each process. For example, when employing SBD tools for hit identification, one might use a “quick and satisfactory” 3D tool to generate a

simple list of samples for screening because screening is relatively inexpensive and quick. In this case, speed of calculation is more important.

However, when conducting studies for the lead optimization, one would want the most accurate methods available because making

compounds is very expensive and time consuming. Therefore, in order to support the scientific process, tools that cross traditional product

lines must be integrated within a unified solution, rather than within individual point solutions.

A tool recently built in the LBD arena (Figure 5) is one of the best illustrations of innovation through confi guration. This tool brings together

3D ligand based design, reporting and web portal technology. It has shown the ability to accurately select compounds for protein types, as

well as the ability to select active compounds from inactive compounds from a closely-related chemical series.1 The example shown in

Figure 5 also demonstrates how nimble Accelrys’ SBI solutions truly are. This lead compound analyzer/locatoris an integrated

pharmacophore portal that was built in less than six months. This can be done for any number of applications, which greatly improves the

users’ ability to leverage their investment in software in order to better meet their needs. Integrated solutions such as this are easy to share

and modify, making them a corporate asset that can be leveraged by expert and non-expert users alike. This allows a company to take

advantage of its overall intellectual capital. This example also illustrates an SBI solution that allows scientists to mine data using

sophisticated methods and visualize complex data types, capabilities that are completely out of the reach of traditional BI tools. As a direct

result from the flexibility to tailor underlying complex scientific methods, this simple-to-use tool perfectly illustrates the concept of “one click

science.” “One click science” allows expert users to tailor complex scientific methodologies into a solution delivered as a set of workflows that

are shared on a portal and are executed by end-users through a single click. While the single click could potentially represent hundreds of

behind-the-scenes operations, to an end-user it is reduced to an easy-to-use tool, which is the essence of SBI solutions.

Figure 5. Graphical user interface of the web-based pharmacophore profi ling tool showing screening results for an active compound set in a detailed pharmacophore profile mode. Left: 2D hit compound structure. Middle: selectable 3D hit compound structure and pharmacophore mapping. Right: Bar chart showing hit models, their score, and model information.

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Scientist/Lab Technician: Phase Analysis from Powder X-ray DataAnother example SBI solution lets organizations capture and deploy complex data analysis algorithms for powder X-ray phase analysis via

simple web interfaces. Powder X-ray analysis is considered an industry standard for form identification and quantification of

pharmaceutical compounds. However, the analysis of these data is an expert activity that requires intricate knowledge of the

experimental setup, a large variety of parameters, and complex fitting algorithms. Accelrys’ Materials Studio provides a comprehensive

set of tools for experts in this field. Through a web-based SBI solution, expert knowledge can be captured and shared with nonexpert

users. Figure 6 shows a web interface where expert settings have been optimized (either from within an organization or offered as an

Accelrys consulting service) and only relevant parameters have been exposed. The data analysis possible through this simple web

interface is as good as the expert tool since it is based on exactly the same functionality and degree of parametric adjustment. This SBI

solution allows non-expert users to easily take advantage of complex analysis tools, while also facilitating information exchange between

the analytical and process optimization departments within pharmaceutical companies.

Scientist/Expert-User: Web-based Tool for the Design of New MaterialsMaterials science spans a tremendous domain that encompasses the automotive, aerospace, electronics, polymer, and catalysis sectors, to name just a few. Materials used by scientists and engineers in these sectors can include minerals, ceramics, metals, metal oxides, and alloys. SBI solutions enable researchers to determine the properties of the materials in detail, search for materials with desired properties, and predict the properties of new, as of yet un-synthesized, materials.

Accelrys is leading a consortium of organizations in a project funded by the UK Department of Trade and Industry (DTI) to put make such SBI solutions available on the desktop of materials scientists everywhere. The project, called Materials Grid, aims to create a dynamic database of materials properties (such as elastic stiffness, dielectric constants, optical properties, heat capacity, electronic band gap) based on experimentally available data and quantum mechanical simulations.

Figure 6. Quantitative phase analysis from powder X-ray data as a “one-click science” application. Non-expert users can perform sophisticated analysis operations on complex data by utilizing previously captured knowledge and only selecting suspected phases within the sample.

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With the solution, users will be able to use a simple web-portal to enter a request for data and search available materials databases. If data are not available, users will be presented with an option to compute the properties using accurate “first principles” methods. Ultimately, as the databases become enriched, QSAR methods will allow users to “reverse engineer” a material to meet their specifications.

The Materials Grid will provide materials scientists with the ability to make rational, informed decisions through unprecedented access to materials properties; it will enable instant sharing of the data across an organization and provide predictive methods that refine themselves as new data become available.

Conclusion

Massive, large-scale development projects have not met the expectations of line of business and IT executives. This “once-and-done” approach is being displaced by a more iterative approach, which offers a greater return on investment by focusing on the rapid, smaller-scale development of applications that can be linked together by web services. Such an approach is made possible today with Accelrys’ Pipeline Pilot solutions, including its award winning modeling, simulation and informat-ics technologies, and its open and standards-based scientific operating platform that gives users the freedom to pick “best of breed” components from multiple vendors and configure the interface to suit their needs. By leveraging these solutions, the scientific and clinical research communities stand to improve productivity, decision making and research efficiency.

ReferenceSteindl, T.M., Schuster, D., Laggner, C., Chuang, K., Hoffmann, R.D., and Langer, T. “Parallel Screening and Activity Profi ling with HIV Protease Inhibitor Pharmacophore

Models,” J. Chem. Inf. Model., 2007, 47, 2, 563 - 571.

Figure 7: The Materials Grid SBI solution will provide materials scientists with the ability to make rational, informed decisions through unprecedented access to materials properties and predictive methods. Left: A typical perovskite, BaTiO3. These represent an important class of materials, since physical properties can be tuned by altering composition. Right: Cordierite, Mg2Al4Si5O18, used in high-temperature applications.