Facilitating Rapid Analysis and Decision Making in the Analytical Lab.
WHITE PAPER
Sponsored by: Accelrys, Inc. Frank Brown, Ph.D., Chief Science Officer, Accelrys March 2009
Abstract
Competitive success requires research and development labs to make fast, accurate decisions about compounds and synthesis routes. With increasing amounts of data available in different formats from wide ranging sources, data collection, analysis, reporting, and distribution is increasingly cumbersome, limiting, and time consuming. Automating each step of the process provides some assistance, but only by a complete integration of activities and resulting data can labs make the kind of improvements required to expedite results.
The Analytical Data Management solution from Accelrys provides such an integrated approach to laboratory process flow and analysis automation. The Accelrys solution manages a broad range of information beginning with outputs from laboratory equipment to industry standard data stores; it compares and analyzes results, linking with the sophisticated processes of best-of-breed analytical tools; it generates reports tailored for each level of audience throughout the organization; and it presents the resulting information in portals or dashboards to ensure consistency and currency. This solution is helping Research & Development (R&D) organizations to make better informed decisions, faster and cheaper.
The Challenges of the Analytical Laboratory
Though the caliber of instrumentation and analytical techniques available for generating and characterizing lab samples has steadily improved over the past twenty years, data analysis remains often a cumbersome process in R&D labs and quality control
manufacturing applications. Electronic lab notebooks (ELNs) have been touted as a solution for expediting the workflow; in reality, such devices do little more than track data. Still missing have been the analytical support capabilities lab personnel need to maximize sample throughput in the lab and quickly and easily disseminate meaningful lab results to stakeholders.
Some of the most critical decisions R&D companies make are driven by those results, yet complex lab environments and cumbersome processes impede the production of timely, reliable, actionable information. The adverse results of this situation include longer time to market, higher risks, and increased overhead costs.
Limitations of Current Tools and Process Flows
An analytic process workflow starts with the issue of a lab request and contains the following steps:
• Data capture: The typical lab environment today includes a variety of equipment ranging from Nuclear Magnetic Resonance (NMR) to Infrared Spectroscopy (IR) machines which are used to generate raw analytic data. The control PCs for this equipment usually have different interfaces and operating systems, collect data in different formats, and store that data in disparate locations. Because there is no single standard for the computers that manage the instruments, collecting and assimilating data samples from these systems often
consumes a large portion of a lab scientist’s valuable time. Additionally, each system requires specialized expertise to operate and maintain, driving up costs and risks.
• Data reduction: The process of reducing the quantity of data produced by analytical instrumentation into meaningful, digestible results may require extensive manual intervention. Validating that the data peaks in a synthesized molecule match a predictive NMR spectrum, for example, can be a labor intensive, error-prone process, and calculations are rarely captured for validation or re-use. Furthermore, disseminating the results of analytical instrumentation collection back to the original service requestors can itself require substantial effort.
• Data indexing: To allow for future reference, a reduced representation of the raw analytical data must be generated and indexed with a link to the raw data. Association with the appropriate metadata—whether it be instrument parameters, thumbnails of the actual spectra,
or abstracted data such as peak lists—is critical as two different machines may provide different interpretations of the raw data depending upon the parameters identified in the associated metadata.
• Reporting: Benefits to the company accrue when data are logically grouped and presented in a concise form that informs and supports product-related decisions. Yet generating reports is often difficult and time consuming because of disparate data types and sources. • Sharing: Distributing test results, reports, and other data across the organization in a consistent, predictable, timely way is
essential if analysis is going to drive scientific and business decision-making. But analytical reports and underlying data sources typically reside in organizational silos. Distributing key information is time-consuming and inefficient, and does not ensure that every scientist, analyst, and decision-maker has access to the most current and complete data sets available.
Each of these separate and often disconnected steps poses its own challenges. To boost efficiency and advance well-founded product decisions across an organization, research labs require a solution that enables them to easily access and manage scientific data generated from different instrumentations and collected over time, rapidly mine that complex data set for results, and report out on those results in real-time with a high degree of confidence in data integrity.
Accelrys Analytical Data Management for Data Integration and Automation
Accelrys, a leading provider of software solutions for life and materials science research companies, has a comprehensive solution that enables R&D to improve the productivity of analytical laboratory operations. The Accelrys Analytical Data Management solution facilitates access, processing, reporting, and sharing of analytical data. It streamlines everyday lab operations from identifying promising candidate compounds for pharmaceutical companies to determining levels of contaminants in chemical manufacturing. And it directly supports effective communication among lab analysts, service requesters, and business decision makers. Researchers benefit from this systems because it
• Helps research laboratories integrate and streamline their processes from beginning to end.
• Provides a common interface for managing data generation and capture across a wide range of instrumentation and operating systems.
• Consolidates experimental data and integrates it with data from other sources such as compound registration databases and inventory systems to provide a seamless and holistic view of a compound under review.
• Performs data reduction steps and generates tailored reports of results while maintaining a trail back to the raw data and instrumentation that produced each outcome.
• Integrates with Web portals so that information can be easily and conveniently shared across an organization.
• Adapts to evolving needs through a flexible, easy-to-use graphical programming interface that does not require labor intensive customization.
With the Accelrys solution, R&D laboratories can spend more time on making sound scientific and business decisions instead of on the challenges and pitfalls of the research and analysis process.
Maximize Sample Throughput with Accelrys Analytical Data Management
At the core of Accelrys’ offering is a unique scientifically-aware operating platform. This platform, the Pipeline Plot Enterprise Server, is capable of managing a wide range of scientific data types and file formats.
Figure 1: Pipeline Pilot Enterprise Server
Pipeline Pilot Enterprise Server centralizes access to complex scientific data scattered across instrument control workstations and provides an integrated view of that data, as illustrated in Figure 1. Addressing each step of the analytical research process, the Analytical Data Management solution enables researchers to:
• Centralize access to complex scientific data scattered across the organization to provide an integrated view of the data regardless of the data type or application which created it.
• Automate collection and assimilation of data in different formats compiled using a variety of analytical techniques, such as LC/MS, Raman/IR, UV/vis, and NMR.
• Conduct complex data analysis using disparate analytical methods, for example, combining statistical similarity measures with cluster techniques to establish similarity amongst spectral data or to detect contaminants that lie outside known data sets.
• Store, track and index large volumes of data in a wide range of formats with standardized indexing for future referencing and retrieval.
• Easily configure reports that target the needs of different groups with drill down capabilities for different levels of management. • Communicate test results and procedures followed to stakeholders in real-time via customizable Web-based portals, dashboards or industry standard tools such as Microsoft SharePoint.
Organizations that have adopted this solution, utilize time previously spent performing repetitive data processing tasks more productively for generating samples and identifying active compounds.
A Solution that Integrates with Analysis Tools
With the Analytical Data Management solution, researchers can expedite the entire laboratory process from data collection through to reporting. That process begins with laboratory data acquisition, often from a wide range of test equipment generating large volumes of data in various formats and locations. Just tracking each file to its source can be a major challenge. The data integration and reduction capabilities of the Accelrys system enables lab managers to consolidate and reduce data to collections that can be analyzed and managed while retaining the original source data and metadata, including the specifications of the hardware and software that originally generated the data to avoid
unnecessary retesting, as illustrated in Figure 2.
Figure 2: Analytical data handling
A data reduction step in a very simple laboratory setting could consist of nothing more than manually examining the data and judging whether it agrees with the anticipated results. More likely, however, data reduction will require running a sophisticated computer algorithm against large volumes of data. Typical data reduction steps might include locating peaks, integrating an area in the spectrum, grouping similar data, and matching data against a database of known data. This labor intensive manual process is prone to user errors. The Analytical Data Management solution facilitates and automates the analysis of collected data. It can rapidly read input from IR and NMR spectra analysis tools, third party databases and spreadsheets containing large quantities of data, and even image data to seamlessly access and manage all of your analytical data.
F i g u r e 3 : D a t a a n d a p p li c a ti o n i n t e g r a tion
Rather than imposing a single set of tools on all laboratory analysts, the Analytical Data Management solution supports a best-of-breed approach by integrating with the leading products across the industry. Scientific applications from a broad range of software vendors can be accessed through a simple Web portal thanks to the flexible, service-oriented architecture of Pipeline Pilot underlying the Analytical Data Management solution. Researchers can even access and execute specialized third-party analysis technologies such as indexing of X-ray data or structure determination from NMR measurements. The results are tracked and managed within the Analytical Data Management solution, eliminating
the need for cumbersome manual consolidation. Figure 4 provides a view of data clustering in the Accelrys solution. F i g u r e 4 : R a m a n d a t a
Reducing Overhead through Streamlined Access to Information
Equally important, the Accelrys solution allows users to integrate with data repositories, so researchers can easily share and manage the vital information generated in lab processes. When compiling characterization data from disparate data sources, a researcher can associate variables such as instrument settings and conditions of sample preparation with the data. This metadata is then cached with information generated about the sample, such as its purity or degree of crystallinity, and made available for review by researchers conducting related analysis. Capturing each component of the research process and making that information transparent and accessible to consumers of the lab results not only enables greater opportunity for data validation; it also helps to reduce duplication of effort.
The ability to report test results in the right format and level of detail for each recipient is built into the Accelrys solution. Views of the raw data can be adapted for each target audience; whereas a lab manager may see only high-level test results, a scientist can drill
down from a report on the observed NMR peak positions to the detailed structures matching those peak positions
This real-time access to complex data analysis can help scientists refine their research processes and connect otherwise disparate data points into meaningful scientific information.
Communicating Results Instantly Wherever They Are Needed
The Accelrys solution not only generates dynamic reports. It also enables communication of results across the organization by integrating reports into Web-portal applications. Because Microsoft SharePoint is currently one of the most popular platforms for information sharing and collaboration, Accelrys partnered with Microsoft to integrate the Accelrys solution with SharePoint. In addition to storing documents on a SharePoint site where they can easily be accessed and managed, Accelrys can actually embed live functionality into a SharePoint portal; customers can create a SharePoint view which is a single access point for all Accelrys tools and protocols. That means that all scientists and managers throughout the organization can have immediate access not just to reports but to all underlying data and services from their desktop.
A Flexible Solution that Adapts to Future Needs
While R&D companies may share some common data analysis needs, no two laboratories are alike. Industry regulations and internal business processes shape the analysis and reporting requirements of each laboratory within an organization’s R&D pipeline. That’s why Analytical Data Management has been designed for maximum flexibility. Comprised of individual functional modules, the solution can be rapidly configured to meet the unique needs of a research lab. Without labor-intensive customization, scientists can also add new modules or adapt existing tools to extend the functionality of the platform to their specific research needs.
The solution includes an easy-to-use graphical configuration interface that enables non-developers to extend the solution as necessary, for example, by building workflow capabilities into the system. Without expensive customization, a lab can automate creation of sample records, assignment of testing responsibilities, and distribution of lab samples to different machines according to a schedule. With each task in the workflow scheduled, stakeholders outside the lab can track the progress of their work requests from the Accelrys portal and review results as analyses progress through the lab.
As research and analysis techniques become more complex and sophisticated, and as the quantity and variety of data needed for sound decision-making continues to grow, researchers need advanced technical tools to support their processes. With the Accelrys Analytical Data Management solution, data collection, analysis, storage, and reporting capabilities have at last caught up with the advanced laboratory equipment that generates today’s analytical data. Now researchers can invest their time doing what they do best: driving the business decisions that make their companies successful.
To learn more about how Accelrys can help your company better manage analytical lab processes, see http://analyticaldata.accelrys.com/
