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Last updated: November 10, 2007
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Sample LIMS/Letter Article

The Benefits of a LIMS In Proteomics
by T. R. Smallmon, LabVantage Solutions and J.K. Ganjei, TissueGene

The LIMS Marketplace

In the Beginning...
The first LIMS were developed in the pharmaceutical and related industries for use as a QA/QC tool in the early 1980's by in-house development departments or under contract by external software houses. These LIMS were exclusively based on mini-computer or mainframe technology, often using proprietary database software as their foundation.

With improvements in performance and price of both computers and Local Area Networks (LANs) in the 1980's, many LIMS programs were developed by commercial software houses — often under contract to specific laboratories. This resulted in a number of small local suppliers with products suited only to the particular application for which they were designed. Nonetheless most research environments — including life science — found these systems to be too rigid for their purposes.

Today...
In the race to discover new opportunities and capitalize on the promise of proteomic research, the challenge isn’t who can work harder, it’s who can work smarter. Every biotechnology and pharmaceutical company is testing uncharted waters, limited only by their ability to conduct detailed studies with lightening speed. There is a need for an Informatics discovery platform to automate intricate laboratory experimental processes, enabling more intense, focused exploration. An ideal solution provides this functionality via a powerful, ‘drag and drop” workflow engine that automates virtually any experiment or study, dramatically streamlining discovery processes. A sustainable, high-throughput software solution that creates an integrated environment for drug discovery and biotechnology research is also needed. This system communicates seamlessly with various public and private research databases, instrument and robots, and virtually any third party software tool to aggregate all discovery information into a single framework for analysis—thus creating a world-class discovery platform. These efficiencies allow labs conducting genomics, sequencing, gene expression, and now proteomics, to more efficiently process millions of experiments per year.

LIMS Overview

LIMS streamline the data flow within the organization and centralize the information into one primary database. The LIMS solution unifies vast and disparate volumes of biological and chemical data along with their related applications and tools, into a single, browser-based scientific interface. Built on an extensible life science-based data model, the platform understands the context of data being integrated, the relationships between associated data, and allows scientists to use the platform to query, view, and analyze research data without being required to reformat their data-gathering methodology or change to multiple product interfaces. The platform also includes a state-driven workflow engine for automating any process. All data deposited into the LIMS database can then be disbursed through electronic or hardcopy reports and queries. The LIMS thus becomes a comprehensive enterprise solution that enables research organizations to focus time and effort on their true mission: production of scientific information.

The Benefit...
Optimizing vial, plate, and array chip assembly—and the analysis of information derived from those holders or array types-—is the key to maximizing experiment throughput. The proteomics LIMS provides complete traceability and integration from sample collection to protein result storage. Scientists can leverage and utilize individual workflow stages within the overall process flow to meet their unique requirements. This is accomplished by tracking, at each stage of the workflow, the sample/aliquot of the parent sample and all uniquely identified data files. It is quite common to have up to six unique identifiers pointing back to the original parent sample at any given time. These capabilities improve productivity and accuracy by eliminating repetitive manual sample entry and data manipulation.

The proteomics LIMS also creates a powerful environment in which scientists can interpret their results. Sample data are quickly combined with data integrated from public or proprietary databases, creating a web of information that provides a context for analysis. In addition, integration with “best of breed” proteomics tools, such as gel image analysis, spot picking, instrument and robotics integration platforms, and web-based search engines—enable scientists to quickly transform data into meaningful information. These products are leaders in their market and help provide a complete end-to-end solution. Scientists also have the freedom to swap workflow solution partners as they please; i.e., all the major Mass Spec manufacturers allow import and export CSV files. This allows each client to tailor his or her preferred tools into the proteomics LIMS solution.

How It All Fits Together

Because proteomics LIMS provide integration for the instruments and AIM systems, they require the ability to generate files in specific third party formats and to parse and store data from these systems. Proteomics LIMS also provide traceability of the raw data files via direct storage in the LIMS database as a BLOB (binary large object) file type or via a referential pointer back to that file stored on a local, networked machine.


Figure 1. This proteomics process exists in thousand of laboratories around the world.

The proteomics process shown in Figure 1 automates the method of moving samples between projects and studies, though aliquots, to gels, to spots on a gel, to a Mass Spectrometer, and finally to protein identification. By centralizing information in one database, an organization can gain insight into sample progress, derive information from this data that has not been available in the past, and quickly disburse information once it is available. This means that once a project and a study for that project are defined, samples can be logged within the LIMS, thus starting the process. The samples can then be tracked through the complete process by reviewing their genealogy within the LIMS. This information reduces the number of verbal inquiries to the lab. Status of the samples, worklists, and results data are available to all who have access to the system via a standard web browser.

Data available within the LIMS database can be easily retrieved and information can be derived that was not available before. Having all data in one location reduces the amount of work to produce a report or create information. This additional time can be used to generate and evaluate additional information. This circular process flow also shows data interchange with multiple third party applications for image analysis and spot detection, instrument/robot integration, and integrated web-based search engines. This process reduces manual “touches” and further provides a complete genealogy tracking of samples and their identification with protein and disease state. The ultimate benefit of a proteomics LIMS is that it allows valuable resources to be used where they are most needed; e.g., the Scientist doing science.

Objectives of a Proteomics LIMS

A Proteomics LIMS is a role-based system that can be configured based upon the user’s role or work type. Users can view data, manipulate data, generate reports, load data, export data, do ad-hoc queries and reports and manage lists directly from the web interface. Since the LIMS is web-based, anyone who can view a web page can use it.

Like other web browser content, the LIMS is page-oriented. The interface should have the following features:
• Capabilities are self-evident
• Intuitive with minimal training required
• Targets one click to get to desired action; two click maximum
• Consistency throughout product
• Supports multiple window opening to leverage larger screens
• Provide easy way to enhance and make client interface changes
• Fully supports virtual laboratory requirements
• New pages can be created using standard HTML editing tools and LIMS Custom Tags

The LIMS contains full multi-lingual translation facilities, and can display a unique language or terminology. Languages supported by Microsoft Windows are supported.

Favorite web pages (within and outside the LIMS) can be listed. Recent items list the last items worked on. Bulletins to communicate with other users in the organization increase communication.

The following sections will touch on each menu item and the benefits provided by this type of system.

Sample
The sample function is the foundation for sample login (request), tracking and monitoring the number and status of samples in process.

The sample function can be configured to request details and information that users need by defining the additional fields required and prompting for them from the web page, including information on the request, requestor, project, study, and experiment. Fields that can be set automatically by the system will be stored automatically. Default values can be defined using templates for the request. Drop down lists are available in validated or non-validated forms. For validated lists, items are selected from a list. For non-validated lists, an existing item can be selected or a new one added. As part of the configuration, different pages can be displayed depending on buttons pushed or on previous answers.

The proteomics LIMS allows new tables to be added and existing tables to be edited using the Database Designer. The data model is not cast in concrete, as no two implementations are exactly alike. The tools include a graphical data model designer and a forms-based data collection designer. There is also a built-in Data Dictionary.

The data model is not a fixed representation of an organization’s information needs. It can evolve over time. The LIMS data model includes a meta-data layer that allows the application to do two important things:

Insulate the end user from direct interaction with the underlying database – The LIMS creates tables, constraints, foreign key linkages, etc. from the definitions in the meta-data layer. The definition process controls what a table can do, in addition to the information it can contain.

Insulate the proteomics LIMS from upgrade difficulties – Since the contents of the LIMS database are contained in the meta-data layer, an upgrade can programmatically eliminate the differences between the upgrade data model and the existing one. This means that the LIMS data model is protected from one version to the next without special precautions.

Gels
One of the major functions within the group is the ability automatically generate worklists or views of samples needing testing. The user can define queries and sorting criteria to organize data in a manner consistent with how tasks and work need to be categorized.

A worklist or backlog report can be viewed or printed sorted by any fields or filtered by any values using the query facility of the LIMS. In addition, the user easily manages the definition and generation of reports to print the results of any query or list of values with the Report Writer. Reports can be activated directly from the LIMS menus. These user-definable reports can be embedded within the LIMS if written in the recommended Report Writer, Business Objects (Figure 2).

Worklists can also be offloaded to an instrument, robot, or third party piece of software to automate the complete process.


Figure 2. This figure shows a list of gels meeting a certain selection criteria, specifically those needing testing.

Images
The LIMS can interface with robots and instrument systems bi-directionally to generate electronic worklists and then dynamically transfer sample readings for each sample or group of samples back into the central database. These capabilities improve productivity and accuracy by eliminating the repetitive, manual sample entry and data manipulation. For instance, the LIMS can build a XML file that includes the analysis number and ID of each gel which can then imported by the gel image analysis and spot-picking package.

Spots
Laboratory data can be entered in many different ways in the proteomics LIMS. Depending on the configuration of each system, data can be entered in one or all of the ways described below:
• Enter data by automatically transferring values from laboratory instruments into LIMS.
• Enter the test results for logged samples by worklist
• Enter data for samples by batch (including QC data)
• Enter ad hoc data — to add or edit any selected parameters or test results for any sample that is not on a worklist
• Enter auxiliary data — to separately store as attachments information that is related to, but independent of, sample information; e.g., product information, etc.

In this case, spot data is bought directly into the LIMS via automated gel spot list import as is shown in Figure 3.


Figure 3. Spot data is bought directly into the LIMS via automated gel spot list import.

MS & PID
Once the gel spots are picked, they are enzymatically digested 'in-gel' and loaded onto array chips for analysis by MALDI-TOF mass spectrometry to create a peptide mass fingerprint. The peptide masses can be used to search DNA or protein databases to identify the protein. The set of masses generated experimentally are compared to the theoretical digest patterns of all proteins in the database and the closest matching are displayed.

Report Generation
When the user is finished entering data, reports or views can be generated. Most commercial LIMS today use third party packages as report generation tools. Reports may be ad hoc or predefined. Users can easily design customized reports and queries to answer in-depth questions. In the proteomics LIMS, there is seamless integration of the Business Objects report writer. In addition, users can utilize any other third-party reporting tools. Business Objects can generate reports directly from within LIMS. Other report writers can generate reports outside of LIMS – from the Web or the client.

One of the most important aspects of LIMS is the ability to prepare and retrieve data and turn it into information quickly and easily. The LIMS eliminates the time-consuming tasks of manual report preparation that often preclude access to the desired information. This information could give new insights or help users run experiments more efficiently. For example, reports can be combined with a specific query in LabVantage’s Sapphire LIMS so that the movement from one array type to another and the information analysis that is derived from these arrays can maximize experimental throughput. The LIMS automates the loading of information into these arrays and precisely tracks the genealogy of each sample.

Other reports can help users obtain the status of samples in the laboratory for testing and interim reports of test results already entered in the system. Management reports such as usage, backlog, and sample turn-around time, help to identify bottlenecks, therefore aiding in management of precious laboratory resources.

Third-party Software
The LIMS provides a platform for easily integrating third-party, Windows or web-based software. This means that when users generate a query, that data can be sent to other programs such as word processors, spreadsheets, statistics, data visualization or analysis packages.

System Security
The LIMS contains functions designed to create multiple levels of users, roles and profiles. Proper set up of the users and roles in conjunction with the profiles will determine which users can perform various functions and have access to certain data elements. A user can be a person or collection of people.

A role defines users that are granted access to tables and groups of tables and thereby its records (rows). It also determines access to pages and to actions (actions that occur automatically when workflows are defined). Depending on the role, access to the data may also be defined; e.g., a submitter may only be allowed to view data, whereas a scientist is allowed to edit and copy.

Users can be assigned to many roles. A role can also be assigned to many users. This means that a many-to-many association exists between users and roles.

A profile defines user privileges and preferences, most notably the content and appearance of pages.

Audit Trail
The proteomics LIMS has very comprehensive “end-to-end” audit trail functionality. The audit trail records and maintains every entry in the system which allows users to check what was changed, when, why and by whom and helps organizations in their efforts to meet regulatory and validation requirements.

The auditing capabilities also help scientists meet requirements in the areas of:
• CGMP (Current Good Manufacturing Practices)
• GMP (Good Manufacturing Practices)
• GLP (Good Laboratory Practices)
• US FDA 21 CFR Part 11 Electronic Signature

The audit trail time and date stamps everything as well as records the name of the person making the changes, the reason for the change, the original data value, and what it was changed to.

Conclusion

The proteomics LIMS streamlines the data flow beyond the four walls of the laboratory. By centralizing all information about a sample and relating it to other scientific information, scientists can improve productivity as well as the quality of information. The key benefits of a proteomics LIMS are:
• Provides complete traceability of every sample
• Acquires, integrates and manages multiple sources of dynamic and static data across the enterprise
• Reduces the amount of clerical work done by highly trained professionals – allows scientist to do more science
• Seamless integration with public/ private databases
• Integrates with a variety of solutions for scientific data interpretation and analysis
21 CFR Part 11 compliance
• Increases communication throughout the organization
• Reduces the number of times data is transcribed increasing the integrity of the data
• Automatic features eliminate the need for human interaction to generate routine reports

In closing, as scientists expand the world’s understanding of complex biological systems, the volume of analytical data will continue to rise. The proteomics LIMS allows the researcher to manage this data and optimize their discovery process.