Overview

The biggest roadblock to Digital Transformation and Data Science is data quality. And mastering FAIR data management can mean significant hurdles for organizations looking to embrace transformation. Managing and analyzing large volumedigital s of data from various sources is complex and time-consuming. And preparing this data for Data Science might be even more. ZONTAL’s Digital Transformation Platform offers a holistic solution to overcome these challenges and unlock the full potential of data.

In this webinar, we will explore how ZONTAL’s digital transformation platform helps labs to overcome the three main challenges that labs face when managing data:

• Data Preservation for ongoing work and from legacy systems
• Digitalization of the Lab with bi-directional data and metadata flow from and to instruments, robots, entire labs, and even between collaborators
• Creating a FAIR Data platform to unlock Data Science initiatives in an open standard and ontology.

About Zontal

ZONTAL offers the leading data platform for the life science industry. We make digital transformation a reality as we deliver game changing solutions to some of the most complex enterprises. We reduce IT overhead, enable AI/ML applications, optimize time-to-market, and increase compliance. ZONTAL has offices in the US, Europe and Asia. Together with our integration and service partners, ZONTAL supports our customers globally, in any country and any time-zone.

The post Mastering Lab Data Management and Data Science with ZONTAL’s Digital Transformation Platform appeared first on Astrix.

The post The Power of Interoperability: Enabling Digital Transformation in Life Sciences: Part 1 appeared first on Astrix.

• delivered on time and within budget
• meets or exceeds all user requirements
• provides business value
• high-level of user adoption.

LIMS projects usually demand a substantial investment of time, money and resources, with implementations costing hundreds of thousands to millions of dollars and requiring hundreds of person days to implement. Failure of a LIMS project can be a huge waste of time and resources, and a financial disaster for the organization involved. As such, it is critical to get a LIMS implementation project right the first time in order to preserve your return on investment. In this blog, we will discuss the seven most common reasons why LIMS implementations fail.

Reasons for LIMS Implementation Failures

There are many reasons why laboratory informatics projects fail. Some of the more common ones include:

Lack of Strategic Planning Prior to LIMS Selection and Implementation

Not taking the time to fully understand your needs (both now and in the future) and develop proper requirements that reflect these needs is probably the most common cause of failure in LIMS implementation projects. Many times, companies simply purchase a LIMS based on reputation and rush to implement their current requirements into the system. The danger here is that you end up with a project that is too focused on time and/or cost at the expense of value. This approach represents a missed opportunity to understand and optimize underlying workflow process that will maximize the business value of the implementation.

Conducting a thorough workflow analysis is essential to develop optimized future-state system requirements that will guide the LIMS selection and implementation and thus ensure your project will produce significant business value for your organization. In addition, the effort (and thus cost) that is required to implement and ultimately maintain the LIMS will be significantly influenced by the quality and clarity of the requirements that are generated and implemented into the system.

Another aspect of strategic planning that is important for the success of many LIMS implementation/integration projects involves the laboratory informatics architecture. Designing a practical enterprise architecture for the laboratory, along with a roadmap to deployment, is essential for any LIMS implementations that involve integration with instruments, parallel and adjacent systems. Having an overall strategic vision for the laboratory informatics ecosystem helps to ensure that the LIMS implementation maximizes business value for your organization and stays within time and budget constraints.

Personnel Resource Challenges

Staffing requirements for a LIMS project can be extremely complex. Wide-ranging knowledge about the different systems available on the market is important to ensure you select the best LIMS for your organization. Additionally, a variety of different skill sets are necessary to accomplish the strategic planning, configuration, integration and validation required to successfully execute a LIMS implementation project. Unforeseen project challenges can also require outside specialists and/or subject matter experts to move the project forward.

Another issue is that there are multiple roles that need to be staffed with internal personnel, and the time commitment required for project duties often means these people cannot continue with the full responsibilities of their day jobs. This can mean that backfilling a number of positions in the lab for the duration of the project may be necessary.

The bottom line is that you need to have a highly competent and skilled project team in place to ensure project success. Several key roles on the project team will likely need to be staffed by the LIMS vendor and/or an external consultant.

Poor Project Management/Governance

A key factor for a successful LIMS implementation is a dedicated project manager (PM) with LIMS experience who is involved in both the planning and ongoing management of the effort. Strong project controls and governance are needed to implement a LIMS successfully, and a LIMS-experienced PM will help to drive triple constraints (on time, on scope and on budget), ensure value realization and help to avoid common people-based challenges.

A formal risk management and mitigation plan should be developed in advance, which should include ongoing reviews of project phases throughout implementation that involve all inside and outside resources. A combination of project management skills, good resources (both internal and external), and methodologies are vital to a successful LIMS implementation.

Poor Communication

Clear and frequent communication between stakeholders is critical to the success of a LIMS implementation. It is vitally important to create and implement a comprehensive project communication plan as part of your LIMS project governance model. The communication plan helps convey critical information necessary to keep the project on track, and also engages all stakeholders so they feel part of the process.

The person or people facilitating communications between stakeholders plays a key role in the communication plan. Different aspects of organizations often speak “different languages” and may have trouble communicating with each other effectively (e.g., IT and lab personnel). It is important to have someone who is well-versed in all the different stakeholder domains facilitating communications in order to avoid misunderstandings.

Excessive Customization

The requirements developed in the workflow analysis conducted at the beginning of the project should be prioritized and implemented in an iterative approach with the “must haves” implemented first as described above. Failure to follow this kind of methodical approach can cause the project to get bogged down in excessive customization to satisfy lower value requirements, leading to project time delays and cost overruns. Unnecessary customization can also occur if there is not at least one person on the project team who is aware of all the configurable functionality available in the LIMS being implemented.

Customization increases the complexity of future maintenance, migration and validation efforts, and can potentially lead to system errors. The bottom line is that LIMS customization should only be done if doing so would provide your organization significant business value or a competitive advantage.

Inadequate Planning for Master Data Management/Migration

Data management/migration is almost always a bigger job than anticipated during a LIMS implementation. Many companies tend to focus on software testing and configuration and put off dealing with master data management or data migration until late in the implementation process, but this can end up causing significant project delays in addition to impacting business continuity in the lab.

For this reason, it is wise to focus on data migration early in the implementation process. Static legacy data (and sometimes dynamic data as well) must be extracted, translated (biggest effort) and loaded into a new location. The actual migration is typically accomplished through a combination of automated programmable migration tools and manual processes. Dynamic data migration should be done last to make sure the new system contains the most up-to-date data.

Conclusion

As discussed in this article, proper planning, adequate financial and personnel resources, and a proven methodology is vital to the success of LIMS implementation projects. There are in fact several other factors that are equally critical to consider in order to ensure project success.

The post Commmon Causes of LIMS Implementation Failures appeared first on Astrix.

With dozens of LIMS vendors now available to choose from, and in increase in specialization in terms of targeted laboratories and increasing demands for cloud-based applications, selecting the best LIMS has become more difficult than ever. In fact, these days there really is no such thing as “the best LIMS.” The focus instead should be on selecting the LIMS that is best for your unique laboratory and organization. In this blog, we will discuss some of the important variables you will need to consider in determining which LIMS will provide the most business value for your organization.

Factors to Consider When Selecting a LIMS

Selecting the best LIMS for your laboratory and overall organization depends on a wide variety of factors that define your business needs. Some of these factors include:

Your Industry. The industry that your lab is operating in is an important factor to consider when choosing the best LIMS for your organization. There are now wide varieties of specialized LIMS on the market that have been designed to support particular industries. LIMS designed to support pharmaceutical industry QC labs, for example, will have a myriad of features to support regulatory compliance – e-signature support, chain of custody, standards and reagents tracking, audit trails, instrument calibration/maintenance, etc. On the other hand, LIMS that are designed for unregulated industries, while having some of the above features, will also have features designed for workflows specific to that industry.

There are also a variety of general purpose LIMS on the market that can be configured to support just about any workflow and/or business need. An organization with a rapidly evolving business environment, and/or a well-established and experienced IT department, may be better served by evaluating a general purpose LIMS rather than a specialized system, due to the ability to make frequent changes to the system via configuration/customization.

Your Lab Type. Are you running a QA/QC lab that supports manufacturing, an analytical lab that supports research, or an early stage R&D lab? The answer to this question may determine the kind of LIMS that will best support your laboratory environment. In addition to targeted LIMS supporting specific industries, there are specialty LIMS that cater to different types of labs within a particular industry. These LIMS have functionality that is tailored to a specific type of laboratory. For example, LIMS that are designed for an analytical lab may be configured to provide a portal allowing researchers at various sites to easily submit samples to your lab for testing.

Your Need for Flexibility in the Platform. While most LIMS have similar functions and capabilities available, different solutions can vary widely as to how the functionality and capabilities are provided and configured.  Some LIMS present a wide array of out-of-the-box (OOB) functions and features already incorporated into the product (i.e., standard) and ready to use upon installation, while others have those features available through configuration via the tools provided by the system.

Most organizations will find an OOB, feature-rich LIMS to be the most appealing option, as it may be easier to implement with a lower total cost of ownership (TCO). Yet, for some organizations with unique needs, a strong IT department and/or a rapidly evolving business environment, may find the flexibility and control inherent in the more customizable/programmable LIMS as a more appropriate choice.

Your IT Architecture. A key factor to consider when choosing a LIMS are the standards your organization’s IT group have established for IT architecture. There are a variety of architectures supported by commercial LIMS today (thin client, thick client, cloud-based), each with their own benefits and drawbacks.

If, for example, your organization has a strong IT department and has made the decision to keep applications within its firewall for security purposes, selecting a SaaS cloud-based LIMS would probably not make sense. On the other hand, if your organization has chosen to reduce IT expenditures by primarily supporting cloud-based lab applications, a LIMS that can only function as a thick and/or thin client would be out of the question.

In order to achieve an integrated laboratory environment providing a high level of business value for your organization, it is important to design a laboratory informatics architecture aligned with business goals, along with a roadmap to deployment, before engaging in a technology selection process for your organization.

Your IT Resources. The LIMS resources your organization has available to implement and support your chosen system will be an important factor in determining which LIMS to select. The resources required to successfully implement and support a thick client LIMS, for example, are extensive. Organizations lacking a strong IT department will likely want to select one of the following:

• A cloud-based system that requires minimal resources to install and maintain.
• A Commercial Off-The-Shelf (COTS) system with extensive functionality already configured.
• A specialty LIMS tailor-made to your industry and lab type, thereby requiring less configuration.

Your Cost Limitations. The TCO of the LIMS solution is invariably an important factor to contemplate when making your LIMS selection. A comprehensive analysis should be conducted, looking at as many factors affecting TCO as possible (e.g., LIMS licenses, standard functionality, extra costs of modules, customization required, annuity maintenance, etc.) for each system being considered. The TCO of a solution is part of what determines “the best” LIMS for your organization.

Conclusion                                                                                  

An effective technology selection process is a critical part of developing an efficient and well-integrated laboratory environment. Care must be taken to avoid purchasing systems not addressing specific business needs, or with features or add-ons that do not yield significant business value.

In this blog, we reviewed just a few of the important factors to consider when choosing the best LIMS for your organization. In our experience, successful laboratory informatics technology selection requires a comprehensive methodology in order to ensure that user adoption of the new system is high, and business value is maximized for your organization. This methodology should include a thorough workflow analysis to develop optimized functional requirements before the technology selection process is engaged.

About Astrix

Astrix is the unrivaled market-leader in creating & delivering innovative strategies, solutions, and people to the life science community.  Through world class people, process, and technology, Astrix works with clients to fundamentally improve business & scientific outcomes and the quality of life everywhere. Founded by scientists to solve the unique challenges of the life science community, Astrix offers a growing array of strategic, technical, and staffing services designed to deliver value to clients across
their organizations.

The post Factors to Consider When Choosing the Best LIMS for Your Organization appeared first on Astrix.

Scientific organizations that have recently undergone a merger, and oftentimes even those that have not, are frequently in the situation where different labs in different locations are using different LIMS technologies/solutions. This scenario serves to inhibit process efficiency, cross-organization data reporting, regulatory compliance, and can result in high IT demand.

Given the advanced capabilities of modern LIMS, and the competitive advantages gained through establishing digital continuity across the product lifecycle, there is a strong incentive for modern scientific organizations with disparate LIMS to harmonize their laboratory environment by integrating the multiple LIMS into a single system. In this blog, we will discuss best practices for a project of this nature.

Strategic Planning: Workflow Analysis

Migrating multiple LIMS into a single system is a significant challenge and should not be taken lightly. In order to accomplish a laboratory harmonization project in a way that creates significant business value for your organization, strategic planning is essential. A project of this magnitude is a fantastic opportunity to optimize your laboratory environment by aligning laboratory functional needs with the strategic needs of the business. Towards this end, the initial phase of the project should be a thorough workflow and business analysis.

In this phase of the project, meetings and interviews are conducted with key bench-level analysts across the multiple sites to develop a complete and accurate picture of the current-state workflows and systems. Additionally, meetings with the organization’s management team are conducted to flush out the goals and vison for the optimized future-state.

With current-state workflows in hand, the project team creates a model of the optimized future-state workflows. Once the future-state model is created, system functionality is constrained to only those functions bringing business benefit to the customer, and system requirements are extracted and documented.

Strategic Planning: Enterprise Architecture for the Lab

Integration requirements for LIMS projects involving multiple systems and sites include laboratory devices and instruments, as well as enterprise systems that need access to laboratory data. In order to create a fully-integrated laboratory environment, it is critical to design a laboratory informatics architecture that is aligned with business goals, along with a strategic roadmap to deployment.

Enterprise Architecture for the lab should follow a best practice Value Engineering methodology to create a strategy that maximizes value delivery and aligns business requirements, technology and people in your organization. This process begins with interviews with the IT personnel to determine the current-state architecture of the technology (applications, information systems, instruments, etc.) and how it supports the objectives of your business. This current-state assessment looks at functions and security, user-defined and core system entities, workflow events, customization, reports, and instrument and system interfaces.

Next, a future state architecture should be designed that is aligned with business goals utilizing the future-state user and business requirements that were developed in the Business Process Analysis stage discussed earlier. The end result of this process is a practical roadmap to implement the overall strategic vision for the laboratory informatics ecosystem architecture. In some instances, transitional architectures will need to be designed to provide business value in early stages, without having to wait until the full vision is implemented down the road.

LIMS Selection, Implementation and Integration

Whether you choose to harmonize and standardize laboratory operations on a new LIMS or a legacy system, the technical, business and user requirements from the strategic planning phase are utilized to guide the technology selection, implementation and integration process.

When integrating the multiple LIMS into a single system, there are a number of best practice recommendations that should be considered during the implementation phase:

Iterate Your Implementation. For a project of this size and complexity, it is wise to implement the future-state vision in stages, with the first iteration being the minimum viable solution to go into production with. Just because you can do something does not mean it is cost or time effective to do so. Once this minimum solution is operational, users can provide feedback as to the pain points that they are experiencing, and then decisions can be made as to whether it makes sense from a financial and time perspective to customize the system to provide further automation.

Have a Data Migration and Management Strategy. Data migration for a project of this nature can be a significant challenge. Much or all of the static (and sometimes dynamic) legacy data will need to be extracted, translated and loaded into a new location. Depending on the value of the data in question, it can be archived, transferred to a new repository where it can be consulted and used to create reports, or fully migrated into the new system to be actively used in the new LIMS.

Sometimes, data will be left in legacy systems (e.g., data for a clinical trial that is currently in process) that will be decommissioned over time. Questions to ask that help to determine your data migration/management strategy include: What is the best location to store all the different types of legacy data? How are we going to get the critical data out of the legacy system and into the new LIMS? How are we going to harmonize data across multiple sites?

Data management/migration for any informatics implementation almost always turns out to be a much bigger task than one might have imagined, but this is especially true when trying to migrate several legacy systems to a new LIMS. It is therefore important to formulate a Master Data Management/Migration Strategy at the beginning of the project in order to avoid significant time and cost overruns as the project proceeds, as well as minimal disruption to your lab operations during migration activities. Static data should be migrated as early as possible, while dynamic data migration should be done last to make sure the new system contains the most up-to-date data.

Once the data has been migrated, regulatory requirements mandate that it must be validated to make sure it is accurate and has been transferred properly. Even if your company is not in a regulated industry, validating migrated data is important to make sure your data is sound.

Think about Security Early. It is important to fully detail the desired user roles and the permissions associated with each role before you build the system. As with managing the static data aspects of the project, designing and implementing user permission layers can be a bigger task than expected. Waiting until the end of the project to implement a security framework is a recipe for cost and time overruns.

Don’t Go Overboard with Instrument Integration. While instrument integration can have wide-ranging benefits for your laboratory, some instrument integrations can be challenging and cause project delays. It is important to have a master instrument integration plan that details what, why and when instruments are to be integrated and also identifies which instruments are worth integrating. Don’t let your project get bogged down by trying to integrate instruments that do not provide significant ROI.

Designate Appropriate Internal and External Resources for Project Implementation. A variety of different skill sets are necessary to accomplish the strategic planning, configuration, integration and validation required to successfully execute a LIMS migration project. Unforeseen project challenges can also require outside specialists and/or subject matter experts to move the project forward.

Staffing requirements for a LIMS project of this nature can be extremely complex. Several key roles on the project team will likely need to be staffed by the LIMS vendor and/or an external consultant. Significant collaboration between external and internal resources is required for the success of any LIMS migration project.

The bottom line is that it is crucial for organizations to have a highly competent and skilled project team in place, along with a good project communication plan, to ensure project success. Make sure you plan on designated internal resources spending significant time on the project, which means they will be less available for their day jobs.

Avoid Customizations Unless They Are Really Required: Extensive customizations to satisfy requirements can dramatically extended project duration and make your system difficult to maintain, validate and upgrade. Best practice is to examine and understand all the configurable out-of-the-box features of the new LIMS, and utilize as many of these as you can in your implementation to meet your requirements and simplify implementation.

Change Management. The new system will be a failure if no one uses it. Users must be consulted and involved in the requirements development process in order to ensure that they will accept and use a new and unfamiliar system. In addition, change management activities should involve a comprehensive training program for users of the new system.

Conclusion

Scientific organizations that have recently undergone a merger can benefit from harmonizing their laboratory environment by integrating multiple legacy LIMS into a single system. Benefits of doing so include elimination of data siloes, improved process efficiency, simplified IT environment, and enhanced innovation and regulatory compliance. The complexity of such a project, however, makes having a highly competent and skilled project team a necessity.

If you would like to have an initial, no obligations consultation with an Astrix informatics expert to discuss your LIMS migration project or your laboratory informatics strategy, please feel free to contact us.

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LIMS implementations usually demand a substantial investment of time, money and resources, typically costing hundreds of thousands to millions of dollars and requiring hundreds of person days to accomplish. Failure of a LIMS project can be a huge waste of time and resources, and a financial disaster for the organization involved. As such, it is critical to get a LIMS implementation right the first time in order to preserve your return on investment.

One important facet of any successful LIMS implementation and/or migration is the design and configuration of master data. In our experience, many companies involved in LIMS implementations tend to focus on software testing and configuration and put off dealing with master data until the end of the project. This is a huge mistake. Master data design and configuration is typically a much bigger job than anticipated and has multimillion-dollar impacts down the road on things like operational efficiency, time to market and LIMS return on investment (ROI).

In an effort to help organizations understand the importance and implications of master data and avoid project delays and cost overruns, we’ve put together a series of articles to highlight LIMS master data best practices. Some of the topics that will be covered in future articles in this series include:

• Master data configuration pitfalls
• Extrapolation of master data from your current paper records
• Master data naming conventions
• Strategies for handling master data in mergers and acquisitions (M&As)
• Designing your master data for maintainability and scalability
• Evolution of master data and change management
• Master data quality control
• Master data harmonization

In this part 1 article of our LIMS master data series, we’ll define master data and discuss the importance of developing a master data plan for your LIMS implementation. Without further ado, let’s dive into our LIMS master data series!

What is Master Data?

Master data can be thought of as the information that needs to be in place in the LIMS for users to be able to use the system as intended. Master data is core, top-level, non-transactional, static data that will be stored in disparate systems and shared across the enterprise, and possibly even beyond to external partners. As master data establishes a standard definition for business-critical data, its accuracy is very important, because it collectively represents a common point of reference and “single source of truth” for your organization. As such, everyone across the organization must agree on master data definitions, standards, accuracy, and authority. ​

Within most LIMS applications, there are two types of data that come into play – static (defined) and dynamic (transactional data). Dynamic data is the data users enter into the system as part of their daily activities such as test results, samples, batches or lots of a product. The master data is typically the static data that defines the structure of the system.

Master data and dynamic data are connected in the sense that the only way that dynamic data can be created is if master data already exists in the system. For example, in order to record a sample of a product for testing (transactional data) in a LIMS, the product name (master data) must exist in the LIMS so that the sample can be associated with a particular product in the system.

In most LIMS applications, various templates provide the ability to house the master data as lists/tables of values that will be used throughout the system. Master data typically includes core data entities like products, materials, specifications, sample types, analyses, lists, locations, reagents, instruments, environmental monitoring schedules, stability protocol templates and users. That said, universal specifications of master data items are not possible, as different laboratory types and/or LIMS will typically have different objects/entities identified as the master data.

Master data is foundational to business success. Even minor issues with master data can cause significant operational problems, and these problems will only be magnified as the organization scales, or reintroduced anytime new products or facilities are implemented. In order to avoid project delays and cost overruns for a LIMS implementation, it is critical to design and configure the master data properly. Towards this end, every LIMS implementation project should include a comprehensive Master Data Plan to ensure success.

Creating a Master Data Plan

In order to ensure a successful LIMS implementation, it is important to create a well thought out Master Data Plan that includes collecting all the master data that needs to be entered, deciding on a testing strategy to verify that the data has been entered accurately, creating a proper naming convention for your master data, and having an appropriate amount of time scheduled for entering the data into the system and testing it.

A Master Data Plan is a formal document that identifies the following:

• The rational for different aspects of the plan (e.g., why you have a specific naming convention)
• List of the organization’s master data that needs to be put into the system
• Schedule for when specific tasks need to be done
• The place(s) where the master data is created
• The people who will be doing the work of entering and testing the data. Note that these people need to have appropriate training for the job.
• How data is transferred into the system (e.g., the data migration plan)

One of the most important aspects of the Master Data Plan is determining what data needs to go into the system. This will involve scheduling an assessment of your data to determine what needs to be classified as master data, and also the master data entities in the LIMS being implemented to know which ones you will use and how. Note that this assessment may be utilized as an opportunity for you to do some housecleaning on your data. For example, you may decide not to add in master data for any test older than 5 years.

Another important feature of the Plan should be deciding on a naming convention. Here, it is important to get agreement on master data naming conventions amongst your user base so that they will be able to easily search for the data they need. Additionally, in organizations with multiple sites, using naming conventions that allow users to find their site-specific master data is crucial.

In a regulated environment, testing and documentation of testing may need to be included as part of your validation package. Towards this end, it is important that the person who tests the master data be different than the person who creates it. The person who does the testing must also have an understanding of the data they are testing and be trained in both the testing procedure and how the test results need to be documented. In addition, the Master Data Plan should document the procedure for updating master data in the system when necessary.

Conclusion

Your organization’s master data should serve to reduce the cost and time to integrate new facilities and enhance your organization’s flexibility to comply with regulations or enter new markets successfully. Over time, the master data contained in your LIMS will likely expand as your business expands with new products, facilities and regulatory bodies. Efficient master data management (MDM) will thus become critical to your operations. Be sure to tune in for the remaining parts of our master data series, where we will discuss the important best practices necessary to ensure your master data is designed and configured to deliver maximum business value for your organization.

Astrix is a laboratory informatics consulting firm that has been serving the scientific community since 1995. Our experienced professionals help implement innovative solutions that allow organizations to turn data into knowledge, increase organizational efficiency, improve quality and facilitate regulatory compliance. If you have any questions about our service offerings, or if you would like have an initial, no obligations consultation with an Astrix informatics expert to discuss your master data strategy or LIMS implementation project, don’t hesitate to contact us.

The post LIMS Master Data Best Practices Part 1: Defining the Terms appeared first on Astrix.

With massive increases in data volume over the last decade, and the growing concern from regulatory agencies around data integrity, integration between informatics systems has become a necessity, especially on systems that generate large amounts of data or that are crucial to the overall laboratory data workflow. Two examples of systems that fall into this category are LIMS (Laboratory Information Management System) and CDS (Chromatography Data System).

Waters Empower 3 is a chromatography data system (CDS) that links to chromatographic instruments to help facilitate management of chromatography test results through data acquisition, processing, reporting and distribution. This system is utilized by organizations across many different sectors – pharmaceuticals, food and beverage, fine chemicals and clinical. Empower 3 generates lots of data with complex calculations and detailed reports and has several tools that address compliance and data integrity concerns such as electronic signatures and audit trails.

Integrating LIMS with Empower 3 provides a number of important benefits for your laboratory:

• Data integrity is improved, since data transcription can be avoided by this integration.
• Higher lab throughput, as all calculations are executed automatically with minimal to no user intervention
• With the usage of electronic signatures on both Empower and LIMS, having a paperless lab becomes much easier.
• Data turnover can be improved by using tools (e.g., remote access or Empower Mobile) that enable users to review and approve data remotely.
• The integration between Empower and your LIMS allows information to be shared across sites globally and helps facilitate site harmonization (e.g., global methods instead of site-specific methods for the same testing, harmonization of processes between sites on where to perform calculations, etc).
• Standardized data workflows and processes make the overall system easier to maintain and support.
• Your lab staff can be reallocated to execute much more meaningful and profitable tasks, as less data transcription is required.
• Instrument OEE (Overall Equipment Effectiveness) can be improved as the overall data approval cycle can be reduced, effectively speeding up your ROI (Return On Investment)

Best Practices for Integrating LIMS with Empower

A few of the key best practices that need to be considered when integrating LIMS with Empower include:

Develop SOPs that guide your company on how to develop and maintain empower projects, templates and customized calculations.

When integrating Empower with LIMS, data can be transferred from Empower to LIMS through different routes depending on the chosen LIMS – direct data transfer, parsing of data from reports, etc. Whatever the integration solution is, changes to the Empower data organization must follow strict controls and thorough analysis to avoid any disruption to the integration between applications. For example, changes in a customized calculation naming convention or report method formatting might impact the LIMS system parsing script capability of capturing information from reports accurately. As such, having SOPs provides a roadmap to be taken each time new requirements or changes arise. These SOPs must include clearly defined responsibilities, comprehensive workflows and enough information to guarantee proper systems operation, maintenance and support throughout the entire systems lifecycle.

Make sure your data is secure throughout the integration process.

Some LIMS systems rely on the parsing of files such as “.csv” to capture data from external systems, and Empower can provide a multitude of exported files through its export method functionality. This can lead to a challenge, however, as these exported files have to be kept somewhere that the LIMS can sweep to identify candidates for parsing. This place can sometimes be a shared folder in the network, or even a local folder on a client computer (depending on LIMS requirements). As these systems generally require some level of read-write access, data security/integrity can become an issue if access privileges are not tightly controlled in order to prevent regular users from accidentally or purposely altering the data. In addition, it is important to develop testing scripts that deliver certainty that data integrity is maintained in all data transfer processes. Making sure that data is secure at every step of the integration between Empower and LIMS is key to assure regulatory agencies that your company has a strong quality culture and is focused on customer safety and product quality.

Build solid, reusable and consistent customized calculations in Empower.

Chromatography data calculations can be complicated and time consuming. They can include multiple formulas and data coming from external systems such as balances and Karl Fisher. In the past, companies relied on Empower in conjunction with external tools such as validated Excel spreadsheets in order to conduct advanced calculations, with the results then later on transcribed into other systems like LIMS or ERP to give continuity to data workflow.

Empower has a powerful tool for customized calculations called custom fields. It is a default functionality from Empower that can be used for a series of applications, such as:

• Create input fields that can receive information typed in by the user (i.e. sample label claimed amount)
• Create fields that will be used by LIMS to transfer data from LIMS to Empower (i.e. the sample id # in LIMS)
• Execute customized calculation based on one or multiple samples (i.e. blank area subtraction, content uniformity, total impurities calculation, etc.)

Having customized calculations developed in Empower is a good way of delivering readily available data to your LIMS, reducing the amount of work your company might have in developing calculations in a much more complex environment (e.g., LIMS). It also brings immediate benefits for the laboratory workload, considering that the final result is already available in Empower during data review process and no extra data treatment is required, making the overall process more time-efficient for the lab analyst. To achieve these benefits, it is imperative that SOPs are established for the proper development, testing, validation and maintenance of these customized calculations.

Figure out if the integration between Empower and the chosen LIMS needs to be bidirectional.

Although bidirectional communication might sound like the most logical way to integrate two applications, the benefits may not outweigh the extra complexity introduced for implementation, maintenance and especially support of this more complete integration. Careful consideration needs to be given to determine if bidirectional communication is the best option.

For example, a typical QC lab usually has a number of system suitability injections that can vary from test method to test method. This makes a scenario where the sample set could be transferred over from LIMS to Empower without any user input/adjustments (adding/removing injections, adding equilibrate/condition column lines, etc.) improbable. As a result, one directional communication from Empower to LIMS would likely be the most cost-effective solution.

In this case, Empower sample set templates could be created with most of the required information filled in, and with some additional custom fields to hold information required by the LIMS such as the LIMS sample ID. These sample ID’s could be added to this sample set manually or using barcode readers, and then after analysis is completed, data would be captured by LIMS through the one direction integration available.

The benefit in this one direction scenario is reducing system complexity and maintenance/support requirements. When the time comes for major upgrades to Empower (e.g., software versioning, Oracle upgrades, etc.), having a cleaner integration will allow you to execute these upgrades with less chances of finding unmapped incompatibilities in the process.

On the other hand, a clinical analysis laboratory with hundreds of samples per day throughput requirements and patient information confidentiality concerns might want to avoid manual user data inputs, so a bidirectional integration would be a good way to guarantee a good lab throughput without compromising on data integrity and patient safety. In addition, clinical analysis laboratories tend to keep technologies for longer periods with no upgrades due to the sensitive nature of their business, so any effort invested in developing a bidirectional integration might last longer in such environments.

Have a proper mapping of where the required data is located within Empower.

Empower data can be located in different tables depending on the data type, but not all data is readily available for extraction, depending on the tools used by your LIMS for data extraction. Some common examples are the summary calculations (i.e., average, sum, %RSD, etc.) that can be added to report method tables. These calculations are executed on the go once you open the report method for data review, but these values are not saved in the Empower database. So in order to extract these values to LIMS, there are two possible pathways your company might have:

• Use parsing tools to parse the Empower report method and extract the required values from it.
• Create customized calculations to execute those report calculations that are not saved in the Empower database, allowing it to be saved once data is processed.

In this example, it is evident that a proper mapping of data location is vital to determine not only the amount of customization required in Empower, but also if your LIMS has all the required tools to fulfill the integration requirements. If your company already owns Empower and is looking at purchasing a LIMS, having a proper knowledge of the available tools within Empower might help your company narrow down the LIMS options to the ones that will better accomplish integration requirements right out of the box.

Conclusion

Integrating different systems and applications within today’s laboratory environment is critical to establishing digital continuity across the product lifecycle, optimizing operational efficiency, enhancing innovation, establishing a foundation for future growth, and maintaining regulatory compliance. This is especially true for global organizations with dispersed laboratories.

As discussed in this blog, integrating Empower and a LIMS is a great way to improve your overall laboratory informatics ecosystem, but there are a number of best practice recommendations that are important to follow in order to maximize the benefits of the integration for your organization. Astrix Technology Group has been helping scientific organizations implement and integrate laboratory informatics systems since 1995. The Astrix Team contains highly experienced and knowledgeable Empower and LIMS experts that can help your organization implement innovative solutions that turn data into knowledge, increase organizational efficiency, improve quality and facilitate regulatory compliance.

The post Best Practices for Integrating LIMS with Empower appeared first on Astrix.

The ability to combine NGS-generated genomic data with clinical data, for example, has revolutionized the Life Science industry, spawning the development of personalized cancer treatments and the field of Precision Medicine. Commonly used NGS processes (e.g., whole exome sequencing, chromatin immunoprecipitation sequencing, DNA target-based sequencing, RNA sequencing, etc.) are leading to many important discoveries and innovative processes in both research and patient-centered settings.

With the ability to generate multiple terabytes of data in a single run, however, widespread use of NGS technology has led to massive datasets for researchers. Managing this data has now become a central challenge for genomics laboratories and biotechnology companies. While data storage options have become relatively inexpensive in today’s digital age, processing and analyzing these enormous datasets has become the new bottleneck.

Scientists conducting research using genomics data need to be able to effectively compare genomes across patient cohorts and retrieve the associated sample information. In this context, laboratory information management systems (LIMS) that archive and organize data in a centralized database have become a necessity for genomics labs and biotechnology companies. LIMS allow scientists to intelligently examine these massive datasets to drive research decisions.

Laboratories looking to implement a LIMS face a dizzying array of options, however. There are now several dozen LIMS vendors on the market, including LIMS that are specifically designed for genomics laboratories. In this blog, we will discuss some of the key features a LIMS serving a genomics laboratory should have and provide an overview of a LIMS selection methodology that helps to ensure you make the right choice for your unique laboratory environment.

Important Criteria for Selecting Genomics LIMS

Genomics research often involves complex, multi-step workflows that frequently need to be adjusted and can span several different laboratories. The experimental complexity of genomics research, along with the massive data volume, create unique challenges for researchers and/or laboratories looking to manage and analyze genomics data. In addition, regulatory bodies have been working to catch up with this dynamic field, and complex guidance and regulations are beginning to emerge that seek to maintain testing accuracy and reliability.

When properly implemented, a LIMS solution can dramatically improve laboratory efficiency and effectiveness, along with regulatory compliance. While system requirements that are unique to your lab should be the foundation of every LIMS selection process, there are number of selection criteria that are typically important for a genomics LIMS. Some examples include:

Easily configurable and customizable. With the cutting-edge research being performed in genomics labs, workflows, protocols, methods and technologies are constantly changing. Genomic LIMS need to be adaptable to help labs accommodate changing technologies and methodologies. Instead of having to call up the LIMS vendor every time something needs to change in the system, the lab team should be able to quickly configure the software. The LIMS should also come with a flexible application program interfaces (API) that allows a lab team with programming expertise to easily customize the system. The bottom line is that the rapid timescales associated with NGS require an easily configurable and customizable LIMS that will enable labs to avoid programming delays and make changes quickly.

Easily integrates with next generation sequencing instrumentation. Integrating instruments with LIMS is one of the primary ways that LIMS improve workflow efficiency in labs. Towards this end, any LIMS utilized by a lab with NGS equipment should integrate (generate and consume instrument files) readily with major next-generation sequencing instrumentation. In order to help automate workflows and speed analysis, the LIMS should:

• Automates the process of setting up a run – scientists specify the samples they want to use, and the LIMS automatically generates the files the sequencer needs for the run.
• Tracks the quality of sequencing data coming from the instruments – it is highly inefficient for labs to wait until the run are complete before evaluating data quality.
• Tracks results – scientists should be able to easily locate the information associated with any particular run.

A good LIMS will enable scientists to avoid having to organize and track sequencing data so they can spend more time on analysis and innovation.

User specific interfaces. NGS work involves collaboration between many different types of scientists to extract the insights that drive innovative medicines. Given each of these scientists needs access to different types of information and performs different tasks, the LIMS needs to be able to provide user specific interfaces to maximize productivity. User specific interfaces are also necessary for data security – users should only have access to the information they need to do their jobs effectively.

Comprehensive sample tracking. NGS biologics add significant complexity to sample tracking and workflows, including the need to track sample lineage and progeny over time. Given this complexity, genomics labs often struggle to effectively track the samples (and associated metadata) used to conduct a particular experiment. To be able to effectively analyze the enormous quantities of data the NGS produces, scientists need to be able to track all the granular details unique to genomics samples throughout the workflow (from sample submission to result reporting). This will allow researchers to see and interrogate sample history over its full lifecycle in a single centralized system, ultimately making it easier for scientists to set up and validate experiment runs.

Compliance Support. Given that genomic research typically involves human samples, genomics laboratories must adhere to a variety of regulations – CLIA, GDPR, HIPAA – administered by US and international agencies in addition to GxP and 21 CRF part 11. There are also frequently stringent state regulations for genetic testing, in addition to both laboratory and scientific professional organization (e.g., College of American Pathologists, Association of Molecular Pathology, American College of Medical Genetics and Genomics) guidelines that need to be integrated into laboratory operations.

As such, the LIMS solution chosen will need to have a robust set of controls that support compliance with applicable regulations and standards on data integrity, validation and privacy. Additionally, the project team needs to have the skills, knowledge and experience necessary to properly develop and apply these controls during the implementation so as to enhance and ensure regulatory compliance for your business.

LIMS Selection Methodology

While the above-mentioned selection criteria are usually applicable for a LIMS serving a genomics lab, every lab is unique, and care should be taken to apply a comprehensive methodology that ensures the best LIMS for your lab is chosen. One of the biggest mistakes companies make when selecting a LIMS is to omit the business analysis necessary to ensure you select the right LIMS for your unique laboratory. Organizations purchasing a LIMS typically have many workflows in place that incorporate manual processes and information stored in disconnected silos such as spreadsheets, emails and paper notebooks. These workflows will need to be completely revamped and optimized to take full advantage of the productivity and efficiency gains that a LIMS can offer.

The first step in any technology selection process should be thorough workflow and business analysis that serves to maximize business value for your organization. Such an analysis utilizes business analysts with domain, industry and system knowledge to document the current state of laboratory operations, as well as an optimized set of future state requirements that will encompass the flexibility necessary for genomic workflows.

Once a set of optimized future-state requirements are generated, it may also be necessary (for large organizations) to design a laboratory informatics architecture that is aligned with business goals, along with a roadmap to deployment, before engaging in a proper technology selection process for your organization. With the proper foundation laid for your selection process in this way, you ensure that the LIMS selected for your laboratory will maximize business value for your organization.

Conclusion

LIMS have proven to be an invaluable tool for laboratories across a wide range of industries for over 30 years now. Due to the unique demands of next generation sequencing, selecting the right LIMS for a genomics laboratory can be a challenging endeavor, however. Genomics labs typically need a flexible, scalable, regulatory-compliant, multifunctional LIMS with a low total cost of ownership (TCO) that satisfies most or all of the selection criteria described above.

While several vendors now produce LIMS specifically designed for genomics labs, some of these systems can be rigid and prescriptive about workflows. A comprehensive methodology that includes a thorough evaluation of hosting options should be followed to ensure that you select the best LIMS for your laboratory.

Astrix  has over 20 years of experience facilitating successful LIMS selections and implementations in pharmaceutical and biotech companies. Our experienced professionals have the experience and knowledge to help you select a LIMS that will allow your organization to turn data into knowledge, increase organizational efficiency, improve quality and facilitate regulatory compliance.

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