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Top 3 Tips to Optimize Bioanalysis

Want better, faster, and more efficient data? Check out these tips.

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    Focus on just three major areas to optimize innovation and achieve better quality, faster, and more efficient bioanalytical study data.

    Bioanalytical (BA) operations want to generate better quality, faster, and more efficient study data. More sensitive instruments, efficient sample management, and robust assays have all delivered huge productivity gains. What is lacking however, is an effective approach to data management. There is more to BA than the method-based execution of tests; the breadth of data assets BA laboratories generate should also be encapsulated. Today’s world leading BA laboratories are being transformed by high-context data and process management electronic laboratory notebooks (ELNs) which help generate superior quality data with high context.

    As BA enterprises become increasingly global, better data management and streamlined reporting offers exciting cost-saving possibilities, as opposed to the increasing difficulties of improving productivity and reducing costs on the operational side. Modern ELN platforms can manage the entire BA data workflow and drive existing Laboratory Information Management Systems (LIMS), sample banks, and analytical instruments. They improve consistency of process across sites and regional compliance with multiple regulatory frameworks.

    Focus on just three major areas to optimize innovation and achieve better quality, faster, and more efficient BA study data:

  • #1. Accelerate Laboratory Throughput

    Modern ELNs focus on the data and, with workflow support, enable you to:

    • capture and organize both structured and unstructured data
    • implement workflow and process management
    • automatically enforce QA
    • review by exception
    • report data by simply running queries

    Inefficiencies caused by data silos are eliminated, while the time taken from sample receipt to report delivery is reduced.

    Far from being simple replacements for paper, an enterprise ELN also delivers integration with LIMS, experimental and cross-experiment analysis, access to external literature, and internal enterprise content. Highly scalable solutions allow scientists to create their own unique methods, enforce compliance with them and flag any deviations. Pulling all the method development data together by query and analyzing trends actively gives real insight into processes and results generated across the organization to accelerate laboratory throughput.

  • #2. Increase Laboratory Capacity

    ELNs reduce the administrative burden on scientists, freeing them up to spend more of their time conducting valuable research rather than time-consuming administration. Data-centric ELNs support an ecosystem of ideas and collaborative information. Laboratory process control, business workflows, and equipment records, alongside instrumental data, are all comprehensively managed.

    Data across multiple runs can be collated into a single report, saving significant amounts of time. Delivery time for study reports can also be dramatically improved, with final reports often available within just one to two weeks after the last sample has been received, compared with one to two months using hybrid or fully paper systems.

  • #3. Improve Data Quality and Traceability to Support Compliance

    Every laboratory submitting BA data to a regulatory agency must comply with identical guidelines. However, all laboratories work differently, which can make the regulatory reporting process hugely resource intensive. Data-centric ELNs help save vast amounts of resource by collating data across multiple runs into a single report. Validated templates provide secure links between the original data and any final calculations for ease of audit. Data is recorded as securely as traditional paper records but with the added advantages of rapid validation of data entries against pre-established business and scientific rules. Data can be captured, verified, and reviewed from the entire BA process in one systematic, compliant environment. In addition, data can be accurately reconstructed months, or even years, later.

    In conclusion, data-centric enterprise ELNs will deliver the next round of productivity gains for BA laboratories. They recognize BA as a complex, inter-dependent process supported by various teams, all contributing to moving innovations from inception to delivery. An effective informatics infrastructure must therefore be placed at the heart of the enterprise for everyone to use. It should be totally paperless, platform neutral, enable complete and secure single point access to data, and integrate intelligently with existing processes.

    Enabling quality-assured methods and regulated study results to be delivered at a competitive pace is for the next generation of optimizing organizational innovation for commercial success.


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