Unleash the power of bioanalytical software: ensure quality with best practice workflows.

Discover how to unleash the power of bioanalytical software to ensure quality and reproducibility in the laboratory using best practice workflows. This article delves into the different stages of best practice workflows and identifies the key elements underpinning each stage. It also looks at the benefits of using bioanalytical software and finally, it reflects on the different types of systems available.

Bioanalytical software has emerged as an indispensable tool for pharmaceutical companies. This cutting-edge technology allows scientists to record, manage and gain significant insight into complex biological data scenarios.

What is a bioanalytical software?

Bioanalytical software is a solution that offers multiple functionalities and is designed to capture, analyze and report on biological data and workflows. These tools are created to help scientists capture and store data generated from laboratory experiments. In addition, it supports the planning element of experiments and the generation of analytical reports. It also provides scientists with in-depth knowledge and insight into the data, allowing them to make informed decisions.

What are the best practice workflows in bioanalytical software?

Bioanalytical software allows scientists to follow a series of workflows to ensure consistency and accuracy of methodology and specifically quality at each stage of the process. It also allows reproducibility of the methods’ results – meaning independent researchers can conduct the same experiment at different times and generate consistent and validated results.

The best practice workflows are:

  1. Sample accessioning stage – Involves the receipt of sample shipments, and includes discrepancy handling, sample transfer and storage.
  2. Registration of samples stage – Samples can be registered and assigned a unique system-generated identification number. Samples can then be assigned a specific location in readiness for analysis. This stage also provides integrated inventory management.
  3. Planning stage – Enables Principal Investigators and Study Directors to outline the recipes, procedures and parameters of the methods and assays that will be conducted and ensures that the experiment is repeatable. Planning also includes the method definition and supporting tasks such as ensuring the required equipment is available for use.
  4. Execution stage – This stage documents the procedures, consistently captures the data, enables any exceptions to be flagged for immediate correction and logs all items used – such as genealogy tracking. This also includes the preparative steps and equipment checks, instrument setup and sample management.
  5. Reporting stage – This final reporting stage can summarize experiment results across the execution workflows within a study, including the calibration curve, quality controls, validation and stability assessment sampling. The types of reports available include, but are not limited to: equipment check reports, exception reports, usage logs and post-process reports. Overall, bioanalytical software can capture data in real time and simplify reporting methods.

What are the key benefits of using this software?

There are several key benefits to using bioanalytical software in the life sciences industry. The main benefits are as follows:

  1. Data management and data analysis
    Bioanalytical software enables efficient processing of small or large quantities of data by automating tasks, which reduces the time spent either entering data into a spreadsheet or using pen and paper to record experiments. It can also record data with a scanner and provides instant in-depth analysis at the touch of a button.
  2. Complying with regulatory requirements
    Bioanalytical software enables an organization to conform to the guidelines, regulations, policies, standards and laws that it must follow.
  3. Improved efficiency and better laboratory workflows
    The software enhances laboratory workflows by streamlining tasks, from sample collection and instrument setup to analysis and reporting. It is also able to track data more efficiently with improved quality measures facilitating experiment reproducibility while reducing study cycle times and accelerating overall time-to-market.
  4. Streamlined reporting
    As part of the workflows, bioanalytical software provides real-time reports that can capture deviations and speed up reporting. The reports offer improved data visualization with charts and graphs, which help simplify complex problems or large data scenarios, clearly illustrating relationships in the data.
  5. Integration with other systems
    Software plays a crucial role in integrating with other software systems – so data can be shared in real-time in a secure and compliant manner. In addition, once a bioanalytical software system has been implemented, it is essential to ensure that it is integrated with instrumentation and existing software infrastructure for improved data quality and integrity so all the data can be stored in a highly contextualized way in a data backbone and can then be used for enhanced insight to enable users to make those informed decisions.

What are the limitations of a bioanalytical software system?

Although there are numerous benefits to adopting a bioanalytical software system, there are also some limitations, including:

  1. Data quality – The quality of the data is dependent on the accuracy of the data that is being entered into the system. Mistakes or inaccuracies can lead to inaccurate results.
  2. Customization – Bioanalytical software offers many functionalities, but if the software does not meet the needs, it is important to find out if it can be customized.
  3. Maintenance and updates – Similarly to any other software system, a bioanalytical software system requires frequent system updates to prevent security breaches, hacks and cyber-attacks to ensure the system runs smoothly.
  4. Operator dependency – The effectiveness of bioanalytical software can be related to the skills and the systems training received by the operator. Quality and regular computer software training is essential to improve the operator’s performance.

Over the years, suppliers of bioanalytical software systems have developed best-practice workflow systems, which play an essential role in today’s modern laboratory. This software provides many benefits, such as improving data accuracy, repeatability and analysis, streamlining processes and reporting while enhancing productivity and collaboration. However, as with any vendor selection, it is important to ensure the bioanalytical software can grow with the organization’s needs and allows for customization. Therefore, with ongoing configurations and improvements, bioanalytical software systems will continue to play a vital role as they help BioPharmaceutical organizations accelerate the discovery, development and manufacture of the next generation of life-changing therapies that advance human health worldwide.

Polar BioAnalysis from IDBS is a bioanalytical software system that enables contract research organizations (CROs) and BioPharma organizations to improve data quality and reproducibility, reduce study cycle times and accelerate time-to-market.


Learn more about Polar BioAnalysis.