IDBS Blog | 25th January 2023

The key to painless data integrity for bioanalysis labs

The past eight years have elicited the highest number of data integrity FDA warning letters in history.¹ And in just the past three years, data integrity warning letters increased from 47% in 2019 to 51% in 2020, to 65% in 2021.² While some industry insiders attribute the rise simply to greater scrutiny, one cannot ignore that issues do exist.

Data without integrity is just numbers — with no value or trustworthiness. As discussed in our blog Bringing Data quality to the CRO/BioPharma partnership, pharmaceutical sponsors rate data quality and data integrity as one of their greatest concerns when outsourcing to a CRO.³ Today’s successful bioanalytical CRO must generate high-quality data for informed, real-time insight and reporting while also supporting regulatory and operational considerations. Maintaining this balance is what will set a CRO apart in the highly competitive outsourcing landscape and inspire the sponsor’s confidence in both the generated data and the CRO partner.

While the CRO industry is tremendously efficient in generating data, there remains a breakdown in efficiency when it comes to reviewing and tracking data for quality and compliance. This inefficiency can often be attributed to manual record keeping as well as missing or even lost data. With the critical role of the bioanalysis data in progressing drug products through preclinical and clinical development, this is a significant area of opportunity for improvement.

Ditch manual data management processes

Data integrity is a critical requirement in early-phase pharmaceutical research, encompassing quality, completeness, accuracy and consistency. The FDA’s 2016 Guidance for Data Integrity⁴ clarified the role of data integrity: Data must be reliable and accurate; meaningful and effective strategies should be implemented to manage data integrity risks based on process understanding. However, data integrity is at risk when relying on manual data transfer. The manually transferred data could be incorrectly entered, possibly duplicated and potentially inaccurate. And, should these data errors go unnoticed, there is potential for risk.

While informatics solutions, such as laboratory information management systems (LIMS), can boost productivity, throughput and scientific accuracy, some bioanalytical labs have recognized that this level of improvement does not scale without a more comprehensive data management strategy. Bioanalytical laboratories may use a LIMS for sample tracking within a study. Nevertheless, there is a large amount of critical information associated with projects, studies and daily runs, which is not captured or tracked in the LIMS but is still required to complete study reports – for example, analytical instrument setup, method validation documentation, sample QC and system calibration records.

Typically, this information resides in paper lab notebooks, study binders or Excel spreadsheets that are handed off to a QC team, which slows the process and burdens method development. Quality control requires multiple checks of date/time stamps, cross-reference checks of logs, and sign-offs as the data is moved and copied for verification to confirm that the QC method is being followed to ensure data integrity.

The solution is to implement a single platform to facilitate documenting balance checks, recording sample information for analytical runs and streamline process workflow to ensure data integrity and reduce transcription errors.

IDBS Polar BioAnalysis, is a cloud-based platform designed to reduce the pain of data integrity. The study management and method execution platform combines electronic data capture with structured workflows and real-time QC to drive bioanalytical processes with embedded data integrity.

Labs that already use industry standard bioanalytical LIMS can leverage tight integrations to ensure project and study hierarchy and attributes (project name, ID, analyte information, etc.) are automatically created and can be updated within Polar BioAnalysis. Sample lists and run information can be retrieved and stored for easier referencing at the bench, such as in a specified plate format. Finally, result data can be transferred from LIMS (or even the analytical instrument) to Polar BioAnalysis for downstream calculations and reporting.

Avoid data integrity risks from uncalibrated bioanalytical equipment

One of the most common data integrity issues our customers highlight can arise when using uncalibrated equipment. Calibrated equipment is crucial for generating reproducible results and maintaining data integrity and compliance with bioanalytical methods. If equipment, such as a balance, is found to be out of calibration, you will have to go back to review every experiment performed on that balance since the last calibration record as all the data will be in doubt. When usage and calibration are manually recorded, determining how that equipment might have been used, and by whom, is incredibly difficult to trace.

Alternatively, a digital system, such as Polar BioAnalysis, prevents data loss by maintaining usage records. Instruments within the bioanalysis laboratory can be attributed with a unique reference that can be tracked in the digital platform. Each instrument or asset can be associated with specific accuracy and acceptance criteria. As the user executes the method workflows through Polar, if the calibration of a specified instrument falls outside the acceptance criteria, the user is automatically alerted and prevented from continuing with the method execution until the potential issue is addressed in real time.

A digital system allows compliance to happen in the background – audit trails and time stamps are recorded through the workflows and don’t need to rely on the scientist remembering to record steps manually. Calibrators and QC samples can be created using built-in templates and referenced within a “run experiment”. Using templates that simplify data capture throughout the experiment mitigates the risk of missing and incomplete data, reducing errors, promoting efficiency and reproducibility and driving quality.

Reduce your QC burden and drive data integrity

Implementing Polar BioAnalysis has been shown to dramatically reduce the QC burden in bioanalytical laboratories while increasing quality. Structured method execution workflows for real-time QC reduce deviations and provide the context for easy access to study data analytics for rapid reporting and audits. Digitizing data into a centralized system can improve operational efficiencies by 20-30%.⁵

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