Enabling Digital Innovation to Transform Cell Line Development
The balancing act of ensuring the integrity and protection of a proprietary cell line development (CLD) process, data generated, and intellectual property (IP) while pursuing creation of a master cell bank is rife with challenges. While instruments and technologies supporting contemporary CLD workflows are more sophisticated than ever, they create more data points and analyze more parameters than can be feasibly processed by hand. The resulting wealth of data can, in turn, create new bottlenecks for a workflow. Securely housing and managing this increasing data output necessitates implementing strategies, software, and solutions that can support an interconnected, interoperable process capable of supplying the right data in the right format at the right time to inform decision-making.
Making the leap from incumbent systems ill-equipped to manage the diversity and breadth of data made possible by new analytical technologies can be incredibly challenging for legacy biopharmaceutical companies. Even those who have transitioned from analog notetaking to electronic systems may see very little benefit from the switch, as they may simply consider an ELN the new repository for any lab notes, and accessible only as a stand-alone piece of information. This lack of interoperability can hamper CLD activities between collaborating labs and can hurt later process development and scale-up activities. Combining these data siloes into a more integrated platform can greatly streamline and optimize a workflow by eliminating duplication of effort, creating efficiencies compounded by new approaches to analytics and automation, and improving data presentation and packaging to better conform to regulatory requirements.
The biologic drug development process is long and complicated, with companies investing years to discover, screen, develop, and optimize drugs. Establishing an integrated, tailored data management strategy is core to getting the drug development journey right. This data management strategy hinges on connecting as many discrete process steps as possible to a centralized platform able to support better, faster insights. To this end, the solutions offered by the Life Sciences companies of Danaher allow users to leverage interconnected and comprehensive data interfaces to manage a drug’s progression within a development ecosystem securely.
Overhauling Data Management Strategies to Support Accelerated Development
For many CLD laboratories, ensuring data integrity is a complex undertaking. The data analysis and storage bottleneck has made housing and managing increasingly large and diverse datasets the norm for these workflows. Additionally, laboratories may not sufficiently communicate these data to other CLD labs within an organization, forming data silos that perpetuate organizational inefficiencies. Transitioning from legacy systems to cloud-based platforms is both crucial and challenging. The idea of transitioning from a system that may work in the present to one that offers greater insights and manipulation is tough. However, complex data interpretation and the potential pain points caused by miscommunication or rework require thinking differently about how data is handled. Having data solutions that are streamlined, interoperable, and easily used can improve both short-term decision-making and later-stage regulatory interactions.
Collecting and transferring data between disconnected systems can create data integrity risks and alignment issues. Maintaining these solutions is often resource-heavy, and these solutions may not provide process-level decision-makers with the information they need to accelerate more efficient and smarter CLD and process optimization. Newer data management technologies are, instead, capable of capturing a holistic view of data and enable data insights that can be leveraged to accelerate processes. These platforms also free up informatics and data science teams from processing raw data, allowing them to drive innovation for other facets of a workflow. In contrast to third-party point solutions, which may serve to address discrete issues as they arise, a connected, end-to-end system purpose-built for biopharmaceutical applications has the potential to transform an organization’s CLD processes, supporting improved experiment design, optimization, reporting, downstream activities, and regulatory submissions.
Achieving an interconnected, optimized digital ecosystem starts with automating data analysis across instruments through analytical software platforms tailored to CLD workflows. Genedata Expressionist is an open, scalable, and customizable software for MS analysis. This solution allows for a flexible, workflow-based approach to automate initial data analyses, intelligent batch processing without human intervention, and interactive in-depth data interrogation. Additionally, its stepwise data processing offers users complete data transparency and control at every workflow step. Similarly, Genedata Selector allows for data analysis across NGS-based workflows and improves transparency by affording users access to all sample information, linked data, analyses performed, and reports generated. The results are analytical solutions that transform raw data into actionable insights that address a workflow’s technical and business needs.
An All-in-One Solution for Lifecycle Management: IDBS Polar
For most biopharmaceutical development teams, data capture approaches are either built on legacy applications like local ELNs, disconnected systems built in-house, or a combination of paper trails, notebooks, and stand-alone instrument software. Convening a CLD process’ disparate data streams to drive decisions is best achieved through a lifecycle management platform, or digital backbone, that can combine and contextualize data in a way that is both user friendly and effective. IDBS Polar, the world’s first BioPharma Lifecycle Management (BPLM) platform, drives operational efficiency with comprehensive data capture and curation, enabling more strategic data analysis.
According to some industry estimates, effective lifecycle management can help expedite development, enabling biological products to reach the market up to three years faster. IDBS Polar Biopharma Lifecycle Management software, a cloud-based system with embedded AI/ML and visual analytics, supports this acceleration through end-to-end analysis encompassing data access, reporting, visualization, and exploration, all without needing specialized analytics tools or data scientists. Polar can further support collaboration by linking a workflow and multiple laboratories. For organizations with different sites working on the same asset, lifecycle management solutions like Polar are indispensable for avoiding redundancies and supporting data access and communication. Employing Polar at the very start of an asset’s development journey can drive insights, as a CLD team can look back at what occurred during initial R&D to understand a process better, and their development can go on to inform later downstream activities.
Having a digital backbone like Polar to capture granular details of what occurs during CLD can help organizations avoid serious setbacks. This can be most readily seen in the atypical adjustments a CLD lab may take to support their unique asset – for example, for cells or products sensitive to even minor temperature fluctuations, a lab may choose to insulate their bioreactors. But if this jacketing isn’t properly noted during tech transfer, it can result in poor outcomes for the next lab in the development process and time-wasting investigations into the root cause. Process recording, as well as instrument-to-software data transfer is also beneficial, as it serves to reduce the potential for error introduced by manual data entry.
Polar is useful for accessing, sharing, and interpreting existing data. It also offers development support for process execution. Part of Polar’s unique value proposition is its guided support of discrete process steps – it can take users through a process operation from start to finish and will flag inconsistencies in a process. Users can then explore the data surrounding a specific step more closely, drilling down on when anomalies occurred to determine what actions of parameters contributed to any issues. Additionally, while Polar does not generate reports automatically, it does pull data relevant to regulators for each step of a CLD workflow, so that when users are ready to file a biologics license application (BLA), all relevant data is immediately accessible.
Employing Digitalization to Drive Innovation
Establishing a CLD workflow primed for success requires more holistic, integrated approaches to data management. Data siloes between process steps, operators, and labs can all create the potential for rework, bottlenecks, and issues with data integrity. Avoiding these pitfalls in the face of more data points than ever requires solutions aimed at convening data, making it accessible and interpretable, and enabling interfaces that support greater monitoring and collaboration. Solutions like IDBS Polar Biopharma Lifecycle Management software, Genedata Expressionist, and Genedata Selector support this digital innovation through platforms optimized to support biopharmaceutical applications and their most crucial process steps from start to finish. Integrating these comprehensive data platforms to complementary automation and analytics solutions is likewise important to supporting accurate, comprehensive CLD while more effectively addressing resourcing, human error, turnaround times, redundancies, and data inconsistencies.