The biopharmaceutical industry is in the midst of a digital revolution–referred to as "Pharma 4.0"–where innovative technologies and data strategies are being introduced to drive efficiency, reduce costs, and accelerate drug development. In a recent SLAS Technology publication1, teams at Biogen and TetraScience outline the challenges facing this movement, and how cloud data pipelines, harmonized data, artificial intelligence, and other tools and technologies will pave the way for digital transformation. The authors describe a proof of concept case study to digitize a ThermoFisher ViiA7 qPCR data workflow that enhances data accessibility, interoperability, and analysis efficiency for protein therapeutic development.
Key takeaways
- Replatforming scientific data: Lab Data Capture (LDC) is a foundational strategy in Analytical Development at Biogen to collect and harmonize siloed scientific data from analytical instruments, reporting systems, and operational platforms. This process facilitates the transformation of diverse, proprietary instrument data into a standardized, harmonized format, enabling seamless data integration across platforms. The result is data that is FAIR: findable, accessible, interoperable, and reproducible.
- Cloud architecture: The Tetra Data Platform significantly contributes to the implementation of LDC by providing cloud infrastructure, tools, and the largest and fastest-growing library of instrument and software data models and integrations. It addresses the hurdles to Pharma 4.0 and data integrity by centralizing, standardizing, and managing scientific data. This is crucial for effective data utilization and regulatory compliance.
- Compliance-by-code: The transition to a compliance-by-code model, supported by LDC and the Tetra Data Platform, ensures laboratory processes and data handling are defined by code and verifiable through an audit trail. This offers a major advantage over manual operating procedures that are written with ambiguity that leads to creative interpretation and differences in execution. Automated processes will standardize workflows and reduce manual deviations from operating procedures, ensuring data quality and confidence. This is especially critical for pharmaceutical activities that adhere to regulated data integrity standards.
- Web applications: Cloud-based analytical applications that integrate with the Tetra Data Platform facilitate easy access and analysis of harmonized data for scientists, simplifying routine analysis and improving the reliability and efficiency of laboratory workflows.
- Cultural and technological shift: The adoption of LDC requires a cultural shift towards digital transformation and compliance-by-code within laboratories. This change is supported by training and upskilling staff to adapt to new technologies and workflows, enabling Biogen to more effectively leverage data for therapeutic development.
Summary
The Pharma 4.0 digital revolution signifies a major transformation for the biopharma industry, driven by advanced technologies and strategic data management. Through the implementation of Lab Data Capture, the use of the Tetra Scientific Data and AI Cloud, and the move toward compliance-by-code, the industry is poised for significant advancements. These strategies produce scientific data that is harmonized, data integrity and regulatory compliance that is automated, and laboratory workflows that are optimized, all facilitating faster and more efficient drug development. This revolution necessitates a cultural and technological shift within the industry that emphasizes the importance of upskilling and embracing digital transformation at all levels. By addressing these key areas, these advancements promise to enhance data integrity, streamline laboratory operations, and ultimately accelerate the delivery of new therapies to patients.
Learn more
- Read the full publication for complete insights from the authors.
- Interested in joining the digital revolution? Reach out to the experts at TetraScience.
References
- Van Den Driessche GA, Bailey D, Anderson EO, Tarselli MA, Blackwell L. Improving protein therapeutic development through cloud-based data integration. SLAS Technol. 2023 Oct;28(5):293-301. doi: 10.1016/j.slast.2023.07.002. Epub 2023 Jul 16. PMID: 37454764.