Off-gas analysis using a magnetic sector mass spectrometer was performed in mammalian cell cultures in the fed-batch mode at the 5 L bench and 50 L pilot scales. Factors affecting the MS gas traces were identified during the duration of the fed-batch cultures. Correlation between viable cell concentration (VCC) and oxygen concentration of the inlet gas into the bioreactor (O 2-in) resulted in R 2 ≈ 0.9; O 2-in could be used as a proxy for VCC. Oxygen mass transfer (kLa) was also quantified throughout the culture period with antifoam addition at different time points which is shown to lower the kLa. Realtime specific oxygen consumption rate (qO 2) of 2-20 pmol/cell/day throughout the bioreactor runs were within the range of values reported in literature for mammalian cell cultures. We also report, to our knowledge, the first instance of a distinct correlation between respiration quotient (RQ) and the metabolic state of the cell culture with regard to lactate production phase (average RQ > 1) and consumption phase (average RQ < 1).

Highlights Data analytics has increasing significantly in recent years in the biopharma sector. No clear trend observed between algorithm utilisation and data size. PLS was found to be most applied algorithm within the biopharmaceutical sector. Majority of the data analytics applications are focused on USP operations. Data analytics will play a key role as the sector transitions towards Industry 4.0.

Data Integrity (DI) in the highly regulated biopharmaceutical sector is of paramount importance to ensure decisions on meeting product specifications are accurate and hence assure patient safety and product quality. The challenge of ensuring DI within this sector is becoming more complex with the growing amount of data generated given increasing adoption of process analytical technology (PAT), advanced automation, high throughput microscale studies, and managing data models created by machine learning (ML) tools. This paper aims to identify DI risks and mitigation strategies in biopharmaceutical manufacturing facilities as the sector moves towards Industry 4.0. To achieve this, the paper examines common DI violations and links them to the ALCOA+ principles used across the FDA, EMA, and MHRA. The relevant DI guidelines from the ISPE's GAMP5 and ISA-95 standards are also discussed with a focus on the role of validated computerised and automated manufacturing systems to avoid DI risks and generate compliant data. The paper also highlights the importance of DI whilst using data analytics to ensure the developed models meet the required regulatory standards for process monitoring and control. This includes a discussion on possible mitigation strategies and methodologies to ensure data integrity is maintained for smart manufacturing operations such as the use of cloud platforms to facilitate the storage and transfer of manufacturing data, and migrate away from paper-based records.