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Cell line development is an essential stage in biopharmaceutical development that often lies on the critical path. Failure to fully characterise the lead clone during initial screening can lead to lengthy project delays during scale-up, which can potentially compromise commercial manufacturing success. In this study, we propose a novel cell line development methodology, referenced as CLD4, which involves four steps enabling autonomous data-driven selection of the lead clone. The first step involves the digitalisation of the process and storage of all available information within a structured data lake. The second step calculates a new metric referenced as the cell line manufacturability index (MICL) quantifying the performance of each clone by considering the selection criteria relevant to productivity, growth and product quality. The third step implements machine learning (ML) to identify any potential risks associated with process operation and relevant critical quality attributes (CQAs). The final step of CLD4 takes into account the available metadata and summaries all relevant statistics generated in steps 1–3 in an automated report utilising a natural language generation (NLG) algorithm. The CLD4 methodology was implemented to select the lead clone of a recombinant Chinese hamster ovary (CHO) cell line producing high levels of an antibody-peptide fusion with a known product quality issue related to end-point trisulfide bond (TSB) concentration. CLD4 identified sub-optimal process conditions leading to increased levels of trisulfide bond that would not be identified through conventional cell line development methodologies. CLD4 embodies the core principles of Industry 4.0 and demonstrates the benefits of increased digitalisation, data lake integration, predictive analytics and autonomous report generation to enable more informed decision making.

Introduction: Membranous nephropathy (MN) is a common cause of adult nephrotic syndrome that progresses to end-stage kidney disease in up to 40% of cases. It is an autoimmune disease characterized by glomerular subepithelial deposits containing IgG. In experimental MN, these deposits activate complement and cause kidney damage. The role of complement in human MN is less clearly defined. To address this, the current study focused on the role of complement in 2 independent primary (p) MN cohorts. Methods: Glomeruli were isolated by laser capture microdissection and analyzed by mass spectrometry, focusing on complement proteins, from kidney biopsy specimens from a pMN cohort (n = 11) and from normal controls (n = 5). Immunohistological staining of kidney biopsy specimens for complement proteins was also done. In a second pMN cohort (n = 13), urine levels of Ba, C5a, and C5b-9 (membrane attack complex [MAC]) were measured. Results: Mass spectrometry identified 8 complement pathway components (C1q, C3, C4, C5, C6, C7, C8, and C9) and 5 complement regulators (complement receptor type 1 [CR1], factor H [FH], FH-related protein 2 [FHR2], vitronectin, and clusterin). All complement levels were significantly higher in the MN groups than in the control group, except the level of CR1, which was lower. All pMN biopsy specimens showed negative or trace staining for C1q, positive staining for C3 and C4, and positive staining for at least 1 component of the lectin pathway. Urine Ba, C5a, and MAC were present in pMN, and their levels correlated (rBa,C5a = 0.87, rBa,MAC = 0.89, and rC5a,MAC = 0.97, P = .001 for each correlation). Conclusion: Elevated glomerular levels of C3, C4, and components of MAC (C5b-9) and absent or decreased levels of the complement regulator CR1, along with increased levels of complement activation products in the urine, support the involvement of complement in the pathogenesis of MN. These data raise the possibility that anti-complement therapies may be effective in some forms of MN.

Abstract Urine is commonly used for clinical diagnosis and biomedical research. The discovery of extracellular vesicles (EV) in urine opened a new fast‐growing scientific field. In the last decade urinary extracellular vesicles (uEVs) were shown to mirror molecular processes as well as physiological and pathological conditions in kidney, urothelial and prostate tissue. Therefore, several methods to isolate and characterize uEVs have been developed. However, methodological aspects of EV separation and analysis, including normalization of results, need further optimization and standardization to foster scientific advances in uEV research and a subsequent successful translation into clinical practice. This position paper is written by the Urine Task Force of the Rigor and Standardization Subcommittee of ISEV consisting of nephrologists, urologists, cardiologists and biologists with active experience in uEV research. Our aim is to present the state of the art and identify challenges and gaps in current uEV‐based analyses for clinical applications. Finally, recommendations for improved rigor, reproducibility and interoperability in uEV research are provided in order to facilitate advances in the field.

OBJECTIVES: The aim of this study was to examine which individual and work-related characteristics predict work outcomes related to sustainable employment among male shift and day workers. METHODS: Between 1 September 2005 and 31 December 2009, data on individual and work-related characteristics of N=5640 employees of Tata Steel in the Netherlands were retrieved from the Occupational Health Service and company registers. Work outcomes related to sustainable employment were (i) temporarily being placed in less strenuous work, (ii) sickness absence ≥6 weeks, and (iii) leaving the organization. Cox proportional hazard analyses were performed for all outcome measures. RESULTS: Similar predictors were found for shift and day workers although some differences were observed. For shift workers, high blood pressure and cardiovascular disease were important predictors for sickness absence. For day workers, insomnia was an important predictor of sickness absence ≥6 weeks. CONCLUSIONS: Similar predictors in magnitude and direction were found for work outcomes related to sustainable employment among shift and day workers. Interventions aimed at enhancing sustainable employability should focus on individual and work-related characteristics.