Staburo supported pegfilgrastim biosimilar development 

Together with Cinfa Biotech GmbH (now Mundipharma Biologics) and the University of Lucerne, Staburo recently published the first part of the results for Pelmeg, a pegfilgrastim biosimilar which is used for preventing neutropenia, induced by chemotherapy (click here to read the whole article DOI: 10.1002/prp2.503). As part of the collaboration, Staburo Principal Statistician and Managing Director Josef Höfler supported the interdisciplinary team with biostatistics expertise, especially in PK/PD.

The team planned, conducted and analysed a single dose, randomized, double-blind, two-way crossover study and demonstrated the comparability for the two PK endpoints examined (area under the concentration curve from time zero to last measurable concentration and the maximum concentration). The PD comparability (area under the effect curve for absolute neutrophil count [ANC]) was demonstrated, as well. The team could show that there are clinically no differences between Pelmeg and the originator with regard to immunogenicity and safety. Pelmeg was approved as a pegfilgrastim biosimilar in Europe.

PD-L1 assay comparability study published

Staburo supported the evaluation of the first multicentric analytical comparability study of PD-L1 expression in urothelial bladder cancer using four clinically developed immunohistochemistry assays. Statistical analyses included the investigation of inter-assay differences using ANOVA and intra-class correlations and the concordance for clinically relevant cut-offs based on Fleiss‘ kappa.

The results suggest that all four currently clinically relevant assays are analytically similar for the evaluation of PD-L1-stained immune cells and three (SP263, 22C3, and 28-8) for PD-L1-stained tumor cells.

The paper, which was recently published in Virchows Archiv, can be downloaded here (Staburo’s Statistics contribution is mentioned in the Acknowledgments): https://rd.springer.com/article/10.1007%2Fs00428-019-02610-z

R Shiny App for Standardized Detection of Outliers in Bioassay Development

The availability of reliable and sensitive assays is an important building block in the production and quality control of biological products. In the development of such assays, unusual or erroneous measurement results need to be detected, but adjudication by human operators is often inconsistent or prone to bias.

To help overcome this challenge, a Shiny app for the statistical detection of such outliers is being developed at Staburo: the Optimal Tool for Tracking of Outliers (OTTO). Close collaboration with the end users throughout the development process ensures that the statistical outlier detection results are in good agreement with subject matter expert evaluations. In particular, a mixed method approach was chosen which significantly reduced false outlier detection rates, compared to conventional statistical methods.

Thanks to the capabilities of the R Shiny technology, the user interface is intuitive and well suited for everyday use in the lab. Features of the app include application of outlier tests, automatic curve refitting after removal of outliers, and report generation for documentation purposes.