OTTO: an R Shiny App for Standardized Detection of Outliers in Bioassay Development

OTTO: an R Shiny App for Standardized Detection of Outliers in Bioassay Development

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.

Data analysis, clinical biostatistics and more.

Staburo @ B2Run2019

Staburo @ B2Run2019

Staburo @ B2Run2019 

Team spirit, speed and strength – this time in action! Staburo started again at this year’s B2Run, after the last one in 2018 was canceled due to safety concerns (click here for the story).

With best weather conditions, 30,000 participants from 1,500 Munich companies ran together to finish in the Olympic Stadium. The race track was 6.1km long and took us through the picturesque 1972 Olympic Park, which alone was worth the effort. Staburo was in the middle of the action, and once again no. 1 in the Biostatistics category, check this graph for our results:

Everyone finished safely (after being cheered on, by great Staburo fans before the finish line) and was greeted and congratulated by the rest of the team. Great achievement!

After some alcohol-free electrolytes, water and fruits, we walked to our beautiful location for dinner, the Italian restaurant “Ciao Francesco” with delicious food.

It was a great evening with sports, fun and dinner!

Data analysis, clinical biostatistics and more.

Staburo @ APF Statistics Leaders Meeting

Staburo @ APF Statistics Leaders Meeting

Staburo took part in the APF Statistics Leaders Meeting

Hosted by Boehringer Ingelheim Pharma GmbH & Co KG, Staburo Managing Director Josef Höfler attended the APF (Arbeitsgruppe Pharmazeutische Forschung) Statistics Leaders Meeting, to hear talks about current statistics topics that are relevant for all biostatisticians that work in the pharmaceutical industry.

The topics ranged from double programming / validation, APF talent support, the AIMS (African Institute of Mathematical Sciences), CDISC programming and data anonymisation.

We thank Boehringer Ingelheim for hosting this event and the APF for inviting us to such a top-class event! We are looking for the next APF (Arbeitsgruppe Pharmazeutische Forschung) Statistics Leaders Meeting!

 

Data analysis, clinical biostatistics and more.

New team member @ Staburo

New team member @ Staburo

New employee @ Staburo

 

We are very happy to welcome Dr. Yesilda Balavarca in our team. Yesilda joins Staburo with her work experience from Deutsches Krebsforschungszentrum (DKFZ) Heidelberg and her excellent education background from University of Hasselt and University of Göttingen. She supports our clients in the areas of biostatistics and statistical programming as a Senior Biostatistician. We are looking forward to a great collaboration!

Data analysis, clinical biostatistics and more.

Training @ Staburo: Response Evaluation Criteria in Solid Tumors (RECIST)

Training @ Staburo: Response Evaluation Criteria in Solid Tumors (RECIST)

Training @ Staburo: Response Evaluation Criteria in Solid Tumors (RECIST)

At Staburo, we are working on a lot of oncology projects. Dealing with data from this particular therapeutic area does not only require good statistical knowledge, but also to understand how the status of the patients themselves is evaluated and which are the medical objectives behind that.

More precisely, this training intended to describe how the patients with solid tumors are evaluated in oncology trials. This occurs with the commonly used RECIST criteria, from which the latest version (1.1) was presented. First, CT or MRI scans are performed for each patient at baseline to describe the existing lesions. At several timepoints of the trial, images are performed again to evaluate these already detected tumor lesions and to detect potentially new lesions. Measurements of lesion sizes are performed on these images, which then lead to a response evaluation: “Complete response”, “partial response”, “stable disease”, “progressive disease” (PD), or “not evaluable”. This response can trigger the (dis-)continuation of patients in the trial (mostly in case of PD) but is also useful to evaluate efficacy of the treatments tested.

Details of the RECIST criteria were presented such as definitions of measurable and non-measurable lesions, target and non-target lesions, measurement rules (including Sum of Longest Diameters), as well as rules for assessing a response to a patient.

The next step of the analysis is the derivation of endpoints with the help of the response assessment. These endpoints were described in the presentation: they are mostly binary endpoints such as Objective Response, and time-to-event endpoints such as Progression-Free Survival. The usual methods of analysis were as well part of the presentation.

Finally, other types of criteria in oncology were shortly introduced: RECIST applies to solid tumors, but not to blood cancers for example where specific criteria are necessary.

Data analysis, clinical biostatistics and more.

Staburo @ DAGStat 2019 in Munich

Staburo @ DAGStat 2019 in Munich

Staburo @ DAGStat Conference 2019 

Several Staburo statisticians attended the DAGStat Conference 2019. The fifth conference of the Deutsche Arbeitsgemeinschaft Statistik took place in the heart of the Bavarian capital, Munich, from March 18 – 22, 2019.
According to the motto “Statistics under one umbrella” the conference was organized as a joint meeting of the “Deutsche Arbeitsgemeinschaft Statistik”. The meeting includes the 65th “Biometrisches Kolloquium” and the spring meeting of the “Deutsche Statistische Gesellschaft“.

Adaptive designs in clinical trials was one of the recurring topics of the conference. Staburo statisticians attended the tutorial on adaptive designs given by Prof Dr. Frank Bretz from Novartis Pharma GmbH and Prof. Dr. Tim Friede from the University Medical Center Göttingen. The tutorial discussed blinded sample size re-estimation and covered principles of group sequential and adaptive designs. Regular guidelines were discussed by Dr. James Hung of the U.S. Food and Drug Administration.
State-of-the-art methods of adaptive designs were further discussed in several conference sessions on Design of Experiments and Clinical Trials. Valuable input on the view of regulatory agencies on current hot topics in regulatory statistics was provided by PD Dr. Benjamin Hofner from the Paul-Ehrlich-Institute.

Dr. Hannes Buchner, Managing Director of Staburo GmbH, was also presenting on “A Novel Approach to Outlier Identification in Bioassays” on the conference. We thank everyone, who joined the talk, for their attendance and interest! If you are interested in this topic, but couldn’t join, just drop us an email to info@staburo.de !

Data analysis, clinical biostatistics and more.