Staburo offers pharmaceutical/biotech companies, contract research organisations, and medical device manufacturers the opportunity to use our statistical expertise.

Our company is a biostatistics and data science service provider with expertise in the field of clinical research. The expertise ranges from the design of clinical phase I-IV trials (statistical input to study protocols, writing of statistical analysis plans, randomization, sample size calculation) and data analysis with SAS and R. For the calculation of pharmacokinetic and pharmacodynamic parameters Winnonlin is used. High quality standards are ensured by independent validation (e.g. independent review, code review or double programming). Our statistics experts supported numerous clients in submissions to FDA and EMA.

We have solid experience in oncology (RECIST) and complex study designs (e.g. adaptive, Bayesian BLRM, outcome depending switching/crossover, biomarker) and the implementation of complex methods in macros (RPSFT, IPE, IPCW). We have set up a simulation toolbox in SAS to find the optimal design and to verify the performance of methods and macros. Our toolbox is also useful for developing custom-fit translational research trials and analyses strategies.

Staburo supports pharmaceutical companies with data preparation for public disclosure on clinicaltrials.gov, EudraCT and other registers.

For the analyses, CDISC standards with ADaM datasets are used to ensure traceability, reproducibility, and compatibility across studies. If necessary, we consult on the anonymisation of clinical data.

Our team members are up-to-date on the EU data transparency legislation, because we participated in public disclosure initiatives for different clients.

We support biosimilars development programs, which play a crucial role in delivering biological medicines to a huge amount of patients. Depending on the client’s needs, we also work on-site for requested periods.

• Analysis datasets
• Tables, listings and figures
• CDISC (SDTM and ADaM) mapping
• Program validation
• Biomarker identification
• Implementation of crossover correction methods in SAS

Disclosure smooth right from the start.

Drafting protocols with disclosure in mind smooths the disclosure process and helps avoid potential compliance issues. To ensure your protocol is tailored for disclosure, our team of experts will support and guide your trial team during protocol drafting, finishing with a protocol review from a disclosure perspective that will ensure all relevant requirements have been addressed.

Successful results posting is crucial.

The posting of results presents evidence-based medical knowledge to the world and is the final important step in what is typically a long and substantial program of research. Since this step is so critical, we at Staburo are determined to post your results successfully regardless of the complexity of the trial design. Our experienced team will guarantee the posting of results, in full compliance with the relevant registries once your trial has been completed.

Your trial has been successfully completed and now some data sharing requests are coming in. You need help in assessing such requests either internally or with external stakeholders? Or you need help getting the data into shape in the form of document redaction for publication according to Policy 0070, ClinicalTrials.gov or journal specifications, or even the anonymization of individual patient data? Staburo will support you here.

You will benefit from broad experience, garnered from the review of close to 2,000 documents and counting.

Let’s have a chat!

Expert tasks

• Consulting on statistical issues
• Crossover correction in oncology (IPCW, IPTW, IPE, RPSFT methods in SAS macros)
• Statistical models for high-dimensional genomic data
• In-depth QoL analyses
• Multiple imputation
• Presentations and statistics workshops
• Data transparency (ClinicalTrials.gov, EudraCT)
• Bayesian Methods (e.g. BLRM for dose escalation, Safety evaluation)
• Adaptive designs
• Data simulation

Clinical trials

• Clinical trial planning (phases I-IV)
• Trial and project statistician tasks
• Sample size calculation
• Randomisation (including emergency envelopes)
• Statistical programming with SDTM and ADaM (SAS, R)
• Validation (e.g. SAS: source code review, double programming)
• Interim analyses
• Survival analysis

• Oncology – strong focus
• Respiratory – many projects as preferred provider
• Allergology
• Cardiovascular
• Central nervous system
• Dentistry
• Dermatology
• Gastroenterology
• Gynaecology
• Haematology