Biostatistics & Data Management

Biostatistics, data management and clinical research methodology are crucial in the Life Sciences sector to define, develop and adopt the most appropriate approach to an experimental investigation. Applying a sound methodology means planning correct and adequate studies from the onset to ensure high-quality data, reliable results and ethical execution.

Effective communication and ongoing collaboration enable our team of physicians, biologists, biotechnologists, data managers and biostatisticians to best support the client by studying the most appropriate investigational design for their needs.

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Our approach
Communication and teamwork

Clear and effective communication are essential for productive cooperation in a team of professionals from different experiences and multidisciplinary backgrounds. A mutual understanding of clinical and statistical terminology is, therefore, the basis of our interactions.

Practical needs and operational limitations

Supporting the client means showing how to best design a tailormade clinical trial, which is methodologically flawless and practically sustainable at every stage, taking into account the practical requirements and operational limitations of the whole research project.

Ethics

No clinical trial is effective without ethics or respect for patients; weighing the needs of clinical research and patients’ protection is one of our core values. 

Related services
  • Drugs
  • Medical and diagnostic devices
  • Food supplements
  • Nutraceuticals
  • Dermocosmetic
  • Research, analysis and interpretation of scientific literature
  • Identification of the most suitable experimental design to suit project objectives and feasibility
  • Definition of primary and secondary study endpoints
  • Identification of the most appropriate and innovative measurement methods and tools
  • Identification of patient selection criteria
  • Identification of the most appropriate statistical methodology (blinding, choice of control group, randomisation, interim analysis, analysis populations)
  • Sample size calculation
  • Statistical analysis
  • Document preparation (Statistical Analysis Plan, Statistical Report)
  • Definition of the best data collection strategy
  • Design of surveys and CRFs (paper and electronic)
  • Management of high-quality and secure databases
  • Data cleansing by implementing manual and automatic checks
  • Coding of medical terminology
  • Document preparation (Data Management Plan & Report, Data Validation Plan)
  • tailored-made training sessions for the study team 
  • theoretical training on data management, methodology and biostatistics
  • training on critical evaluation of literature and study documentation
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Insight articles
Main mistakes planning a study
The importance of Sample Size calculation in clinical research
Clinical Endpoints
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