Role of biostatisticians in clinical trials

Pepgra CRO biostatisticians excel in the application and communication of statistical science in medical device, drug development, food, nutraceuticals, tobacco, etc. They play a central role in promoting innovative, scientific, quantitative decision-making throughout the drug or device development life cycle.

This blog talks about the importance of their role in clinical trials.

So why are biostatisticians important?

You must ensure the involvement of a clinical statistician for the benefit of the clinical trial and team members because they play a key role in clinical trials. For example, knowledge of how to derive the factors in the analysis/inference of the resulting data is pivotal. The statistician should be part of the project at the outset to ensure the data makes sense in terms of clinical significance rather than statistical significance; hence, they reduce chances of performing data analysis that cannot answer vital questions pertaining to the clinical trial. Considering safety and efficacy (with negligible adverse reactions), biostatisticians observe any one or both of the following:

• 1) Whether drug A fares better than drug B.
• 2) Whether the medical device performs better in contrast to that of the predicate/equivalent device that is available in the market.

Pepgra CRO offers plenty of opportunities to provide statistical and data-related leadership across the business within a highly regulated medical devices environment. In the medical device segment, the statistician is responsible for selecting and advising on the most appropriate study design, statistical methods, analysis, and presentation of data and the automation of validated routine analyses as required, to support product release and regulatory (CE & FDA) requirements. In the longer run, the role entails building and leading the organization’s statistical support team.

Role of biostatisticians

Statisticians have the skills and knowledge required to work with therapeutic specialists and clinicians to analyze and design studies to minimize bias and achieve study objectives. They establish the core research question in a quantifiable manner to

• formulate hypothesis;
• develop statistical analysis plan (SAP);
• select the appropriate test;
• select the apt sample size;
• collect data;
• perform the test; and develop TLG (tables, listings, and graphs); and finally, report the inference.

Moreover, they also review protocols before the final review and involve in data management, quality monitoring, and safety of clinical trials.

Reducing the possibility of bias is imperative. Minimize bias by ensuring that the conditions of the experiment are consistent with the Good Clinical Practice (GCP) guidelines and adhering to a detailed protocol to ensure that all clinical trial members and all labs participating in the trial strive toward the same specifications. Please note that bias may persist even though the aforementioned conditions are up to the mark.

Role in in-vitrio experiments

In-vitro studies involve tests using assay plates and within each well the cells are exposed to different treatments or doses before the endpoint of interest is measured. Biostatisticians analyze the data collected from these tests. The number of replicates required for each dose/treatment will be dependent on the statistical tests in the analysis. Often, for convenience, all replicates for treatment X will be completed followed by treatment Y, and so on; this could potentially introduce bias to the experiment, which could be mitigated by randomizing the order of each treatment application using randomized blocks and Latin squares designs.

Role in animal experiments

The design of animal experiments is often very similar to that of human trials, where biostatisticians analyze data collected from blood samples, measure physical attributes such as body mass and collect samples of urine and excreta; alternatively, a trial may involve the sacrifice of animals at specific time points to examine the internal organs.

Role in human experiments

As with human trials, a biostatisticians test a number of designs on animals; the common ones are completely randomized, randomized block, and factorial designs. They also use sequential, crossover, and Latin square designs.

What are their responsibilities?

Here are the roles and responsibilities:

• Data management;
• Monitoring quality, safety, and efficacy;
• Provide statistical and data related leadership across the business Responsible for product release and performance monitoring;
• Oversee data related aspects of DV and product performance testing for regulatory submissions;
• Design, analyze and formally report on studies/experiments;
• Liaise as statistics subject-matter expert in preparing and participating in internal and external audits of the quality management system (QMS) for all data analysis.
• Support products throughout their life cycle, from concept, throughout development and launch, to post-market surveillance;
• Communicate the interpretation of experiments, clinical studies and fitness evaluations to management; and finally,
• Ensure data is compliant with the native protocols, regulations, and standards.

What to look for in a biostatistician?

Before you hire biostatisticians for your clinical trial, ensure they possess the following skills:

• Good statistical interpretation skills;
• Ability to select the correct statistical analysis depends on the ability to define correct type of variables being analyzed; therefore, know-how on measurement scales is pivotal;
• Knowledge of ISO 13485, CE and FDA requirements, with experience supporting regulatory submissions and regulatory statistical issues;
• Knowledge of India, China, and South American regulatory protocols is a plus;
• Experience in the product batch release and performance monitoring of test strip systems;
• Know-how of diverse methodologies, drug indications, design and analysis of experiments, DV and clinical studies experience supporting new product development;
• Identify missing data, inconsistent data, outliers, and unexpected lack of variability and deviation in the protocol;
• Perform data transformation, estimation, confidence intervals, hypothesis testing, adjustment of significance and confidence interval.
• Examine data trends in terms of consistency, range, and data variability within and across sites;
• Statistical Analysis Plan (SAP) development, mock tables, and List of Tables (LoT);
• Guide programmers and validate TLGs;
• Compare multiple treatments: Intent-to-treat (ITT) analysis, multiple primary variables (e.g., Dunnett’s, Bonferroni Correction, closed test procedures, and single primary treatment comparison), treatment through centre interaction, dose response analysis, and magnitude effect;
• Evaluate significant or systematic errors in data collection and report on-site or across site. Report data integrity problems or potential data manipulation;
• Analyze characteristics of the sites and performance metrics;
• Interim analysis to compare treatment arms with respect to efficacy or safety;
• Develop statistical analysis plan: technical and detailed elaboration of the principle features stated in the protocol;
• Proficiency in common statistical analysis programs (SAS, R, AMOS, Eviews, Strata, etc.); and finally,
• Respond to request and queries from regulators.

Pepgra provides statistical leadership, expertise, and advice to ensure that safe and effective drugs are available to the community. For more information on Pepgra CRO biostatistical programming solutions, click here.

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