30 years of biostatistics support condensed into 3 hours
In the era of data-driven research, solid planning accompanied by appropriate statistical analysis is no longer optional; it is now essential.
This masterclass is designed specifically for life sciences professionals who wish to improve the integrity, reproducibility, and impact of their work through rigorous, robust, and robust statistical methods.
This 3-hour masterclass during which the key elements of the recommendations and regulations of the various government agencies (Health Canada, FDA, EMA, etc.) are presented with their concrete implications on the practices to be respected. Aimed at both management teams and scientific staff, the workshop allows stakeholders to be made aware of these issues. In itself, the masterclass is sufficient to allow startups to self-assess their practices and offer them tools to improve the points they consider problematic.
Masterclass Programme
1. Introduction: Scientific & Economic Context
In an era defined by data, the difference between true direction and false direction lies in how you collect, analyze, and interpret information. This section of the masterclass enables life sciences professionals to leverage statistics not just as a tool, but also as a strategic asset.
The Principles of Scientific Research and the Links with Statistical Tools
- The experiment: Transitioning from the sample to the target population
- Representativeness and reproducibility of studies and experiments
- Analysis and interpretation of results: p-value, a scientific and economic holy grail to be demystified
The Constraints of Startups
- Scientific principles put to the test of funding and deadlines
- Regulatory constraints
- A long-term vision: building the scientific history of society
Good Practices – 3 Guiding Principles
- Rigorous test planning
- A predictable, adapted and adequate statistical analysis of results
- Effective reporting and communication of results
2. Best Practices for Planning Experiments & Collecting Data
Behind every breakthrough is a well-planned experiment, and behind every reliable result is high-quality data. This section of the masterclass is your essential guide to applying sound statistical principles from the very beginning of your research.
Clarity of the research question: type of comparison, endpoint(s), factors, etc.
Use the knowledge already acquired to streamline each test
Adequate & Efficient Representation of Variability
- Biological variation
- Replication vs replicate
Control the Risk of Bias
- Randomization
- Blinding
Detection of Relevant Clinical/Biological Effects
- Establish and justify the desired clinical effect
- Calculate the chances of detecting the desired effect
- Statistical power and sample size
Choosing a Scientifically & Economically Efficient Experimental Structure
3. Adequate Data Analysis
In today’s data-rich world, the power of your conclusions depends not only on the data you possess, but also on its appropriate and appropriate statistical processing. This section of the masterclass provides you with the essential tools, techniques, and critical thinking skills needed to transform data into reliable information.
Preparing the Collected Data
- Pre-processing and manipulation of raw data
- The treatment of extreme values “outliers”
- Handling missing data
- Impacts on power and risk of bias
The Choice of a Statistical Data Processing Method
- Reflect the structure of experience
- Verify the underlying conditions of use of statistical methods
- Control and model sources of variability to maximize the chances of detecting important differences
Controlling Multiplicity
- The basic principle: rationalize the analysis of the results or risk reaching erroneous conclusions
- Corrective measures
- The statistical approach: effective but expensive tools
- The scientific method: “primary endpoints”, proof of mastery of the research topic
Management of experimental hazards: when everything does not go as planned…
- Adapt to unexpected events
- Anticipate potential problems
- Making the most of an experimental “failure”
4. Reporting of Studies & Results
In the life sciences, how you present your results is just as important as how you generate them. This section of the masterclass is designed to help you improve the clarity, credibility, and impact of your study reports through statistically sound practices.
The Research Protocol
- A somewhat trying but rewarding task
- A guarantee of quality for investors
The Data Analysis Report
- A realistic assessment
- Update the advancement of the company’s scientific knowledge
Scientific Communications
- Highlight rigour to better convince
- Aim for high-profile journals
Conclusion: Meeting the Challenges of Startups
- Good statistical practices: binding rules or efficiency gains?
- Find acceptable compromises
- Some possible solutions
Masterclass Duration
The duration of this masterclass is 3 hours.
Target Audience
The masterclass is aimed at both the management team and the scientific team, ideally both simultaneously to stimulate discussions on the subject.
Aimed at enabling startups to assess the adequacy of their scientific approach with regulatory requirements, it can stand on its own or be supplemented by different interventions for further reflection.