Responsible data science for clinical studies
Responsible conduct and considerations regarding safety and ethics is essential for data science, especially when it has an impact on human lives. This is particularly the case for clinical studies when it comes to safety and confidentiality of the participants and ensuring the statistical validity of any analysis.
For any clinical data analysis project, we particularly consider the following aspects of the GCP (Good Clinical Practice) guidelines.
Good clinical practice
Data management
The clinical data stays on the machine where the clinical data analysis is conducted, whether you want to perform the analyses yourself or have us support you.
Therefore, the modeling can be carried out on a machine that adheres to the regulatory requirements for the individual project.
Depending on your needs and requirements, we have different options to choose from:
- The computers of your scientists or the secure computers of our scientists.
- Dedicated machines at our offices or in our ISO-27001 certified and GDPR compliant server cluster located in Germany.
- A physical and dedicated GxP validated machine provided by you, located in one of our offices with secure access provided to specified team members.
- A computer at your location, where specified team members either have physical or secure remote VPN access.
In short, you are in control of the access and level of confidentiality that should be considered for your data.
If you have requirements for a bespoke solution, reach out to us.
Participant confidentiality
Data quality assurance
The outcome of QLattice models can be readily understood by clinicians and patients. The QLattice models have been classified as highly trustworthy by external assessors composed of disease experts and key opinion leaders. The models provide reproducible, transparent and highly interpretable results that can help identify inclusion/exclusion criteria for statistical analysis plans for clinical trials.
