AdWare Research provides data management and biostatistics services according to the regulatory requirements, international guidelines (FDA 21CFR Part11 and ICH E3, E6, E9, etc.). The procedures are regulated also in SOPs. The regulation-compatible data collecting and cleaning is done with the in-house developed Mythos CDMS. SAS/SPSS programme is used for data processing and for statistical analysis.
We provide the following data management services:
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- Writing the data management part of the study protocol
- Preparing the Data Management Plan (DMP)
- Writing the Data Cleaning Plan (DCP)
- Designing and preparing the CRFs/eCRFs based on the protocol or CRF form according to CDISC CDASH standards if needed
- Preparing and validating the data entry system corresponding to the study protocol (Using ORACLE® database)
- Data cleaning/Query management
- MedDRA, ATC coding under medical control
- Single or double data entry with QA
- Importing external data
- Reporting from the database according to the Sponsors’ requests
- Database closing, archiving
- CDISC SDTM database transformation (aCRF, SDTM datasets, Reviewers’ Guide, define XML)
- QA of the above activities according to ICH E6 (Guideline for Good Clinical Practice)
We can support not only pharmaceutical, but medical device, dietary supplements, healthy food, cosmetic development, other clinical research, epidemiological, veterinary, non-clinical and agricultural research projects, but our system is suitable for handling any questionnaires, please contact us for further information.
SAS or SPSS programs are used for analyzing the data imported from the cleaned and closed database. We can also perform the statistical analysis on databases that were not collected and managed by our company.
We provide the following biostatistics services:
- Sample size determination
- Writing the statistical part of the study protocol (also according to ICH E9 R1 addendum (estimand strategy) if required)
- Randomization procedure and preparing the randomization envelopes
- Writing the statistical analysis plan (SAP)
- Preparing the mock tables
- Preparing CDISC ADaM datasets (ADaM and other related datasets, Analysis programs, Define files, ADRG)
- Statistical analyses according to SAP using SAS® or SPSS software according to ICH E9 guidelines
- Preparing the tabulated forms, listings and figures
- Writing the statistical report according to ICH E9 (Structure and Content of Clinical Study Reports)
- QA of the above activities according to ICH E6 (Guideline for Good Clinical Practice)
Adaptive design can make clinical trials more flexible by utilising results accumulating in the trial to modify the trial’s course in accordance with pre-specified rules. Trials with an adaptive design are often more efficient, informative and ethical than trials with a traditional fixed design since they often make better use of resources such as time and money, and might require fewer participants. Adaptive designs can be applied across all phases of clinical research, from early-phase dose escalation to confirmatory trials.
Parameters that can be modified during adaptive trials:
- sample size,
- inclusion and exclusion criteria
- dose,
- number of treatment arms,
- number of visits
- data to be collected.
We have experience in designing adaptive trials, can support projects with protocol writing, data analysis, and our Mythos CDMS system meets the data collection and management requirements for adaptive trials.
With our strategic partners we can provide full scale project management for clinical trials. We provide assistance in:
- site selection, feasibility (phaseI-IV)
- licensing, dossier compilation
- contracting
- monitoring
- continuous test management
- data management and biostatistics
- preparation of medical reports
The services are provided according to ICH GCP.
For all clinical trials, whether the trial is terminated or terminated prematurely, the Sponsor shall prepare and submit a clinical study report to the competent authorities. The clinical study report should include a description of the study (clinical and statistical), presentation and analysis of the data.
With our strategic partners we prepare clinical study reports according to ICH E3 guideline.
Due to technological innovation in the life sciences in recent decades, there has been a dynamic increase in the number of data available in each research. In addition to the classical statistical tools, the processing of the increased amount of data requires methods using artificial intelligence (supervised / unsupervised learning algorithms) that can be used to create applications for predictive, prognostic or diagnostic purposes. Our colleagues have experience in this field and can support projects with data mining.
