During clinical research studies, a significant amount of data is generated that needs to be carefully processed, analyzed, interpreted, and reported.
To make crucial decisions during a clinical study, high-quality data is needed quickly. Quotient Sciences Data Sciences function supports clinical trials conducted at our Miami, FL and Nottingham, UK clinics, providing customers with rapid insight to help make better decisions about their drug programs.
The key functions of data sciences at Quotient Sciences include:
Database Programming
The electronic Case Report Form (eCRF) is a collection of digital forms used in clinical research to collect data about study participants. The Database Programming team sets up and maintains eCRFs for all clinical studies carried out at Quotient Sciences, including making design amendments as required.
Statistical Analysis Software (SAS) is also used to program complex data checks and load external data, such as safety laboratory data, for reconciliation with the eCRF.
Data Management
The Data Management Plan (DMP) is an important document outlining how clinical research data will be managed during and after a study. Data management is responsible for ownership of the DMP, data cleaning, reconciliation of serious adverse events (SAEs), external data, coding, and query issue and review.
Another key task within data mangement is the database close/lock at the end of a clinical study. This prevents further changes to the database in preparation for data analysis. Finally, this team is also responsible for the generation of interim safety data listings for rapid dose decision meetings.
Statistics
The statistics function provides input on the clinical study protocol, including sample size calculation and randomization. The team also manages the Reporting and Analysis Plan (RAP), which describes all the planned data analyses and output requirements for a clinical study, and performs formal statistical analysis and interpretation of study data.
Statistical Programming
This function is responsible for programming Clinical Data Interchange Standards Consortium (CDISC) datasets, including Study Data Tabulation Model (SDTM), Analysis Data Model (ADaM), and define-XML, as well as study listings, tables, and figures. Using SAS software, the team loads data from the analysis of clinical study samples conducted by our bioanalysis team or external vendors.
Pharmacokinetics
The Pharmacokinetics team derives PK parameters, which assist in characterizing how the drug is absorbed, distributed, metabolized, and eliminated from the body, such as the area under the plot of plasma concentration of a drug versus time after dosage (AUC) and the highest concentration of a drug in the blood after dosage (Cmax), using Phoenix WinNonlin software. This data is used for interim and final PK reports.
Medical Writing
The Medical Writing team are a core part of the Data Sciences department, responsible for writing the clinical study protocol, including any protocol amendments and the final clinical study report (CSR) for all the clinical studies carried out at Quotient Sciences.
Data science experts work to global standard operating procedures (SOPs) and templates, and use industry-leading systems and software to drive data quality and reporting to meet customer expectations. On-study changes to early-phase trial designs and dosing are common, so we take a flexible approach to meet those demands. Faster data means that we can provide earlier interim data and pharmacokinetic (PK) reports for on-study dosing that aid in formulation development decisions.
All functions play a key role in delivering crucial clinical trial data in order to streamline the drug development process for our customers and accelerate their molecule to their next project milestone.To learn more or ask a question about our data sciences services, contact us today.