Skip to main content.

Clinical Trial & Data Coordination

research graphic
Graphic of science terms with "research" highlighted 


To facilitate quality clinical trials by providing the research community with comprehensive and innovative trial design, data, and project management, and statistical analysis services that help move research studies efficiently and rigorously from the initial proposal through execution, analysis, and dissemination.


The Department of Biostatistics & Data Science Clinical Trials and Data Coordination Section offers comprehensive study design, data and project management, and analysis support services to investigators conducting clinical trials using a team approach. We assist with studies supported by federal and foundation grants and industry contracts, including investigator-initiated trials (IITs).  We offer a team of individuals with experience in designing and conducting multicenter clinical trials.

Data Coordinating Center flowchart
Data Coordinating Center flowchart

The steps for the Data Coordinating Center are as follows:

  • The study teams are encouraged to get their project registered very early in the process
  • Once the project is registered, the project manager from Department of Biostatistics & Data Science will have an initial discussion with the study team regarding the scope of the project
  • Post-scope finalization, the study team has the opportunity to conduct a feasibility analysis using tools such as C3OD or HERON
  • The next stage after study feasibility would be to develop sample size and power for the study using statistical tools such as SAS, R, FACTS, etc.
  • The final protocol is then submitted to the appropriate review boards.
  • Post IRB approval the study database built and validated.
  • Once the study is activated for recruitment, the accrual is continuously monitored until the study is closed for recruitment
  • During the active enrollment stage, the statistical team will be responsible for developing the Data Safety and Monitoring Reports along with the interim analysis.
  • Post follow-up duration, the statistical team will conduct data cleaning and lock the database and generate a final analysis report
  • Based on the results, the team would disseminate results through manuscript publication and conference presentations.
Study Design
  • Assistance in the development of study hypotheses and outcomes.
  • Optimizing study design, including both frequentist and Bayesian approaches. 
  • Implementation of innovative study designs, including Bayesian designs and fully Bayesian adaptive designs.
  • Development of new study designs that provide maximum efficiency in the presence of study parameters, restrictions, and assumptions.
  • Protocol preparation and implementation.
Statistical Methods & Analysis
  • Development and application of innovative statistical methods unique to the challenges of the ongoing studies in the section.
  • Drafting statistical analysis plans (SAPs).
  • Report generation for sponsors and government agencies.
  • Interim analyses.
  • DSMB reports
Data Capture and Management

Our primary data management tool is the Comprehensive Research Information System (CRIS) powered by WCG Velos eResearch.  CRIS is a secure web-based Clinical Information Management System (CTMS) where data and protocol information can be entered efficiently and in a standardized format compliant with Federal reporting standards. CRIS supports participant recruitment, study monitoring, trial design, protocol management, data safety monitoring, case report form construction and dissemination, integration of tissue and clinical information, clinical trial execution and query management, and integration with third-party clinical systems. CRIS is 21 CFR Part 11 compliant and meets various industry and Federal standards. In one comprehensive environment, CRIS can support multi-center, cooperative group, and investigator-initiated research through advanced technology and security features. Utilization of CRIS can improve research productivity, efficiency, collaboration, and data integrity. CRIS provides the following capabilities:

  • Creating, maintaining, and editing participant data, such as demographics, labs, medications, diagnosis, clinical history, and tissue samples;
  • Creating and maintaining research protocols;
  • Tracking the development of study protocols, versions, amendments, and IRB approvals/renewals;
  • Creating participant screening and enrolling criteria;
  • Creating and disseminating case report forms for clinical trials and outcomes studies;
  • Associating tissue samples with other clinical data at both participant and study levels;
  • Creating participant schedules and recording clinical results and participant status in research protocols;
  • Creating user and multi-organization research networks;
  • Recording, maintaining and reporting of adverse events;
  • Storing and reporting on all participant- and study-level clinical data;
  • Conducting study queries and generating standard and ad hoc clinical reports;
  • Exporting clinical data to third-party analytical tools.
  • Protocol-specific CRF development, complete with testing and appropriate implementation.
  • Validation testing.
  • Implementation of quality control/assurance procedures.

CRIS Training Request Form

 For more training and access information, please contact the CRIS Support Team at


  • Financial management services.
  • Coordination of study functions, including travel and meeting arrangements, teleconferences, and site payment. 
  • Site initiating/training expertise.
  • Site monitoring.
  • Foster the use of innovative statistical methods for the design and implementation of multicenter clinical trials.
  • Provide educational opportunities to students and researchers at the KUMC regarding the design and analysis of multicenter clinical trials, through both formal and informal venues.
Accrual Prediction

Subject recruitment for medical research is challenging. Slow patient accrual leads to delays in research. Accrual monitoring during the process of recruitment is critical. We developed a Bayesian method that integrates researchers’ experience on previous trials and data from the current study to provide reliable prediction of the accrual rate for clinical studies. In this R package, we present functions for Bayesian accrual prediction which can be easily used by statisticians and clinical researchers.

  • Online tool:
  • R software ‘accrual’ package for download from the Comprehensive R Archive Network.
  • We also have webpage reports for all IITs in the KUCC and some outside of the KUCC.
  • Custom reports in CRIS can be built and automatically email to the study team.
  • KUCC Accrual Summary
  • KUCC Study Startup Tracker
Clinical Trial Design Studio

To foster collaboration and methodological developments in novel trial designs, we instituted the Fixed and Adaptive Clinical Trial Simulator Working Group in 2018. This group meets biweekly and is comprised of faculty, staff, and trainees with an interest in the application and development of methods/tools for novel clinical trial design and execution. The ultimate goal of this group is the development of novel clinical trial designs that result in trials that are smaller in size, stronger in statistical power, faster to conduct, and benefit more trial participants as compared to more traditional designs.

Design Papers

The leadership and faculty in our group have developed and applied new statistical methodologies for novel clinical trial designs. Some examples of these trials and published results can be found on the websites of the faculty listed below. Click the faculty member's name to see their individual profile.

For questions regarding the section, please contact:

Byron Gajewski, Ph.D. 
Professor, Department of Biostatistics & Data Science, co-Director, Biostatistics and Informatics Shared Resource, The University of Kansas Cancer Center

Milind Phadnis, Ph.D.
Associate Professor, Department of Biostatistics & Data Science, co-Leader (IITs)  Biostatistics and Informatics Shared Resource, The University of Kansas Cancer Center

Dinesh Pal Mudaranthakam, Ph.D. MBA
Assistant Professor, Department of Biostatistics & Data Science, co-Leader (Informatics & IITs), Biostatistics and Informatics Shared Resource, The University of Kansas Cancer Center, Department of Biostatistics & Data Science

Trials Operations Faculty

Lexie Brown, Ph.D.
Research Assistant Professor, Department of Biostatistics & Data Science

Kate Young, Ph.D.
Research Assistant Professor, Department of Biostatistics & Data Science

For analytical services, please submit your project or grant by filling out our Project Registration Form.

Project Registration Form

KU School of Medicine

University of Kansas Medical Center
Department of Biostatistics & Data Science
3901 Rainbow Boulevard
Mailstop 1026
Kansas City, KS 66160