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CCTS calls for abstracts and mentor award nominations for 2026 Spring Conference

The UK CCTS will hold its 21st annual Spring Conference on March 31, 2026. Abstract submissions and nominations for mentor awards are now open.

Translational Engineering Technology for Women’s Health Applications

Female reproductive and gynecologic health are historically understudied fields that would significantly benefit from engineering expertise due to the unique biomechanical environment in the female reproductive tract and the dynamic tissue changes orchestrated throughout the menstrual cycle by sex hormones. With the synergistic techniques of tissue engineering, biomaterials science, biomechanics, and reproductive biology, we engineer models of the female reproductive system and female lower urinary tract, including the endometrium, decidua, vagina, and bladder.

How Much More Data Do I Need? Interim Sample Size Re-estimation

Presented by:   Sergey Tarima, PhD   Associate Professor   Department of Biostatistics   University of Kentucky   

2026 CCTS Spring Conference

Visit the 2026 CCTS Spring Conference Page

Call for Abstracts: 2026 CCTS Spring Conference

The UK Center for Clinical and Translational Science is accepting abstracts for oral and poster presentations at its 2026 Spring Conference, which will be held on Tuesday, March 31.

Updated Eligibility Criteria for UK Reliance Agreements

UK is updating Reliance Agreement eligibility criteria for multi-site research to be reviewed and approved by a single IRB, to also include non-federally funded research conducted at multiple sites under the same research protocol.

Advancing a Novel Bloodborne Infection and Drug Supply Surveillance System through a Translational Science Collaboration

Presenters:Hilary L. Surratt, PhDProfessor, Behavioral Science   Kristen McLaurin, PhDAssistant Professor, Pharmaceutical Sciences

Dose Selection Balancing Efficacy and Toxicity Using Bayesian Model Averaging (BMA)

Presenter:A. Lawrence Gould, PhDMERCK & Co.

Vision Foundry: A System for Training Foundational Vision AI Models

Objective This presentation introduces Vision Foundry, a platform that enables researchers to train and customize foundational vision AI models using their own imaging data. We will explore how this capability empowers new forms of discovery, analysis, and collaboration in medical and bioinformatics research. Presented by