Analytical, Diagnostic and Therapeutic Techniques and Equipment Commons^™

A Machine Learning Approach For Predicting Clinical Trial Patient Enrollment In Drug Development Portfolio Demand Planning, Ahmed Shoieb

Masters Theses

One of the biggest challenges the clinical research industry currently faces is the accurate forecasting of patient enrollment (namely if and when a clinical trial will achieve full enrollment), as the stochastic behavior of enrollment can significantly contribute to delays in the development of new drugs, increases in duration and costs of clinical trials, and the over- or under- estimation of clinical supply. This study proposes a Machine Learning model using a Fully Convolutional Network (FCN) that is trained on a dataset of 100,000 patient enrollment data points including patient age, patient gender, patient disease, investigational product, study phase, blinded …

Oncolytic Viruses: Cancer Treatment Going Viral, Rhianna N. Bronson

Chancellor’s Honors Program Projects

No abstract provided.

Joint Reaction Force And Contributions Of Surrounding Muscles To Knee Joint Load During Stair Ascent In Total Knee Replacement Patients And Healthy Individuals, Robert Jacob Rasnick

Masters Theses

Total knee replacement (TKR) is commonly used to correct end stage knee osteoarthritis (OA) of the knee joint. Unfortunately, difficulty with stair climbing has been seen to exist, prolonging the challenges of TKR patents. Complete understanding of loading at the knee is of great interest in order to aid patient populations, implant manufacturers, rehabilitation, and future research. The outcome of a TKR is intended to reestablish normal motion and loading of the knee. Musculoskeletal modeling provides a means to accurately approximate joint loading and the corresponding muscle contributions during a movement.

The purpose of the present study was to examine …

Control Of Inflammation In Pancreatic Β-Cells: Role Of Arylpyrazole Compounds, Whitney Lyn Powell

EURēCA: Exhibition of Undergraduate Research and Creative Achievement

No abstract provided.

Immunologic Risk Prediction Model For Kidney Graft Function, Christina Diane Bishop

Doctoral Dissertations

Clinicians lack appropriate non-invasive methods to be able to predict, diagnose, and reduce the risk of rejection in the years following kidney transplantation. Protocol biopsies and monitoring of serum creatinine levels are the most common methods of monitoring graft function after transplant; however, they have several negative aspects. Use of traditional factors regarding donors and recipients such as Human Leukocyte Antigen (HLA) DNA typing, pre-transplant anti-HLA antibody levels, and basic demographics (age, ethnicity/race, gender), has proved inadequate for post-transplant graft monitoring past the first few years. We propose that by utilizing immunologic factors available to clinicians across the United States, …

Development Of An Autonomous Mammalian Lux Reporter System, Daniel Michael Close

Doctoral Dissertations

Since its characterization, the definitive shortcoming of the bacterial luciferase (lux) bioluminescent reporter system has been its inability to express at a functional level in the eukaryotic cellular background. While recent developments have allowed for lux function in the lower eukaryote Saccharomyces cerevisiae, they have not provided for autonomous function in higher eukaryotes capable of serving as human biomedical proxies. Here it is reported for the first time that, through a process of poly-bicistronic expression of human codon-optimized lux genes, it is possible to autonomously produce a bioluminescent signal directly from mammalian cells. The low background of …