Multivariate Analysis Commons^™

Efficient Development Of Density-Insensitive Near-Infrared Methods For In-Line Drug Content Monitoring In Continuous Powder Streams, Natasha L. Velez-Silva

Electronic Theses and Dissertations

A well-defined action plan to respond effectively to sudden changes in product demand is critical for preventing drug shortages within the pharmaceutical industry. An effective way to increase the output of a continuous manufacturing (CM) process is through flow rate adjustments. However, robust analytical methods must be in place to ensure consistent analytical performance across varying flow rates. Existing approaches for mitigating the physical effects of flow rate on Near-Infrared (NIR) measurements are often burdensome. Thus, efficient robust modeling strategies that reduce the current calibration burden and ensure model insensitivity to the physical variations in CM systems are needed. In …

Advancement Of Iterative Optimization Technology Algorithms Toward Calibration-Free Process Analytical Technology Applications, Adam Rish

Electronic Theses and Dissertations

The expansion of spectroscopic process analytical technology (PAT) tools within the pharmaceutical industry has the potential to elevate the current state-of-the-art of pharmaceutical manufacturing by offering opportunities for reduced quality testing times, enhanced process control, and greater production flexibility. Spectroscopic PAT tools are dependent on multivariate models to extract the relevant information from the spectral outputs. However, there is a substantial calibration burden for developing and maintaining these multivariate models that discourages the application of PAT, despite the encouragement from regulators. This has led to an interest in calibration-free methods such as iterative optimization technology (IOT) for spectroscopic PAT that …

Identifying Risk Factors Related To Premature Birth Through Binary Logistic And Proportional Odds Ordinal Logistic Regression, Clayton Elwood

Electronic Theses and Dissertations

Premature birth has been identified as the single greatest cause of death worldwide in children under the age of five. This thesis will implement binary logistic regression and proportional odds ordinal logistic regression to predict different levels of premature birth and identify associated risk factors. The models will be built from the Center for Disease Control and Prevention's 2014 Vital Statistics Natality Birth Data containing nearly 4 million live births within the United States. Odds ratios and confidence intervals on risk factors were produced utilizing binary logistic regression.

Designing A Calibration Set In Spectral Space For Efficient Development Of An Nir Method For Tablet Analysis, Md Anik Alam

Electronic Theses and Dissertations

Designing a calibration set is the first step in developing a spectroscopic calibration method for quantitative analysis of pharmaceutical tablets. This step is critical because successful model development depends on the suitability of the calibration data. For spectroscopic-based methods, traditional concentration based techniques for designing calibration sets are prone to have redundant information while simultaneously lacking necessary information for a successful calibration model. The traditional method also follows the same design approach for different spectroscopic techniques and different formulations, thereby lacks the optimizing capability to be technique and formulation specific.

A method for designing a calibration set in the Near …