Author ORCID Identifier

https://orcid.org/0000-0002-3572-9374

Date Available

10-15-2018

Year of Publication

2018

Degree Name

Doctor of Philosophy (PhD)

Document Type

Doctoral Dissertation

College

Pharmacy

Department/School/Program

Pharmaceutical Sciences

First Advisor

Dr. Robert A. Lodder

Abstract

QBEST, a novel statistical method, can be applied to the problem of estimating the No Observed Adverse Effect Level (NOAEL or QNOAEL) of a New Molecular Entity (NME) in order to anticipate a safe starting dose for beginning clinical trials. The NOAEL from QBEST (called the QNOAEL) can be calculated using multiple disparate studies in the literature and/or from the lab. The QNOAEL is similar in some ways to the Benchmark Dose Method (BMD) used widely in toxicological research, but is superior to the BMD in some ways. The QNOAEL simulation generates an intuitive curve that is comparable to the dose-response curve. The NOAEL of ellagic acid (EA) is calculated for clinical trials as a component therapeutic agent (in BSN476) for treating Chikungunya infections. Results are used in a simulation based on nonparametric cluster analysis methods to calculate confidence levels on the difference between the Effect and the No Effect studies. In order to evaluate the statistical power of the algorithm, simulated data clusters with known parameters are fed into the algorithm in a separate study, testing the algorithm’s accuracy and precision “Around the Compass Rose” at known coordinates along the circumference of a multidimensional data cluster. The specific aims of the proposed study are to evaluate the accuracy and precision of the QBEST Simulation and QNOAEL compared to the Benchmark Dose Method, and to calculate the QNOAEL of EA for BSN476 Drug Development.

Digital Object Identifier (DOI)

https://doi.org/10.13023/etd.2018.394

Funding Information

Funding provided by the PhRMA Foundation, Grant 3048113957.

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