Photochemical Sciences Ph.D. Dissertations

Title

Implementation of High Throughput Screening Strategies in Optical Sensing for Pharmaceutical Engineering

Date of Award

2017

Document Type

Dissertation

Degree Name

Doctor of Philosophy (Ph.D.)

Department

Photochemical Sciences

First Advisor

Pavel Anzenbacher (Advisor)

Second Advisor

Alexis Dee Ostrowski (Committee Member)

Third Advisor

R. Marshall Wilson (Committee Member)

Fourth Advisor

Ernesto E. Delgado (Committee Member)

Abstract

Modern molecular sensors are essential parts of many emerging medical technologies and have been utilized in reducing healthcare costs in developed countries, environmental monitoring, disease diagnosis, and in increasing the response of the world to pandemics or bioterrorism. Due to the rapidly developing fields of supramolecular chemistry and optical detection, new sensing approaches have been developed for the recognition of many essential molecules in aqueous solutions and biologicals fluids. Particularly, the emergence of fluorescent molecular sensors has opened up a direction for the evolution of differential sensing in the nanometric scale, something of which traditional electronic sensors were not capable. In this dissertation, we present the development and application of sensing approaches aimed at two types of chemical problems.

Part of this dissertation focuses on the development of a high-throughput protocol using molecular self-assemblies for the recognition of chiral drugs and drug-related compounds that play an important role in pharmacology, toxicology, and pharmacokinetics. Chiral drug separation is now a central subject for pharmaceutical development and clinical therapeutics due to the advancement of asymmetric synthesis in the production of single enantiomer drugs or precursors with greater therapeutic benefits and low toxicity.

The second topic describes the development of an optical assay aimed at detecting opioids in complex biological environments. Opioids and their synthetic analogues have been the cause of many accidental deaths across the world. We develop an optical assay that is simple, computationally robust, efficient and can detect low concentrations of opioids in complex media. This high-throughput sensor array is capable of sensing opiates and their metabolites in urine when mixed with other chemical agents. Moreover, it is capable via machine learning techniques of recognizing new opiate-related compounds, which opens opportunities in the development of new treatments for the opioid epidemic.

Our work is a scientific contribution, merging concepts of chemistry and chemical engineering to balance molecular sensor development and minimal resource utilization.

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