Improved drug development and disease diagnosis using tailored light-molecule interactions
Abstract/Contents
- Abstract
- Light-matter interactions are critical for many modern biomedical techniques, from fluorescence-based DNA sequencing to photoablation of tumors. Even so, existing optical diagnostic tools can be slow and existing drug treatments often have adverse side effects. Here, we explore two methods for improving drug purification and disease diagnosis based on tailored light-molecule interactions. First, I will discuss how the optical-frequency magnetic resonances of dielectric nanoparticles can be used to separate chiral molecules for enantiopure pharmaceuticals. Currently, half of pharmaceuticals on the market are chiral, but 90% of these are sold as mixtures since existing chemical methods are expensive and time consuming. Yet, the non-therapeutic enantiomer can reduce efficacy and lead to adverse side effects. Illumination with circularly polarized light provides a potentially cost-effective and versatile alternative but can due to the weak nature of chiral light-matter interactions. Using silicon nanospheres as a model system, I explore electromagnetic design parameters to enhance enantioselective light absorption in chiral molecules while maintaining total molecular absorption rates. With optimized particles, enhancements in the rates of enantioselective absorption can reach 7X, leading to a projected 50% increase in yield for the separation of the molecule camphor. Next, I will discuss how Raman spectroscopy can enable rapid identification of bacteria. I acquire Raman spectra from over 60,000 bacterial cells, spanning 30 strains from 22 species and covering 95% of all bacterial infections treated at Stanford Hospital. This large reference dataset allows us to apply machine learning techniques to accurately identify bacteria strains and antibiotic treatments. I show how this method translates to clinical patient samples, predicting treatment for 25 patient isolates with 99.0±1.9% accuracy. This work lays the foundation for a technique that could allow for accurate and targeted treatment of bacterial infections within hours, reducing healthcare costs and antibiotics misuse, limiting antimicrobial resistance, and improving patient outcomes.
Description
| Type of resource | text |
|---|---|
| Form | electronic resource; remote; computer; online resource |
| Extent | 1 online resource. |
| Place | California |
| Place | [Stanford, California] |
| Publisher | [Stanford University] |
| Copyright date | 2019; ©2019 |
| Publication date | 2019; 2019 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Ho, Chi-Sing |
|---|---|
| Degree supervisor | Brongersma, Mark L |
| Degree supervisor | Dionne, Jennifer Anne |
| Thesis advisor | Brongersma, Mark L |
| Thesis advisor | Dionne, Jennifer Anne |
| Thesis advisor | Banaei, Niaz |
| Degree committee member | Banaei, Niaz |
| Associated with | Stanford University, Department of Applied Physics. |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Chi-Sing Ho. |
|---|---|
| Note | Submitted to the Department of Applied Physics. |
| Thesis | Thesis Ph.D. Stanford University 2019. |
| Location | electronic resource |
Access conditions
- Copyright
- © 2019 by Chi-Sing Ho
- License
- This work is licensed under a Creative Commons Attribution Non Commercial 3.0 Unported license (CC BY-NC).
Also listed in
Loading usage metrics...