Giant magnetoresistive biosensors for point-of-care and personalized pain medicine
Abstract/Contents
- Abstract
- Currently, there is an opioid epidemic sweeping the United States of America, as well as many countries around the world, resulting in more annual opioid overdose deaths in the USA than deaths from firearms or automobile accidents. One common pathway for opioids entering the hands of opioid naïve individuals is through the prescription of opioids for postoperative pain management, which can develop into opioid misuse and chronic opioid use. Recent advances in point-of-care (POC) technologies offer an opportunity to combat the epidemic through innovations in pain medicine, reducing the need for prescription opioids through the careful management of pain pre- and post- operatively. Using versatile and multiplexable giant magnetoresistive biosensor arrays, we demonstrate two tools which can enable clinicians to proactively optimize opioid delivery postoperatively through POC opioid monitoring and reduce opioid use through targeted referrals for non-pharmacological adjuvant treatments like hypnosis. The first tool demonstrates that giant magnetoresistive (GMR) nanosensors offer a quantitative, sensitive, and rapid solution for low-cost, sample-to-answer opioid detection at the POC. We utilized the robust nature of GMR nanosensors by developing a competitive morphine assay and characterizing it in saliva, blood, and plasma. We then implemented the assay on a fully automated POC GMR platform and demonstrated its duality to detect either morphine or hydromorphone using only 180μl of direct saliva without the need for pre-processing. The second tool developed in this work addresses the need for targeted hypnosis referrals for pain treatment, known as hypnotic analgesia. Through our work, inexpensive genotyping of 4 single nucleotide polymorphisms (SNPs) in the catechol-o-methyltransferase (COMT) gene was performed using giant magnetoresistive biosensors to determine if hypnotizable individuals can be identified for targeted hypnosis referrals. We show that this tool is 100% accurate compared with pyrosequencing, and we use it to genotype three cohorts of patient samples involved in hypnosis studies. Using this same 4-SNP COMT genotyping tool, we then investigated phenotypes of hypnotizability, which may modulate the benefit of hypnosis treatments due to the heterogeneity of experience of hypnosis between individuals. We propose this heterogeneity is underpinned by limitations in the mechanistic understanding of variants of hypnotizability phenotypes, and we investigate if genetic differences in COMT activity is a mechanism for the divergence of hypnotizability phenotypes via cognitive-behavioral assessments in an exploratory study. These results together suggest that optimal COMT diplotypes may be associated with the inwardly attentive phenotype of hypnotizability, and that the 4-SNP COMT GMR assay may be able to be used to differentiate the two phenotypes of hypnotizability. Finally, we demonstrate how the 4-SNP COMT genotyping assay can be translated to the POC in two different formats.
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 | 2022; ©2022 |
| Publication date | 2022; 2022 |
| Issuance | monographic |
| Language | English |
Creators/Contributors
| Author | Cortade, Dana Lee |
|---|---|
| Degree supervisor | Wang, Shan X |
| Thesis advisor | Wang, Shan X |
| Thesis advisor | Hong, Guosong |
| Thesis advisor | Spiegel, David, 1945- |
| Degree committee member | Hong, Guosong |
| Degree committee member | Spiegel, David, 1945- |
| Associated with | Stanford University, Department of Materials Science and Engineering |
Subjects
| Genre | Theses |
|---|---|
| Genre | Text |
Bibliographic information
| Statement of responsibility | Dana Lee Cortade. |
|---|---|
| Note | Submitted to the Department of Materials Science and Engineering. |
| Thesis | Thesis Ph.D. Stanford University 2022. |
| Location | https://purl.stanford.edu/bf611mb8825 |
Access conditions
- Copyright
- © 2022 by Dana Lee Cortade
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