DOI: 10.5281/zenodo.10402431
title: Analytical Validation of Aptamer-Based Serum Vancomycin Monitoring Relative to Automated Immunoassays

description: ***ABSTRACT***

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The practice of monitoring therapeutic drug concentrations in patient biofluids can significantly improve clinical outcomes while simultaneously minimizing adverse side effects. A model example of this practice is vancomycin dosing in intensive care units. If dosed correctly, vancomycin can effectively treat methicillin-resistant staphylococcus aureus (MRSA) infections. However, it can also induce nephrotoxicity or fail to kill the bacteria if dosed too high or low, respectively. Although undeniably important to achieve effectiveness, therapeutic drug monitoring remains inconvenient in practice, due primarily to the lengthy process of sample collection, transport to a centralized facility, and analysis using costly instrumentation. Adding to this workflow is the possibility of backlogs at centralized clinical laboratories, which is not uncommon and may result in additional delays between biofluid sampling and concentration measurement, which can negatively affect clinical outcomes. Here we explore the possibility of using point-of-care, electrochemical aptamer-based (E-AB) sensors to minimize the time delay between biofluid sampling and drug measurement. Specifically, we conducted a clinical agreement study comparing the measurement outcomes of E-AB sensors to the benchmark automated competitive immunoassays for vancomycin monitoring in serum. Our results demonstrate that E-ABs are selective for free vancomycin—the active form of the drug—over total vancomycin. In contrast, competitive immunoassays measure total vancomycin, including both protein-bound and free drug. Accounting for these differences in a pilot study consisting of 85 clinical samples, we demonstrate that the E-AB vancomycin measurement achieved a 95% positive correlation rate with the benchmark immunoassays. Therefore, we conclude that E-AB sensors could provide clinically useful stratification of patient samples at trough sampling to guide effective vancomycin dose recommendations.

 

***README FILE ***

_________________________

Project: Analytical Validation of Aptamer-Based Serum Vancomycin Monitoring Relative to Automated Immunoassays

Date Accepted: December 5th, 2023

DOI: 

Contact: Netz Arroyo, netzarroyo@jhmi.edu

 

ORGANIZATION

 

All files in this repository are sorted based on their corresponding figure in the associated manuscript

and supplementary information document (both found at DOI above). Organization and files found in each figure folder 

are as follows:

 

- 'Figure_1':

- Final .svg image for Figure 1.

 

- 'Figure_2':

-"Figure_2.png"

- PNG image of Figure 2. Figure panels were generated as detailed in the following entries. Figure was compiled in Adobe Illustrator. 

-"swv trace.svg"

- SVG file for Panel C. Generated using Igor Pro v8 from data in file "SWV Traces.pxp".

-"ON&OFF.svg"

- SVG file for Panel D . Generated using Igor Pro v8 from data in file "Signal ON&OFF.pxp". 

-"ratio box whisker plot.svg"

- SVG file for Panel E. Generated using Igor Pro v8.  

-"calibration.svg"

- SVG file for Panel F. Generated using Igor Pro v8. 

-Data:  "SWV Traces.xlsx"

"SWV Traces.csv"

"SWV Traces.pxp" 

Data was obtained from sheet "SWV curves" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. Data in all files are identical, except for file format.

-Data:  "Signal ON&OFF.xlsx"

"Signal ON&OFF.csv"

"Signal ON&OFF.pxp" 

Data was obtained from sheet "signal-on&signal-off" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. Data in all files are identical, except for file format. Regression to the Hill equation

was performed in Igor Pro v8, constraining rate=1.

-Data:  "Dose response curve box plot.xlsx"

"Dose response curve box plot.csv"

"Dose response curve box plot.pxp" 

Data was obtained from sheet "Curve fitting_Ratio(SUM_MEA)" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. Data in all files are identical, except for file format. Box and whisker plot was generated using

Igor Pro v8.

-Data:  "Day1-Day6 Dose Response Curve.xlsx"

"Day1-Day6 Dose Response Curve.csv"

"Day1-Day6 Dose Response Curve.pxp" 

Data was obtained from sheet "Curve fitting_Ratio(SUM_MEA)" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. Data in all files are identical, except for file format. Nonlinear regression to the Hill equation

was generated using Igor Pro v8. No variables were constrained.

 

-'Figure_3':

- DATA FOR FIGURE 3 WAS OBTAINED FROM THE "Ratiometric response" SHEET OF THE FILE "Confidential_ZiO Health Stability Test Data" RECIEVED 12:08, NOVEMBER 8 2023, FROM FRANCESCA NAPOLI.

- DATA FROM FIELDS "Average response to 12.5 mg/L  for chips tested in specific week" AND "SD response to 12.5 mg/L  for chips tested in specific week" (ROWS 39 AND 40) , WITH ASSOCIATED TIMEPOINT IDENTIFIERS, WERE EXTRACTED AND USED AS RECIEVED

- IN ROWS 41 AND 42, DATA FROM THE 0.1 MG/L CONCENTRATION POINT (ROW 13) WAS EXCTRACTED AND PROCESSED IN THE SAME WAY AS "Average response to 12.5 mg/L  for chips tested in specific week" AND "SD response to 12.5 mg/L  for chips tested in specific week" (I.E, AVERAGE AND STANDARD DEVIATION OF THREE OR FOUR CHIPS PER WEEK)

- TIMEPOINT IDENTIFIERS WERE CONVERTED TO NUMERIC AND GIVEN THE TITLE "Time" and UNIT "Weeks"

- FIELD "Average response to 12.5 mg/L  for chips tested in specific week" WAS TITLED "12.5 mg/L Sensor response ratio" AND GIVEN UNIT "360Hz/20Hz"

- FIELD "SD response to 12.5 mg/L  for chips tested in specific week" WAS TITLED "12.5 mg/L SD" AND GIVEN UNIT "360Hz/20Hz"

- THE SAME WAS DONE FOR THE 0.1 MG/l CONCENTRATION DATA

- DATA FILE USED FOR MAKING THE FIGURE IS "2023_11_08_Chip_Stability.pxp"

- BOTH O.1 MG/L AND 12.5 MG/L WERE SUBJECTED TO LINEAR REGRESSION ANALYSIS IN IGOR V8

 

-'Figure_4':

- Final PNG image for Figure 4.

 

-'Figure_5':

- "2023_11_07_Fig5.png"

- Final .PNG file used for Figure 5. Panels were arranged and Mean/StDev numbers were added in Adobe Illustrator.

- "EAB_diff.svg"

-.svg file used for panel A of Figure 5. Generated in Igor v8.

- "EAB_pct_aveplot.svg"

-.svg file used for panel C of Figure 5. Generated in Igor v8.

- "ImA_diff.svg"

-.svg file used for panel B of Figure 5. Generated in Igor v8.

- "ImA_pct_aveplot.svg"

-.svg file used for panel D of Figure 5. Generated in Igor v8.

- Data: "2023_07_10_Differentials.xlsx"

"2023_07_10_Differentials.csv"

"2023_07_10_Differentials.pxp"

Data was obtained from sheet "Predict con.c" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. 

-'Figure_6':

- "2023_07_12_Fig6.png"

- Final .PNG file used for Figure 6. Panels were arranged and statistics valued added in Adobe Illustrator.

- "serum.svg"

-.svg file used for panel A of Figure 5. Generated in Igor v8 from Table 0.

- "Filtrate smaller points.svg"

-.svg file used for panel C of Figure 5. Generated in Igor v8 from Graph 0.

- "Filtrate_insert.svg"

-.svg file used for panel B of Figure 5. Generated in Igor v8 from Graph 5.

- "Bland-Altman.svg"

-.svg file used for panel D of Figure 5. Generated in Igor v8 from Graph 1.

- "Bland-Altman insert.svg"

-.svg file used for panel D of Figure 5. Generated in Igor v8 from Graph 1.

- "Rplot0_png.png"

-.png file of Bangdiwala plot. Generated in Rstudio by code mentioned below.

- "Agreement plot code.txt"

-Code used to generate Bangdiwala agreement plot using Rstudio. 

- Data: "Concentrations_all.xlsx"

"Concentrations_all.csv"

Data was obtained from sheet "Predict con.c" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. 

- Data: "Bland-Altman.xlsx"

"Bland-Altman.csv"

Data was obtained from sheet "Bland–Altman Plot" of Excel file "ZiO-JHU_March 2023_Data processing Updates" recieved 10:37 EST, June 2 2023, from Yu Liu. 

Data was used as recieved, and imported to Igor Pro v8 for plotting. 

- Data: "ROC-input data for agreement plot.xlsx"

"ROC-input data for agreement plot.csv"

Data was recieved 12:30 EST, December 7 2023, from Francesca Napoli.

- Data: "Fig6.pxp"

Table 0: all samples from "Concentrations_all.xlsx"

Table 1: average and difference values for EA-B filtrate samples vs immunoassay filtrate samples from "Bland-Altman.xlsx", as well as upper and lower 95% CI boundaries

Table 2: samples sorted by concentration and filtered by immunoassay values <15mg/L and <10mg/L.

Graph 0: plot of immunoassay vs E-AB serum concentration values from Table 0.

Graph 1: plot of immunoassay vs E-AB filtrate concentration values from Table 0.

Graph 2: plot of average vs difference values from Tablel 1.

Graph 4: plot of filtered immunoassay vs E-AB filtrate concentration values <10mg/L from Table 3.

Graph 5: plot of filtered immunoassay vs E-AB filtrate concentration values <15mg/L from Table 3.

 

 

NOTES

 

(1) Raw voltammetry data is the property of ZiO Health, and is therefore not available for public release. All data presented here were extracted from raw voltammetric traces by ZiO Health,

and transfered to the Arroyo lab for further analysis. 

 

(2) RStudio is available at: https://posit.co/products/open-source/rstudio/

 

(3) Igor Pro is available at: https://www.wavemetrics.com/