Noninvasive wearable electroactive pharmaceutical monitoring for personalized therapeutics

Abstract

To achieve the mission of personalized medicine, centering on delivering the right drug to the right patient at the right dose, therapeutic drug monitoring solutions are necessary. In that regard, wearable biosensing technologies, capable of tracking drug pharmacokinetics in noninvasively retrievable biofluids (e.g., sweat), play a critical role, because they can be deployed at a large scale to monitor the individuals' drug transcourse profiles (semi)continuously and longitudinally. To this end, voltammetry-based sensing modalities are suitable, as in principle they can detect and quantify electroactive drugs on the basis of the target's redox signature. However, the target's redox signature in complex biofluid matrices can be confounded by the immediate biofouling effects and distorted/buried by the interfering voltammetric responses of endogenous electroactive species. Here, we devise a wearable voltammetric sensor development strategy-centering on engineering the molecule-surface interactions-to simultaneously mitigate biofouling and create an "undistorted potential window" within which the target drug's voltammetric response is dominant and interference is eliminated. To inform its clinical utility, our strategy was adopted to track the temporal profile of circulating acetaminophen (a widely used analgesic and antipyretic) in saliva and sweat, using a surface-modified boron-doped diamond sensing interface (cross-validated with laboratory-based assays, R2 ∼ 0.94). Through integration of the engineered sensing interface within a custom-developed smartwatch, and augmentation with a dedicated analytical framework (for redox peak extraction), we realized a wearable solution to seamlessly render drug readouts with minute-level temporal resolution. Leveraging this solution, we demonstrated the pharmacokinetic correlation and significance of sweat readings.

Keywords: personalized pharmacotherapy; pharmacokinetics; surface engineering; therapeutic drug monitoring; wearable sensors.

Conflict of interest statement

The authors declare no competing interest.

Figures

Fig. 1.

A fully integrated, wearable voltammetric drug monitoring solution: design rationale and application. (A) A voltammetric smartwatch, which can be applied to track the circulating drug’s pharmacokinetics (PK) by providing proxy readouts in noninvasively retrievable biofluids. (B) An illustrative exploded view of the smartwatch components (containing microfluidic housing, Nafion/H-BDDE sensor, signal processing/transmission circuitry, LCD screen, and battery units, all embedded within a 3D-printed case). (C) Seamless operational workflow of the devised wearable voltammetric drug monitoring solution, utilizing an engineered voltammetric sensing interface to create an undistorted potential window for target drug detection (in the presence of endogenous electroactive interferents).

Fig. 2.

Engineering a voltammetric sensing interface for APAP detection within a created undistorted potential window with a high biofouling resistance. (A–C) Characterization of the individual DPV response of the selected endogenous electroactive interferents and the target (with respect to the electrochemical background) using O-BDDE (A), H-BDDE (B), and Nafion/H-BDDE (C) sensors. (Upper) Twenty-five micromolar UA, 20 μM Tyr, 20 μM Trp. (Lower) Ten micromolar APAP. The interferents’ potential windows of influence (distorted windows) and the undistorted windows are annotated. (D–F) Characterization of the DPV response of the target in presence of interferents (all at the same concentration levels as stated above) using O-BDDE (D), H-BDDE (E), and Nafion/H-BDDE (F) sensors. (G–I) Sequentially recorded differential pulse voltammograms of a sweat sample (spiked with 10 μM APAP) on SPCE (G), H-BDDE (H), and Nafion/H-BDDE (I) interfaces. (J) Corresponding voltammetric peak current of the spiked-sweat measurements (extracted with the aid of the analytical framework). The values are normalized with respect to those obtained in the corresponding first rounds. (Inset) The schematic of biofouling.

Fig. 3.

Nafion/H-BDDE-enabled ex situ APAP quantification in noninvasively retrieved biofluid samples of (A, C, and E) saliva and (B, D, and F) sweat. (A and B) Differential pulse voltammograms of unspiked and spiked (with 1, 5, 10, 20, 40, 60, 80, and 100 μM APAP) saliva (A) and sweat (B) samples. (Insets) The corresponding analytical framework-extracted peak current. (C and D) Sensor-measured APAP concentration in the saliva (C) and sweat (D) samples of a human subject, collected before and at intermittent time points after the oral administration of a medication containing 650 mg APAP. (Insets) The schematics of saliva collection and iontophoresis-based sweat stimulation. (E and F) Sensor-measured APAP concentrations in saliva (E) and sweat (F) samples versus the corresponding LC-MS/MS readouts.

Fig. 4.

A Nafion/H-BDDE-enabled wearable solution for on-body pharmacokinetic monitoring. (A) System-level block diagram of the developed wearable solution, consisting of microfluidic, sensing, and electronic interfaces, and an analytical framework. The top-view photo of the Nafion/H-BDDE-based sensor illustrates the footprint of the working (3.6-mm diameter), counter, and reference electrodes (WE, CE, and RE) used. (B) Photo of the custom-developed wireless DPV readout circuit board, which integrates commercially available electronic components, including 1) an MCU, 2) a DAC, 3) a TIA, 4) an ADC, 5) a Bluetooth transceiver module, and 6) a thin-film-transistor LCD screen. (C) Sensor’s response to solutions with varying APAP concentration levels, where the APAP solutions were introduced by a continuous flow setup (Inset). Peak current values were extracted using the analytical framework. (D) The captured and processed differential pulse voltammograms of sweat (performed by the wearable solution), corresponding to four representative time points. (Top) Raw measurements and estimated baselines (Bottom). Baseline-corrected voltammograms to derive the APAP levels. (E) The measured APAP concentration levels in sweat and saliva versus time after oral administration of APAP. Each of the measurement series were fitted into a single-compartment pharmacokinetic model. (F) Schematic of the applied single-compartment model and the tabulated pharmacokinetic parameters, which were extracted from the APAP readouts shown in E.