Proceedings of the National Academy of Sciences

A wearable patch for continuous levodopa monitoring in sweat: Towards exertion and power-free pharmacodynamic assessment in Parkinson’s disease

T Tamoghna Saha (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) M Muhammad Inam Khan (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) K Katherine Longardner (Department of Neurosciences, University of California, San Diego) B Barak Sabbagh (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) K Kaiwen Zheng H Hugo de Mendoza (Department of Mechanical Engineering, University of California, San Diego) G Gaoyuan Ji (Department of Electrical and Computer Engineering, University of California, San Diego) B Bumsik Choi (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) Z Zongnan Wang (Department of Mechanical Engineering, University of California, San Diego) R Rosie Pham (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) M Michael Skipworth (Department of Neurosciences, University of California, San Diego) E Eshita Shah (Department of Electrical and Computer Engineering, University of California, San Diego) M Maria Reynoso (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) C Chochanon Moonla (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) A Abdulhameed Abdal (Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0448, United States) D Debika Datta (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) S Samar Singh Sandhu (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) P Ponnusamy Nandhakumar (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) A Artur Jedrzak (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) S Shichao Ding (Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego) L Lu Yin (Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education) of the Second Affiliated Hospital and Institute of Translational Medicine, Zhejiang University School of Medicine) I Irene Litvan (Department of Neurosciences, University of California, San Diego) J Joseph Wang (Aiiso Yufeng Li Family Department of Chemical and Nano Engineering)

Abstract

Precision management of Parkinson’s disease (PD) requires frequent levodopa (L-dopa) dose adjustments, yet current monitoring relies on subjective symptom reporting and infrequent blood testing. Here, we present a soft, fingertip-mounted wearable platform for continuous, noninvasive L-dopa monitoring. By combining osmotically harvested passive sweat with soft hydrogels, a potentiometric sensing strategy, and individualized calibration, the platform estimates blood L-dopa information from sweat without external power or iontophoresis. Strong correlations between sweat and high-performance liquid chromatography (HPLC)-measured blood L-dopa concentrations were observed in healthy ( P r = 0.85 ) and PD subjects ( P r = 0.88 ) following a single immediate-release L-dopa/carbidopa dose. Low motor symptom scores aligned with peak L-dopa levels, confirming pharmacodynamic relevance. L-dopa cleared faster in PD patients despite similar bioavailability to healthy subjects, while recorded hemodynamic responses showed short hypotensive trends for both groups. Machine learning identified sweat and blood pressure as key contributors toward accurate estimation of blood L-dopa levels (mean absolute error = 2.02 µM vs. ground truth). Overall, our easy-to-use, energy-efficient wearable supports real-time, stimulation-free monitoring, potentially enabling at-home dosage adjustments and paving the way for future autonomous closed-loop L-dopa therapeutic system development.

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Article Details

Volume / Issue Vol. 123, Issue 32
Published August 11, 2026
ISSN 0027-8424
Publisher National Academy of Sciences

Journal Info

Proceedings of the National Academy of Sciences

National Academy of Sciences
ISSN: 0027-8424 Life Sciences

Authors (23)

T

Tamoghna Saha

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

M

Muhammad Inam Khan

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

K

Katherine Longardner

Department of Neurosciences, University of California, San Diego

B

Barak Sabbagh

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

K

Kaiwen Zheng

H

Hugo de Mendoza

Department of Mechanical Engineering, University of California, San Diego

G

Gaoyuan Ji

Department of Electrical and Computer Engineering, University of California, San Diego

B

Bumsik Choi

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

Z

Zongnan Wang

Department of Mechanical Engineering, University of California, San Diego

R

Rosie Pham

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

M

Michael Skipworth

Department of Neurosciences, University of California, San Diego

E

Eshita Shah

Department of Electrical and Computer Engineering, University of California, San Diego

M

Maria Reynoso

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

C

Chochanon Moonla

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

A

Abdulhameed Abdal

Aiiso Yufeng Li Family Department of Chemical and Nano Engineering, University of California, San Diego, 9500 Gilman Drive, La Jolla, California 92093-0448, United States

D

Debika Datta

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

S

Samar Singh Sandhu

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

P

Ponnusamy Nandhakumar

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

A

Artur Jedrzak

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

S

Shichao Ding

Aiiso Yufeng Li Family Department of Chemical and Nanoengineering, University of California, San Diego

L

Lu Yin

Cancer Institute (Key Laboratory of Cancer Prevention and Intervention, China National Ministry of Education) of the Second Affiliated Hospital and Institute of Translational Medicine, Zhejiang University School of Medicine

I

Irene Litvan

Department of Neurosciences, University of California, San Diego

J

Joseph Wang

Aiiso Yufeng Li Family Department of Chemical and Nano Engineering

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