Precision Injection-Compression Molding and Functional Integration of Hollow Microneedle Microfluidic Chips for Minimally Invasive Continuous Health Monitoring.

Authors

Baishun Zhao, Dimitrios Kontziampasis, Mingyong Zhou, Wangqing Wu, Zhiyu Yang, Bingyan Jiang, Dou Zhang

Published in

Small (Weinheim an der Bergstrasse, Germany). Pages e76125. Oct 09, 2026. Epub Oct 09, 2026.

Abstract

Real-time biomarker monitoring through interstitial fluid (ISF) sampling using hollow microneedle (HMN) arrays is crucial for personalized precision medicine and chronic disease management. However, clinical translation faces a critical bottleneck: the absence of stable, cost-effective, scalable high-precision manufacturing technologies. This work systematically establishes a comprehensive end-to-end solution encompassing precise molding and functional integration. We employed injection-compression molding with multi-objective optimization algorithms to elucidate relationships between critical process parameters and HMN array molding quality. The results demonstrate that positioning the HMN array at the far-gate locations enhances filling quality and reduces core-pin impact force by 15%, revealing the underlying physical mechanisms governed by shear heating effects and pressure transmission dynamics, which enriches conventional micro-injection molding theory. The optimized process achieves >6.8% filling ratio improvement and 10% injection pressure reduction. Furthermore, we established a complete design and fabrication workflow for ISF extraction chips, developed patterned microelectrode bonding technology for complex microchannel sealing, and validated in situ detection platform advantages. In vitro testing validated safe and efficient ISF extraction with a 95% success rate while maintaining exceptional portability for wearable health monitoring applications. This work provides theoretical and practical guidance for scalable HMN manufacturing, establishing a foundation for commercializing next-generation continuous health monitoring systems.

PMID:
42852944
Bibliographic data and abstract were imported from PubMed on 09 Oct 2026.

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