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Annual Review of Biomedical Engineering

Volume 27, 2025

Lessons Learned and Challenges Ahead in the Translation of Implantable Microscale Sensors and Actuators

  • Jae Young Park1,2,3, Nikolas Barrera4, Tianyu Bai5, Ellis Meng4,6, Hui Fang5 and Hyowon Lee1,2,3
  • 1Weldon School of Biomedical Engineering, Purdue University, West Lafayette, Indiana, USA; email: [email protected] 2Center for Implantable Devices, Purdue University, West Lafayette, Indiana, USA 3Birck Nanotechnology Center, Purdue University, West Lafayette, Indiana, USA 4Alfred E. Mann Department of Biomedical Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA; email: [email protected] 5Thayer School of Engineering, Dartmouth College, Hanover, New Hampshire, USA; email: [email protected] 6Ming Hsieh Department of Electrical and Computer Engineering, Viterbi School of Engineering, University of Southern California, Los Angeles, California, USA
  • Vol. 27:211-233 (Volume publication date May 2025)
  • First published as a Review in Advance on February 06, 2025
  • Copyright © 2025 by the author(s).
    This work is licensed under a Creative Commons Attribution 4.0 International License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. See credit lines of images or other third-party material in this article for license information.

Abstract

Microscale sensors and actuators have been widely explored by the scientific community to augment the functionality of conventional medical implants. However, despite the many innovative concepts proposed, a negligible fraction has successfully made the leap from concept to clinical translation. This shortfall is primarily due to the considerable disparity between academic research prototypes and market-ready products. As such, it is critically important to examine the lessons learned in successful commercialization efforts to inform early-stage translational research efforts. Here, we review the regulatory prerequisites for market approval and provide a comprehensive analysis of commercially available microimplants from a device design perspective. Our objective is to illuminate both the technological advances underlying successfully commercialized devices and the key takeaways from the commercialization process, thereby facilitating a smoother pathway from academic research to clinical impact.

Keyword(s): biosensor, drug delivery system, implantable microdevice, microcatheter, microstent, neural interface, translational research
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2025-05-01
2025-06-21
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Literature Cited

  1. 1.
    Mordor Intell. 2024.. Medical implants market size & share analysis—growth trends & forecasts (2024–2029). Rep. , Mordor Intell., Hyderabad, India:
     [Google Scholar]
  2. 2.
    Food Drug Admin. (FDA). 2017.. Classification of products as drugs and devices & additional product classification issues: guidance for industry and FDA staff. Rep. , FDA, Silver Spring, MD:
     [Google Scholar]
  3. 3.
    Food Drug Admin. (FDA). 2020.. Overview of device regulation. . US Food & Drug Administration. https://www.fda.gov/medical-devices/device-advice-comprehensive-regulatory-assistance/overview-device-regulation
    [Google Scholar]
  4. 4.
    Natl. Arch. 2024.. Part 58—good laboratory practice for nonclinical laboratory studies. . Code of Federal Regulations. https://www.ecfr.gov/current/title-21/chapter-I/subchapter-A/part-58
    [Google Scholar]
  5. 5.
    Food Drug Admin. (FDA). 2018.. Product classification. Database, US Food & Drug Admin., Silver Spring, MD:. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfpcd/classification.cfm
    [Google Scholar]
  6. 6.
    Kustas A, Pandya S. 2015.. Regulatory affairs: how understanding the current FDA processes will shape the future of your medical device. Rep. , CMC Consult. Group, Munich, Germany:
     [Google Scholar]
  7. 7.
    Food Drug Admin. (FDA). 2023.. Breakthrough devices program. . US Food & Drug Administration. https://www.fda.gov/medical-devices/how-study-and-market-your-device/breakthrough-devices-program
    [Google Scholar]
  8. 8.
    Food Drug Admin. (FDA). 2022.. Humanitarian device exemption. . US Food & Drug Administration. https://www.fda.gov/medical-devices/premarket-submissions-selecting-and-preparing-correct-submission/humanitarian-device-exemption
    [Google Scholar]
  9. 9.
    Malvehy J, Ginsberg R, Sampietro-Colom L, Ficapal J, Combalia M, Svedenhag P. 2022.. New regulation of medical devices in the EU: impact in dermatology. . J. Eur. Acad. Dermatol. Venereol. 36:(3):360–64
     [Crossref] [Google Scholar]
  10. 10.
    Food Drug Admin. (FDA). 2021.. FDA Summary of Safety and Effectiveness Data (SSED). Rep. PMA P200021 , FDA, Silver Spring, MD:. . https://www.accessdata.fda.gov/cdrh_docs/pdf20/P200021B.pdf
    [Google Scholar]
  11. 11.
    Barchowsky A. 2020.. Systemic and immune toxicity of implanted materials. . In Biomaterials Science: An Introduction to Materials in Medicine, pp. 791–99. New York: Cambridge, MA:: Academic Press. , 4th ed..
     [Google Scholar]
  12. 12.
    Cent. Devices Radiol. Health, Cent. Biol. Eval. Res. 2023.. Use of International Standard ISO 10993-1, “Biological evaluation of medical devices—part 1: evaluation and testing within a risk management process.” Guid. Doc., US Food & Drug Admin., Silver Spring, MD:
     [Google Scholar]
  13. 13.
    Int. Electrotech. Comm. 2024.. Medical electrical equipment—all parts. IEC 60601–1:2024 SER Series. Int. Stand., IEC, Geneva:. https://webstore.iec.ch/en/publication/2603
    [Google Scholar]
  14. 14.
    Int. Electrotech. Comm. 2016.. Electromagnetic compatibility (EMC)—part 4-1: testing and measurement techniques—overview of IEC 61000-4 series. Tech. Rep. 61000-4-1 , IEC, Geneva:. https://webstore.iec.ch/en/publication/24660
    [Google Scholar]
  15. 15.
    Int. Electrotech. Comm. 2024.. Environmental testing—part 2: tests—all parts. IEC 60068-2:2024 SER Series. Int. Stand., IEC, Geneva:. https://webstore.iec.ch/en/publication/62437
    [Google Scholar]
  16. 16.
    Int. Org. Stand. (ISO). 2014.. Implants for surgery—active implantable medical devices—part 1: general requirements for safety, marking and for information to be provided by the manufacturer. ISO 14708-1:2014. Int. Stand., ISO, Geneva:. https://www.iso.org/standard/52804.html
    [Google Scholar]
  17. 17.
    Br. Stand. Inst. (BSI). 2024.. Multi-part document BS EN 45502-2—active implantable medical devices. Stand., BSI, London:. https://doi.org/10.3403/BSEN45502-2
    [Google Scholar]
  18. 18.
    Am. Natl. Stand. Inst. 2017.. Cochlear implant systems: requirements for safety, functional verification, labeling and reliability reporting. ANSI/AAMI CI86:2017. Stand., ANSI, New York:. https://webstore.ansi.org/standards/aami/ansiaamici862017
    [Google Scholar]
  19. 19.
    Stijnman PRS, Steensma BR, van den Berg CAT, Raaijmakers AJE. 2022.. A perturbation approach for ultrafast calculation of RF field enhancements near medical implants in MRI. . Sci Rep. 12:(1):4224
     [Crossref] [Google Scholar]
  20. 20.
    Rezai AR, Finelli D, Nyenhuis JA, Hrdlicka G, Tkach J, et al. 2002.. Neurostimulation systems for deep brain stimulation: in vitro evaluation of magnetic resonance imaging-related heating at 1.5 tesla. . J. Magnet. Reson. Imaging 15:(3):241–50
     [Crossref] [Google Scholar]
  21. 21.
    Bhusal B, Bhattacharyya P, Baig T, Jones S, Martens M. 2018.. Measurements and simulation of RF heating of implanted stereo-electroencephalography electrodes during MR scans. . Magn. Reson. Med. 80:(4):1676–85
     [Crossref] [Google Scholar]
  22. 22.
    Mosher ZA, Sawyer JR, Kelly DM. 2018.. MRI safety with orthopedic implants. . Orthop. Clin. N. Am. 49:(4):455–63
     [Crossref] [Google Scholar]
  23. 23.
    Am. Soc. Test. Mater. Int. 2020.. Standard test method for measurement of radio frequency induced heating on or near passive implants during magnetic resonance imaging. . ASTM F2182-19e2. Int. Stand., ASTM Int., West Conshohocken, PA:. https://www.astm.org/f2182-19e02.html
    [Google Scholar]
  24. 24.
    Int. Org. Stand. (ISO). 2018.. Assessment of the safety of magnetic resonance imaging for patients with an active implantable medical device. ISO/TS 10974:2018. Int. Stand., ISO, Geneva:. https://www.iso.org/standard/65055.html
    [Google Scholar]
  25. 25.
    Yu L, Kim B, Meng E. 2014.. Chronically implanted pressure sensors: challenges and state of the field. . Sensors 14:(11):20620–44
     [Crossref] [Google Scholar]
  26. 26.
    Lee J, Shin S, Lee S, Song J, Kang S, et al. 2018.. Highly sensitive multifilament fiber strain sensors with ultrabroad sensing range for textile electronics. . ACS Nano 12:(5):4259–68
     [Crossref] [Google Scholar]
  27. 27.
    Siontorou CG, Nikoleli G-PD, Nikolelis DP, Karapetis S, Tzamtzis N, Bratakou S. 2017.. Point-of-care and implantable biosensors in cancer research and diagnosis. . In Next Generation Point-of-Care Biomedical Sensors Technologies for Cancer Diagnosis, pp. 115–32. Singapore:: Springer Singapore
     [Google Scholar]
  28. 28.
    Rangel-Castillo L, Gopinath S, Robertson CS. 2008.. Management of intracranial hypertension. . Neurol Clin. 26:(2):521–41
     [Crossref] [Google Scholar]
  29. 29.
    Smith M. 2008.. Monitoring intracranial pressure in traumatic brain injury. . Anesth. Analg. 106:(1):240–48
     [Crossref] [Google Scholar]
  30. 30.
    Walek KW, Leary OP, Sastry R, Asaad WF, Walsh JM, et al. 2022.. Risk factors and outcomes associated with external ventricular drain infections. . Infect. Control Hosp. Epidemiol. 43:(12):1859–66
     [Crossref] [Google Scholar]
  31. 31.
    Ko JK, Cha SH, Choi BK, Lee J Il, Yun EY, Choi CH. 2014.. Hemorrhage rates associated with two methods of ventriculostomy: external ventricular drainage versus ventriculoperitoneal shunt procedure. . Neurol. Med. Chir. 54:(7):545–51
     [Crossref] [Google Scholar]
  32. 32.
    Zhong J, Dujovny M, Park HK, Perez E, Perlin AR, Diaz FG. 2003.. Advances in ICP monitoring techniques. . Neurol. Res. 25:(4):339–50
     [Crossref] [Google Scholar]
  33. 33.
    Harary M, Dolmans RG, Gormley W. 2018.. Intracranial pressure monitoring—review and avenues for development. . Sensors 18:(2):465
     [Crossref] [Google Scholar]
  34. 34.
    Raboel PH, Bartek J, Andresen M, Bellander BM, Romner B. 2012.. Intracranial pressure monitoring: invasive versus non-invasive methods—a review. . Crit. Care Res. Pract. 2012::1–14
     [Crossref] [Google Scholar]
  35. 35.
    Jiang N, Flyax S, Kurz W, Jakobi M, Tasoglu S, et al. 2021.. Intracranial sensors for continuous monitoring of neurophysiology. . Adv. Mater. Technol. 6:(12):2100339
     [Crossref] [Google Scholar]
  36. 36.
    Honjol Y, Rajkumar VS, Parent-Harvey C, Selvasandran K, Kordlouie S, et al. 2020.. Current view and prospect: implantable pressure sensors for health and surgical care. . Med. Devices Sens. 3:(3):e10068
     [Crossref] [Google Scholar]
  37. 37.
    Evensen KB, Eide PK. 2020.. Measuring intracranial pressure by invasive, less invasive or non-invasive means: limitations and avenues for improvement. . Fluids Barriers CNS. 17:(1):34
     [Crossref] [Google Scholar]
  38. 38.
    Zhong J, Dujovny M, Park HK, Perez E, Perlin AR, Diaz FG. 2003.. Advances in ICP monitoring techniques. . Neurol. Res. 25:(4):339–50
     [Crossref] [Google Scholar]
  39. 39.
    Rot S, Dweek M, Gutowski P, Goelz L, Meier U, Lemcke J. 2020.. Comparative investigation of different telemetric methods for measuring intracranial pressure: a prospective pilot study. . Fluids Barriers CNS. 17:(1):63
     [Crossref] [Google Scholar]
  40. 40.
    Millar. 2021.. Innovation spotlight: Codman Microsensor® ICP transducer. . Millar. https://millar.com/OEM-Solutions/Pressure-Sensor-Solutions/Codman-Microsensor-ICP-Transducer/
    [Google Scholar]
  41. 41.
    Müller SJ, Henkes E, Gounis MJ, Felber S, Ganslandt O, Henkes H. 2023.. Non-invasive intracranial pressure monitoring. . J. Clin. Med. 12:(6):2209
     [Crossref] [Google Scholar]
  42. 42.
    Shin J, Liu Z, Bai W, Liu Y, Yan Y, et al. 2019.. Bioresorbable optical sensor systems for monitoring of intracranial pressure and temperature. . Sci. Adv. 5:(7):eaaw1899
     [Crossref] [Google Scholar]
  43. 43.
    Chen Y, Lu D, Xing H, Ding H, Luo J, et al. 2024.. Recent progress in MEMS fiber-optic Fabry-Perot pressure sensors. . Sensors 24:(4):1079
     [Crossref] [Google Scholar]
  44. 44.
    Mesquita ET, Jorge AJL, Rabelo LM, Souza CV Jr. 2016.. Understanding hospitalization in patients with heart failure. . Int. J. Cardiovasc. Sci. 30::81–90
     [Google Scholar]
  45. 45.
    Volterrani M, Spoletini I, Angermann C, Rosano G, Coats AJ. 2019.. Implantable devices for heart failure monitoring: the CardioMEMS™ system. . Eur. Heart J. Suppl. 21:(Suppl._M):M50–53
     [Crossref] [Google Scholar]
  46. 46.
    Curtain JP, Lee MMY, McMurray JJ, Gardner RS, Petrie MC, Jhund PS. 2023.. Efficacy of implantable haemodynamic monitoring in heart failure across ranges of ejection fraction: a systematic review and meta-analysis. . Heart 109:(11):823–31
     [Crossref] [Google Scholar]
  47. 47.
    Boehmer JP, Hariharan R, Devecchi FG, Smith AL, Molon G, et al. 2017.. A multisensor algorithm predicts heart failure events in patients with implanted devices. . JACC Heart Fail. 5:(3):216–25
     [Crossref] [Google Scholar]
  48. 48.
    Omar R, Saliba W, Khatib M, Zheng Y, Pieters C, et al. 2024.. Biodegradable, biocompatible, and implantable multifunctional sensing platform for cardiac monitoring. . ACS Sens. 9:(1):126–38
     [Crossref] [Google Scholar]
  49. 49.
    Liu W, Wang X. 2023.. Recent advances of nanogenerator technology for cardiovascular sensing and monitoring. . Nano Energy 117::108910
     [Crossref] [Google Scholar]
  50. 50.
    Tham YC, Li X, Wong TY, Quigley HA, Aung T, Cheng CY. 2014.. Global prevalence of glaucoma and projections of glaucoma burden through 2040: a systematic review and meta-analysis. . Ophthalmology 121:(11):2081–90
     [Crossref] [Google Scholar]
  51. 51.
    Samet S, Ong JA, Ahmed IIK. 2019.. Hydrus microstent implantation for surgical management of glaucoma: a review of design, efficacy and safety. . Eye Vis. 6::32
     [Crossref] [Google Scholar]
  52. 52.
    Lichter PR, Musch DC, Gillespie BW, Guire KE, Janz NK, et al. 2001.. Interim clinical outcomes in the Collaborative Initial Glaucoma Treatment Study comparing initial treatment randomized to medications or surgery. . Ophthalmology 108::1943–53
     [Crossref] [Google Scholar]
  53. 53.
    Enders P, Cursiefen C. 2020.. Device profile of the EYEMATE-IO™ system for intraocular pressure monitoring: overview of its safety and efficacy. . Expert. Rev. Med. Devices 17:(6):491–97
     [Crossref] [Google Scholar]
  54. 54.
    Dunbar GE, Shen B, Aref A. 2017.. The Sensimed Triggerfish contact lens sensor: efficacy, safety, and patient perspectives. . Clin. Ophthalmol. 11::875–82
     [Crossref] [Google Scholar]
  55. 55.
    Szurman P, Gillmann K, Seuthe A-M, Dick HB, Hoffmann EM, et al. 2023.. EYEMATE-SC trial: twelve-month safety, performance, and accuracy of a suprachoroidal sensor for telemetric measurement of intraocular pressure. . Ophthalmology 130:(3):304–12
     [Crossref] [Google Scholar]
  56. 56.
    Joseph JI. 2021.. Review of the long-term implantable Senseonics continuous glucose monitoring system and other continuous glucose monitoring systems. . J. Diabetes Sci. Technol. 15:(1):167–73
     [Crossref] [Google Scholar]
  57. 57.
    Yang C, Huang X, Li X, Yang C, Zhang T, et al. 2021.. Wearable and implantable intraocular pressure biosensors: recent progress and future prospects. . Adv. Sci. 8:(6):2002971
     [Crossref] [Google Scholar]
  58. 58.
    Sanchez I, Martin R. 2019.. Advances in diagnostic applications for monitoring intraocular pressure in glaucoma: a review. . J. Optom. 12:(4):211–21
     [Crossref] [Google Scholar]
  59. 59.
    Hui P, Shtyrkova K, Zhou C, Chen X, Chodosh J, et al. 2020.. Implantable self-aligning fiber-optic optomechanical devices for in vivo intraocular pressure-sensing in artificial cornea. . J. Biophotonics 13:(7):e202000031
     [Crossref] [Google Scholar]
  60. 60.
    Shapero A, Agarwal A, Martinez JC, Emami A, Humayun MS, Tai Y-C. 2019.. Wireless implantable intraocular pressure sensor with parylene-oil-encapsulation and forward-angled RF coil. . In 2019 IEEE 32nd International Conference on Micro Electro Mechanical Systems (MEMS), pp. 21–24. New York:: IEEE
     [Google Scholar]
  61. 61.
    Shapero A, Tai Y-C. 2018.. Parylene-oil-encapsulated low-drift implantable pressure sensors. . In 2018 IEEE Micro Electro Mechanical Systems (MEMS), pp. 47–50. New York: IEEE
     [Google Scholar]
  62. 62.
    Joseph JI, Eisler G, Diaz D, Khalf A, Loeum C, Torjman MC. 2018.. Glucose sensing in the subcutaneous tissue: attempting to correlate the immune response with continuous glucose monitoring accuracy. . Diabetes Technol. Ther. 20:(5):321–24
     [Crossref] [Google Scholar]
  63. 63.
    Shang T, Zhang JY, Thomas A, Arnold MA, Vetter BN, et al. 2022.. Products for monitoring glucose levels in the human body with noninvasive optical, noninvasive fluid sampling, or minimally invasive technologies. . J. Diabetes Sci. Technol. 16:(1):168–214
     [Crossref] [Google Scholar]
  64. 64.
    Lee I, Probst D, Klonoff D, Sode K. 2021.. Continuous glucose monitoring systems—current status and future perspectives of the flagship technologies in biosensor research. . Biosens. Bioelectron. 181::113054
     [Crossref] [Google Scholar]
  65. 65.
    Senseonics Inc. 2024.. Eversense CGM. . Ascensia Diabetes Care. https://www.eversensecgm.com/
    [Google Scholar]
  66. 66.
    Vaddiraju S, Kastellorizios M, Legassey A, Burgess D, Jain F, Papadimitrakopoulos F. 2015.. Needle-implantable, wireless biosensor for continuous glucose monitoring. . In 2015 IEEE 12th International Conference on Wearable and Implantable Body Sensor Networks (BSN), pp. 1–5. New York:: IEEE
     [Google Scholar]
  67. 67.
    Unruh RM, Roberts JR, Nichols SP, Gamsey S, Wisniewski NA, McShane MJ. 2015.. Preclinical evaluation of poly(HEMA-co-acrylamide) hydrogels encapsulating glucose oxidase and palladium benzoporphyrin as fully implantable glucose sensors. . J. Diabetes Sci. Technol. 9:(5):985–92
     [Crossref] [Google Scholar]
  68. 68.
    Schmidt A, Ulrich M, Winkler B, Klaeffling C, Bausback Y, et al. 2010.. Angiographic patency and clinical outcome after balloon-angioplasty for extensive infrapopliteal arterial disease. . Catheter. Cardiovasc. Interv. 76:(7):1047–54
     [Crossref] [Google Scholar]
  69. 69.
    Schillinger M, Minar E. 2012.. Percutaneous treatment of peripheral artery disease. . Circulation 126:(20):2433–40
     [Crossref] [Google Scholar]
  70. 70.
    Wisniewski NA, Nichols SP, Gamsey SJ, Pullins S, Au-Yeung KY, et al. 2017.. Tissue-integrating oxygen sensors: continuous tracking of tissue hypoxia. . Adv. Exp. Med. Biol. 977::377–83
     [Crossref] [Google Scholar]
  71. 71.
    Montero-Baker MF, Au-Yeung KY, Wisniewski NA, Gamsey S, Morelli-Alvarez L, et al. 2015.. The first-in-man “Si Se Puede” study for the use of micro-oxygen sensors (MOXYs) to determine dynamic relative oxygen indices in the feet of patients with limb-threatening ischemia during endovascular therapy. . J. Vasc. Surg. 61:(6):1501–10.e1
     [Crossref] [Google Scholar]
  72. 72.
    Sonmezoglu S, Maharbiz MM. 2020.. 34.4 A 4.5mm3 deep-tissue ultrasonic implantable luminescence oxygen sensor. . In 2020 IEEE International Solid- State Circuits Conference (ISSCC), pp. 454–56. New York:: IEEE
     [Google Scholar]
  73. 73.
    Wolfram C, Stahlberg E, Pfeiffer N. 2019.. Patient-reported nonadherence with glaucoma therapy. . J. Ocular Pharmacol. Ther. 35:(4):223–28
     [Crossref] [Google Scholar]
  74. 74.
    Chawla A, Mcgalliard JN, Batterbury M. 2007.. Use of eyedrops in glaucoma: How can we help to reduce non-compliance?. Acta Ophthalmol. Scand. 85:(4):464
     [Crossref] [Google Scholar]
  75. 75.
    Yasin MN, Svirskis D, Seyfoddin A, Rupenthal ID. 2014.. Implants for drug delivery to the posterior segment of the eye: a focus on stimuli-responsive and tunable release systems. . J. Control. Release 196::208–21
     [Crossref] [Google Scholar]
  76. 76.
    Harasymowycz PJ, Papamatheakis DG, Latina M, De Leon M, Lesk MR, Damji KF. 2005.. Selective laser trabeculoplasty (SLT) complicated by intraocular pressure elevation in eyes with heavily pigmented trabecular meshworks. . Am. J. Ophthalmol. 139:(6):1110–13
     [Crossref] [Google Scholar]
  77. 77.
    Gedde SJ, Feuer WJ, Shi W, Lim KS, Barton K, et al. 2018.. Treatment outcomes in the Primary Tube Versus Trabeculectomy study after 1 year of follow-up. . Ophthalmology 125:(5):650–63
     [Crossref] [Google Scholar]
  78. 78.
    Jabłońska J, Lewczuk K, Konopińska J, Mariak Z, Rękas M. 2022.. Microinvasive glaucoma surgery: a review and classification of implant-dependent procedures and techniques. . Acta Ophthalmol. 100:(2):e327–38
     [Crossref] [Google Scholar]
  79. 79.
    Habbe KJ, Kohlhaas M, Langwieder C, Fili S. 2023.. Foreign body reaction after CyPass® Micro-Stent implantation: a case series. . Graefes Arch. Clin. Exp. Ophthalmol. 261:(2):513–20
     [Crossref] [Google Scholar]
  80. 80.
    Pereira ICF, van de Wijdeven R, Wyss HM, Beckers HJM, den Toonder JMJ. 2021.. Conventional glaucoma implants and the new MIGS devices: a comprehensive review of current options and future directions. . Eye 35::3202–21
     [Crossref] [Google Scholar]
  81. 81.
    Park H, Raffiee AH, John SWM, Ardekani AM, Lee H. 2018.. Towards smart self-clearing glaucoma drainage device. . Microsyst Nanoeng. 4::35
     [Crossref] [Google Scholar]
  82. 82.
    Bhushan B. 2007.. Nanotribology and nanomechanics of MEMS/NEMS and BioMEMS/BioNEMS materials and devices. . Microelectron. Eng. 84:(3):387–412
     [Crossref] [Google Scholar]
  83. 83.
    Farra R, Sheppard NF, McCabe L, Neer RM, Anderson JM, et al. 2012.. First-in-human testing of a wirelessly controlled drug delivery microchip. . Sci. Transl. Med. 4::122ra21
     [Crossref] [Google Scholar]
  84. 84.
    Grayson ACR, Shawgo RS, Johnson AM, Flynn NT, Li Y, et al. 2004.. A BioMEMS review: MEMS technology for physiologically integrated devices. . Proc. IEEE 92::6–21
     [Crossref] [Google Scholar]
  85. 85.
    Santini JT, Richards AC, Scheidt R, Cima MJ, Langer R. 2000.. Microchips as controlled drug-delivery devices. . Angew. Chem. Int. Ed. Engl. 39:2396–407
     [Google Scholar]
  86. 86.
    Matsumoto S, Ichikawa N. 2008.. New methods for liquid encapsulation in polymer MEMS structures. . In 2008 IEEE 21st International Conference on Micro Electro Mechanical Systems, pp. 415–18. New York:: IEEE
     [Google Scholar]
  87. 87.
    Coppola S, Nasti G, Vespini V, Mecozzi L, Castaldo R, et al. 2019.. Quick liquid packaging: encasing water silhouettes by three-dimensional polymer membranes. . Sci. Adv. 5:(5):eaat5189
     [Crossref] [Google Scholar]
  88. 88.
    Park J, Bertsch A, Martin-Olmos C, Brugger J. 2023.. Nanoliter liquid packaging in a bioresorbable microsystem by additive manufacturing and its application as a controlled drug delivery device. . Adv. Funct. Mater. 33:(38):2302385
     [Crossref] [Google Scholar]
  89. 89.
    Tran KTM, Nguyen TD. 2023.. Lithography in drug delivery. . In Nano- and Microfabrication Techniques in Drug Delivery, Vol. 2: Advanced Clinical Pharmacy—Research, Development and Practical Applications, ed. D Lamprou , pp. 249–74. Cham, Switz.:: Springer
     [Google Scholar]
  90. 90.
    Pinto SFT, Santos HA, Sarmento BFCC. 2024.. New insights into nanomedicines for oral delivery of glucagon-like peptide-1 analogs. . Wiley Interdiscip. Rev. Nanomed. Nanobiotechnol. 16:(2):e1952
     [Crossref] [Google Scholar]
  91. 91.
    Freedman BR, Kuttler A, Beckmann N, Nam S, Kent D, et al. 2022.. Enhanced tendon healing by a tough hydrogel with an adhesive side and high drug-loading capacity. . Nat. Biomed. Eng. 6:(10):1167–79
     [Crossref] [Google Scholar]
  92. 92.
    Chappel E, Dumont-Fillon D. 2021.. Micropumps for drug delivery. . In Drug Delivery Devices and Therapeutic Systems, pp. 31–61. Amsterdam:: Elsevier
     [Google Scholar]
  93. 93.
    Humayun M, Santos A, Altamirano JC, Ribeiro R, Gonzalez R, et al. 2014.. Implantable micropump for drug delivery in patients with diabetic macular edema. . Transl. Vis. Sci. Technol. 3:(6):5
     [Crossref] [Google Scholar]
  94. 94.
    Cobo A, Sheybani R, Tu H, Meng E. 2016.. A wireless implantable micropump for chronic drug infusion against cancer. . Sens. Actuators A Phys. 239::18–25
     [Crossref] [Google Scholar]
  95. 95.
    Gutiérrez-Hernández J-C, Caffey S, Abdallah W, Calvillo P, González R, et al. 2014.. One-year feasibility study of Replenish MicroPump for intravitreal drug delivery: a pilot study. . Transl. Vis. Sci. Technol. 3:(4):8
     [Crossref] [Google Scholar]
  96. 96.
    Ziemys A, Kojic M, Milosevic M, Kojic N, Hussain F, et al. 2011.. Hierarchical modeling of diffusive transport through nanochannels by coupling molecular dynamics with finite element method. . J. Comput. Phys. 230:(14):5722–31
     [Crossref] [Google Scholar]
  97. 97.
    Ziemys A, Grattoni A, Fine D, Hussain F, Ferrari M. 2010.. Confinement effects on monosaccharide transport in nanochannels. . J. Phys. Chem. B 114:(34):11117–26
     [Crossref] [Google Scholar]
  98. 98.
    Bruno G, Di Trani N, Hood RL, Zabre E, Filgueira CS, et al. 2018.. Unexpected behaviors in molecular transport through size-controlled nanochannels down to the ultra-nanoscale. . Nat. Commun. 9:(1):1682
     [Crossref] [Google Scholar]
  99. 99.
    Pons-Faudoa FP, Ballerini A, Sakamoto J, Grattoni A. 2019.. Advanced implantable drug delivery technologies: transforming the clinical landscape of therapeutics for chronic diseases. . Biomed. Microdevices 21:(2):47
     [Crossref] [Google Scholar]
  100. 100.
    NanoMedical Systems. 2022.. Nanotechnology transforming drug delivery: nStrada is a subcutaneous implant that provides long-term, constant release of a wide range of drugs and biologics. . NanoMedical Systems. https://nanomedsys.com
    [Google Scholar]
  101. 101.
    Dunlap CF, Colachis SC, Meyers EC, Bockbrader MA, Friedenberg DA. 2020.. Classifying intracortical brain-machine interface signal disruptions based on system performance and applicable compensatory strategies: a review. . Front. Neurorobot. 14::558987
     [Crossref] [Google Scholar]
  102. 102.
    Collinger JL, Wodlinger B, Downey JE, Wang W, Tyler-Kabara EC, et al. 2013.. High-performance neuroprosthetic control by an individual with tetraplegia. . Lancet 381:(9866):557–64
     [Crossref] [Google Scholar]
  103. 103.
    Hochberg LR, Serruya MD, Friehs GM, Mukand JA, Saleh M, et al. 2006.. Neuronal ensemble control of prosthetic devices by a human with tetraplegia. . Nature 442:(7099):164–71
     [Crossref] [Google Scholar]
  104. 104.
    Musk E. 2019.. An integrated brain-machine interface platform with thousands of channels. . J. Med. Internet Res. 21:(10):e16194
     [Crossref] [Google Scholar]
  105. 105.
    Cernat M, Borțun D, Matei C. 2022.. Remote controlled individuals? The future of Neuralink: ethical perspectives on the human-computer interactions. . In Proceedings of the 24th International Conference on Enterprise Information Systems (ICEIS 2022), Vol. 2, pp. 348–54. Setúbal, Port.: Sci. Technol. Publ., Lda (SciTePress). https://doi.org/10.5220/0011086700003179
    [Google Scholar]
  106. 106.
    Lozano AM, Lipsman N, Bergman H, Brown P, Chabardes S, et al. 2019.. Deep brain stimulation: current challenges and future directions. . Nat. Rev. Neurol. 15:(3):148–60
     [Crossref] [Google Scholar]
  107. 107.
    Suarez-Perez A, Gabriel G, Rebollo B, Illa X, Guimerà-Brunet A, et al. 2018.. Quantification of signal-to-noise ratio in cerebral cortex recordings using flexible MEAs with co-localized platinum black, carbon nanotubes, and gold electrodes. . Front. Neurosci. 12::862
     [Crossref] [Google Scholar]
  108. 108.
    Qiang Y, Gu W, Liu Z, Liang S, Ryu JH, et al. 2021.. Crosstalk in polymer microelectrode arrays. . Nano Res. 14:(9):3240–47
     [Crossref] [Google Scholar]
  109. 109.
    Zheng XS, Tan C, Castagnola E, Cui XT. 2021.. Electrode materials for chronic electrical microstimulation. . Adv. Healthc. Mater. 10:(12):2100119
     [Crossref] [Google Scholar]
  110. 110.
    Seymour JP, Kipke DR. 2007.. Neural probe design for reduced tissue encapsulation in CNS. . Biomaterials 28:(25):3594–607
     [Crossref] [Google Scholar]
  111. 111.
    Hotson G, Fifer MS, Acharya S, Benz HL, Anderson WS, et al. 2014.. Coarse electrocorticographic decoding of ipsilateral reach in patients with brain lesions. . PLOS ONE 9:(12):e115236
     [Crossref] [Google Scholar]
  112. 112.
    Oxley TJ, Yoo PE, Rind GS, Ronayne SM, Lee CMS, et al. 2021.. Motor neuroprosthesis implanted with neurointerventional surgery improves capacity for activities of daily living tasks in severe paralysis: first in-human experience. . J. Neurointerv. Surg. 13:(2):102–8
     [Crossref] [Google Scholar]
  113. 113.
    Borton DA, Yin M, Aceros J, Nurmikko A. 2013.. An implantable wireless neural interface for recording cortical circuit dynamics in moving primates. . J. Neural Eng. 10:(2):026010
     [Crossref] [Google Scholar]
  114. 114.
    Regalado A. 2015.. A brain-computer interface that works wirelessly. . MIT Technol. Rev., Jan. 14. https://www.technologyreview.com/2015/01/14/169635/a-brain-computer-interface-that-works-wirelessly/
    [Google Scholar]
  115. 115.
    Muqit MMK, Hubschman JP, Picaud S, McCreery DB, van Meurs JC, et al. 2020.. PRIMA subretinal wireless photovoltaic microchip implantation in non-human primate and feline models. . PLOS ONE 15:(4):e0230713
     [Crossref] [Google Scholar]
  116. 116.
    Szurman P, Mansouri K, Dick HB, Mermoud A, Hoffmann EM, et al. 2023.. Safety and performance of a suprachoroidal sensor for telemetric measurement of intraocular pressure in the EYEMATE-SC trial. . Br. J. Ophthalmol. 107:(4):518–24
     [Crossref] [Google Scholar]
  117. 117.
    Nagaraja S, Pelton AR. 2020.. Corrosion resistance of a Nitinol ocular microstent: implications on biocompatibility. . J. Biomed. Mater. Res. B Appl. Biomater. 108:(6):2681–90
     [Crossref] [Google Scholar]
/content/journals/10.1146/annurev-bioeng-110122-121128
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Lessons Learned and Challenges Ahead in the Translation of Implantable Microscale Sensors and Actuators
Annual Review of Biomedical Engineering 27, 211 (2025); https://doi.org/10.1146/annurev-bioeng-110122-121128
/content/journals/10.1146/annurev-bioeng-110122-121128
/content/journals/10.1146/annurev-bioeng-110122-121128
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