Soft robot–mediated autonomous adaptation to fibrotic capsule formation for improved drug delivery

The foreign body response impedes the function and longevity of implantable drug delivery devices. As a dense fibrotic capsule forms, integration of the device with the host tissue becomes compromised, ultimately resulting in device seclusion and treatment failure. We present FibroSensing Dynamic Soft Reservoir (FSDSR), an implantable drug delivery device capable of monitoring fibrotic capsule formation and overcoming its effects via soft robotic actuations. Occlusion of the FSDSR porous membrane was monitored over 7 days in a rodent model using electrochemical impedance spectroscopy. The electrical resistance of the fibrotic capsule correlated to its increase in thickness and volume. Our FibroSensing membrane showed great sensitivity in detecting changes at the abiotic/biotic interface, such as collagen deposition and myofibroblast proliferation. The potential of the FSDSR to overcome fibrotic capsule formation and maintain constant drug dosing over time was demonstrated in silico and in vitro. Controlled closed loop release of methylene blue into agarose gels (with a comparable fold change in permeability relating to 7 and 28 days in vivo) was achieved by adjusting the magnitude and frequency of pneumatic actuations after impedance measurements by the FibroSensing membrane. By sensing fibrotic capsule formation in vivo, the FSDSR will be capable of probing and adapting to the foreign body response through dynamic actuation changes. Informed by real-time sensor signals, this device offers the potential for long-term efficacy and sustained drug dosing, even in the setting of fibrotic capsule formation. Description A sensor-enabled pneumatically actuated drug delivery device enables adaptation to the foreign body response.

[1]  Claudia E. Varela,et al.  Dynamic actuation enhances transport and extends therapeutic lifespan in an implantable drug delivery platform , 2022 .

[2]  Markus A. Horvath,et al.  Dynamic actuation enhances transport and extends therapeutic lifespan in an implantable drug delivery platform , 2022, Nature Communications.

[3]  Sheng Xu,et al.  Soft wearable devices for deep-tissue sensing , 2022, Nature Reviews Materials.

[4]  RaviPrakash Magisetty,et al.  New Era of Electroceuticals: Clinically Driven Smart Implantable Electronic Devices Moving towards Precision Therapy , 2022, Micromachines.

[5]  C. Walsh,et al.  Skeletal muscle regeneration with robotic actuation–mediated clearance of neutrophils , 2021, Science Translational Medicine.

[6]  K. Schenke-Layland,et al.  The foreign body response to an implantable therapeutic reservoir in a diabetic rodent model. , 2021, Tissue engineering. Part C, Methods.

[7]  Runhui Liu,et al.  Bio-inspired poly-DL-serine materials resist the foreign-body response , 2021, Nature Communications.

[8]  B. Hinz,et al.  Implant Fibrosis and the Underappreciated Role of Myofibroblasts in the Foreign Body Reaction , 2021, Cells.

[9]  Scott T. Robinson,et al.  Additive Manufacturing of Multi‐Scale Porous Soft Tissue Implants That Encourage Vascularization and Tissue Ingrowth , 2021, Advanced healthcare materials.

[10]  G. Shen,et al.  Wearable, Implantable, and Interventional Medical Devices Based on Smart Electronic Skins , 2021, Advanced Materials Technologies.

[11]  R. Hovorka,et al.  New closed-loop insulin systems , 2021, Diabetologia.

[12]  A. Baker,et al.  Mechanobiological conditioning of mesenchymal stem cells for enhanced vascular regeneration , 2021, Nature Biomedical Engineering.

[13]  A. Baker,et al.  Mechanobiological Conditioning Enhances Mesenchymal Stem Cell-Induced Vascular Regeneration , 2021, Nature Biomedical Engineering.

[14]  J. Saad,et al.  Nonsteroidal Anti-Inflammatory Drugs Toxicity , 2020 .

[15]  Conor J Walsh,et al.  Ultra-sensitive and resilient compliant strain gauges for soft machines , 2020, Nature.

[16]  Matthew D. Murbach,et al.  impedance.py: A Python package for electrochemical impedance analysis , 2020, J. Open Source Softw..

[17]  Christopher G. Rylander,et al.  Controlled Catheter Movement Affects Dye Dispersal Volume in Agarose Gel Brain Phantoms , 2020, Pharmaceutics.

[18]  Mauro Serpelloni,et al.  Impedance-Based Monitoring of Mesenchymal Stromal Cell Three-Dimensional Proliferation Using Aerosol Jet Printed Sensors: A Tissue Engineering Application , 2020, Materials.

[19]  Scott T. Robinson,et al.  Implantable Therapeutic Reservoir Systems for Diverse Clinical Applications in Large Animal Models , 2020, Advanced healthcare materials.

[20]  J. Elisseeff,et al.  Interleukin 17 and senescent cells regulate the foreign body response to synthetic material implants in mice and humans , 2020, Science Translational Medicine.

[21]  Reijo Lappalainen,et al.  Classification of Wood Chips Using Electrical Impedance Spectroscopy and Machine Learning , 2020, Sensors.

[22]  T. Ryan,et al.  Human skin fibrosis: up‐regulation of collagen type III gene transcription in the fibrotic skin nodules of lower limb lymphoedema , 2019, Tropical medicine & international health : TM & IH.

[23]  Claudia E. Varela,et al.  An actuatable soft reservoir modulates host foreign body response , 2019, Science Robotics.

[24]  Daniel G. Anderson,et al.  Long-Term Implant Fibrosis Prevention in Rodents and Non-Human Primates Using Localized Deliverable Crystals , 2019, Nature Materials.

[25]  David S. Monahan,et al.  A bioresorbable biomaterial carrier and passive stabilization device to improve heart function post-myocardial infarction. , 2019, Materials science & engineering. C, Materials for biological applications.

[26]  K. Ngiam,et al.  Big data and machine learning algorithms for health-care delivery. , 2019, The Lancet. Oncology.

[27]  O. Veiseh,et al.  Domesticating the foreign body response: Recent advances and applications. , 2019, Advanced drug delivery reviews.

[28]  Matthew A. Bochenek,et al.  Alginate encapsulation as long-term immune protection of allogeneic pancreatic islet cells transplanted into the omental bursa of macaques , 2018, Nature Biomedical Engineering.

[29]  M. Schoenfisch,et al.  Influence of diabetes on the foreign body response to nitric oxide-releasing implants. , 2018, Biomaterials.

[30]  O. De Wever,et al.  Tumour tissue transport after intraperitoneal anticancer drug delivery , 2017, International journal of hyperthermia : the official journal of European Society for Hyperthermic Oncology, North American Hyperthermia Group.

[31]  C. Toumazou,et al.  Clinical Safety and Feasibility of the Advanced Bolus Calculator for Type 1 Diabetes Based on Case-Based Reasoning: A 6-Week Nonrandomized Single-Arm Pilot Study. , 2016, Diabetes technology & therapeutics.

[32]  Daniel G. Anderson,et al.  Correction: Corrigendum: Long-term glycemic control using polymer-encapsulated human stem cell–derived beta cells in immune-competent mice , 2016, Nature Medicine.

[33]  Wendy F. Liu,et al.  Biomolecular strategies to modulate the macrophage response to implanted materials. , 2016, Journal of materials chemistry. B.

[34]  Robert Langer,et al.  Combinatorial hydrogel library enables identification of materials that mitigate the foreign body response in primates , 2016, Nature Biotechnology.

[35]  Ellen T Roche,et al.  Biologic-free mechanically induced muscle regeneration , 2016, Proceedings of the National Academy of Sciences.

[36]  Matthew A. Bochenek,et al.  Long term Glycemic Control Using Polymer Encapsulated, Human Stem-Cell Derived β-cells in Immune Competent mice , 2016, Nature Medicine.

[37]  D. Grainger,et al.  Addressing Medical Device Challenges with Drug–Device Combinations , 2015 .

[38]  Patrick Garda,et al.  Relevance of impedance spectroscopy for the monitoring of implant-induced fibrosis: A preliminary study , 2015, 2015 IEEE Biomedical Circuits and Systems Conference (BioCAS).

[39]  Michael Glogauer,et al.  Macrophages, Foreign Body Giant Cells and Their Response to Implantable Biomaterials , 2015, Materials.

[40]  Christofer Toumazou,et al.  Advanced Insulin Bolus Advisor Based on Run-To-Run Control and Case-Based Reasoning , 2015, IEEE Journal of Biomedical and Health Informatics.

[41]  Jun‐Seok Oh,et al.  Probing the transport of plasma-generated RONS in an agarose target as surrogate for real tissue: dependency on time, distance and material composition , 2015 .

[42]  O. Stojadinović,et al.  Clinical application of growth factors and cytokines in wound healing , 2014, Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society.

[43]  M. Toledano,et al.  Effect of the hydration on the biomechanical properties in a fibrin-agarose tissue-like model. , 2014, Journal of biomedical materials research. Part A.

[44]  D. Bates,et al.  Fitting Linear Mixed-Effects Models Using lme4 , 2014, 1406.5823.

[45]  Lauren M. Huyett,et al.  Closed-Loop Artificial Pancreas Systems: Engineering the Algorithms , 2014, Diabetes Care.

[46]  N. Malathi,et al.  Evaluation of myofibroblasts by expression of alpha smooth muscle actin: a marker in fibrosis, dysplasia and carcinoma. , 2014, Journal of clinical and diagnostic research : JCDR.

[47]  P. Bainbridge,et al.  Wound healing and the role of fibroblasts. , 2013, Journal of wound care.

[48]  Karl A. Sillay,et al.  The Substitute Brain and the Potential of the Gel Model , 2013, Annals of neurosciences.

[49]  Shaoyi Jiang,et al.  Zwitterionic hydrogels implanted in mice resist the foreign-body reaction , 2013, Nature Biotechnology.

[50]  P. Fryer,et al.  Investigation of the diffusion of dyes in agar gels , 2012 .

[51]  A. Griffa,et al.  Experimental investigation of collagen waviness and orientation in the arterial adventitia using confocal laser scanning microscopy , 2012, Biomechanics and modeling in mechanobiology.

[52]  David W. Smith,et al.  Computational Modeling of Fluid Flow and Intra-Ocular Pressure following Glaucoma Surgery , 2010, PloS one.

[53]  Fotios Papadimitrakopoulos,et al.  Biomaterials/Tissue Interactions: Possible Solutions to Overcome Foreign Body Response , 2010, The AAPS Journal.

[54]  L. DiPietro,et al.  Factors Affecting Wound Healing , 2010, Journal of dental research.

[55]  E. Erdfelder,et al.  Statistical power analyses using G*Power 3.1: Tests for correlation and regression analyses , 2009, Behavior research methods.

[56]  Fotios Papadimitrakopoulos,et al.  A Review of the Biocompatibility of Implantable Devices: Current Challenges to Overcome Foreign Body Response , 2008, Journal of diabetes science and technology.

[57]  Olivera Stojadinovic,et al.  PERSPECTIVE ARTICLE: Growth factors and cytokines in wound healing , 2008, Wound repair and regeneration : official publication of the Wound Healing Society [and] the European Tissue Repair Society.

[58]  James M. Anderson,et al.  Foreign body reaction to biomaterials. , 2008, Seminars in immunology.

[59]  R. Sundararajan,et al.  Electrical Impedance Spectroscopy Study of Biological Tissues. , 2008, Journal of electrostatics.

[60]  Mahadevabharath R. Somayaji,et al.  Prediction of convection-enhanced drug delivery to the human brain. , 2008, Journal of theoretical biology.

[61]  B. Ratner,et al.  Foreign Body Response Investigated With an Implanted Biosensor by In Situ Electrical Impedance Spectroscopy , 2008, IEEE Sensors Journal.

[62]  H. Im,et al.  Repetitive mechanical stretching modulates IL-1beta induced COX-2, MMP-1 expression, and PGE2 production in human patellar tendon fibroblasts. , 2005, Gene.

[63]  Ryuta Saito,et al.  Reflux-free cannula for convection-enhanced high-speed delivery of therapeutic agents. , 2005, Journal of neurosurgery.

[64]  R. Ferrier,et al.  Pulkovo Observatory and the National Observatory Movement: An Historical Overview , 1990 .

[65]  E. Barsoukov,et al.  Impedance spectroscopy : theory, experiment, and applications , 2005 .

[66]  M. Borggrefe,et al.  Intravascular electric impedance spectroscopy of atherosclerotic lesions using a new impedance catheter system , 2005, Basic Research in Cardiology.

[67]  H. Cheung,et al.  New insight into deformation-dependent hydraulic permeability of gels and cartilage, and dynamic behavior of agarose gels in confined compression. , 2003, Journal of biomechanics.

[68]  U. Ungerstedt,et al.  Analyte flux through chronically implanted subcutaneous polyamide membranes differs in humans and rats. , 2002, American journal of physiology. Endocrinology and metabolism.

[69]  R. Hernández-Pando,et al.  Inflammatory cytokine production by immunological and foreign body multinucleated giant cells , 2000, Immunology.

[70]  E. Gersing Impedance spectroscopy on living tissue for determination of the state of organs , 1998 .

[71]  M. Kenward,et al.  Small sample inference for fixed effects from restricted maximum likelihood. , 1997, Biometrics.

[72]  R K Jain,et al.  Hindered diffusion in agarose gels: test of effective medium model. , 1996, Biophysical journal.

[73]  J Jossinet,et al.  Tissue impedance: a historical overview. , 1995, Physiological measurement.

[74]  J. Levick Flow through interstitium and other fibrous matrices. , 1987, Quarterly journal of experimental physiology.

[75]  Kenneth S. Cole,et al.  ELECTRIC PHASE ANGLE OF CELL MEMBRANES , 1932, The Journal of general physiology.

[76]  Rania M. Hathout,et al.  Machine learning methods in drug delivery , 2021 .

[77]  N. Frangogiannis,et al.  The role of α-smooth muscle actin in fibroblast-mediated matrix contraction and remodeling. , 2017, Biochimica et biophysica acta. Molecular basis of disease.

[78]  Kurt Hornik,et al.  ctree : Conditional Inference Trees , 2015 .

[79]  S. Gad Foreign Body Response , 2014 .

[80]  J. Ross Macdonald,et al.  Impedance spectroscopy , 2006, Annals of Biomedical Engineering.

[81]  D. Banabic,et al.  Recent advances and applications , 2004 .

[82]  H. Schwan Electrical properties of tissue and cell suspensions. , 1957, Advances in biological and medical physics.

[83]  A. W. E. E. K. L. Y. J. O U R N A L D E V O T E D T O T H E A D V A N C E,et al.  S C I E N C E , 2022 .