Microphysiological endothelial models to characterize subcutaneous drug absorption

Main Article Content

Giovanni S. Offeddu
Jean Carlos Serrano
Zhengpeng Wan
Mark A. Bryniarski
Sara C. Humphreys
Sophia W. Chen
Hamsini Dhoolypala
Kip Conner
Roger D. Kamm


The high variability in subcutaneous bioavailability of protein therapeutics is poorly understood, contributing to critical delays in patient access to new therapies. Preclinical animal and in vitro models fail to provide a physiologically relevant testbed to parse potential contributors to human bioavailability, therefore new strategies are necessary. Here, we present a microphysiological model of the human hypodermal vasculature at the injection site to study the interactions of administered protein therapeutics within the microenvironment that influence subcutaneous bioavailability. Our model combines human dermal endothelial cells, fibroblasts, and adipocytes, self-assembled into three-dimensional, perfusable microvessels that express relevant extracellular matrix. We demonstrate the utility of the model for measurement of biophysical parameters within the hypodermal microenvironment that putatively impact protein kinetics and distribution at the injection site. We propose that microphysiological models of the subcutaneous space have applications in preclinical development of protein therapeutics intended for subcutaneous administration with optimal bioavailability.

Article Details

How to Cite
Offeddu, G. S., Serrano, J. C., Wan, Z., Bryniarski, M. A., Humphreys, S. C., Chen, S. W., Dhoolypala, H., Conner, K. and Kamm, R. D. (2023) “Microphysiological endothelial models to characterize subcutaneous drug absorption”, ALTEX - Alternatives to animal experimentation, 40(2), pp. 299–313. doi: 10.14573/altex.2207131.

Amsden, B. (1999). An obstruction-scaling model for diffusion in homogeneous hydrogels. Macromolecules 32, 874-879. doi:10.1021/ma980922a

Avery, L. B., Wade, J., Wang, M. et al. (2018). Establishing in vitro in vivo correlations to screen monoclonal antibodies for physicochemical properties related to favorable human pharmacokinetics. MAbs 10, 244-255. doi:10.1080/19420862.2017.1417718

Axpe, E., Chan, D., Offeddu, G. S. et al. (2019). A multiscale model for solute diffusion in hydrogels. Macromolecules 52, 6889-6897. doi:10.1021/acs.macromol.9b00753

Baluk, P. and McDonald, D. M. (2008). Markers for microscopic imaging of lymphangiogenesis and angiogenesis. Ann N Y Acad Sci 1131, 1-12. doi:10.1196/annals.1413.001

Betts, A., Keunecke, A., van Steeg, T. J. et al. (2018). Linear pharmacokinetic parameters for monoclonal antibodies are similar within a species and across different pharmacological targets: A comparison between human, cynomolgus monkey and hFcRn Tg32 transgenic mouse using a population-modeling approach. MAbs 10, 751-764. doi:10.1080/19420862.2018.1462429

Boswell, C. A., Tesar, D. B., Mukhyala, K. et al. (2010). Effects of charge on antibody tissue distribution and pharmacokinetics. Bioconjug Chem 21, 2153-2163. doi:10.1021/bc100261d

Bown, H. K., Bonn, C., Yohe, S. et al. (2018). In vitro model for predicting bioavailability of subcutaneously injected monoclonal antibodies. J Control Release 273, 13-20. doi:10.1016/j.jconrel.2018.01.015

Braverman, I. M. (2000). The cutaneous microcirculation. J Investig Dermatol Symp Proc 5, 3-9. doi:10.1046/j.1087-0024.2000.00010.x

Breslin, J. W., Yang, Y., Scallan, J. P. et al. (2019). Lymphatic vessel network structure and physiology. Compr Physiol 9, 207-299. doi:10.1002/cphy.c180015

Bumbaca, D., Boswell, C. A., Fielder, P. J. et al. (2012). Physiochemical and biochemical factors influencing the pharmacokinetics of antibody therapeutics. AAPS J 14, 554-558. doi:10.1208/s12248-012-9369-y

Challa, D. K., Velmurugan, R., Ober, R. J. et al. (2014). FcRn: From molecular interactions to regulation of IgG pharmacokinetics and functions. Curr Top Microbiol Immunol 382, 249-272. doi:10.1007/978-3-319-07911-0_12

Chen, M. B., Whisler, J. A., Jeon, J. S. et al. (2013). Mechanisms of tumor cell extravasation in an in vitro microvascular network platform. Integr Biol 5, 1262-1271. doi:10.1039/c3ib40149a

Clauss, M. A. and Jain, R. K. (1990). Interstitial transport of rabbit and sheep antibodies in normal and neoplastic tissues. Cancer Res 50, 3487-3492.

Corovic, S., Markelc, B., Dolinar, M. et al. (2015). Modeling of microvascular permeability changes after electroporation. PLoS One 10, 1-16. doi:10.1371/journal.pone.0121370

Datta-Mannan, A., Lu, J., Witcher, D. R. et al. (2015a). The interplay of non-specific binding, target-mediated clearance and FcRn interactions on the pharmacokinetics of humanized antibodies. MAbs 7, 1084-1093. doi:10.1080/19420862.2015.1075109

Datta-Mannan, A., Thangaraju, A., Leung, D. et al. (2015b). Balancing charge in the complementarity-determining regions of humanized mAbs without affecting pl reduces non-specific binding and improves the pharmacokinetics. MAbs 7, 483-493. doi:10.1080/19420862.2015.1016696

De L. Davies, C., Berk, D. A., Pluen, A. et al. (2002). Comparison of IgG diffusion and extracellular matrix composition in rhabdomyosarcomas grown in mice versus in vitro as spheroids reveals the role of host stromal cells. Br J Cancer 86, 1639-1644. doi:10.1038/sj.bjc.6600270

Dostalek, M., Prueksaritanont, T. and Kelley, R. F. (2017). Pharmacokinetic de-risking tools for selection of monoclonal antibody lead candidates. MAbs 9, 756-766. doi:10.1080/19420862.2017.1323160

Farahat, W. A., Wood, L. B., Zervantonakis, I. K. et al. (2012). Ensemble analysis of angiogenic growth in three-dimensional microfluidic cell cultures. PLoS One 7, e37333. doi:10.1371/journal.pone.0037333

Gill, K. L., Gardner, I., Li, L. et al. (2016). A bottom-up whole-body physiologically based pharmacokinetic model to mechanistically predict tissue distribution and the rate of subcutaneous absorption of therapeutic proteins. AAPS J 18, 156-170. doi:10.1208/s12248-015-9819-4

Hajal, C., Ibrahim, L., Serrano, J. C. et al. (2021). The effects of luminal and trans-endothelial fluid flow s on the extravasation and tissue invasion of tumor cells in a 3D in vitro microvascular platform. Biomaterials 265, 120470. doi:10.1016/j.biomaterials.2020.120470

Hajal, C., Offeddu, G. S., Shin, Y. et al. (2022). Engineered human blood-brain barrier microfluidic model for vascular permeability analyses. Nat Protoc 17, 95-128. doi:10.1038/s41596-021-00635-w

Hammel, J. H. and Bellas, E. (2020). Endothelial cell crosstalk improves browning but hinders white adipocyte maturation in 3D engineered adipose tissue. Integr Biol 12, 81-89. doi:10.1093/intbio/zyaa006

Hötzel, I., Theil, F. P., Bernstein, L. J. et al. (2012). A strategy for risk mitigation of antibodies with fast clearance. MAbs 4, 753-760. doi:10.4161/mabs.22189

Hu, S. and D’Argenio, D. Z. (2020). Predicting monoclonal antibody pharmacokinetics following subcutaneous administration via whole-body physiologically-based modeling. J Pharmacokinet Pharmacodyn 47, 385-409. doi:10.1007/s10928-020-09691-3

Hu, X. and Weinbaum, S. (1999). A new view of Starling’s hypothesis at the microstructural level. Microvasc Res 58, 281-304. doi:10.1006/mvre.1999.2177

Imayama, S. and Urabe, H. (1986). Fine structural deformation of the dermal capillary following immersion fixation procedure. J Dermatol 13, 339-344. doi:10.1111/j.1346-8138.1986.tb02952.x

Jones, H. M., Zhang, Z., Jasper, P. et al. (2019). A physiologically-based pharmacokinetic model for the prediction of monoclonal antibody pharmacokinetics from in vitro data. CPT Pharmacometrics Syst Pharmacol 8, 738-747. doi:10.1002/psp4.12461

Kagan, L. (2014). Special section on DMPK of therapeutic proteins – Minireview: Pharmacokinetic modeling of the subcutaneous absorption of therapeutic proteins. Drug Metab Dispos 42, 1890-1905. doi:10.1124/dmd.114.059121

Kelly, R. L., Sun, T., Jain, T. et al. (2015). High throughput cross-interaction measures for human IgG1 antibodies correlate with clearance rates in mice. MAbs 7, 770-777. doi:10.1080/19420862.2015.1043503

Kelly, R. L., Yu, Y., Sun, T. et al. (2016). Target-independent variable region mediated effects on antibody clearance can be FcRn independent. MAbs 8, 1269-1275. doi:10.1080/19420862.2016.1208330

Komarova, Y. and Malik, A. B. (2009). Regulation of endothelial permeability via paracellular and transcellular transport pathways. Annu Rev Physiol 72, 463-493. doi:10.1146/annurev-physiol-021909-135833

Kraft, T. E., Richter, W. F., Emrich, T. et al. (2020). Heparin chromatography as an in vitro predictor for antibody clearance rate through pinocytosis. MAbs 12, 1683432. doi:10.1080/19420862.2019.1683432

Li, B., Tesar, D., Boswell, C. A. et al. (2014). Framework selection can influence pharmacokinetics of a humanized therapeutic antibody through differences in molecule charge. MAbs 6, 1255-1264. doi:10.4161/mabs.29809

Liu, L., Jacobsen, F. W., Everds, N. et al. (2017). Biological characterization of a stable effector functionless (SEFL) monoclonal antibody scaffold in vitro. J Biol Chem 292, 1876-1883. doi:10.1074/jbc.M116.748707

Liu, Y., Caffry, I., Wu, J. et al. (2014). High-throughput screening for developability during early-stage antibody discovery using self-interaction nanoparticle spectroscopy. MAbs 6, 483-492. doi:10.4161/mabs.27431

Mach, H., Gregory, S. M., MacKiewicz, A. et al. (2011). Electrostatic interactions of monoclonal antibodies with subcutaneous tissue. Ther Deliv 2, 727-736. doi:10.4155/tde.11.31

McLennan, D. N., Porter, C. J. H. and Charman, S. A. (2005). Subcutaneous drug delivery and the role of the lymphatics. Drug Discov Today Technol 2, 89-96. doi:10.1016/j.ddtec.2005.05.006

Mehta, D. and Malik, A. B. (2006). Signaling mechanisms regulating endothelial permeability. Physiol Rev 86, 279-367. doi:10.1152/physrev.00012.2005

Michel, C. C. and Curry, F. E. (1999). Microvascular permeability. Physiol Rev 79, 703-761. doi:10.1152/physrev.1999.79.3.703

Moore, J. E. and Bertram, C. D. (2018). Lymphatic system flows. Annu Rev Fluid Mech 50, 459-482. doi:10.1146/annurev-fluid-122316-045259

Na, H.-W., Kim, H. S., Choi, H. et al. (2022). Transcriptome analysis of particulate matter 2.5-induced abnormal effects on human sebocytes. Int J Mol Sci 23, 11534. doi:10.3390/ijms231911534

Nugent, L. J. and Jain, R. K. (1984). Extravascular diffusion in normal and neoplastic tissues. Cancer Res 44, 238-244.

Offeddu, G. S., Axpe, E., Harley, B. A. C. et al. (2018). Relationship between permeability and diffusivity in polyethylene glycol hydrogels. AIP Adv 8, 105006. doi:10.1063/1.5036999

Offeddu, G. S., Possenti, L., Loessberg-Zahl, J. T. et al. (2019a). Application of transmural flow across in vitro microvasculature enables direct sampling of interstitial therapeutic molecule distribution. Small 15, e1902393. doi:10.1002/smll.201902393

Offeddu, G. S., Haase, K., Gillrie, M. R. et al. (2019b). An on-chip model of protein paracellular and transcellular permeability in the microcirculation. Biomaterials 212, 115-125. doi:10.1016/j.biomaterials.2019.05.022

Offeddu, G. S., Serrano, J. C., Chen, S. W. et al. (2021a). Microheart: A microfluidic pump for functional vascular culture in microphysiological systems. J Biomech 119, 110330. doi:10.1016/j.jbiomech.2021.110330

Offeddu, G. S., Haase, K., Wan, Z. et al. (2021b). Personalized models of breast cancer desmoplasia reveal biomechanical determinants of drug penetration. bioRxiv, 2021.12.12.472296. doi:10.1101/2021.12.12.472296

Offeddu, G. S., Hajal, C., Foley, C. R. et al. (2021c). The cancer glycocalyx mediates intravascular adhesion and extravasation during metastatic dissemination. Commun Biol 4, 255. doi:10.1038/s42003-021-01774-2

Ono, S., Egawa, G. and Kabashima, K. (2017). Regulation of blood vascular permeability in the skin. Inflamm Regen 37, 11. doi:10.1186/s41232-017-0042-9

Ovacik, M. and Lin, K. (2018). Tutorial on monoclonal antibody pharmacokinetics and its considerations in early development. Clin Transl Sci 11, 540-552. doi:10.1111/cts.12567

Polley, M. Y. C. (2011). Practical modifications to the time-to-event continual reassessment method for phase I cancer trials with fast patient accrual and late-onset toxicities. Stat Med 30, 2130-2143. doi:10.1002/sim.4255

Porter, C. J. H. and Charman, S. A. (2000). Lymphatic transport of proteins after subcutaneous administration. J Pharm Sci 89, 297-310. doi:10.1002/(SICI)1520-6017(200003)89:3<297::AID-JPS2>3.0.CO;2-P

Richter, W. F., Bhansali, S. G. and Morris, M. E. (2012). Mechanistic determinants of biotherapeutics absorption following SC administration. AAPS J 14, 559-570. doi:10.1208/s12248-012-9367-0

Rippe, B. and Haraldsson, B. (1994). Transport of macromolecules across microvascular walls: The two-pore theory. Physiol Rev 74, 163-219. doi:10.1152/physrev.1994.74.1.163

Risueño, I., Valencia, L., Jorcano, J. L. et al. (2021). Skin-on-a-chip models: General overview and future perspectives. APL Bioeng 5, 030901. doi:10.1063/5.0046376

Ryman, J. T. and Meibohm, B. (2017). Pharmacokinetics of monoclonal antibodies. CPT Pharmacometrics Syst Pharmacol 6, 576-588. doi:10.1002/psp4.12224

Sanabria, H., Kubota, Y. and Waxham, M. N. (2007). Multiple diffusion mechanisms due to nanostructuring in crowded environments. Biophys J 92, 313-322. doi:10.1529/biophysj.106.090498

Sánchez-Félix, M., Burke, M., Chen, H. H. et al. (2020). Predicting bioavailability of monoclonal antibodies after subcutaneous administration: Open innovation challenge. Adv Drug Deliv Rev 167, 66-77. doi:10.1016/j.addr.2020.05.009

Schindelin, J., Arganda-Carreras, I., Frise, E. et al. (2012). Fiji: An open-source platform for biological-image analysis. Nat Methods 9, 676-682. doi:10.1038/nmeth.2019

Schlothauer, T., Rueger, P., Stracke, J. O. et al. (2013). Analytical FcRn affinity chromatography for functional characterization of monoclonal antibodies. MAbs 5, 576-586. doi:10.4161/mabs.24981

Schmid-Schonbein, G. W. (1990). Microlymphatics and lymph flow. Physiol Rev 70, 987-1028. doi:10.1152/physrev.1990.70.4.987

Schoch, A., Kettenberger, H., Mundigl, O. et al. (2015). Charge-mediated influence of the antibody variable domain on FcRn-dependent pharmacokinetics. Proc Natl Acad Sci U S A 112, 5997-6002. doi:10.1073/pnas.1408766112

Serrano, J. C., Gillrie, M. R., Li, R. et al. (2022). On-chip engineered human lymphatic microvasculature for physio-/pathological transport phenomena studies. bioRxiv, 2022.03.06.483122. doi:10.1101/2022.03.06.483122

Shin, Y., Han, S., Jeon, J. S. et al. (2012). Microfluidic assay for simultaneous culture of multiple cell types on surfaces or within hydrogels. Nat Protoc 7, 1247-1259. doi:10.1038/nprot.2012.051

Sutterby, E., Thurgood, P., Baratchi, S. et al. (2020). Microfluidic skin-on-a-chip models: Toward biomimetic artificial skin. Small 16, e202002515. doi:10.1002/smll.202002515

Swaminathan, R., Hoang, C. P. and Verkman, A. S. (1997). Photobleaching recovery and anisotropy decay of green fluorescent protein GFP-S65T in solution and cells: Cytoplasmic viscosity probed by green fluorescent protein translational and rotational diffusion. Biophys J 72, 1900-1907. doi:10.1016/S0006-3495(97)78835-0

Swartz, M. A. (2001). The physiology of the lymphatic system. Adv Drug Deliv Rev 50, 3-20. doi:10.1016/S0169-409X(01)00150-8

Tarbell, J. M. and Cancel, L. M. (2016). The glycocalyx and its significance in human medicine. J Intern Med 280, 97-113. doi:10.1111/joim.12465

Thomas, V. A. and Balthasar, J. P. (2019). Understanding inter-individual variability in monoclonal antibody disposition. Antibodies 8, 56. doi:10.3390/antib8040056

Thurber, G. M., Schmidt, M. M. and Wittrup, K. D. (2008). Antibody tumor penetration: Transport opposed by systemic and antigen-mediated clearance. Adv Drug Deliv Rev 60, 1421-1434. doi:10.1016/j.addr.2008.04.012

Tuma, P. L. and Hubbard, A. L. (2003). Transcytosis: Crossing cellular barriers. Physiol Rev 83, 871-932. doi:10.1152/physrev.00001.2003

Vidarsson, G., Dekkers, G. and Rispens, T. (2014). IgG subclasses and allotypes: From structure to effector functions. Front Immunol 5, 520. doi:10.3389/fimmu.2014.00520

Wang, W., Wang, E. Q. and Balthasar, J. P. (2008). Monoclonal antibody pharmacokinetics and pharmacodynamics. Clin Pharmacol Ther 84, 548-558. doi:10.1038/clpt.2008.170

Whisler, J. A., Chen, M. B. and Kamm, R. D. (2013). Control of perfusable microvascular network morphology using a multiculture microfluidic system. Tissue Eng Part C Methods 20, 543-552. doi:10.1089/ten.tec.2013.0370

Wu, F., Bhansali, S. G., Law, W. C. et al. (2012). Fluorescence imaging of the lymph node uptake of proteins in mice after subcutaneous injection: Molecular weight dependence. Pharm Res 29, 1843-1853. doi:10.1007/s11095-012-0708-6

Xu, D. and Esko, J. D. (2014). Demystifying heparan sulfate-protein interactions. Annu Rev Biochem 83, 129-157. doi:10.1146/annurev-biochem-060713-035314

Yadav, D. B., Sharma, V. K., Boswell, C. A. et al. (2015). Evaluating the use of antibody variable region (Fv) charge as a risk assessment tool for predicting typical cynomolgus monkey pharmacokinetics. J Biol Chem 290, 29732-29741. doi:10.1074/jbc.M115.692434

Yang, F., Carmona, A., Stojkova, K. et al. (2021). A 3D human adipose tissue model within a microfluidic device. Lab Chip 21, 435-446. doi:10.1039/d0lc00981d