Advertisement

Methods and Study Designs for Characterizing the Pharmacokinetics and Pharmacodynamics of Carrier-Mediated Agents

  • Allison N. Schorzman
  • Andrew T. Lucas
  • John R. Kagel
  • William C. ZamboniEmail author
Protocol
  • 951 Downloads
Part of the Methods in Molecular Biology book series (MIMB, volume 1831)

Abstract

Major advances in carrier-mediated agents (CMAs), which include nanoparticles, nanosomes, and conjugates, have revolutionized drug delivery capabilities over the past decade. While providing numerous advantages, such as greater solubility, duration of exposure, and delivery to the site of action over their small molecule counterparts, there is substantial variability in systemic clearance and distribution, tumor delivery, and pharmacologic effects (efficacy and toxicity) of these agents. In this chapter, we focus on the analytical and phenotypic methods required to design a study that characterizes the pharmacokinetics (PK) and pharmacodynamics (PD) of all forms of these nanoparticle-based drug agents. These methods include separation of encapsulated and released drugs, ultrafiltration for measurement of non-protein bound active drug, microdialysis to measure intra-tumor drug concentrations, immunomagnetic separation and flow cytometry for sorting cell types, and evaluation of spatial distribution of drug forms relative to tissue architecture by mass spectrometry imaging and immunohistochemistry.

Key words

Nanoparticles Carrier-mediated agents Pharmacokinetics Pharmacodynamics Immune system Mononuclear phagocyte system (MPS) 

Notes

Acknowledgments

We thank Amanda Van Swearingen, Maria Sambade, and Carey Anders (Lineberger Comprehensive Cancer Center, University of North Carolina at Chapel Hill (UNC)) for the TNBC spleen samples; the UNC Mouse Phase 1 Unit (UNC) for the T11 spleen samples; the Animal Studies Core (UNC) for animal handling; Andrew Madden, Gina Song, Allison Schorzman, and William Zamboni (UNC Eshelman School of Pharmacy) for study design and sample processing; and Guillaume Robichaud, Jeremy Barry, and David Muddiman (Department of Chemistry, North Carolina State University) for MALDESI MSI analysis.

References

  1. 1.
    Ge Y, Tiwari A, Li S (2011) Nanomedicine – bridging the gap between nanotechnology and medicine. Adv Mater Lett 2(1):1–2CrossRefGoogle Scholar
  2. 2.
    Caron WP, Song G, Kumar P et al (2012) Interpatient pharmacokinetic and pharmacodynamic variability of carrier-mediated anticancer agents. Clin Pharmacol Ther 91(5):802–812PubMedCrossRefGoogle Scholar
  3. 3.
    Laginha K, Mumbengegwi D, Allen T (2005) Liposomes targeted via two different antibodies: assay, B-cell binding and cytotoxicity. Biochim Biophys Acta 1711(1):25–32PubMedCrossRefGoogle Scholar
  4. 4.
    Yurkovetskiy AV, Hiller A, Syed S et al (2004) Synthesis of a macromolecular camptothecin conjugate with dual phase drug release. Mol Pharm 1(5):375–382PubMedPubMedCentralCrossRefGoogle Scholar
  5. 5.
    Zamboni WC (2005) Liposomal, nanoparticle, and conjugated formulations of anticancer agents. Clin Cancer Res 11(23):8230–8234PubMedCrossRefGoogle Scholar
  6. 6.
    Zamboni WC, Gervais AC, Egorin MJ et al (2004) Systemic and tumor disposition of platinum after administration of cisplatin or STEALTH liposomal-cisplatin formulations (SPI-077 and SPI-077 B103) in a preclinical tumor model of melanoma. Cancer Chemother Pharmacol 53(4):329–336PubMedCrossRefGoogle Scholar
  7. 7.
    Laverman P, Boerman OC, Oyen WJG et al (2001) In vivo applications of PEG liposomes: unexpected observations. Crit Rev Ther Drug Carrier Syst 18(6):551–566PubMedCrossRefGoogle Scholar
  8. 8.
    Schell RF, Sidone BJ, Caron WP et al (2014) Meta-analysis of inter-patient pharmacokinetic variability of liposomal and non-liposomal anticancer agents. Nanomedicine 10(1):109–117PubMedCrossRefGoogle Scholar
  9. 9.
    Zamboni WC (2008) Concept and clinical evaluation of carrier-mediated anticancer agents. Oncologist 13(3):248–260PubMedCrossRefGoogle Scholar
  10. 10.
    Petschauer JS, Madden AJ, Kirschbrown WP et al (2015) The effects of nanoparticle drug loading on the pharmacokinetics of anticancer agents. Nanomedicine (Lond.) 10(3):446–463CrossRefGoogle Scholar
  11. 11.
    Jain RK (1996) Delivery of molecular medicine to solid tumors. Science 271:1079PubMedCrossRefGoogle Scholar
  12. 12.
    Zamboni WC, Houghton PJ, Hulstein JL et al (1999) Relationship between tumor extracellular fluid exposure to topotecan and response in human neuroblastoma xenografts and cell lines. Cancer Chemother Pharmacol 43:269–276PubMedCrossRefGoogle Scholar
  13. 13.
    Balch CM, Reintgen DS, Kirkwood JM et al (1997) Cutaneous Melanoma. In: DeVita VT, Hellman S, Rosenberg SA (eds) Cancer: principles and practice of oncology, 5th edn. Lippincott-Raven, Philadelphia, p 1947Google Scholar
  14. 14.
    Muller M, Mader RM, Steiner B et al (1997) 5-fluorouracil kinetics in the interstitial tumor space: clinical response in breast cancer patients. Cancer Res 57:2598PubMedGoogle Scholar
  15. 15.
    Blochl-Daum B, Muller M, Meisinger V et al (1996) Measurement of extracellular fluid carboplatin kinetics in melanoma metastases with microdialysis. Br J Cancer 73:920PubMedPubMedCentralCrossRefGoogle Scholar
  16. 16.
    Yuan Q, Hein S, Misra RD (2010) New generation of chitosan-encapsulated ZnO quantum dots loaded with drug: synthesis, characterization and in vitro drug delivery response. Acta Biomater 6(7):2732–2739PubMedCrossRefGoogle Scholar
  17. 17.
    Dipali SR, Kulkarni SB, Betageri GV (1996) Comparative study of separation of non-encapsulated drug from unilamellar liposomes by various methods. J Pharm Pharmacol 48:1112–1115PubMedCrossRefGoogle Scholar
  18. 18.
    Mayer LD, St. Onge G (1995) Determination of free and liposome-associated doxorubicin and vincristine levels in plasma under equilibrium conditions employing ultrafiltration techniques. Anal Biochem 232(2):149–157PubMedCrossRefGoogle Scholar
  19. 19.
    Zamboni WC, Strychor S, Joseph E et al (2007) Plasma, tumor, and tissue disposition of STEALTH liposomal CKD-602 (S-CKD602) and nonliposomal CKD-602 in mice bearing A375 human melanoma xenografts. Clin Cancer Res 13(23):7217PubMedCrossRefGoogle Scholar
  20. 20.
    Song G, Darr DB, Santos CM et al (2014) Effects of tumor microenvironment heterogeneity on nanoparticle disposition and efficacy in breast cancer tumor models. Clin Cancer Res 20:6083–6095PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Walsh MD, Hanna SK, Sen J et al (2012) Pharmacokinetics and antitumor efficacy of XMT-1001, a novel, polymeric topoisomerase I inhibitor, in mice bearing HT-29 human colon carcinoma xenografts. Clin Cancer Res 18(9):2591–2602PubMedCrossRefGoogle Scholar
  22. 22.
    Young C, Schluep T, Hwang J et al (2011) CRLX101 (formerly IT-101)–a novel nanopharmaceutical of camptothecin in clinical development. Curr Bioact Compd 7(1):8–14PubMedPubMedCentralCrossRefGoogle Scholar
  23. 23.
    Musteata FM, Pawliszyn J, Qian MG et al (2006) Determination of drug plasma protein binding by solid phase microextraction. J Pharm Sci 95(8):1712–1722PubMedCrossRefPubMedCentralGoogle Scholar
  24. 24.
    Rowland M (1980) Plasma protein binding and therapeutic drug monitoring. Ther Drug Monitor 2:29–37CrossRefGoogle Scholar
  25. 25.
    Tillement JP, Lhoste F, Giudicelli JF (1978) Diseases and drug protein binding. Clin Pharmacokinet 3(2):144–154PubMedCrossRefGoogle Scholar
  26. 26.
    Taylor S, Harker A (2006) Modification of the ultrafiltration technique to overcome solubility and non-specific binding challenges associated with the measurement of plasma protein binding corticosteroids. J Pharm Biomedical Analysis 41:299–303CrossRefGoogle Scholar
  27. 27.
    Mortier KA, Lambert WE (2006) Determination of unbound docetaxel and paclitaxel in plasma by ultrafiltration and liquid chromatography –tandem mass spectrometry. J Chrom A 1108:195–201CrossRefGoogle Scholar
  28. 28.
    U.S. Department of Health and Human Services, Food and Drug Administration Center for Drug Evaluation and Research (CDER), Center for Veterinary Medicine (CVM). Guidance for industry bioanalytical method validation. May 2001Google Scholar
  29. 29.
    Boucher Y, Jain RK (1992) Microvascular pressure is the principal driving force for interstitial hypertension in solid tumors: implication for vascular collapse. Cancer Res 52(5110):1992Google Scholar
  30. 30.
    Presant CA, Wolf W, Waluch V et al (1994) Association of intratumoral pharmacokinetics of fluorouracil with clinical response. Lancet 343:1184–1187PubMedCrossRefPubMedCentralGoogle Scholar
  31. 31.
    Front D, Isreal O, Iosilevsky G et al (1987) Human lung tumors: SPECT quantitation of differences in co-57 bleomycin uptake. Radiology 165:129–133PubMedCrossRefPubMedCentralGoogle Scholar
  32. 32.
    Fishman AJ, Alpert NM, Babich JW et al (1997) The role of positron emission tomography in pharmacokinetic analysis. Drug Metab Rev 29:923–956CrossRefGoogle Scholar
  33. 33.
    Brunner M, Muller M (2002) Microdialysis: an in vivo approach for measuring drug delivery in oncology. Eur J Clin Pharmacol 58(4):227–234PubMedCrossRefPubMedCentralGoogle Scholar
  34. 34.
    Muller M, Schmid R, Georgopoulos A et al (1995) Application of microdialysis to clinical pharmacokinetics in humans. Clin Pharmacol Ther 57:371PubMedCrossRefPubMedCentralGoogle Scholar
  35. 35.
    Johansen MJ, Newman RA, Madden T (1997) The use of microdialysis in pharmacokinetics and pharmacodynamics. Pharmacotherapy 17:464PubMedPubMedCentralGoogle Scholar
  36. 36.
    Kehr J (1993) A survey on quantitation microdialysis: theoretical models and practical limitations. J Neurosci Methods 48:251PubMedCrossRefGoogle Scholar
  37. 37.
    Blakeley JO, Olson J, Grossman SA et al (2009) Effect of blood brain barrier permeability in recurrent high grade gliomas on the intratumoral pharmacokinetics of methotrexate: a microdialysis study. J Neuro-Oncol 91:51–58CrossRefGoogle Scholar
  38. 38.
    Tegeder I, Brautigam L, Seegal M et al (2003) Cisplatin tumor concentrations after intra-arterial cisplatin infusion or embolization in patients with oral cancer. Clin Pharmacol Ther 73:417–426PubMedCrossRefPubMedCentralGoogle Scholar
  39. 39.
    Chaurasia CS, Müller M, Bashaw EW et al (2007) AAPS-FDA workshop white paper: microdialysis principles, application, and regulatory perspectives report from the joint AAPS-FDA workshop, November 4-5, 2005, Nashville, TN. AAPS J 9(1):E48–E59PubMedCentralCrossRefPubMedGoogle Scholar
  40. 40.
    Leggas M, Zhuang Y, Welden J et al (2004) Microbore HPLC method with online microdialysis for measurement of topotecan lactone and carboxylate in murine CSF. J Pharm Sci 93:2284–2295PubMedCrossRefPubMedCentralGoogle Scholar
  41. 41.
    Ettinger SN, Poellmann CC, Wisniewski NA et al (2001) Urea as a recovery marker for quantitative assessment of tumor interstitial solutes with microdialysis. Cancer Res 61(21):7964–7970PubMedPubMedCentralGoogle Scholar
  42. 42.
    Ekstrom PO, Andersen A, Saeter G et al (1997) Continuous intratumoral microdialysis during high-dose methotrexate therapy in a patient with malignant fibrous histiocytoma of the femur; a case report. Cancer Chemother Pharmacol 39(3):267–272PubMedPubMedCentralGoogle Scholar
  43. 43.
    Thompson JF, Siebert GA, Anissimov YG et al (2001) Microdialysis and response during regional chemotherapy by isolated limb infusion of melphalan for limb malignancies. Br J Cancer 85(2):157–165PubMedPubMedCentralCrossRefGoogle Scholar
  44. 44.
    Conley BA, Ramsland TS, Sentz DL et al (1999) Antitumor activity, distribution, and metabolism of 13-cis-retinoic acid as a single agent or in combination with tamoxifen in established human MCF-7 xenografts in mice. Cancer Chemother Pharmacol 43:183–197PubMedCrossRefPubMedCentralGoogle Scholar
  45. 45.
    Zamboni WC, Gajjar AJ, Mandrell TD et al (1998) A four-hour topotecan infusion achieves cytotoxic exposure throughout the neuroaxis in the nonhuman primate model: implications for treatment of children with metastatic medulloblastoma. Clin Cancer Res 4(10):2537–2544PubMedPubMedCentralGoogle Scholar
  46. 46.
    Shapiro H (1995) Practical flow cytometry. Wiley-Lis, New YorkGoogle Scholar
  47. 47.
    DePalma A (1997) Developments in biomagnetic separations focus on new affinity mechanisms. Genet Eng News 17:11Google Scholar
  48. 48.
    Busch J, Huber P, Pfluger E et al (1994) Enrichment of fetal cells from maternal blood by high gradient magnetic cell sorting (double MACS) for PCR-based genetic analysis. Prenatal Diagn 14:1129–1140CrossRefGoogle Scholar
  49. 49.
    Miltenyi S, Muller W, Weichel W et al (1990) High gradient magnetic cell separation. Cytometry 11:231–238PubMedCrossRefPubMedCentralGoogle Scholar
  50. 50.
    Schmitz B, Radbruch A, Kummel T et al (1994) Magnetic activated cell sorting (MACS) is a new immunomagnetic method for megakaryocytic cell isolation: comparison of different separation techniques. Eur J Hematol 52:267–275CrossRefGoogle Scholar
  51. 51.
    Manyonda IT, Soltys AJ, Hay FC (1992) A critical evaluation of the magnetic cell sorter and its use in the positive and negative selection of CD45RO+ cells. J Immunol Methods 149:1–10PubMedCrossRefPubMedCentralGoogle Scholar
  52. 52.
    Molday RS, Molday LL (1984) Separation of cells labeled with immunospecific iron dextran microspheres using high gradient magnetic chromatography. FEBS Lett 170(2):232–238PubMedCrossRefPubMedCentralGoogle Scholar
  53. 53.
    Blanchard D, Gaillard C, Hermann P et al (1994) Role of CD40 antigen and interleukin-2 in T cell-dependent human B lymphocyte growth. Eur J Immunol 4(2):330–335CrossRefGoogle Scholar
  54. 54.
    Servida F, Soligo D, Caneva L et al (1996) Functional and morphological characterization of immunomagnetically selected CD34+ hematopoietic progenitor cells. Stem Cells 14(4):430–438PubMedCrossRefPubMedCentralGoogle Scholar
  55. 55.
    de Wynter EA, Coutinho LH, Pei X et al (1995) Comparison of purity and enrichment of CD34+ cells from bone marrow, umbilical cord and peripheral blood (primed for apheresis) using five separation systems. Stem Cells 13(5):524–532PubMedCrossRefPubMedCentralGoogle Scholar
  56. 56.
    Kato K, Radbruch A (1993) Isolation and characterization of CD34+ hematopoietic stem cells from human peripheral blood by high-gradient magnetic cell sorting. Cytometry 14(4):384–392PubMedCrossRefPubMedCentralGoogle Scholar
  57. 57.
    Radbruch A, Mechtold B, Thiel A et al (1997) In: Darzynkiewicz Z, Robinson JP, Crissman HA (eds) Methods cell biology. Academic Press, San Diego, pp 387–402Google Scholar
  58. 58.
    Thiele J, Wickenhauser C, Baldus SE et al (1995) Characterization of CD34+ human hemopoietic progenitor cells from the peripheral blood: enzyme-, carbohydrate- and immunocytochemistry, morphometry, and ultrastructure. Leuk Lymphoma 16(5–6):483–491PubMedCrossRefPubMedCentralGoogle Scholar
  59. 59.
    Irsch J, Hunzelmann N, Tesch H et al (1996) Effects of osteogenic protein-1 (OP-1, BMP-7) on bone matrix protein expression by fetal rat calvarial cells are differentiation stage specific. Immunotechnology 169(1):115–125Google Scholar
  60. 60.
    Miller MC, Doyle GV, Terstappen LW (2010) Significance of circulating tumor cells detected by the CellSearch™ system in patients with metastatic breast colorectal and prostate cancer. J Onco 2010:617421Google Scholar
  61. 61.
    Aichler M, Walch A (2015) MALDI imaging mass spectrometry: current frontiers and perspectives in pathology research and practice. Lab Investig 95(4):422–431PubMedCrossRefPubMedCentralGoogle Scholar
  62. 62.
    Nilsson A, Goodwin RJA, Shariatgorji M et al (2015) Mass spectrometry imaging in drug development. Anal Chem 87:1437–1455PubMedCrossRefPubMedCentralGoogle Scholar
  63. 63.
    Norris JL, Caprioli RM (2013) Analysis of tissue specimens by matrix-assisted laser desorption/ionization imaging mass spectrometry in biological and clinical research. Chem Rev 113(4):2309–2342PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Prideaux B, Stoeckli M (2012) Mass spectrometry imaging for drug distribution studies. J Proteome 75:4999–5013CrossRefGoogle Scholar
  65. 65.
    Solon E, Schweitzer A, Stoeckli A et al (2012) Autoradiography, MALDI-MS, and SIMS-MS imaging in pharmaceutical discovery and development. AAPS J 12:11–26CrossRefGoogle Scholar
  66. 66.
    McDonnell LA, Heeren RMA (2007) Imaging mass spectrometry. Mass Spectrom Rev 26:606–643PubMedCrossRefPubMedCentralGoogle Scholar
  67. 67.
    Stoeckli M, Chaurand P, Hallahan DE et al (2001) Imaging mass spectrometry: a new technology for the analysis of protein expression in mammalian tissues. Nat Med 7(4):493–496PubMedCrossRefPubMedCentralGoogle Scholar
  68. 68.
    Christensen J, Litherland K, Faller T et al (2014) Biodistribution and metabolism studies of lipid nanoparticle-formulated internally [3H]-labeled siRNA in mice. Drug Metab Dispos 42:431–440PubMedCrossRefPubMedCentralGoogle Scholar
  69. 69.
    Bruinen AL, van Oevelen C, Eijkel GB et al (2016) Mass spectrometry imaging of drug related crystal-like structures in formalin-fixed frozen and paraffin embedded rabbit kidney tissue sections. J Am Soc Mass Spectrom 24:117–123CrossRefGoogle Scholar
  70. 70.
    Casadonte R, Caprioli RM (2011) Proteomic analysis of formalin-fixed paraffin-embedded tissue by MALDI imaging mass spectrometry. Nat Protoc 6(11):1695–1709PubMedPubMedCentralCrossRefGoogle Scholar
  71. 71.
    Vismeh R, Waldon DJ, Teffera Y et al (2012) Localization and quantification of drugs in animal tissues by use of desorption electrospray ionization mass spectrometry imaging. Anal Chem 84:5439–5445PubMedCrossRefGoogle Scholar
  72. 72.
    Cornett DS, Frappier SL, Caprioli RM (2008) MALDI-FTICR imaging mass spectrometry of drugs and metabolites in tissue. Anal Chem 80:5648–5653PubMedPubMedCentralCrossRefGoogle Scholar
  73. 73.
    Kolarova L, Vanhara P, Pena-Mendez EM et al (2014) Tissue visualization mediated by nanoparticles: from tissue staining to mass spectrometry tissue profiling and imaging. In: Seifalian A, de Mal A, Kalaskar DM (eds) Nanomedicine. One Central Press, Manchester, UK, pp 468–489Google Scholar
  74. 74.
    Greer T, Sturm R, Li L (2011) Mass spectrometry imaging for drugs and metabolites. J Proteome 74:2617–2631CrossRefGoogle Scholar
  75. 75.
    Mascini NE, Eijkel GB, ter Brugge P et al (2015) The use of mass spectrometry imaging to predict treatment response of patient-derived xenograft models of triple-negative breast cancer. J Proteomic Res 14:1069–1075CrossRefGoogle Scholar
  76. 76.
    Robichaud G, Barry JA, Muddiman DC (2014) IR-MALDESI mass spectrometry imaging of biological tissue sections using ice as a matrix. J Am Soc Mass Spectrom 25:319–328PubMedPubMedCentralCrossRefGoogle Scholar
  77. 77.
    Sampson JS, Hawkridge AM, Muddiman DC (2006) Generation and detection of multiply-charged peptides and proteins by matrix-assisted laser desorption electrospray ionization (MALDESI) Fourier transform ion cyclotron resonance mass spectrometry. J Am Soc Mass Spectrom 17:1712–1716PubMedCrossRefPubMedCentralGoogle Scholar
  78. 78.
    Nazari M, Muddiman DC (2015) Cellular-level mass spectrometry imaging using infrared matrix-assisted laser desorption electrospray ionization (IR-MALDESI) by oversampling. Anal Bioanal Chem 407:2265–2271PubMedCrossRefPubMedCentralGoogle Scholar
  79. 79.
    Jurchen JC, Rubakhin SS, Sweedler JV (2005) MALDI-MS imaging of features snaller than the size of the laser beam. J Am Soc Mass Spectrom 16(10):1654–1659PubMedCrossRefPubMedCentralGoogle Scholar
  80. 80.
    Bokhart MT, Rosen E, Thompson C et al (2015) Quantitative mass spectrometry imaging of emtricitabine in cervical tissue model using infrared matrix-assisted laser desorption electrospray ionization. Anal Bioanal Chem 407(8):2073–2084PubMedCrossRefGoogle Scholar
  81. 81.
    Pockley AG, Foulds GA, Oughton JA et al (2015) Immune cell phenotyping using flow cytometry. Curr Protoc Toxicol 66:18.8.1–18.834CrossRefGoogle Scholar
  82. 82.
    Boland JW, Foulds GA, Ahmedzai SH et al (2014) A preliminary evaluation of the effects of opioids on innate and adaptive human in vitro immune function. BMJ Support Palliat Care 4:357–367PubMedCrossRefGoogle Scholar
  83. 83.
    Caron WP, Lay JC, Fong AM et al (2013) Translational studies of phenotypic probes for the mononuclear phagocyte system and liposomal pharmacology. J Pharmacol Exp Ther 347:599–606PubMedPubMedCentralCrossRefGoogle Scholar
  84. 84.
    Brahmer JR, Drake CG, Wollner I et al (2010) Phase I study of single-agent anti-programmed death-1 (MDX-1106) in refractory solid tumors: safety, clinical activity, pharmacodynamics, and immunologic correlates. J Clin Oncol 28:3167–3175PubMedPubMedCentralCrossRefGoogle Scholar
  85. 85.
    Latek R, Fleener C, Lamian V et al (2009) Assessment of belatacept-mediated costimulation blockade through evaluation of CD80/86-receptor saturation. Transplantation 87:926–933PubMedCrossRefGoogle Scholar
  86. 86.
    Dunphy CH (2004) Applications of flow cytometry and immunohistochemistry to diagnostic hematopathology. Arch Pathol Lab Med 128:1004–1022PubMedGoogle Scholar
  87. 87.
    Al-Mawali A, Gillis D, Lewis I (2009) The role of multiparameter flow cytometry for detection of minimal residual disease in acute myeloid leukemia. Am J Clin Pathol 131(1):16–26PubMedCrossRefGoogle Scholar
  88. 88.
    Muratori M, Forti G, Baldi E (2008) Comparing flow cytometry and fluorescence microscopy for analyzing human sperm DNA fragmentation by TUNEL labeling. Cytometry A 73(9):785–787. https://doi.org/10.1002/cyto.a.20615CrossRefPubMedGoogle Scholar
  89. 89.
    Knetter SM, Tuggle CK, Wannemuehler MJ et al (2014) Organic barn dust extract exposure impairs porcine macrophage function in vitro: implications for respiratoryhealth. Vet Immunol Immunopathol 157(1–2):20–30PubMedCrossRefGoogle Scholar
  90. 90.
    Murtas D, Maric D, De Giorgi V (2013) IRF-1 responsiveness to IFN-_ predicts different cancer immune phenotypes. Br J Cancer 109(1):76–82PubMedPubMedCentralCrossRefGoogle Scholar
  91. 91.
    Barteneva NS, Fasler-Kan E, Vorobjev IA (2012) Imaging flow cytometry: coping with heterogeneity in biological systems. J Histochem Cytochem 60(10):723–733PubMedPubMedCentralCrossRefGoogle Scholar
  92. 92.
    Marangon I, Boggetto N, Ménard-Moyon C et al (2012) Intercellular carbon nanotube translocation assessed by flow cytometry imaging. Nano Lett 12(9):4830–4837PubMedCrossRefGoogle Scholar
  93. 93.
    Wulff S (ed) (2006) Flow cytometry educational guide, 2nd edn. Dako, Fort Collins, CO., CarpinteriaGoogle Scholar
  94. 94.
    Watson JV (1999) The early fluidic and optical physics of cytometry. Cytometry 38:1–14CrossRefGoogle Scholar
  95. 95.
    Orfao A, Ruiz-Arguelles A, Lacombe F et al (1995) Flow cytometry: its applications in hematology. Haematologica 80:69–81PubMedGoogle Scholar
  96. 96.
    Mandy FF, Bergeron M, Minkus T (1995) Principles of flow cytometry. Transfus Sci 16:303–314PubMedCrossRefGoogle Scholar
  97. 97.
    Recktenwald DJ (1993) Introduction to flow cytometry: principles, fluorochromes, instrument set-up, calibration. J Hematother 2:387–394PubMedCrossRefGoogle Scholar
  98. 98.
    Wittwer CT, Knape WA, Bristow MR et al (1989) The quantitative flow cytometric plasma OKT3 assay. Its potential application in cardiac transplantation. Transplantation 48:533–535PubMedCrossRefGoogle Scholar
  99. 99.
    Fulton RJ, McDade RL, Smith PL et al (1997) Advanced multiplexed analysis with the FlowMetrix system. Clin Chem 43:1749–1756PubMedGoogle Scholar
  100. 100.
    Lucas A, Madden AJ, Zamboni WC (2015) Formulation and physiologic factors affecting the pharmacology of carrier-mediated anticancer agents. Expert Opin Drug Metab Toxicol 11(9):1419–1433PubMedCrossRefGoogle Scholar
  101. 101.
    Jain RK, Stylianopoulos T (2010) Delivering nanomedicine to solid tumors. Nat Rev Clin Oncol 7:653–664PubMedPubMedCentralCrossRefGoogle Scholar
  102. 102.
    Hu Y, Rip J, Gaillard PJ et al (2017) The impact of liposomal formulations on the release and brain delivery of methotrexate: an in vivo microdialysis study. J Pharm Sci. https://doi.org/10.1016/j.xphs.2017.03.009
  103. 103.
    Hopkins AM, Moghaddami M, Foster DJ et al (2017) Intracellular CD3+ T lymphocyte teriflunomide concentration is poorly correlated with and has greater variability than unbound plasma teriflunomide concentration. Drug Metab Dispos 45(1):8–16PubMedCrossRefGoogle Scholar
  104. 104.
    Guo P, Yang J, Bielenberg DR et al (2017) A quantitative method for screening and identifying molecular targets for nanomedicine. J Control Release. https://doi.org/10.1016/j.jconrel.2017.03.030
  105. 105.
    Lucas AT, Herity LB, Kornblum ZA et al (2017) Pharmacokinetic and screening studies of the interaction between mononuclear phagocyte system and nanoparticle formulations and colloid forming drugs. Int J Pharm 526(1-2):443–454PubMedCrossRefGoogle Scholar
  106. 106.
    Lucas AT, White TF, Deal AM et al (2017) Profiling the relationship between tumor-associated macrophages and pharmacokinetics of liposomal agents in preclinical murine models. Nanomedicine 13(2):471–482PubMedCrossRefGoogle Scholar
  107. 107.
    Li F, Ulrich M, Jonas M et al (2017) Tumor associated macrophages can contribute to antitumor activity through FcgR-mediated processing of antibody-drug conjugates. Mol Cancer Ther. https://doi.org/10.1158/1535-7163.MCT-17-0019
  108. 108.
    Torok S, Rezeli M, Kelemen O et al (2017) Limited tumor tissue drug penetration contributes to primary resistance against angiogenesis inhibitors. Theranostics 7(2):400–412PubMedPubMedCentralCrossRefGoogle Scholar
  109. 109.
    Fujiwara Y, Masaru F, Manabe S et al (2016) Imaging mass spectrometry for the precise design of antibody-drug conjugates. Sci Rep 6:24954PubMedPubMedCentralCrossRefGoogle Scholar
  110. 110.
    Giordano S, Zucchetti M, Decio A et al (2016) Heterogeneity of paclitaxel distribution in different tumor models assessed by MALDI mass spectrometry imaging. Sci Rep 6:39284PubMedPubMedCentralCrossRefGoogle Scholar
  111. 111.
    Salphati L, Alicke B, Heffron TP et al (2016) Brain distribution and efficacy of the brain penetrant PI3K inhibitor GDC-0084 in orthotopic mouse models of human glioblastoma. Drug Metab Disp 44:1881–1889CrossRefGoogle Scholar
  112. 112.
    Pokorny JL, Calligaris D, Gupta SK et al (2015) The efficacy of the Wee1 inhibitor MK-1775 combined with temozolomide is limited by heterogenous distribution across the blood-brain barrier in glioblastoma. Clin Cancer Res 21(8):1916–1924PubMedPubMedCentralCrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  • Allison N. Schorzman
    • 1
  • Andrew T. Lucas
    • 1
  • John R. Kagel
    • 1
  • William C. Zamboni
    • 1
    Email author
  1. 1.Translational Oncology and Nanoparticle Drug Development Initiative (TOND2I) Lab, UNC Eshelman School of Pharmacy, UNC Lineberger Comprehensive Cancer Center, Carolina Center for Cancer Nanotechnology ExcellenceThe University of North Carolina at Chapel HillChapel HillUSA

Personalised recommendations