Advertisement

The AAPS Journal

, 21:24 | Cite as

Systemic Bioequivalence Is Unlikely to Equal Target Site Bioequivalence for Nanotechnology Oncologic Products

  • Jessie L.-S. AuEmail author
  • Ze Lu
  • Roberto A. Abbiati
  • M. Guillaume Wientjes
Commentary
  • 50 Downloads

Abstract

Approval of generic drugs by the US Food and Drug Administration (FDA) requires the product to be pharmaceutically equivalent to the reference listed drug (RLD) and demonstrate bioequivalence (BE) in effectiveness when administered to patients under the conditions in the RLD product labeling. Effectiveness is determined by drug exposure at the target sites. However, since such measurement is usually unavailable, systemic exposure is assumed to equal target site exposure and systemic BE to equal target site BE. This assumption, while it often applies to small molecule drug products that are readily dissolved in biological fluids and systemically absorbed, is unlikely to apply to nanotechnology products (NP) that exist as heterogeneous systems and are subjected to dimension- and material-dependent changes. This commentary provides an overview of the intersecting and spatial-dependent processes and variables governing the delivery and residence of oncologic NP in solid tumors. In order to provide a quantitative perspective of the collective effects of these processes, we used quantitative systems pharmacology (QSP) multi-scale modeling to capture the physicochemical and biological events on several scales (whole-body, organ/suborgan, cell/subcellular, spatial locations, time). QSP is an emerging field that entails using modeling and computation to facilitate drug development; an analogous approach (i.e., model-informed drug development) is advocated by to FDA. The QSP model-based simulations illustrated that small changes in NP attributes (e.g., size variations during manufacturing, interactions with proteins in biological milieu) could lead to disproportionately large differences in target site exposure, rending systemic BE unlikely to equal target site BE.

KEY WORDS

FDA nanotechnology  quantitative systems pharmacology systemic bioequivalence target site bioequivalence 

Abbreviations

ANDA

Abbreviated New Drug Application

API

Active pharmaceutical ingredient

AUC

Area under concentration-time-curve

BE

Bioequivalence

Cmax

Maximum concentration

CQA

Critical quality attribute

C-T

Concentration-time

ECM

Extracellular matrix

FDA

US Food and Drug Administration

kon, koff, and kin

Respective rate constants of NP binding and release from cell membrane, and internalization

NP

Nanotechnology products

PC

Protein corona

PK

Pharmacokinetic

QSP

Quantitative systems pharmacology

RES

Reticuloendothelial system

RLD

Reference listed drug.

Notes

Funding Information

This work was supported in part by research grants R01GM100487 from the National Institute of General Medical Sciences and R01EB015253 from the National Institute of Biomedical Imaging and Bioengineering, NIH, DHHS, the Mosier Endowed Chair in Pharmaceutical Sciences at University of Oklahoma Health Sciences Center, and the Chair in Systems Pharmacology at Taipei Medical University.

Compliance with Ethical Standards

Conflict of Interest

JA, GW and ZL have ownership interests in Optimum Therapeutics LLC, which is involved in developing cancer nanotechnologies.

References

  1. 1.
    Fang L, Kim MJ, Li Z, Wang Y, DiLiberti CE, Au J, et al. Model-informed drug development and review for generic products: summary of FDA Public Workshop. Clin Pharmacol Ther. 2018;104:27–30.CrossRefGoogle Scholar
  2. 2.
    Sorger PK, Allerheiligen SRB, Abernethy DR, Altman RB, Brouwer KLR, Califano A, et al. Quantitative and systems pharmacology in the post-genomic era: new approaches to discovering drugs and understanding therapeutic mechanisms. An NIH White Paper by the QSP Workshop. Group. 2011.Google Scholar
  3. 3.
    Lionberger R. Using quantitative methods and modeling to transform generic drug development and review. https://www.fda.gov/downloads/Drugs/NewsEvents/UCM582148.pdf. 2017. Accessed 31 Oct 2018.
  4. 4.
    USFDA. Guidance for industry: considering whether an FDA-regulated product involves the application of nanotechnology. https://www.fda.gov/downloads/RegulatoryInformation/Guidances/UCM401695.pdf. 2014. Accessed 31 Oct 2018.
  5. 5.
    USFDA. Guidance for industry: drug products, including biological products, that contain nanomaterials. https://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM588857.pdf. 2017. Accessed 31 Oct 2018.
  6. 6.
    Zheng N, Sun DD, Zou P, Jiang W. Scientific and regulatory considerations for generic complex drug products containing nanomaterials. AAPS J. 2017;19:619–31.CrossRefGoogle Scholar
  7. 7.
    Bobo D, Robinson KJ, Islam J, Thurecht KJ, Corrie SR. Nanoparticle-based medicines: a review of FDA-approved materials and clinical trials to date. Pharm Res. 2016;33:2373–87.CrossRefGoogle Scholar
  8. 8.
    D’Mello SR, Cruz CN, Chen ML, Kapoor M, Lee SL, Tyner KM. The evolving landscape of drug products containing nanomaterials in the United States. Nat Nanotechnol. 2017;12:523–9.CrossRefGoogle Scholar
  9. 9.
    USFDA. Drugs@FDA database. https://www.fda.gov/Drugs/InformationOnDrugs/ucm135821.htm 2018. Accessed 10 Dec 2018.
  10. 10.
    Johnson EM, Ojwang JO, Szekely A, Wallace TL, Warnock DW. Comparison of in vitro antifungal activities of free and liposome-encapsulated nystatin with those of four amphotericin B formulations. Antimicrob Agents Chemother. 1998;42:1412–6.CrossRefGoogle Scholar
  11. 11.
    Clark JM, Whitney RR, Olsen SJ, George RJ, Swerdel MR, Kunselman L, et al. Amphotericin B lipid complex therapy of experimental fungal infections in mice. Antimicrob Agents Chemother. 1991;35:615–21.CrossRefGoogle Scholar
  12. 12.
    Usmani SS, Bedi G, Samuel JS, Singh S, Kalra S, Kumar P, et al. THPdb: database of FDA-approved peptide and protein therapeutics. PLoS One. 2017;12:e0181748.CrossRefGoogle Scholar
  13. 13.
    USFDA. Generic drugs: questions & answers. https://www.fda.gov/drugs/resourcesforyou/consumers/questionsanswers/ucm100100.htm. 2018. Accessed 31 Oct 2018.
  14. 14.
    Code of Federal Regulations. Applications for FDA approval to market a new drug - definations, 21 CFR 314.3. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=314.3. 2018. Accessed 31 Oct 2018.
  15. 15.
    Code of Federal Regulations. Types of evidence to measure bioavailability or establish bioequivalence, 21 CFR 320.24. https://www.accessdata.fda.gov/scripts/cdrh/cfdocs/cfcfr/CFRSearch.cfm?fr=320.24. 2018. Accessed 31 Oct 2018.
  16. 16.
    USFDA. Guidance for industry: submission of summary bioequivalence data for ANDAs. https://www.fda.gov/downloads/Drugs/.../Guidances/UCM134846.pdf. 2011. Accessed 31 Oct 2018.
  17. 17.
    USFDA. Guidance for industry: bioequivalence studies with pharmacokinetic endpoints for drugs submitted under an ANDA. https://www.fda.gov/downloads/drugs/guidances/ucm377465.pdf. 2013. Accessed 31 Oct 2018.
  18. 18.
    USFDA. Guidance for industry: statistical approaches to establishing bioequivalence. https://www.fda.gov/downloads/drugs/guidances/ucm070244.pdf. 2001. Accessed 31 Oct 2018.
  19. 19.
    USFDA. Reducing the hurdles for complex generic drug development. https://www.fda.gov/NewsEvents/Newsroom/FDAVoices/ucm612010.htm. 2017. Accessed 31 Oct 2018.
  20. 20.
    USFDA. Guidance for Industry: formal meetings between FDA and ANDA applicants of complex products under GDUFA. https://www.fda.gov/downloads/drugs/guidancecomplianceregulatoryinformation/guidances/ucm578366.pdf. 2017. Accessed 31 Oct 2018.
  21. 21.
    USFDA. Guidance for industry: use of nanomaterials in food for animals. https://www.fda.gov/downloads/AnimalVeterinary/GuidanceComplianceEnforcement/GuidanceforIndustry/UCM401508.pdf. 2015. Accessed 31 Oct 2018.
  22. 22.
    USFDA. Guidance for industry: assessing the effects of significant manufacturing process changes, including emerging technologies, on the safety and regulatory status of food ingredients and food contact substances, including food ingredients that are color additives. https://www.fda.gov/downloads/Food/GuidanceRegulation/GuidanceDocumentsRegulatoryInformation/UCM616225.pdf. 2014. Accessed 31 Oct 2018.
  23. 23.
    USFDA. Guidance for industry: safety of nanomatrials in comestic products. https://www.fda.gov/downloads/Cosmetics/GuidanceRegulation/GuidanceDocuments/UCM300932.pdf. 2014. Accessed 31 Oct 2018.
  24. 24.
    USFDA. Guidance for industry: liposome drug products chemistry, manufacturing, and controls; human pharmacokinetics and bioavailability; and labeling documentation. https://www.fda.gov/downloads/drugs/guidances/ucm070570.pdf . 2018. Accessed 31 Oct 2018.
  25. 25.
    USFDA. Orange Book preface. https://www.fda.gov/drugs/developmentapprovalprocess/ucm079068.htm. 2018. Accessed 31 Oct 2018.
  26. 26.
    Li Y, Wang J, Wientjes MG, Au JL. Delivery of nanomedicines to extracellular and intracellular compartments of a solid tumor. Adv Drug Deliv Rev. 2012;64:29–39.CrossRefGoogle Scholar
  27. 27.
    Au JL, Jang SH, Wientjes MG. Clinical aspects of drug delivery to tumors. J Control Release. 2002;78:81–95.CrossRefGoogle Scholar
  28. 28.
    Au JL, Yeung BZ, Wientjes MG, Lu Z, Wientjes MG. Delivery of cancer therapeutics to extracellular and intracellular targets: determinants, barriers, challenges and opportunities. Adv Drug Deliv Rev. 2016;97:280–301.CrossRefGoogle Scholar
  29. 29.
    Au JL, Jang SH, Zheng J, Chen CT, Song S, Hu L, et al. Determinants of drug delivery and transport to solid tumors. J Control Release. 2001;74:31–46.CrossRefGoogle Scholar
  30. 30.
    Au JL, Lu Z, Wientjes MG. Versatility of particulate carriers: development of pharmacodynamically optimized drug-loaded microparticles for treatment of peritoneal cancer. AAPS J. 2015;17:1065–79.CrossRefGoogle Scholar
  31. 31.
    Jang SH, Wientjes MG, Lu D, Au JL. Drug delivery and transport to solid tumors. Pharm Res. 2003;20:1337–50.CrossRefGoogle Scholar
  32. 32.
    Lu Z, Wientjes MG, Au JL. Development of drug-loaded particles for intraperitoneal therapy. In: Wim P. Ceelen, Edward Levine, editors. Intraperitoneal cancer therapy: principles and practice. CRC Press; 2015. p. 331–344.Google Scholar
  33. 33.
    Lu Z, Wang J, Wientjes MG, Au JL. Intraperitoneal therapy for peritoneal cancer. Future Oncol. 2010;6:1625–41.CrossRefGoogle Scholar
  34. 34.
    Wang J, Lu Z, Wientjes MG, Au JL. Delivery of siRNA therapeutics: barriers and carriers. AAPS J. 2010;12:492–503.CrossRefGoogle Scholar
  35. 35.
    Wang J, Lu Z, Gao Y, Wientjes MG, Au JL. Improving delivery and efficacy of nanomedicines in solid tumors: role of tumor priming. Nanomedicine (Lond). 2011;6:1605–20.CrossRefGoogle Scholar
  36. 36.
    Au JL, Abbiati RA, Wientjes MG, Lu Z. Target site delivery and residence of nano-medicines: application of quantitative systems pharmacology. Pharmacol.Rev. (Accepted).Google Scholar
  37. 37.
    Nguyen VH, Lee BJ. Protein corona: a new approach for nanomedicine design. Int J Nanomedicine. 2017;12:3137–51.CrossRefGoogle Scholar
  38. 38.
    Strojan K, Leonardi A, Bregar VB, Krizaj I, Svete J, Pavlin M. Dispersion of nanoparticles in different media importantly determines the composition of their protein corona. PLoS One. 2017;12:e0169552.CrossRefGoogle Scholar
  39. 39.
    Corbo C, Molinaro R, Tabatabaei M, Farokhzad OC, Mahmoudi M. Personalized protein corona on nanoparticles and its clinical implications. Biomater Sci. 2017;5:378–87.CrossRefGoogle Scholar
  40. 40.
    Barbero F, Russo L, Vitali M, Piella J, Salvo I, Borrajo ML, et al. Formation of the protein corona: the interface between nanoparticles and the immune system. Semin Immunol. 2017;34:52–60.CrossRefGoogle Scholar
  41. 41.
    Lai ZW, Yan Y, Caruso F, Nice EC. Emerging techniques in proteomics for probing nano-bio interactions. ACS Nano. 2012;6:10438–48.CrossRefGoogle Scholar
  42. 42.
    Ahsan SM, Rao CM, Ahmad MF. Nanoparticle-protein interaction: the significance and role of protein corona. Adv Exp Med Biol. 2018;1048:175–98.CrossRefGoogle Scholar
  43. 43.
    Treuel L, Nienhaus GU. Toward a molecular understanding of nanoparticle-protein interactions. Biophys Rev. 2012;4:137–47.CrossRefGoogle Scholar
  44. 44.
    Walkey CD, Chan WC. Understanding and controlling the interaction of nanomaterials with proteins in a physiological environment. Chem Soc Rev. 2012;41:2780–99.CrossRefGoogle Scholar
  45. 45.
    Setyawati MI, Tay CY, Docter D, Stauber RH, Leong DT. Understanding and exploiting nanoparticles’ intimacy with the blood vessel and blood. Chem Soc Rev. 2015;44:8174–99.CrossRefGoogle Scholar
  46. 46.
    Monopoli MP, Aberg C, Salvati A, Dawson KA. Biomolecular coronas provide the biological identity of nanosized materials. Nat Nanotechnol. 2012;7:779–86.CrossRefGoogle Scholar
  47. 47.
    Yang ST, Liu Y, Wang YW, Cao A. Biosafety and bioapplication of nanomaterials by designing protein-nanoparticle interactions. Small. 2013;9:1635–53.CrossRefGoogle Scholar
  48. 48.
    Mariam J, Sivakami S, Dongre PM. Albumin corona on nanoparticles - a strategic approach in drug delivery. Drug Deliv. 2015:1–9.Google Scholar
  49. 49.
    Monteiro-Riviere NA, Samberg ME, Oldenburg SJ, Riviere JE. Protein binding modulates the cellular uptake of silver nanoparticles into human cells: implications for in vitro to in vivo extrapolations? Toxicol Lett. 2013;220:286–93.CrossRefGoogle Scholar
  50. 50.
    Bonvin D, Aschauer U, Alexander DTL, Chiappe D, Moniatte M, Hofmann H, et al. Protein corona: impact of lymph versus blood in a complex in vitro environment. Small. 2017;13.Google Scholar
  51. 51.
    Vilanova O, Mittag JJ, Kelly PM, Milani S, Dawson KA, Radler JO, et al. Understanding the kinetics of protein-nanoparticle corona formation. ACS Nano. 2016;10:10842–50.CrossRefGoogle Scholar
  52. 52.
    Hadjidemetriou M, Al-Ahmady Z, Kostarelos K. Time-evolution of in vivo protein corona onto blood-circulating PEGylated liposomal doxorubicin (DOXIL) nanoparticles. Nanoscale. 2016;8:6948–57.CrossRefGoogle Scholar
  53. 53.
    Chen F, Wang G, Griffin JI, Brenneman B, Banda NK, Holers VM, et al. Complement proteins bind to nanoparticle protein corona and undergo dynamic exchange in vivo. Nat Nanotechnol. 2017;12:387–93.CrossRefGoogle Scholar
  54. 54.
    Tenzer S, Docter D, Kuharev J, Musyanovych A, Fetz V, Hecht R, et al. Rapid formation of plasma protein corona critically affects nanoparticle pathophysiology. Nat Nanotechnol. 2013;8:772–81.CrossRefGoogle Scholar
  55. 55.
    Kurtz-Chalot A, Klein J, Pourchez J, Boudars D, Bin V, Alcantara GB, et al. Adsorption at cell surface and cellular uptake of silica nanoparticles with different surface chemical functionalizations: impact on cytotoxicity. J NanoparticleRes. 2014;16:2738.CrossRefGoogle Scholar
  56. 56.
    Behzadi S, Serpooshan V, Sakhtianchi R, Muller B, Landfester K, Crespy D, et al. Protein corona change the drug release profile of nanocarriers: the “overlooked” factor at the nanobio interface. Colloids Surf B Biointerfaces. 2014;123:143–9.CrossRefGoogle Scholar
  57. 57.
    Lara S, Alnasser F, Polo E, Garry D, Lo Giudice MC, Hristov DR, et al. Identification of receptor binding to the biomolecular corona of nanoparticles. ACS Nano. 2017;11:1884–93.CrossRefGoogle Scholar
  58. 58.
    McConnell KI, Shamsudeen S, Meraz IM, Mahadevan TS, Ziemys A, Rees P, et al. Reduced cationic nanoparticle cytotoxicity based on serum masking of surface potential. J Biomed Nanotechnol. 2016;12:154–64.CrossRefGoogle Scholar
  59. 59.
    Yin H, Chen R, Casey P, Ke PC, Davis T, Chen C. Reducing the cytotoxicity of ZnO nanoparticles by a pre-formed protein corona in a supplemented cell culture medium. RSC Adv. 2015;5:73963–73.CrossRefGoogle Scholar
  60. 60.
    Deng ZJ, Liang M, Monteiro M, Toth I, Minchin RF. Nanoparticle-induced unfolding of fibrinogen promotes Mac-1 receptor activation and inflammation. Nat Nanotechnol. 2011;6:39–44.CrossRefGoogle Scholar
  61. 61.
    Mirsadeghi S, Dinarvand R, Ghahremani MH, Hormozi-Nezhad MR, Mahmoudi Z, Hajipour MJ, et al. Protein corona composition of gold nanoparticles/nanorods affects amyloid beta fibrillation process. Nanoscale. 2015;7:5004–13.CrossRefGoogle Scholar
  62. 62.
    Muller LK, Simon J, Rosenauer C, Mailander V, Morsbach S, Landfester K. The transferability from animal models to humans: challenges regarding aggregation and protein corona formation of nanoparticles. Biomacromolecules. 2018;19:374–85.CrossRefGoogle Scholar
  63. 63.
    Hanash S. Disease proteomics. Nature. 2003;422:226–32.CrossRefGoogle Scholar
  64. 64.
    Conrads TP, Fusaro VA, Ross S, Johann D, Rajapakse V, Hitt BA, et al. High-resolution serum proteomic features for ovarian cancer detection. Endocr Relat Cancer. 2004;11:163–78.CrossRefGoogle Scholar
  65. 65.
    Caputo D, Papi M, Coppola R, Palchetti S, Digiacomo L, Caracciolo G, et al. A protein corona-enabled blood test for early cancer detection. Nanoscale. 2017;9:349–54.CrossRefGoogle Scholar
  66. 66.
    Au JL, Guo P, Gao Y, Lu Z, Wientjes MG, Tsai M, et al. Multiscale tumor spatiokinetic model for intraperitoneal therapy. AAPS J. 2014;16:424–39.CrossRefGoogle Scholar
  67. 67.
    Abbiati RA, Au JL. Quantitative systems pharmacology on cancer drug delivery to target sites: application of chemical engineering tools. In: Manca D, editor. Quantitative systems pharmacology: models and model-based systems with applications. Elsevier; 2018. p. 239–270.Google Scholar
  68. 68.
    Gao Y, Li M, Chen B, Shen Z, Guo P, Wientjes MG, et al. Predictive models of diffusive nanoparticle transport in 3-dimensional tumor cell spheroids. AAPS J. 2013;15:816–31.CrossRefGoogle Scholar
  69. 69.
    Gillies RJ, Schornack PA, Secomb TW, Raghunand N. Causes and effects of heterogeneous perfusion in tumors. Neoplasia. 1999;1:197–207.CrossRefGoogle Scholar
  70. 70.
    Nitta N, Takakusagi Y, Kokuryo D, Shibata S, Tomita A, Higashi T, et al. Intratumoral evaluation of 3D microvasculature and nanoparticle distribution using a gadolinium-dendron modified nano-liposomal contrast agent with magnetic resonance micro-imaging. Nanomedicine. 2018;14:1315–24.CrossRefGoogle Scholar
  71. 71.
    Searle EJ, Telfer BA, Mukherjee D, Forster DM, Davies BR, Williams KJ, et al. Akt inhibition improves long-term tumour control following radiotherapy by altering the microenvironment. EMBO Mol Med. 2017;9:1646–59.CrossRefGoogle Scholar
  72. 72.
    Stapleton S, Milosevic M, Allen C, Zheng J, Dunne M, Yeung I, et al. A mathematical model of the enhanced permeability and retention effect for liposome transport in solid tumors. PLoS One. 2013;8:e81157.CrossRefGoogle Scholar
  73. 73.
    Deen WM. Hindered transport of large molecules in liquid-filled pores. AICHE J. 1987;33:1409–25.CrossRefGoogle Scholar
  74. 74.
    Meijer EF, Baish JW, Padera TP, Fukumura D. Measuring vascular permeability in vivo. Methods Mol Biol. 2016;1458:71–85.CrossRefGoogle Scholar
  75. 75.
    Chen Q, Krol A, Wright A, Needham D, Dewhirst MW, Yuan F. Tumor microvascular permeability is a key determinant for antivascular effects of doxorubicin encapsulated in a temperature sensitive liposome. Int J Hyperth. 2008;24:475–82.CrossRefGoogle Scholar
  76. 76.
    Yuan F, Leunig M, Huang SK, Berk DA, Papahakjopoulos D, Jain RK. Microvascular permeability and interstitial penetration of sterically stabilized (stealth) liposomes in a human tumor xenograft. Cancer Res. 1994;54:3352–6.PubMedGoogle Scholar
  77. 77.
    Gerlowski LE, Jain RK. Microvascular permeability of normal and neoplastic tissues. Microvasc Res. 1986;31:288–305.CrossRefGoogle Scholar
  78. 78.
    Baxter LT, Jain RK. Transport of fluid and macromolecules in tumors. I. Role of interstitial pressure and convection. Microvasc Res. 1989;37:77–104.CrossRefGoogle Scholar
  79. 79.
    Stapleton S, Milosevic M, Tannock IF, Allen C, Jaffray DA. The intra-tumoral relationship between microcirculation, interstitial fluid pressure and liposome accumulation. J Control Release. 2015;211:163–70.CrossRefGoogle Scholar
  80. 80.
    Jain RK, Tong RT, Munn LL. Effect of vascular normalization, by antiangiogenic therapy on interstitial hypertension, peritumor edema, and lymphatic metastasis: insights from a mathematical model. Cancer Res. 2007;67:2729–35.CrossRefGoogle Scholar
  81. 81.
    Baxter LT, Jain RK. Transport of fluid and macromolecules in tumors. II. Role of heterogeneous perfusion and lymphatics. Microvasc Res. 1990;40:246–63.CrossRefGoogle Scholar
  82. 82.
    Reed RK, Townsley MI, Taylor AE. Estimation of capillary reflection coefficients and unique PS products in dog paw. Am J Phys. 1989;257:H1037–41.Google Scholar
  83. 83.
    Ballard K, Perl W. Osmotic reflection coefficients of canine subcutaneous adipose tissue endothelium. Microvasc Res. 1978;16:224–36.CrossRefGoogle Scholar
  84. 84.
    Blanco E, Shen H, Ferrari M. Principles of nanoparticle design for overcoming biological barriers to drug delivery. Nat Biotechnol. 2015;33:941–51.CrossRefGoogle Scholar
  85. 85.
    Celgene Corporation and Abraxis BioScience LLC Citizen Petition. https://www.regulations.gov/contentStreamer?documentId=FDA-2015-P-0732- 0001&attachmentNumber=1&contentType=pdf. 2015. Accessed 31 Oct 2018.
  86. 86.
    Desai, N. P., Soon-Shiong, P., and Trieu, V. Compositions and methods of delivery of pharmacological agents. U.S. Patent 7,820,788. 2010.Google Scholar
  87. 87.
    Desai, N. P., Soon-Shiong, P., and Trieu, V. Compositions and methods of delivery of pharmacological agents. U.S. Patent 8,138,229. 2012.Google Scholar
  88. 88.
    Desai, N. P. and Soon-Shiong, P. Formulations of pharmacological agents, methods for the preparation thereof and methods for the use thereof. U.S. Patent 8,853,260. 2014.Google Scholar
  89. 89.
    Abraxane® Package Insert. https://media.celgene.com/content/uploads/abraxane-pi.pdf 2018. Accessed 31 Oct 2018.
  90. 90.
    Lu D, Wientjes MG, Lu Z, Au JL. Tumor priming enhances delivery and efficacy of nanomedicines. J Pharmacol Exp Ther. 2007;322:80–8.CrossRefGoogle Scholar
  91. 91.
    Lomis N, Westfall S, Farahdel L, Malhotra M, Shum-Tim D, Prakash S. Human serum albumin nanoparticles for use in cancer drug delivery: process optimization and in vitro characterization. Nanomaterials (Basel). 2016;6:116.CrossRefGoogle Scholar

Copyright information

© American Association of Pharmaceutical Scientists 2019

Authors and Affiliations

  • Jessie L.-S. Au
    • 1
    • 2
    • 3
    • 4
    Email author
  • Ze Lu
    • 1
    • 2
  • Roberto A. Abbiati
    • 1
    • 3
  • M. Guillaume Wientjes
    • 1
    • 2
  1. 1.Institute of Quantitative Systems PharmacologyCarlsbadUSA
  2. 2.Optimum Therapeutics LLCCarlsbadUSA
  3. 3.Department of Pharmaceutical SciencesUniversity of OklahomaOklahoma CityUSA
  4. 4.College of PharmacyTaipei Medical UniversityTaipeiRepublic of China

Personalised recommendations