High-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsules

Handle URI:
http://hdl.handle.net/10754/626706
Title:
High-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsules
Authors:
Ray, Aniruddha; Li, Shuoran; Segura, Tatiana; Ozcan, Aydogan ( 0000-0002-0717-683X )
Abstract:
Design and synthesis of degradable nanoparticles are very important in drug delivery and biosensing fields. Although accurate assessment of nanoparticle degradation rate would improve the characterization and optimization of drug delivery vehicles, current methods rely on estimating the size of the particles at discrete points over time using, for example, electron microscopy or dynamic light scattering (DLS), among other techniques, all of which have drawbacks and practical limitations. There is a significant need for a high-throughput and cost-effective technology to accurately monitor nanoparticle degradation as a function of time and using small amounts of sample. To address this need, here we present two different computational imaging-based methods for monitoring and quantification of nanoparticle degradation. The first method is suitable for discrete testing, where a computational holographic microscope is designed to track the size changes of protease-sensitive protein-core nanoparticles following degradation, by periodically sampling a subset of particles mixed with proteases. In the second method, a sandwich structure was utilized to observe, in real-time, the change in the properties of liquid nanolenses that were self-assembled around degrading nanoparticles, permitting continuous monitoring and quantification of the degradation process. These cost-effective holographic imaging based techniques enable high-throughput monitoring of the degradation of any type of nanoparticle, using an extremely small amount of sample volume that is at least 3 orders of magnitude smaller than what is required by, for example, DLS-based techniques.
Citation:
Ray A, Li S, Segura T, Ozcan A (2017) High-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsules. ACS Photonics 4: 1216–1224. Available: http://dx.doi.org/10.1021/acsphotonics.7b00122.
Publisher:
American Chemical Society (ACS)
Journal:
ACS Photonics
Issue Date:
25-Apr-2017
DOI:
10.1021/acsphotonics.7b00122
Type:
Article
ISSN:
2330-4022; 2330-4022
Sponsors:
The Ozcan Research Group at UCLA gratefully acknowledges the support of the Presidential Early Career Award for Scientists and Engineers (PECASE), the Army Research Office (ARO; W911NF-13-1-0419 and W911NF-13-1-0197), the ARO Life Sciences Division, the National Science Foundation (NSF) CBET Division Biophotonics Program, the NSF Emerging Frontiers in Research and Innovation (EFRI) Award, the NSF EAGER Award, the NSF INSPIRE Award, NSF Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Program, Office of Naval Research (ONR), the National Institutes of Health (NIH), the Howard Hughes Medical Institute (HHMI), Vodafone Americas Foundation, the Mary Kay Foundation, Steven & Alexandra Cohen Foundation, and KAUST. This work is based upon research performed in a laboratory renovated by the National Science Foundation under Grant No. 0963183, which is an award funded under the American Recovery and Reinvestment Act of 2009 (ARRA). The authors also acknowledge Alborz Feizi for his help with the LabVIEW code, Derek Tseng for his help with the production of 3D CAD images, and Dr. Euan McLeod for his help with the particle sizing code. The Segura Laboratory gratefully acknowledges the funding from the National Institutes of Health R01-NS079691.
Appears in Collections:
Publications Acknowledging KAUST Support

Full metadata record

DC FieldValue Language
dc.contributor.authorRay, Aniruddhaen
dc.contributor.authorLi, Shuoranen
dc.contributor.authorSegura, Tatianaen
dc.contributor.authorOzcan, Aydoganen
dc.date.accessioned2018-01-04T07:51:40Z-
dc.date.available2018-01-04T07:51:40Z-
dc.date.issued2017-04-25en
dc.identifier.citationRay A, Li S, Segura T, Ozcan A (2017) High-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsules. ACS Photonics 4: 1216–1224. Available: http://dx.doi.org/10.1021/acsphotonics.7b00122.en
dc.identifier.issn2330-4022en
dc.identifier.issn2330-4022en
dc.identifier.doi10.1021/acsphotonics.7b00122en
dc.identifier.urihttp://hdl.handle.net/10754/626706-
dc.description.abstractDesign and synthesis of degradable nanoparticles are very important in drug delivery and biosensing fields. Although accurate assessment of nanoparticle degradation rate would improve the characterization and optimization of drug delivery vehicles, current methods rely on estimating the size of the particles at discrete points over time using, for example, electron microscopy or dynamic light scattering (DLS), among other techniques, all of which have drawbacks and practical limitations. There is a significant need for a high-throughput and cost-effective technology to accurately monitor nanoparticle degradation as a function of time and using small amounts of sample. To address this need, here we present two different computational imaging-based methods for monitoring and quantification of nanoparticle degradation. The first method is suitable for discrete testing, where a computational holographic microscope is designed to track the size changes of protease-sensitive protein-core nanoparticles following degradation, by periodically sampling a subset of particles mixed with proteases. In the second method, a sandwich structure was utilized to observe, in real-time, the change in the properties of liquid nanolenses that were self-assembled around degrading nanoparticles, permitting continuous monitoring and quantification of the degradation process. These cost-effective holographic imaging based techniques enable high-throughput monitoring of the degradation of any type of nanoparticle, using an extremely small amount of sample volume that is at least 3 orders of magnitude smaller than what is required by, for example, DLS-based techniques.en
dc.description.sponsorshipThe Ozcan Research Group at UCLA gratefully acknowledges the support of the Presidential Early Career Award for Scientists and Engineers (PECASE), the Army Research Office (ARO; W911NF-13-1-0419 and W911NF-13-1-0197), the ARO Life Sciences Division, the National Science Foundation (NSF) CBET Division Biophotonics Program, the NSF Emerging Frontiers in Research and Innovation (EFRI) Award, the NSF EAGER Award, the NSF INSPIRE Award, NSF Partnerships for Innovation: Building Innovation Capacity (PFI:BIC) Program, Office of Naval Research (ONR), the National Institutes of Health (NIH), the Howard Hughes Medical Institute (HHMI), Vodafone Americas Foundation, the Mary Kay Foundation, Steven & Alexandra Cohen Foundation, and KAUST. This work is based upon research performed in a laboratory renovated by the National Science Foundation under Grant No. 0963183, which is an award funded under the American Recovery and Reinvestment Act of 2009 (ARRA). The authors also acknowledge Alborz Feizi for his help with the LabVIEW code, Derek Tseng for his help with the production of 3D CAD images, and Dr. Euan McLeod for his help with the particle sizing code. The Segura Laboratory gratefully acknowledges the funding from the National Institutes of Health R01-NS079691.en
dc.publisherAmerican Chemical Society (ACS)en
dc.subjectcomputational microscopyen
dc.subjectdrug deliveryen
dc.subjectholographic microscopyen
dc.subjectlensless imagingen
dc.subjectnanoparticle degradationen
dc.subjecton-chip imagingen
dc.subjectprotease-mediated degradationen
dc.titleHigh-Throughput Quantification of Nanoparticle Degradation Using Computational Microscopy and Its Application to Drug Delivery Nanocapsulesen
dc.typeArticleen
dc.identifier.journalACS Photonicsen
dc.contributor.institutionBioengineering Department, University of California, Los Angeles, California 90095, United Statesen
dc.contributor.institutionElectrical Engineering Department, University of California, Los Angeles, California 90095, United Statesen
dc.contributor.institutionDepartment of Chemical and Biomolecular Engineering, University of California, Los Angeles, California 90095, United Statesen
dc.contributor.institutionCalifornia NanoSystems Institute (CNSI), University of California, Los Angeles, California 90095, United Statesen
dc.contributor.institutionDepartment of Medicine, Dermatology, University of California, Los Angeles, California 90095, United Statesen
dc.contributor.institutionDepartment of Surgery, David Geffen School of Medicine, University of California, Los Angeles, California 90095, United Statesen
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