{"id":{"repo_id":"uiuc","oai_identifier":"oai:www.ideals.illinois.edu:2142/99493"},"canonical_url":"https://search.dev.ndltd.org/etd/uiuc/oai:www.ideals.illinois.edu:2142/99493","repository":{"repo_id":"uiuc","name":"University of Illinois - Urbana-Champaign","base_url":"https://www.ideals.illinois.edu/oai-pmh"},"display":{"title":"Multiplexed immunoassay development for precision medicine diagnostics and protein characterization using silicon photonic microring resonators","abstract":"Precision medicine offers the potential to transform healthcare by utilizing detailed biochemical insights into a patient’s disease state for therapeutic decision-making. Numerous disease specific biomarkers have emerged, but few are as dynamic and information-rich as those associated with the immune system. The immune system operates through a pathogen specific, biologically conserved response to coordinate detection and clearance. Immune cell associated signaling molecules, cytokines, modulate the immune response and their associated dynamics are ideal for monitoring host response. Profiling the immune response correlated to system perturbations provides a clinically valuable result for functional diagnostics. Immunoassays are a powerful tool to quantitatively measure cytokine levels in biological solutions. While enzyme-linked immunosorbent assays have been the gold standard technique, multiplexed approaches have rapidly developed in response to the need for more complex biological signatures to precisely describe disease states. While many of these assays demonstrate robust intra-assay performance, variable inter-assay and multi-center performance is a consistent issue. Additionally, the inherent physiological fluctuations from patient-specific, but disease independent sources have largely hindered the clinical implementation of these assays. This dissertation describes promising approaches to address the analytical and clinical challenges facing immune profiling guided precision medicine. Chapter 2 outlines the fundamental requirements for developing robust multiplexed immunoassays with silicon photonic microring resonator arrays. Using this basic protocol for assay development, Chapters 3 and 4 describe two distinct approaches toward diagnosing and monitoring infectious disease related states. Chapter 3 focuses on designing a functional diagnostic immunoassay for latent tuberculosis infection (LTBI) with the absolute assay output normalized by each subject’s basal immune response. Using this personalized normalization strategy, machine learning feature selection yielded promising results toward a diagnostic signature. Chapter 4 describes a multiplexed immune profiling approach incorporating rich temporal dynamics throughout the treatment of sepsis. The rapid immunoassay provides the cytokine trajectories of each subject throughout treatment, illustrating the dynamic changes accompanying immune challenge and subsequent therapeutic intervention. Chapter 5 leverages the near-real time monitoring capabilities of the platform to characterize the differential binding kinetics of monomeric and dimeric therapeutic antibodies as a means of structural characterization. Finally, Chapter 6 discusses the future of the LTBI diagnostic signature development, outlining a significant expansion of the biomarker panel, informatic analysis, and subject study enrollment.","abstract_html":"Precision medicine offers the potential to transform healthcare by utilizing detailed biochemical insights into a patient’s disease state for therapeutic decision-making. Numerous disease specific biomarkers have emerged, but few are as dynamic and information-rich as those associated with the immune system. The immune system operates through a pathogen specific, biologically conserved response to coordinate detection and clearance. Immune cell associated signaling molecules, cytokines, modulate the immune response and their associated dynamics are ideal for monitoring host response. Profiling the immune response correlated to system perturbations provides a clinically valuable result for functional diagnostics. Immunoassays are a powerful tool to quantitatively measure cytokine levels in biological solutions. While enzyme-linked immunosorbent assays have been the gold standard technique, multiplexed approaches have rapidly developed in response to the need for more complex biological signatures to precisely describe disease states. While many of these assays demonstrate robust intra-assay performance, variable inter-assay and multi-center performance is a consistent issue. Additionally, the inherent physiological fluctuations from patient-specific, but disease independent sources have largely hindered the clinical implementation of these assays. This dissertation describes promising approaches to address the analytical and clinical challenges facing immune profiling guided precision medicine. Chapter 2 outlines the fundamental requirements for developing robust multiplexed immunoassays with silicon photonic microring resonator arrays. Using this basic protocol for assay development, Chapters 3 and 4 describe two distinct approaches toward diagnosing and monitoring infectious disease related states. Chapter 3 focuses on designing a functional diagnostic immunoassay for latent tuberculosis infection (LTBI) with the absolute assay output normalized by each subject’s basal immune response. Using this personalized normalization strategy, machine learning feature selection yielded promising results toward a diagnostic signature. Chapter 4 describes a multiplexed immune profiling approach incorporating rich temporal dynamics throughout the treatment of sepsis. The rapid immunoassay provides the cytokine trajectories of each subject throughout treatment, illustrating the dynamic changes accompanying immune challenge and subsequent therapeutic intervention. Chapter 5 leverages the near-real time monitoring capabilities of the platform to characterize the differential binding kinetics of monomeric and dimeric therapeutic antibodies as a means of structural characterization. Finally, Chapter 6 discusses the future of the LTBI diagnostic signature development, outlining a significant expansion of the biomarker panel, informatic analysis, and subject study enrollment.","abstract_has_math":false,"creators":["Robison, Heather Marie"],"institution":"University of Illinois at Urbana-Champaign","degree_name":"Ph.D.","degree_level":"Dissertation","degree_discipline":"Chemistry","degree_department":null,"school":null,"contributors":["Bailey, Ryan C.","Mitchell, Douglas A.","Bhargava, Rohit","Han, Hee-Sun"],"advisors":[],"committee_chairs":[],"committee_members":[],"year":2018,"date_issued":"2018-03-13T17:35:24Z","date_published":"2018-03-13T17:35:24Z","updated_at":"2026-07-22T22:24:37Z","subjects":["Whispering gallery mode sensors","Immunoassay","Biomarker","Protein detection","Multiplex","Quantitative analysis"],"languages":["en"],"rights":["Copyright 2017 Heather M. 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Immunoassays are a powerful tool to quantitatively measure cytokine levels in biological solutions. While enzyme-linked immunosorbent assays have been the gold standard technique, multiplexed approaches have rapidly developed in response to the need for more complex biological signatures to precisely describe disease states. While many of these assays demonstrate robust intra-assay performance, variable inter-assay and multi-center performance is a consistent issue. Additionally, the inherent physiological fluctuations from patient-specific, but disease independent sources have largely hindered the clinical implementation of these assays. This dissertation describes promising approaches to address the analytical and clinical challenges facing immune profiling guided precision medicine. Chapter 2 outlines the fundamental requirements for developing robust multiplexed immunoassays with silicon photonic microring resonator arrays. Using this basic protocol for assay development, Chapters 3 and 4 describe two distinct approaches toward diagnosing and monitoring infectious disease related states. Chapter 3 focuses on designing a functional diagnostic immunoassay for latent tuberculosis infection (LTBI) with the absolute assay output normalized by each subject’s basal immune response. Using this personalized normalization strategy, machine learning feature selection yielded promising results toward a diagnostic signature. Chapter 4 describes a multiplexed immune profiling approach incorporating rich temporal dynamics throughout the treatment of sepsis. The rapid immunoassay provides the cytokine trajectories of each subject throughout treatment, illustrating the dynamic changes accompanying immune challenge and subsequent therapeutic intervention. Chapter 5 leverages the near-real time monitoring capabilities of the platform to characterize the differential binding kinetics of monomeric and dimeric therapeutic antibodies as a means of structural characterization. Finally, Chapter 6 discusses the future of the LTBI diagnostic signature development, outlining a significant expansion of the biomarker panel, informatic analysis, and subject study enrollment.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-12-01","The student, Heather Robison, accepted the attached license on 2017-11-29 at 10:02.","The student, Heather Robison, submitted this Dissertation for approval on 2017-11-29 at 10:19.","This Dissertation was approved for publication on 2017-11-29 at 15:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11777 on 2018-03-13 at 10:34:09","Made available in DSpace on 2018-03-13T17:35:24Z (GMT). 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Numerous disease specific biomarkers have emerged, but few are as dynamic and information-rich as those associated with the immune system. The immune system operates through a pathogen specific, biologically conserved response to coordinate detection and clearance. Immune cell associated signaling molecules, cytokines, modulate the immune response and their associated dynamics are ideal for monitoring host response. Profiling the immune response correlated to system perturbations provides a clinically valuable result for functional diagnostics. Immunoassays are a powerful tool to quantitatively measure cytokine levels in biological solutions. While enzyme-linked immunosorbent assays have been the gold standard technique, multiplexed approaches have rapidly developed in response to the need for more complex biological signatures to precisely describe disease states. While many of these assays demonstrate robust intra-assay performance, variable inter-assay and multi-center performance is a consistent issue. Additionally, the inherent physiological fluctuations from patient-specific, but disease independent sources have largely hindered the clinical implementation of these assays. This dissertation describes promising approaches to address the analytical and clinical challenges facing immune profiling guided precision medicine. Chapter 2 outlines the fundamental requirements for developing robust multiplexed immunoassays with silicon photonic microring resonator arrays. Using this basic protocol for assay development, Chapters 3 and 4 describe two distinct approaches toward diagnosing and monitoring infectious disease related states. Chapter 3 focuses on designing a functional diagnostic immunoassay for latent tuberculosis infection (LTBI) with the absolute assay output normalized by each subject’s basal immune response. Using this personalized normalization strategy, machine learning feature selection yielded promising results toward a diagnostic signature. Chapter 4 describes a multiplexed immune profiling approach incorporating rich temporal dynamics throughout the treatment of sepsis. The rapid immunoassay provides the cytokine trajectories of each subject throughout treatment, illustrating the dynamic changes accompanying immune challenge and subsequent therapeutic intervention. Chapter 5 leverages the near-real time monitoring capabilities of the platform to characterize the differential binding kinetics of monomeric and dimeric therapeutic antibodies as a means of structural characterization. Finally, Chapter 6 discusses the future of the LTBI diagnostic signature development, outlining a significant expansion of the biomarker panel, informatic analysis, and subject study enrollment.","Submission published under a 24 month embargo labeled 'Closed Access', the embargo will last until 2019-12-01","The student, Heather Robison, accepted the attached license on 2017-11-29 at 10:02.","The student, Heather Robison, submitted this Dissertation for approval on 2017-11-29 at 10:19.","This Dissertation was approved for publication on 2017-11-29 at 15:09.","DSpace SAF Submission Ingestion Package generated from Vireo submission #11777 on 2018-03-13 at 10:34:09","Made available in DSpace on 2018-03-13T17:35:24Z (GMT). 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