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1.
Anal Chem ; 92(24): 16274-16283, 2020 12 15.
Article in English | MEDLINE | ID: mdl-33236892

ABSTRACT

More than 100 monoclonal antibodies (mAbs) are in industrial and clinical development to treat myriad diseases. Accurate quantification of mAbs in complex media, derived from industrial and patient samples, is vital to determine production efficiency or pharmacokinetic properties. To date, mAb quantification requires time and labor-intensive assays. Herein, we report a novel dual-affinity ratiometric quenching (DARQ) assay, which combines selective biorecognition and quenching of fluorescence signals for rapid and sensitive quantification of therapeutic monoclonal antibodies (mAbs). The reported assay relies on the affinity complexation of the target mAb by the corresponding antigens and Protein L (PrL, which targets the Fab region of the antibody), respectively, labeled with fluorescein and rhodamine. Within the affinity complex, the mAb acts as a scaffold framing the labeled affinity tags (PrL and antigen) in a molecular proximity that results in ratiometric quenching of their fluorescence emission. Notably, the decrease in fluorescence emission intensity is linearly dependent upon mAb concentration in solution. Control experiments conducted with one affinity tag only, two tags labeled with equal fluorophores, or two tags labeled with fluorophores of discrete absorbance and emission bands exhibited significantly reduced effect. The assay was evaluated in noncompetitive (pure mAb) and competitive conditions (mAb in a Chinese Hamster Ovary (CHO) cell culture harvest). The "DARQ" assay is highly reproducible (coefficient of variation ∼0.8-0.7%) and rapid (5 min), and its sensitivity (∼0.2-0.5 ng·mL-1), limit of detection (75-119 ng·mL-1), and dynamic range (300-1600 ng·mL-1) are independent of the presence of CHO host cell proteins.


Subject(s)
Antibodies, Monoclonal/analysis , Spectrometry, Fluorescence/methods , Animals , Antibodies, Monoclonal/immunology , Antibodies, Monoclonal/therapeutic use , Antigens/immunology , CHO Cells , Cricetulus
2.
Curr Stem Cell Res Ther ; 15(8): 674-684, 2020.
Article in English | MEDLINE | ID: mdl-32148200

ABSTRACT

Exosomes and biomimetic nanoparticles have great potential to develop into a wide-scale therapeutic platform within the regenerative medicine industry. Exosomes, a subgroup of EVs with diameter ranging from 30-100 nm, have recently gained attention as an innovative approach for the treatment of various diseases, including heart disease. Their beneficial factors and regenerative properties can be contrasted with various cell types. Various biomimetic nanoparticles have also emerged as a unique platform in regenerative medicine. Biomimetic nanoparticles are a drug delivery platform, which have the ability to contain both biological and fabricated components to improve therapeutic efficiency and targeting. The novelty of these platforms holds promise for future clinical translation upon further investigation. In order for both exosome therapeutics and biomimetic nanoparticles to translate into large-scale clinical treatment, numerous factors must first be considered and improved. Standardization of different protocols, from exosome isolation to storage conditions, must be optimized to ensure batches are pure. Standardization is also important to ensure no variability in this process across studies, thus making it easier to interpret data across different disease models and treatments. Expansion of clinical trials incorporating both biomimetic nanoparticles and exosomes will require a standardization of fabrication and isolation techniques, as well as stricter regulations to ensure reproducibility across various studies and disease models. This review will summarize current research on exosome therapeutics and the application of biomimetic nanoparticles in cardiac regenerative medicine, as well as applications for exosome expansion and delivery on a large clinical scale.


Subject(s)
Biomimetics , Exosomes , Heart Diseases/therapy , Nanoparticles , Regenerative Medicine , Reproducibility of Results
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