Taken together, recEpMab-37, established by the CBIS method, is useful for detecting EpCAM in various applications.ĭesigning an antibody with the desired affinity to the antigen is challenging, often achieved by lengthening the hydrophobic CDRs, which can lead to aggregation and cause major hindrance to the development of successful biopharmaceutical products. Furthermore, recEpMab-37 could stain formalin-fixed paraffin-embedded colorectal carcinoma tissues by immunohistochemistry. In Western blot analysis, recEpMab-37 detected the EpCAM of CHO/EpCAM and Caco-2 cells. We observed that EpCAM amino acids between 144 to 164 are involved in recEpMab-37 binding. The K D of recEpMab-37 for CHO/EpCAM and Caco-2 was 2.0 × 10 −8 M and 3.2 × 10 −8 M, respectively. In contrast, recEpMab-37 did not react with EpCAM-knocked out Caco-2 cells. One of the established recombinant anti-EpCAM mAbs, recEpMab-37 (mouse IgG 1, kappa), reacted with EpCAM-overexpressed Chinese hamster ovary-K1 cells (CHO/EpCAM) or a colorectal carcinoma cell line (Caco-2). We characterized them using flow cytometry, Western blotting, and immunohistochemistry. In this study, we established anti-EpCAM monoclonal antibodies (mAbs) using the Cell-Based Immunization and Screening (CBIS) method. Therefore, EpCAM is thought to be a promising target for cancer diagnosis and therapy. EpCAM is involved in cell adhesion, proliferation, survival, stemness, and tumorigenesis. The epithelial cell adhesion molecule (EpCAM) is a cell surface glycoprotein, which is widely expressed on normal and cancer cells. Overall, the proposed methods are robust, accurate, and cost- and time-effective. The proposed methods are applicable to rats or monkeys with the same degree of accuracy. The predicted PK parameters from fixed exponents were comparable with the predicted PK parameters estimated from human concentration–time profiles. The results of the study indicated that the exponent 0.9 and the combination of exponents of 0.9 and 0.8 (two exponents, 0.8 and 0.9, were used) were the best method to predict human concentration–time profiles and, subsequently, human PK parameters. The PK parameters were also scaled to humans from monkeys or rats using fixed exponents and compared with the PK parameters predicted from predicted human concentration–time profiles. Eight methods with different exponents of volume of distribution (0.8–1) as well as exponents of clearance (0.85), along with the exponents of volume of distribution for 5 ADCs, were used to predict human concentration–time profiles. The objective of this study is to predict human concentration–time profiles of antibody–drug conjugates (ADCs) and subsequently predict pharmacokinetic parameters in humans from rats or monkeys. Knowledge of human concentration–time profiles from animal data can be useful during early drug development.
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To view the papers in pdf format, click on the "PDF Full-text" link, and use the free Adobe Reader to open them. PDF is the official format for papers published in both, html and pdf forms.You may sign up for e-mail alerts to receive table of contents of newly released issues.Issues are regarded as officially published after their release is announced to the table of contents alert mailing list.To accelerate patient-specific antibody discovery, we compared two unique approaches for screening anti-AQP4 antibodies from yeast antibody surface display libraries. In neuromyelitis optica (NMO), the identification of antibodies targeting the aquaporin-4 (AQP4) membrane protein traditionally involves the labor-intensive and time-consuming process of single B-cell sorting, followed by antibody cloning, expression, purification, and analysis for anti-AQP4 activity. A rapid and effective method to identify disease-specific antibodies from clinical patients is important for understanding autoimmune diseases and for the development of effective disease therapies.
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