The orientation of the biological molecule immobi-lized on a solid surface has been critical in devel-opment of various applications. In this study, ori-entation of antibody was retained by protecting the antigen-bind...The orientation of the biological molecule immobi-lized on a solid surface has been critical in devel-opment of various applications. In this study, ori-entation of antibody was retained by protecting the antigen-binding site of the antibody prior to immo-bilization to -functionalized mixed self-assembled monolayer (SAM) of 12-mercaptododecanoic acid and 1-heptanethiol. More importantly, the number of immobilization bonds formed between each an-tigen-binding site protected antibody molecule and the solid surface was controlled by optimizing the mole fraction of the activated carboxyl group of the linker molecules in the mixed SAM. The amount of antibody used in this study was approximately equivalent to the amount for one monolayer surface coverage. The resulting activity of protected immo-bilized antibody was about 10 fold higher than that of random immobilized展开更多
This work addresses the multiscale optimization of the puri cation processes of antibody fragments. Chromatography decisions in the manufacturing processes are optimized, including the number of chromatography columns...This work addresses the multiscale optimization of the puri cation processes of antibody fragments. Chromatography decisions in the manufacturing processes are optimized, including the number of chromatography columns and their sizes, the number of cycles per batch, and the operational ow velocities. Data-driven models of chromatography throughput are developed considering loaded mass, ow velocity, and column bed height as the inputs, using manufacturing-scale simulated datasets based on microscale experimental data. The piecewise linear regression modeling method is adapted due to its simplicity and better prediction accuracy in comparison with other methods. Two alternative mixed-integer nonlinear programming (MINLP) models are proposed to minimize the total cost of goods per gram of the antibody puri cation process, incorporating the data-driven models. These MINLP models are then reformulated as mixed-integer linear programming (MILP) models using linearization techniques and multiparametric disaggregation. Two industrially relevant cases with different chromatography column size alternatives are investigated to demonstrate the applicability of the proposed models.展开更多
文摘The orientation of the biological molecule immobi-lized on a solid surface has been critical in devel-opment of various applications. In this study, ori-entation of antibody was retained by protecting the antigen-binding site of the antibody prior to immo-bilization to -functionalized mixed self-assembled monolayer (SAM) of 12-mercaptododecanoic acid and 1-heptanethiol. More importantly, the number of immobilization bonds formed between each an-tigen-binding site protected antibody molecule and the solid surface was controlled by optimizing the mole fraction of the activated carboxyl group of the linker molecules in the mixed SAM. The amount of antibody used in this study was approximately equivalent to the amount for one monolayer surface coverage. The resulting activity of protected immo-bilized antibody was about 10 fold higher than that of random immobilized
文摘This work addresses the multiscale optimization of the puri cation processes of antibody fragments. Chromatography decisions in the manufacturing processes are optimized, including the number of chromatography columns and their sizes, the number of cycles per batch, and the operational ow velocities. Data-driven models of chromatography throughput are developed considering loaded mass, ow velocity, and column bed height as the inputs, using manufacturing-scale simulated datasets based on microscale experimental data. The piecewise linear regression modeling method is adapted due to its simplicity and better prediction accuracy in comparison with other methods. Two alternative mixed-integer nonlinear programming (MINLP) models are proposed to minimize the total cost of goods per gram of the antibody puri cation process, incorporating the data-driven models. These MINLP models are then reformulated as mixed-integer linear programming (MILP) models using linearization techniques and multiparametric disaggregation. Two industrially relevant cases with different chromatography column size alternatives are investigated to demonstrate the applicability of the proposed models.
