Publications by authors named "Chyi-Shin Chen"

Article Synopsis
  • * The study created machine learning models to predict these effects for amino acids and monoclonal antibodies using basic molecular descriptors, with validation through real-world data and scientific literature.
  • * These models offer a new in silico approach that simplifies and speeds up the biopharmaceutical process, enhancing understanding of molecular interactions without relying solely on traditional experimental methods.
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Although empirical methods have been introduced in the process development of continuous chromatography, the common approach to optimize a multi-column continuous capture chromatography (periodic counter-current chromatography, PCCC) process heavily relies on numerical model simulations and the number of experiments. In addition, different multi-column settings in PCCC add more design variables in process development. In this study, we have developed a rational method for designing PCCC processes based on iterative calculations by mechanistic model-based simulations.

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Thermodynamic studies on protein adsorption onto chromatographic surfaces mainly focus on the molecular level interaction between proteins and ligands. Yet, not much attention is given to the study of polymer grafted ligand architecture effect on thermodynamic parameters, nor to the relation between chromatographic parameters and the directly obtained thermodynamic parameters. These relations are needed in order to confer meaning and to ease future data interpretation of thermodynamic studies of protein adsorption.

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A new method was proposed for increasing the capture chromatography process efficiency, linear flow-velocity gradient (LFG). The method uses a linear decreasing flow-velocity gradient with time during the sample loading. The initial flow velocity, the final flow velocity and the gradient time are the parameters to be tuned.

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In the chromatographic separation process of oligonucleotides (ONs), mechanistic understanding of their binding and diffusion processes is of significant importance to determine operating conditions in a fast and robust way. In this work, we determined the number of binding sites and the diffusivities of ONs in a polymer grafted anion exchange chromatography through linear gradient experiments (LGE) being carried out at selected four to five gradient slopes. Synthetic poly (T)s with length ranging from 3 to 90-mer were employed as a model of an antisense oligonucleotide with typical lengths of 10 - 30 bases.

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Previously, a predictive model was developed to identify optimal blends of expensive high-quality and cheaper low-quality feedstocks for a given geographical location that can deliver high sugar yields. In this study, the optimal process conditions were tested for application at commercially-relevant higher biomass loadings. We observed lower sugar yields but 100% conversion to ethanol from a blend that contained only 20% high-quality feedstock.

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Background: Lignocellulosic biomass is an important resource for renewable production of biofuels and bioproducts. Enzymes that deconstruct this biomass are critical for the viability of biomass-based biofuel production processes. Current commercial enzyme mixtures have limited thermotolerance.

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