%0 Generic
%A Picanço Castanheira da Silva, Tiago
%D 2023
%T Data accompanying dissertation Continuous Chromatography of Biopharmaceuticals - Next Generation Process Development
%U 
%R 10.4121/6a9f2c8a-d953-4ca8-8bbd-28b51b6de638.v1
%K Continuous Chromatography
%K High‐Throughput Process Development
%K High-Throughput Screening
%K Integrated Continuous Biomanufacturing
%K Microfluidics
%K Modeling
%X <p>This folder contains data generated during the PhD project: Biopharmaceutical Continuous Chromatography - Next Generation Process Development</p><p>By Tiago Picanço Castanheira da Silva in Delft University of Technology</p><p>Supervisors: Marcel Ottens and Michel Eppink</p><p>Department of Biotechnology, Section of Bioprocess Engineering&nbsp;</p><p>When using the data, please refer using:</p><p><strong>Silva <em>et al.</em> (2022)</strong> Small, smaller, smallest: Miniaturization of chromatographic process development (doi: <a href="https://doi.org/10.1016/j.chroma.2022.463451" target="_blank">10.1016/j.chroma.2022.463451</a>), <strong>Silva <em>et al.</em> (2023) </strong>Digital Twin in High Throughput Chromatographic Process Development for Monoclonal Antibodies (under submission), <strong>Silva <em>et al.</em> (2023) </strong>Integrated Continuous Chromatography for Capture and Polishing at High Protein Load (under submission).</p><p></p><p>The data is divided into 3 folders, each referring to one chapter in the dissertation:</p><p>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Chapter 4: Small, smaller, smallest: Miniaturization of chromatographic process development.</p><p>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Chapter 5: Digital Twin in High Throughput Chromatographic Process Development for Monoclonal Antibodies.</p><p>-&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;&nbsp;Chapter 6: Integrated Continuous Chromatography for Capture and Polishing at High Protein Load.</p><p>Within each folder, the data is organized in a folder corresponding to the chapter content to which it refers to (figure and tables).</p>
%I 4TU.ResearchData