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Massachusetts Institute of Technology

A computational framework for predicting CHO cell culture performance in bioreactors

Abstract

dc:description.abstract

Breaking the trade-off between speed and productivity is a key milestone across industries. In particular, in the biopharmaceutical industry this trade-off is exacerbated by a highly regulated environment, which hinders continuous improvement and fixes future manufacturing costs. Given the complexity of living organisms and the improvement in quality of life offered by the product - which demand agile development - the industry has traditionally taken phenomenological approaches to process development, generally sacrificing costs. Nonetheless, technological developments and lower entry barriers make the biopharmaceutical industry far more competitive than in its origins, demanding efficient and reliable processes. Developing efficient manufacturing processes for new products while being agile to market is a key differentiating capability of Amgen's process development organization.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Sloan School of Management
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2019

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Cárcamo Behrens, Martín.
Advisor dc:contributor.advisor
  • Douglas Lauffenburger and Roy Welsch.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • MIT theses are protected by copyright. They may be viewed, downloaded, or printed from this source but further reproduction or distribution in any format is prohibited without written permission.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/123055
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/123055

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Cárcamo Behrens, Martín.. A computational framework for predicting CHO cell culture performance in bioreactors. Massachusetts Institute of Technology, 2019. https://hdl.handle.net/1721.1/123055