Grant: Alliance Grants
University of Waterloo
$70,711.00
Optimization of cell-culture based flu vaccine manufacturing process: genetic engineering and mathematical model-based approaches
FY 2024-25
Summary
Flublok, the focus of the current proposal, is a recombinant flu vaccine produced in insect cell culture using the Baculovirus Expression Vector System (BEVS) that provides an attractive alternative to the currently prevalent egg-based influenza vaccine. Egg-based technology is limited due to: i- limited egg supply during a pandemic; ii- allergic reactions to egg-derived proteins; iii- lengthy manufacturing process; and iv- virus propagation in eggs can cause undesired mutations. Flublok is a highly attractive option since it overcomes the limitations of the egg-based vaccine.
Flublok is based on the production of the most antigenic protein of influenza viruses: haemagglutinin (HA), and is currently manufactured by our industrial collaborator, Sanofi. It is the first influenza vaccine produced by means of modern recombinant DNA technology. Flublok efficacy is reported as superior to egg based vaccine (75% vs 63%). However, due to its higher cost, it is crucial to optimize the Flublok manufacturing process. Hence, the main goal of this project is to improve yield and recovery of active hemagglutinin (HA) in insect cell cultures. The work will be carried out by two PhD students in the Department of Chemical Engineering of the University of Waterloo and be supervised by Professors Marc Aucoin and Hector Budman. The work involves both experimental as well as theoretical (modelling/optimization) work. HA yield improvement will be pursued using two strategies each conducted by one of the two PhD students: PhD 1- genetic engineering of the Baculovirus system through manipulation of specific promoters and enhancers, in conjunction with infection parameters, e.g. multiplicity of infection and time of harvest, to improve the level of protein production; and PhD 2- Model based optimization of cell culture parameters: media composition, temperature, multiplicity of infection (MOI) and time of infection (TOI) will be optimized using a novel Artificial Intelligence (AI) based modelling approach. Online sensors needed for estimation of key variables will be also developed.
Program
Alliance Grants
Recipient
Location
Ontario, Canada
Recipient Type
Academia
Type
Grant
Source
NSERC's Awards Data
As published
Application id
598068-2024
Name nom
Budman, Hector H
Department département
Chemical Engineering
Organization id
33
Institution établissement
University of Waterloo
Province en
Ontario
Province fr
Ontario
Country en
CANADA
Country fr
CANADA
Fiscal year exercice financier
2024
Competition year année de concours
2024
Award amount
70711
Program id
ALLRP
Program name en
Alliance Grants
Program name fr
Subventions Alliance
Group en
RESEARCH PARTNERSHIPS
Group fr
PARTENARIATS DE RECHERCHE
Committee code
96
Committee name en
RPP Internal Decision Cttee
Committee name fr
Cté de décision interne - PPR
Area of application code
1201
Area of application group en
Advancement of knowledge
Area of application group fr
Avancement des connaissances
Area of application en
Life sciences (including biotechnology)
Area of application fr
Sciences de la vie (y compris biotechnologie)
Research subject code
1802
Research subject group en
Chemical engineering
Research subject group fr
Génie chimique
Research subject en
Biochemical engineering
Research subject fr
Génie biochimique
Field of research list names en
Not available
Field of research list names fr
Non disponible
Socioeconomic objective list names en
Not available
Socioeconomic objective list names fr
Non disponible
Application title
Optimization of cell-culture based flu vaccine manufacturing process: genetic engineering and mathematical model-based approaches
Keywords
baculovirus; bioreactor; cell culture; flu vaccine; genetic engineering; insect cells; modelling; optimization; population balance model; systems biology
Application summary
Flublok, the focus of the current proposal, is a recombinant flu vaccine produced in insect cell culture using the Baculovirus Expression Vector System (BEVS) that provides an attractive alternative to the currently prevalent egg-based influenza vaccine. Egg-based technology is limited due to: i- limited egg supply during a pandemic; ii- allergic reactions to egg-derived proteins; iii- lengthy manufacturing process; and iv- virus propagation in eggs can cause undesired mutations. Flublok is a highly attractive option since it overcomes the limitations of the egg-based vaccine.
Flublok is based on the production of the most antigenic protein of influenza viruses: haemagglutinin (HA), and is currently manufactured by our industrial collaborator, Sanofi. It is the first influenza vaccine produced by means of modern recombinant DNA technology. Flublok efficacy is reported as superior to egg based vaccine (75% vs 63%). However, due to its higher cost, it is crucial to optimize the Flublok manufacturing process. Hence, the main goal of this project is to improve yield and recovery of active hemagglutinin (HA) in insect cell cultures. The work will be carried out by two PhD students in the Department of Chemical Engineering of the University of Waterloo and be supervised by Professors Marc Aucoin and Hector Budman. The work involves both experimental as well as theoretical (modelling/optimization) work. HA yield improvement will be pursued using two strategies each conducted by one of the two PhD students: PhD 1- genetic engineering of the Baculovirus system through manipulation of specific promoters and enhancers, in conjunction with infection parameters, e.g. multiplicity of infection and time of harvest, to improve the level of protein production; and PhD 2- Model based optimization of cell culture parameters: media composition, temperature, multiplicity of infection (MOI) and time of infection (TOI) will be optimized using a novel Artificial Intelligence (AI) based modelling approach. Online sensors needed for estimation of key variables will be also developed.
