A Bioprocess Design for Microbial Production of Taxol

Project Summary

Paclitaxel (Taxol) is a small molecule drug belonging to the taxane family. It is one of the most commonly used chemotherapeutics, used for treatment of many cancers, as a monotherapy or in combination with other drugs to treat breast, lung and ovarian cancer as well as Kaposi’s sarcoma. Taxol is on the World Health Organization’s (WHO) List of Essential Medicines, a list that includes most the important medications for basic health. The worldwide demand for paclitaxel is exceeding the current supply. 

Themes and Categories
Year
2015

In addition the current cost of paclitaxel limits use in many parts of the developing world. Lower cost sources of paclitaxel can have an immediate impact to human health worldwide. Currently taxol is approved in the U.S. as first line of treatment for breast, ovarian and non-small cell lung cancer. The annual new cases of these cancers are ~ 540,000 in the United States.

Project Team

  • Banskota, S.
  • Ciesla T.J.
  • Moreb, E.

BME 590-02 Fall 2015 

Project Details

Market size: U.S. market : 1,100 kg per year

Process design included:

  • Genetically engineered E. coli Strain
  • Heterologous Taxol production pathway
  • Engineered host strain
  • GMP fermentation process
  • 5 step downstream recovery process 

Results

Our conceptual design results in cost competitive production 

  • $0.43/mg - including a 25% return
  • ~$ 5M in capital investment
  • Current pricing is ~ $0.50/mg 

Download the project poster for more details (PDF).

Related People

Related Projects

Shannon Houser (Stats/BioChem), Junbo Guan (MIDS), and Gaurav Sirdeshmukh (Stats) spent ten weeks exploring data concerning child and family health in Yolo County, CA. Using R Shiny, the team produced an interactive data dashboard that enables Yolo County residents to find healthcare and childcare providers, food resources, and transportation information.

View the team's project poster here

Watch the team's final presentation on Zoom:

 

Project Lead: Leigh Ann Simmons (UC Davis)

Sean Fiscus (Math/Econ/EnvEng), Alyssa Shi (Stats), Yamil Lopez-Ruiz (BME/CS), Emmanuel Mokel (Stats/Math) spent ten weeks working with data from CovIdentify, a study that focuses on using wearables to predict and diagnose COVID-19 and the Flu. The team improved the memory efficiency of analytic pipelines, and added capacity to ingest different types of data. This project built upon the work accomplished by the Duke Bass Connections team and the Duke MIDS capstone project.

 

View the team's project poster here

Watch the team's final presentation on Zoom:

 

Project Lead: Jessilyn Dunn

A large and growing trove of patient, clinical, and organizational data is collected as a part of the “Help Desk” program at Durham’s Lincoln Community Health Center. Help Desk is a group of student volunteers who connect with patients over the phone and help them navigate to community resources (like food assistance programs, legal aid, or employment centers). Data-driven approaches to identifying service gaps, understanding the patient population, and uncovering unseen trends are important for improving patient health and advocating for the necessity of these resources. Disparities in food security, economic stability, education, neighborhood and physical environment, community and social context, and access to the healthcare system are crucial social determinants of health, which studies indicate account for nearly 70% of all health outcomes.