Hybrid systems and LIFE methods for Mycobacterium tuberculosis

Project Title: Hybrid systems and LIFE methods for Mycobacterium tuberculosis
Program:
CAREERS (323)

Project Image: https://support.access-ci.org/system/files/webform/project/106/med%20Pic%20CAREERS.PNG
Tags:
matlab (2)

Status: Complete
Project Leader
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Project Leader:
Benedetto  Piccoli

Email: piccoli@camden.rutgers.edu
Mobile Phone: {Empty}
Work Phone: (856) 225-6356

Project Personnel
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Mentor(s):
Galen Collier (420), Sean McQuade (540)

Student-facilitator(s):
Christopher Denaro (566)

Mentee(s):
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Project Information
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Project Description:
Mycobacterium tuberculosis infected one third of world population and current therapies
involve up to 4 antibiotics and 6 months of treatment. Using MTB gene expression data
From the main available drugs, KEGG and other databases for pathways and Linear-in-flux-expression (briefly LIFE) methodology, we aim to evaluate the potential effectiveness of drug combination therapies. We can do this by simulating the evolution of metabolites with the LIFE technique.
Another goal is to include hybrid methods to model metabolic pathway changes in MTB due to immune system, drug action, and other environmental conditions. Large scale metabolic and gene-regulation network dynamics will be used to assess drug treatment.


Project Information Subsection
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Project Deliverables:
Matlab code will be written to test several four-drug treatments of TB on several key metabolic networks. We will use this simulator to produce results for publishing. There are two planned papers, one for hybrid systems and one for comparing simulators to clinical trials for specific drug combinations.

Project Deliverables:
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Student Research Computing Facilitator Profile:
Graduate student in mathematics is sought who is comfortable in programing with Matlab.

Mentee Research Computing Profile:
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Student Facilitator Programming Skill Level: Practical applications
Mentee Programming Skill Level: {Empty}
Project Institution: Rutgers-Camden
Project Address:
303 Cooper St
Camden, New Jersey. 08102

Anchor Institution: CR-Rutgers
Preferred Start Date: 11/02/2020
Start as soon as possible.: No
Project Urgency: Already behind3Start date is flexible
Expected Project Duration (in months): 6
Launch Presentation: {Empty}
Launch Presentation Date: 02/10/2021
Wrap Presentation: {Empty}
Wrap Presentation Date: 08/11/2021
Project Milestones:
- Milestone Title: Simulation update
  Milestone Description: Add drug combinations to a suite of simulations used treatments against clinical experiments. Document the scripts used for simulation to make this usable for future modelers.
  Completion Date Goal: 2021-02-01
- Milestone Title: Pathway Completion for Simulation
  Milestone Description: Write part of simulator which completes metabolic pathways so that we can simulate them with the action of drug treatment. 
  Completion Date Goal: 2021-02-20
- Milestone Title: New drug data
  Milestone Description: Design and write script to include new microarray data that indicates genomic response to different drugs used for treatment. 
  Completion Date Goal: 2021-04-30
- Milestone Title: Submit for publication
  Milestone Description: The preceding milestones will culminate in a publication of our findings using the simulator to investigate treatment.

Github Contributions: {Empty}
Planned Portal Contributions (if any):
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Planned Publications (if any):
Publication comparing effectiveness of drug combinations to clinical studies leveraging microarray data and pharmacokinetic studies.


What will the student learn?:
The student will learn to acquire microarray data from databases, analyze the data with matlab tools, and present the analysis for publication, as well as learn about the design process for new drug treatments. The student will learn why it is necessary to use computational techniques to evaluate the hundreds of 4-drug treatments considered for tuberculosis. The student will also gain experience with managing code written by another, and organizing this code to facilitate explanation to other group members on its function.

What will the mentee learn?:
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What will the Cyberteam program learn from this project?:
The Cyberteam will be shown how computational tools are forging new methods of drug discovery. This project represents front line efforts to discover new drug treatments to multi-drug resistant diseases, such as tuberculosis.

HPC resources needed to complete this project?:
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Notes:
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Final Report
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What is the impact on the development of the principal discipline(s) of the project?:
This project development is a key step in building a framework to revolutionize drug discovery. It is necessary to use animal models and animal testing at present to develop new drugs. Eventually scientists will have superior simulators for testing drug reaction to a human patient. This project implements a way to better define and simulate metabolic networks.

What is the impact on other disciplines?:
Computational methods of this kind will likely overtake classical methods in chemistry and biochemistry.

Is there an impact physical resources that form infrastructure?:
No.

Is there an impact on the development of human resources for research computing?:
Yes, this will be a crucial resource as computational biology techniques become widespread.

Is there an impact on institutional resources that form infrastructure?:
yes, as this metabolic modeling framework, and other things like this become used regularly, computing clusters will become more needed.

Is there an impact on information resources that form infrastructure?:
Yes, methods used in this project, and other similar methods can build a sophisticated library on metabolic network responses.

Is there an impact on technology transfer?:
No.

Is there an impact on society beyond science and technology?:
Yes, this has the capacity to find better drugs to increase people's overall health.

Lessons Learned:
There is a large group of researchers that are ready and willing to help and share valuable knowledge.

Overall results:
The experience was successful in terms of encouraging the student to go out and find the help from collaborators. I was impressed with the students' ambitious behavior.