Hybrid systems and LIFE methods for Mycobacterium tuberculosis

Submission Number: 74
Submission ID: 106
Submission UUID: 885c3f5b-632a-4e20-b499-9e4ce7cb6b3f
Submission URI: /form/project

Created: Fri, 10/23/2020 - 17:23
Completed: Fri, 10/23/2020 - 17:58
Changed: Tue, 08/02/2022 - 15:03

Remote IP address: 73.10.232.250
Submitted by: Sean McQuade
Language: English

Is draft: No
Webform: Project
Hybrid systems and LIFE methods for Mycobacterium tuberculosis
CAREERS
med Pic CAREERS.PNG
matlab (2)
Complete

Project Leader

Benedetto Piccoli
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(856) 225-6356

Project Personnel

Galen Collier, Sean McQuade
Christopher Denaro
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Project Information

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

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.
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Graduate student in mathematics is sought who is comfortable in programing with Matlab.
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Practical applications
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Rutgers-Camden
303 Cooper St
Camden, New Jersey. 08102
CR-Rutgers
11/02/2020
No
Already behind3Start date is flexible
6
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02/10/2021
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08/11/2021
  • 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.
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Publication comparing effectiveness of drug combinations to clinical studies leveraging microarray data and pharmacokinetic studies.
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.
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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.
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Final Report

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.
Computational methods of this kind will likely overtake classical methods in chemistry and biochemistry.
No.
Yes, this will be a crucial resource as computational biology techniques become widespread.
yes, as this metabolic modeling framework, and other things like this become used regularly, computing clusters will become more needed.
Yes, methods used in this project, and other similar methods can build a sophisticated library on metabolic network responses.
No.
Yes, this has the capacity to find better drugs to increase people's overall health.
There is a large group of researchers that are ready and willing to help and share valuable knowledge.
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.