Difference between revisions of "Team:SHSU China/Model"

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<h1> Modeling</h1>
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<p>Mathematical models and computer simulations provide a great way to describe the function and operation of BioBrick Parts and Devices. Synthetic Biology is an engineering discipline, and part of engineering is simulation and modeling to determine the behavior of your design before you build it. Designing and simulating can be iterated many times in a computer before moving to the lab. This award is for teams who build a model of their system and use it to inform system design or simulate expected behavior in conjunction with experiments in the wetlab.</p>
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                <h1 class="heading mb-4">Model</h1>
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                <div class="lead">Predicting Future Results</div>
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<h3> Gold Medal Criterion #3</h3>
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Convince the judges that your project's design and/or implementation is based on insight you have gained from modeling. This could be either a new model you develop or the implementation of a model from a previous team. You must thoroughly document your model's contribution to your project on your team's wiki, including assumptions, relevant data, model results, and a clear explanation of your model that anyone can understand.  
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The model should impact your project design in a meaningful way. Modeling may include, but is not limited to, deterministic, exploratory, molecular dynamic, and stochastic models. Teams may also explore the physical modeling of a single component within a system or utilize mathematical modeling for predicting function of a more complex device.
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                <li  > <a href="/Team:SHSU_China/Description ">Description</a></li>
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                <h3 class="block-44-heading">Model</h3>
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                <div class="block-44-meta">Yan Luo</div>
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<h3>Physiologically Based Pharmacokinetic Model on Intravitreal Injection of Exosomes:</h3>
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<b>1:Overview</b>
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<p>Physiologically based pharmacokinetic (PBPK) modeling is now widely used drug research and development. PBPK model use experimental data to quantitatively simulate drug absorption, elimination and distribution in the body.</p>
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<p>Team NJU_China in 2015 and 2017 made attempts on modeling exosome circulation in blood. But the parameters in their model is  estimated in a very imprecise way and no estimation method is given. We’ve designed a more accurate version of the model using Simbiology in MATLAB, which has a GUI that can be easily operated. The parameters in our model is based on previous imaging results and analysis on exosome property. The model can be easily modified for other use.</p>
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<b>2: Introduction to PRPK modelling</b>
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<p>Mathematical modeling is frequently used in pharmacokinetics (PK) to help analyse the proper dosing and effectiveness of drug designed. These models are used to describe how the drug concentration in plasma or other tissue change through time. A classical model simply has a compartment representing plasma and one or two other units representing other tissues.</p>
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<p>Compartments are linked with each other using rate constants. Rate constants do not generally have any physiological meaning, but can be transformed into PK descriptors like clearance and volume of distribution. </p>
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<p>Compared to basic PK models, PRPK models includes a larger number of compartments that correspond to different organs in the body. The compartments are connected by flow rates which simulates the blood flow. Each compartment is defined by a tissue volume and tissue blood flow rate. Most models usually assumes liver and kidney being the only sites for clearance.</p>
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<p>To further simulate the distribution of drug after injection, tissue partitioning coefficient (K) is needed, which represents how drug may bound to a certain tissue. K is used to calculate Qout for a tussle which represents the combination of a drug with one tissue. As each tissue is with different binding behavior for organic compounds, K needs to be calculated based on the physical and chemical parameters of each drug.
 
</p>
 
</p>
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<b>3: Exosome Circulation</b>
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<p>Exosome circulation in blood is very different compared to other drugs, for the following results is seen in trafficking result of circulating exosomes, prediction can also be made using results from liposomes:</p>
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<p>1: Negatively charged liposomes, whose physical characteristics are considered to be similar to those of exosomes, are rapidly taken up by macrophages of the mononuclear phagocyte system (MPS) .</p>
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<p>2: Several studies demonstrated that intravenously injected exosomes accumulate in MPS tissues such as liver and spleen.</p>
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<p>3: Hepatic and splenic macrophages take up exosomes administered by intravenous injection, and exosomes derived from various kinds of cells are captured by macrophages</p>
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<b>4: Important Parameters:</b>
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<p>Basic data like tissue weight and serum flow of mouse is from normal PRPK data. For K values, PRPK modeling data on negative charged liposome is used (Leonid Kagan, Pavel Gershkovich 2011). Liver clearance data is gained from exosome tracking result (Héctor Peinado 1 Maša Alečković 2012). Macrophage clearance of exosomes is estimated using calculation of exosome decreasing rate in experiments (Takafumi Imai, Yuki Takahashi 2015).</p>
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<p><img src="https://static.igem.org/mediawiki/2018/9/91/T--SHSU_China--parametrs.png" alt="Image placeholder" class="img-fluid"></p>
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<b>5: Equations</b>
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<p><img src="https://static.igem.org/mediawiki/2018/f/f9/T--SHSU_China--equations.png" alt="Image placeholder" class="img-fluid"></p>
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<b>6: Modeling result</b>
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<p>Modeling results match the experimental half-life of exosomes and matches the concentration of exosomes in spleen, liver and lung long after plasma exosomes are depleted.</p>
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<p><img src="https://static.igem.org/mediawiki/2018/3/36/T--SHSU_China--model0.png" class="img-fluid"></p>
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<h3> Inspiration </h3>
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Here are a few examples from previous teams:
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<li><a href="https://2016.igem.org/Team:Manchester/Model">2016 Manchester</a></li>
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<li><a href="https://2016.igem.org/Team:TU_Delft/Model">2016 TU Delft</li>
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<li><a href="https://2014.igem.org/Team:ETH_Zurich/modeling/overview">2014 ETH Zurich</a></li>
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<li><a href="https://2014.igem.org/Team:Waterloo/Math_Book">2014 Waterloo</a></li>
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</ul>
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Latest revision as of 02:47, 18 October 2018

ExoBlood SHSU_China

Model

Predicting Future Results

Model

Yan Luo

Physiologically Based Pharmacokinetic Model on Intravitreal Injection of Exosomes:

1:Overview

Physiologically based pharmacokinetic (PBPK) modeling is now widely used drug research and development. PBPK model use experimental data to quantitatively simulate drug absorption, elimination and distribution in the body.

Team NJU_China in 2015 and 2017 made attempts on modeling exosome circulation in blood. But the parameters in their model is estimated in a very imprecise way and no estimation method is given. We’ve designed a more accurate version of the model using Simbiology in MATLAB, which has a GUI that can be easily operated. The parameters in our model is based on previous imaging results and analysis on exosome property. The model can be easily modified for other use.

2: Introduction to PRPK modelling

Mathematical modeling is frequently used in pharmacokinetics (PK) to help analyse the proper dosing and effectiveness of drug designed. These models are used to describe how the drug concentration in plasma or other tissue change through time. A classical model simply has a compartment representing plasma and one or two other units representing other tissues.

Compartments are linked with each other using rate constants. Rate constants do not generally have any physiological meaning, but can be transformed into PK descriptors like clearance and volume of distribution.

Compared to basic PK models, PRPK models includes a larger number of compartments that correspond to different organs in the body. The compartments are connected by flow rates which simulates the blood flow. Each compartment is defined by a tissue volume and tissue blood flow rate. Most models usually assumes liver and kidney being the only sites for clearance.

To further simulate the distribution of drug after injection, tissue partitioning coefficient (K) is needed, which represents how drug may bound to a certain tissue. K is used to calculate Qout for a tussle which represents the combination of a drug with one tissue. As each tissue is with different binding behavior for organic compounds, K needs to be calculated based on the physical and chemical parameters of each drug.

3: Exosome Circulation

Exosome circulation in blood is very different compared to other drugs, for the following results is seen in trafficking result of circulating exosomes, prediction can also be made using results from liposomes:

1: Negatively charged liposomes, whose physical characteristics are considered to be similar to those of exosomes, are rapidly taken up by macrophages of the mononuclear phagocyte system (MPS) .

2: Several studies demonstrated that intravenously injected exosomes accumulate in MPS tissues such as liver and spleen.

3: Hepatic and splenic macrophages take up exosomes administered by intravenous injection, and exosomes derived from various kinds of cells are captured by macrophages

4: Important Parameters:

Basic data like tissue weight and serum flow of mouse is from normal PRPK data. For K values, PRPK modeling data on negative charged liposome is used (Leonid Kagan, Pavel Gershkovich 2011). Liver clearance data is gained from exosome tracking result (Héctor Peinado 1 Maša Alečković 2012). Macrophage clearance of exosomes is estimated using calculation of exosome decreasing rate in experiments (Takafumi Imai, Yuki Takahashi 2015).

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5: Equations

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6: Modeling result

Modeling results match the experimental half-life of exosomes and matches the concentration of exosomes in spleen, liver and lung long after plasma exosomes are depleted.

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