Team:NJU China/Modeling

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</br></br>
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<a href="https://2013.igem.org"><img src="https://static.igem.org/mediawiki/2013/8/80/NJU-Miniminiminilogocolored.png" ></a>
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         <div class="container">
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<h2>Introduction</h2>
<h2>Introduction</h2>
<div class="pra">
<div class="pra">
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</br></br></br></br>
Pharmacokinetics is the quantitative study of the drug absorption, distribution and metabolism within the body. It shows the fluctuation of the drug concentration within a certain part of the body along the time. For a new drug, we need to first experimentally obtain the pharmacokinetic parameters and then make the pharmacokinetic model to predict the concentration change after drug administration. Thus pharmacokinetic model plays a vital role in new drug development. Since our targeting-exosome is a brand new drug delivery system, we need to make a pharmacokinetic model to check if it can really target the specific site we want and predict the concentration change within that site.
Pharmacokinetics is the quantitative study of the drug absorption, distribution and metabolism within the body. It shows the fluctuation of the drug concentration within a certain part of the body along the time. For a new drug, we need to first experimentally obtain the pharmacokinetic parameters and then make the pharmacokinetic model to predict the concentration change after drug administration. Thus pharmacokinetic model plays a vital role in new drug development. Since our targeting-exosome is a brand new drug delivery system, we need to make a pharmacokinetic model to check if it can really target the specific site we want and predict the concentration change within that site.
</div>
</div>
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<section class="st-panel st-color" id="st-panel-2">
<section class="st-panel st-color" id="st-panel-2">
<div class="st-deco" data-icon="2"></div>
<div class="st-deco" data-icon="2"></div>
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<h2>Pharmacokinetic modeling</h2>
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<h2>Pharmacokinetic Modeling</h2>
<div class="pra">
<div class="pra">
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<!-- <img width="500px"; height="400px"; src="https://static.igem.org/mediawiki/2013/5/5d/293t_mv.jpg" style="margin-right:10px; float:left;"/> -->
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<img width="500px"; height="400px"; src="https://static.igem.org/mediawiki/2013/5/54/NJU-Moduling-2-1.png" style="margin-right:10px; float:left;"/>
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</br></br></br>
After drug administration, what happened within the body is quite complex and all the tissues are involved in the drug metabolism. In order to construct a pharmacokinetic model, we need to first make a few simplification of the body to make a pharmacokinetic model feasible.</br></br>
After drug administration, what happened within the body is quite complex and all the tissues are involved in the drug metabolism. In order to construct a pharmacokinetic model, we need to first make a few simplification of the body to make a pharmacokinetic model feasible.</br></br>
Based on the multi-compartmental model, we divide the human body into central compartment (blood circulation) and peripheral compartment (body tissues). Since the exosome is administrated by intravenous injection, we assume that the concentration of exosome within the blood circulation reached its peak soon after injection and there is no variation within different parts of the blood circulation. Inspired by the pharmacokinetic model made by iGEM Slovenia 2012, we subdivide the peripheral compartment into liver (our target organ), kidney, lung, rapidly perfused tissues (such as skin, muscle) and slowly perfused tissues (such as spleen, heart). Each peripheral compartment has blood exchange with the central blood circulation, and during this process, certain percentage of exosome flow through a compartment will be absorbed. Apart from that, some of the exosome get into the kidney will be eliminated. Based on these simplifications, our multi-compartmental model is shown in the figure 1.</br>
Based on the multi-compartmental model, we divide the human body into central compartment (blood circulation) and peripheral compartment (body tissues). Since the exosome is administrated by intravenous injection, we assume that the concentration of exosome within the blood circulation reached its peak soon after injection and there is no variation within different parts of the blood circulation. Inspired by the pharmacokinetic model made by iGEM Slovenia 2012, we subdivide the peripheral compartment into liver (our target organ), kidney, lung, rapidly perfused tissues (such as skin, muscle) and slowly perfused tissues (such as spleen, heart). Each peripheral compartment has blood exchange with the central blood circulation, and during this process, certain percentage of exosome flow through a compartment will be absorbed. Apart from that, some of the exosome get into the kidney will be eliminated. Based on these simplifications, our multi-compartmental model is shown in the figure 1.</br>
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<img width="500px"; height="500px"; src="https://static.igem.org/mediawiki/2013/5/54/NJU-Moduling-2-1.png" style="margin-right:10px; float:left;"/>
 
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</section>
</section>
<section class="st-panel" id="st-panel-3">
<section class="st-panel" id="st-panel-3">
<div class="st-deco" data-icon="3"></div>
<div class="st-deco" data-icon="3"></div>
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<h2>Targeting module</h2>
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<h2>Parameters</h2>
<div class="pra" ><!--style="overflow-y:scroll;"-->
<div class="pra" ><!--style="overflow-y:scroll;"-->
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<img width="500px"; height="500px"; src="https://static.igem.org/mediawiki/2013/e/e7/Tra.png" style="margin-right:10px; float:right;"/ usemap="liver">
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<img width="300px"; height="390px"; src="https://static.igem.org/mediawiki/2013/7/79/NJU-Module-3-1.png" style="margin-right:10px; float:right;"/ usemap="liver">
<map name="liver">
<map name="liver">
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</br></br></br>
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Specificity is one of the most vital goals that many different drug delivery system want to achieve, and that is also exactly what we are expecting from our biomissile.
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For exosome is a brand new area of research, there are almost no papers have documentation of their pharmacokinetic figures. Since liposomes are also bilayer-membrane vesicles and the diameter of liposome is same as that of exosome, we used the figures from liposome study to predict some of figures we need to use[1][2][3][4]. Apart from that, we also obtain the figures concerning blood flow and organ volume from the documentation of iGEM Slovenia 2012.</br></br>
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</br> </br>
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&nbsp;&nbsp;&nbsp;&nbsp;Qi – blood flows to tissues </br>

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To achieve specificity, we need to make our exosomes able to recognize distinctive sites within the body. In order to do that, the first step we took towards our exosome is outside modification. We wanted to add a target protein onto the surface of the exosomes to endow it with specificity, therefore we need to first find a protein naturally expressed on the surface of the exosomes and then fuse our target protein to the membrane protein of exosomes.
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&nbsp;&nbsp;&nbsp;Pi-percentage of drug absorption in each compartment</br>
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</br> </br>
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&nbsp;&nbsp;&nbsp;&nbsp;Kmi – metabolism rate in each compartment</br>
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After a round of screen of the different membrane proteins on the exosomes’ surface, we chose to use lamp 2b to construct our fusion protein.
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</br> </br>
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Lamp 2b (lysosomal associated membrane protein 2b) is a protein ubiquitously expressed on the surface of the exosomes. By genetically engineering a target protein to the outmembrane part of the lamp 2b, we can use the lamp 2b to bring our target protein to the surface of the exosomes. Thus we can endow the exosome with site-specificity by the addition of the fusion protein.
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</br> </br>
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As the target protein in the lamp 2b is an exchangeable part, we can use different target protein to direct our exosomes to different parts of human body.
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</br> </br>
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Liver，T cells and especially brain are poor targeting sites for previous drug delivery system. In order to prove that our target module does work, we choose to target these sites for testing.
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</br>
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To see more about
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<a href="https://2013.igem.org/Team:NJU_China/Project/Brain" style="color:blue;" >Brain</a>
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,
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<a href="https://2013.igem.org/Team:NJU_China/Project/Liver" style="color:blue;">Liver</a>
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and
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<a href="https://2013.igem.org/Team:NJU_China/Project/T cell" style="color:blue;">T cell</a>  
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targeting.
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</div>
</div>
</section>
</section>
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<section class="st-panel st-color" id="st-panel-4">
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<div class="st-deco" data-icon="4"></div>
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<h2>Killing Module</h2>
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<h2>Mass balance equation of Exosome</h2>
<div class="pra" style="overflow-y:scroll;" >
<div class="pra" style="overflow-y:scroll;" >
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Based on the utilization of natural exosome produced by HEK 293T cells and the modification of the surface protein, lamp-2b, now we have got a site-specific drug carrier, which can bring medicine to cells with a certain kind of receptors. In order to expand power of our system, we decide to pack the carrier with our disease-killing device, siRNA.</br></br>
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A. The concentration change of the exosome within each compartment over time</br></br>
 +
a .The central compartment-blood circulation</br>
 +
The exosomes are removed from the blood through two main ways: distribution to other compartments and metabolism in the blood. Based on that, the mass balance equation of exosomes goes like follows:</br></br></br>
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Recently, small interfering RNA (siRNA) is emerging as a promising therapeutic drug against a wide array of diseases. siRNA functions through the RNA interference pathway. Normal double-stranded RNA is first processed by Dicer and Argo to become short double-stranded RNA, which is about 21-25bp in length. Then it will recruit other proteins to form RISC( RNA induced silencing complex). One of the two RNA stands in the RISC will be degraded and the remaining strand can specifically recognize other mRNA by base pairing. Once the RISC bind to other complementary mRNA, it will destroy the mRNA through the RNAi pathway. By designing siRNA against certain virus genes, we can use siRNA as molecular medicine for diseases treatment. siRNAs are well tolerated and have suitable pharmacokinetic properties
 
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</br></br>
 
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This discovery encouraged us to harness siRNA as specific targeted drugs producing a therapeutic benefit in our system. Now, not only can we carry drugs into a specific site, but also the drug itself specifically turn off the disease-causing gene expression rather than destroy the whole cell or disrupt normal protein production in a healthy cell. </br></br>
 
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Design  </br>                                                
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b. The peripheral compartments</br>
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We carried out this experiment in the HBV testing model to verify that our big idea can work in real human disease.
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There are two main factors affect the concentration fluctuation in peripheral compartments: absorption from the blood and metabolism within the compartments.</br>
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The first step in designing a siRNA for viral gene silencing is to choose the siRNA target sites.  
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For kidney, there is an additional factor, which is the elimination rate of the exosomes by kidney.</br>
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Firstly, we should find 21 nt sequences in the target mRNA from Hepatitis b virus (HBV) genome that begin with an AA dinucleotide. </br>
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Thus the mass balance equations of the peripheral compartments are listed as below:</br></br></br>
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And then, choose target sites from among the ‘AA sequences’ based on guidelines like ‘Target sequence should have a GC content of around 50%’; ‘Avoid stretches of 4 or more bases such as AAAA, CCCC; ’‘Avoid regions with GC content <30% or > 60%.’</br>
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Liver:</br>
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We completed the first two steps in the software, siRNA Designer.</br>
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<img width="453px"; height="81px"; src="https://static.igem.org/mediawiki/igem.org/7/79/M3-Model-%E5%BE%AE%E5%88%86liver.png"></br></br>
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Finally, we performed BLAST homology search to avoid off-target effects on other genes or sequences</br></br>
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Lung:</br>
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After screening the HBV genome using the methods mentioned above, we ultimately find three candidates as our anti-HBV siRNA</br>
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<img width="427px"; height="81px"; src="https://static.igem.org/mediawiki/igem.org/thumb/0/08/M3-Model-%E5%BE%AE%E5%88%86lung.png/800px-M3-Model-%E5%BE%AE%E5%88%86lung.png"></br></br>
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siRNA 308 TATGCCTCAAGGTCGGTCGTT  against HBx gene in HBV genome</br>
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Kidney:</br>
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siRNA 467 TCCCATAGGAATCTTGCGAAA  against HBsAG gene in HBV genome</br>
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<img width="448px"; height="77px"; src="https://static.igem.org/mediawiki/igem.org/7/71/M3-Model-%E5%BE%AE%E5%88%86kidney.png"></br></br>
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siRNA 516 ACAAATGGCACTAGTAAACTG  against HBsAg gene in HBV genome</br>
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Rapidly perfused tissues:</br>
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The number 308, 467 and 516 in the siRNA indicates their target sites within their target gene.</br></br>
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<img width="372px"; height="70px"; src="https://static.igem.org/mediawiki/igem.org/0/01/M3-Model-%E5%BE%AE%E5%88%86rpt.png"></br></br>
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Slowly perfused tissues:</br>
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<img width="363px"; height="70px"; src="https://static.igem.org/mediawiki/igem.org/6/63/M3-Model-%E5%BE%AE%E5%88%86spt.png"></br></br>
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We cloned these three siRNAs into the vector pENTR/U6, which is a plasmid backbone for high yield of siRNA.</br>
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Solving all the mass equations above, we can get the function which show the concentration change within each compartment along the time:</br></br></br>
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By cloning the siRNAs into eukaryotic expression vectors, large amounts of corresponding siRNAs can be produced by the cell, instead of chemically synthesizing the siRNAs.</br>
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Blood circulation:</br>
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In these vectors, we use an RNA polymerase Ⅲpromoter U6 to direct the transcription of siRNA， and an enhancer which greatly increases the gene transcription </br></br>
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<img width="300px"; height="65px"; src="https://static.igem.org/mediawiki/igem.org/5/54/M3-Model-%E6%96%B9%E7%A8%8Bblood.png"></br></br>
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Liver:</br>
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<img width="655px"; height="106px"; src="https://static.igem.org/mediawiki/igem.org/e/ec/M3-Model-%E6%96%B9%E7%A8%8Bliver.png"></br></br>
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Lung:</br>
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<img width="652px"; height="106px"; src="https://static.igem.org/mediawiki/igem.org/8/8e/M3-Model-%E6%96%B9%E7%A8%8Blung.png"></br></br>
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Kidney:</br>
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<img width="637px"; height="107px"; src="https://static.igem.org/mediawiki/igem.org/4/40/M3-Model-%E6%96%B9%E7%A8%8Bkidney.png"></br></br>
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Rapidly perfused tissues:</br>
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<img width="642px"; height="102px"; src="https://static.igem.org/mediawiki/igem.org/0/0c/M3-Model-%E6%96%B9%E7%A8%8Brpt.png"></br></br>
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Slowly perfused tissues:</br>
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<img width="644px"; height="116px"; src="https://static.igem.org/mediawiki/igem.org/8/81/M3-Model-%E6%96%B9%E7%A8%8Bspt.png"></br></br>
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B. Examine the relationship between the exosome concentration change over time and absorption percentage within liver.
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</br></br>
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<img width="655px"; height="106px"; src="https://static.igem.org/mediawiki/igem.org/e/ec/M3-Model-%E6%96%B9%E7%A8%8Bliver.png"></br></br>
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Results</br>
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C. Examine the relationship between the exosme concentration change over time and drug half-life within liver.</br></br>
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1.siRNA screen</br>
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<img width="655px"; height="106px"; src="https://static.igem.org/mediawiki/igem.org/e/ec/M3-Model-%E6%96%B9%E7%A8%8Bliver.png"></br></br>
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Since we have designed three types of siRNA target to different HBV genes, we need to determine which one would be optimal for HBV treatment. </br></br>
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To achieve this goal, we first tested their relative expression level in cells and exosomes. Expression of them was confirmed by quantitative PCR (qPCR) analysis of transfected HEK 293t cells and exosomes collected from the culture medium. The result suggested that 467 siRNA had much higher level of expression in both cells (Fig.1) and exosomes (36h post-transfection)(Fig.2). Since we need high yield of siRNA in the exosome, we decided to choose 467 as our ‘kill device’.</br></br>
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<img src="https://static.igem.org/mediawiki/2013/c/ca/Nju_Project-4-1.png"></br>
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Fig.1 :qPCR analysis of relative siRNA level in 293t cells. Result showed that 467 siRNA has a relatively higher level of expression than that of 308 siRNA and 516 siRNA. </br></br>
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<img src="https://static.igem.org/mediawiki/2013/0/0e/Priject-4-2.png"></br>
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Fig.2 :qPCR analysis of relative siRNA level in 293t cells. 24 hours after transfection, 516 has a relatively higher expression level in exosomes. However, after 36h’s transfection, 467 performed a significant increase in expression level, almost 100 times of that of 516 and 308. Therefore, together with the data from Fig.1, we eliminated 516 siRNA and 308 siRNA from our list.</br></br>
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2.Silencing effect of siRNA 4667 towards HBsAG</br>
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We investigated the silencing effectiveness of siRNA 467 towards HBsAG to guarantee that it would work as we want. By qPCR analysis of HepG2 cell co-transfected with both siRNA 467 plasmid and HBsAg plasmid, we observed the significant down-regulation of HBsAg gene (Fig.3). This demonstrated that our siRNA 467 does function to silence the target gene, yet it could not prove that 467 siRNA would also work when it was encapsulated into our exosomes.</br></br>
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<img src="https://static.igem.org/mediawiki/2013/e/e0/NjuProject-4-3.png"></br>
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Fig. 3 :Silencing of HBsAg by siRNA 467. All groups were transfected by Lipo 2000. Control group was transfected with empty plasmid. siRNA-free group was transfected with HBsAg overexpression plasmid, and experimental group with both HBsAg overexpression plasmid and 467 siRNA plasmid. The result suggested that 467 siRNA successfully down-regulatethe HBsAg gene.</br></br>
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3.Silencing effect of siRNA 467 towards HBsAg after encapsulated in exosome</br>
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After transfecting 293t cells with 467 siRNA plasmids, we collected exsomes and then co-cultured them with HepG2 cells which had been transfected with HBsAg over-expression plasmid. qPCR analysis confirmed that the down-regulation of HBsAg was significant(Fig.4), and thus proved that our 467 siRNA could work effectively in exosomes.</br></br>
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<img src="https://static.igem.org/mediawiki/2013/1/1d/NjuProject-4-4.png"></br>
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Fig.4:
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All groups were transfected by Lipo. The first group was transfected without any plasmid while other three groups were transfected with HBsAg over-expression plasmid. Second group cultured without exogenous exosomes. Third group co-cultured with empty exosomes, and fourth with exosomes containing siRNA 467. These two kinds of exosomes were collected from 293t cells transfected without and with 467 siRNA plasmid, respectively. Then every group was analyzed for their HBsAg gene expression level through qPCR. Since group 2 and group 3 showed a similar level of expression, either of which is significantly higher than group 1, the HBsAg gene did express in those cells. Yet group 4, which was co-cultured with 467 exosomes, showed a relatively lower HBsAg expression level. That may indicate that 467 contained in exosomes had down-regulated the target gene.</br></br>
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4.Absolute quantification of siRNA 467 encapsulated into exosome</br>
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In order to better apply our exosomes in further experiment (mice experiment, for example), we needed to absolutely quantify the siRNA productivity in each μg of exosomes (whose quantity is measured base on protein concentration). By qPCR analysis of a series of siRNA with given concentration, we drew a standard curve (Fig.5). Then using this curve, we were able to determine the siRNA quantity within exosomes. Also, we tested the quantity of siRNA from both 24h post-transfection and 48h post-transfection in each experiment. The results showed that 24 hours after the transfection, the quantity of siRNA per 1μg exosome was 8*10-2 fmol in exosomes(Fig.6). However, after 48 hours, the number nearly doubled. It was 2*10-1 fmol(siRNA)/μg(exosome) in exosomes. The results helped us determine the dose of injection for mouse and establish the mathematical model.</br></br>
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<img width="554px" height="299px" src="https://static.igem.org/mediawiki/2013/6/6a/M3-Project-killing-_Fig5.png"></br>
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Fig.5 siRNA 467 Standard Curve drawn through a series siRNA with given concentration.</br></br>
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<img width="554px" height="299px" src="https://static.igem.org/mediawiki/2013/8/8e/M3-Project-killing-_Fig6.png"></br>
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<img width="125px"; height="71px"; src="https://static.igem.org/mediawiki/igem.org/a/a0/M3-model-kel.png"></br></br>
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Fig.6 Absolute quantification of siRNA 467 in exosomes, 24h and 48h post transfection, respectively.</br></br>
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</div>
</div>
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<section class="st-panel" id="st-panel-5">
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<div class="st-deco" data-icon="5"></div>
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<h2>Achievement</h2>
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<h2>Results and Conclusions</h2>
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<div class="pra" >Starting from March, our lab work continues for 7 months. During these 7 months, we first came up with the idea of ‘biomissile’ via brainstorming, then carefully designed every component of our biomissile. And the most difficult part was to experimentally prove that every part of the system can work properly. From the hard work of the past 7 months, we have successfully done the following:</br></br>
+
<div class="pra" style="overflow-y:scroll;" >
-
We designed and created a new anti-HBV siRNA biobrick(BBa_K1180000), and experimentally validated that it can significantly suppress the HBV viral gene. Apart from that, after transfection of HEK 293T cells with this part, the siRNA can be successfully encapsulated into the exosmes produced by the cells.</br></br>
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A.Exosome concentration change over time within each compartment</br>
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We designed and constructed a liver-targeting fusion protein (BBa_K1180003) . After transfecting the HEK 293T cells with this plasmid, we monitored the exosomes with this fusion protein on its surface successfully get into the Hep G2 cell. </br></br>
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<img width="620px"; height="400px"; src="https://static.igem.org/mediawiki/2013/6/60/Nju-Moduling-5-1.png" style="margin-right:10px;"/>
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We designed and constructed a brain-targeting fusion protein(BBa_K1180002). After transfecting the HEK 293T cells with this plasmid, the exosomes produced by the HEK 293T cells can successfully bring the siRNA contained into the mouse brain.</br></br>
+
</br>
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Combining the targeting module and kill module together, firstly it can target specific sites, apart from that, the siRNA contained within the exosome can specifically destroy the disease related gene. Thus we realize the idea of boimissile by using our engineered exosome for target-destruction of disease. </div>
+
Figure.2 Exosome concentration change along the time in different compartments.
 +
</br></br></br>
 +
As we can see from the figure.2, the concentration of exosomes in the blood falls down along the time while the concentration of exosomes in the peripheral compartment goes up first then falls down. Comparing the concentration change of exosomes over time in the liver(our target organ) with other tissues, we can easily see that the peak concentration of exosomes in liver is much higher than that of non-target tissues. Thus we can assure that the after add the liver targeting protein to the exosome (the percentage of exosomes get into the liver increases), the concentration of exosomes in the liver greatly outnumber that in other tissues.
 +
</br></br>
 +
B.The relationship between the exosome concentration change over time and absorption percentage in liver.</br>
 +
<img width="750px"; height="600px"; src="https://static.igem.org/mediawiki/2013/0/06/Nju-Moduling-5-2.png" style="margin-right:10px;"/></br>
 +
Figure.3 exosome concentration change over time with different absorption percentage in liver
 +
</br></br></br>
 +
The difference of exosome distribution between liver and other tissues lie in that the absorption percentage of exosomes in liver is much higher than that in other tissues. After plot concentration change over time and absorption percentage in 3D(Figure.3),we can see that as the absorption percentage increases, the peak of drug concentration also goes up. To achieve higher concentration in liver, we can make outside modification to exosomes to direct more exosomes into the liver.
 +
</br></br>
 +
C.The relationship between the exosome concentration change over time and drug half-life.</br>
 +
<img width="850px"; height="500px"; src="https://static.igem.org/mediawiki/2013/2/2e/NJU-Moduling-5-3.png" style="margin-right:10px;"/></br>
 +
Figure.4 exosome concentration change over time with different exosome halflife in liver
 +
</br></br></br>
 +
Encapsulate the siRNA into exosomes can great increase the half-life of the siRNA, and via outside modification we can change the half-life of the exosome. As we can see from Figure.4 , after the drug half-life increases, the concentration falls more slowly so that the drug can function more time in the target tissue.
 +
</br></br></br>
 +
Reference:</br>
 +
1. Ishida T, Harashima H, Kiwada H. Liposome clearance[J]. Bioscience reports, 2002, 22: 197-224.
 +
</br></br>
 +
2. Dams ETM, Laverman P, Oyen W JG, et al. Accelerated blood clearance and altered biodistribution of repeated injections of sterically stabilized liposomes[J]. Journal of Pharmacology and Experimental Therapeutics, 2000, 292(3): 1071-1079.
 +
</br></br>
 +
3. Gao S, Dagnaes-Hansen F, Nielsen EJB, et al. The effect of chemical modification and nanoparticle formulation on stability and biodistribution of siRNA in mice[J]. Molecular Therapy, 2009, 17(7): 1225-1233.
 +
</br></br>
 +
4. Morrissey DV, Lockridge JA, Shaw L, et al. Potent and persistent in vivo anti-HBV activity of chemically modified siRNAs[J]. Nature biotechnology, 2005, 23(8): 1002-1007.
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</div>
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</section>
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Introduction Pharmacokinetic Modeling Parameters Mass balance equation of exosome Results and conclusions

Introduction





Pharmacokinetics is the quantitative study of the drug absorption, distribution and metabolism within the body. It shows the fluctuation of the drug concentration within a certain part of the body along the time. For a new drug, we need to first experimentally obtain the pharmacokinetic parameters and then make the pharmacokinetic model to predict the concentration change after drug administration. Thus pharmacokinetic model plays a vital role in new drug development. Since our targeting-exosome is a brand new drug delivery system, we need to make a pharmacokinetic model to check if it can really target the specific site we want and predict the concentration change within that site.

Pharmacokinetic Modeling




After drug administration, what happened within the body is quite complex and all the tissues are involved in the drug metabolism. In order to construct a pharmacokinetic model, we need to first make a few simplification of the body to make a pharmacokinetic model feasible.

Based on the multi-compartmental model, we divide the human body into central compartment (blood circulation) and peripheral compartment (body tissues). Since the exosome is administrated by intravenous injection, we assume that the concentration of exosome within the blood circulation reached its peak soon after injection and there is no variation within different parts of the blood circulation. Inspired by the pharmacokinetic model made by iGEM Slovenia 2012, we subdivide the peripheral compartment into liver (our target organ), kidney, lung, rapidly perfused tissues (such as skin, muscle) and slowly perfused tissues (such as spleen, heart). Each peripheral compartment has blood exchange with the central blood circulation, and during this process, certain percentage of exosome flow through a compartment will be absorbed. Apart from that, some of the exosome get into the kidney will be eliminated. Based on these simplifications, our multi-compartmental model is shown in the figure 1.

Parameters




For exosome is a brand new area of research, there are almost no papers have documentation of their pharmacokinetic figures. Since liposomes are also bilayer-membrane vesicles and the diameter of liposome is same as that of exosome, we used the figures from liposome study to predict some of figures we need to use[1][2][3][4]. Apart from that, we also obtain the figures concerning blood flow and organ volume from the documentation of iGEM Slovenia 2012.

    Qi – blood flows to tissues

    Pi-percentage of drug absorption in each compartment
    Kmi – metabolism rate in each compartment

Mass balance equation of Exosome

A. The concentration change of the exosome within each compartment over time

a .The central compartment-blood circulation
The exosomes are removed from the blood through two main ways: distribution to other compartments and metabolism in the blood. Based on that, the mass balance equation of exosomes goes like follows:


b. The peripheral compartments
There are two main factors affect the concentration fluctuation in peripheral compartments: absorption from the blood and metabolism within the compartments.
For kidney, there is an additional factor, which is the elimination rate of the exosomes by kidney.
Thus the mass balance equations of the peripheral compartments are listed as below:


Liver:


Lung:


Kidney:


Rapidly perfused tissues:


Slowly perfused tissues:


Solving all the mass equations above, we can get the function which show the concentration change within each compartment along the time:


Blood circulation:


Liver:


Lung:


Kidney:


Rapidly perfused tissues:


Slowly perfused tissues:


B. Examine the relationship between the exosome concentration change over time and absorption percentage within liver.



C. Examine the relationship between the exosme concentration change over time and drug half-life within liver.





Results and Conclusions

A.Exosome concentration change over time within each compartment

Figure.2 Exosome concentration change along the time in different compartments.


As we can see from the figure.2, the concentration of exosomes in the blood falls down along the time while the concentration of exosomes in the peripheral compartment goes up first then falls down. Comparing the concentration change of exosomes over time in the liver(our target organ) with other tissues, we can easily see that the peak concentration of exosomes in liver is much higher than that of non-target tissues. Thus we can assure that the after add the liver targeting protein to the exosome (the percentage of exosomes get into the liver increases), the concentration of exosomes in the liver greatly outnumber that in other tissues.

B.The relationship between the exosome concentration change over time and absorption percentage in liver.

Figure.3 exosome concentration change over time with different absorption percentage in liver


The difference of exosome distribution between liver and other tissues lie in that the absorption percentage of exosomes in liver is much higher than that in other tissues. After plot concentration change over time and absorption percentage in 3D(Figure.3),we can see that as the absorption percentage increases, the peak of drug concentration also goes up. To achieve higher concentration in liver, we can make outside modification to exosomes to direct more exosomes into the liver.

C.The relationship between the exosome concentration change over time and drug half-life.

Figure.4 exosome concentration change over time with different exosome halflife in liver


Encapsulate the siRNA into exosomes can great increase the half-life of the siRNA, and via outside modification we can change the half-life of the exosome. As we can see from Figure.4 , after the drug half-life increases, the concentration falls more slowly so that the drug can function more time in the target tissue.


Reference:
1. Ishida T, Harashima H, Kiwada H. Liposome clearance[J]. Bioscience reports, 2002, 22: 197-224.

2. Dams ETM, Laverman P, Oyen W JG, et al. Accelerated blood clearance and altered biodistribution of repeated injections of sterically stabilized liposomes[J]. Journal of Pharmacology and Experimental Therapeutics, 2000, 292(3): 1071-1079.

3. Gao S, Dagnaes-Hansen F, Nielsen EJB, et al. The effect of chemical modification and nanoparticle formulation on stability and biodistribution of siRNA in mice[J]. Molecular Therapy, 2009, 17(7): 1225-1233.

4. Morrissey DV, Lockridge JA, Shaw L, et al. Potent and persistent in vivo anti-HBV activity of chemically modified siRNAs[J]. Nature biotechnology, 2005, 23(8): 1002-1007.

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