Publications https://www.imi-tristan.eu/ en PBPK Modelling of PV in Rats https://www.imi-tristan.eu/node/406 <span>PBPK Modelling of PV in Rats</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>19.08.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-07-20T12:00:00Z">20.07.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-d7fdd183-d060-49c1-910f-30793d71e1ea coh-component-instance-d7fdd183-d060-49c1-910f-30793d71e1ea ssa-instance-1532798025 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-f1e15723-e76e-47ba-bffa-c072af8b8f74 coh-component-instance-f1e15723-e76e-47ba-bffa-c072af8b8f74 ssa-instance-769564607 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>PBPK Modelling of gadoxetate in rat liver</h2> <p><strong>Physiologically Based Pharmacokinetic Modeling of Transporter-Mediated Hepatic Disposition of Imaging Biomarker Gadoxetate in Rats</strong></p> <p><em>Daniel Scotcher, Nicola Melillo, Sirisha Tadimalla, Adam S. Darwich, Sabina Ziemian, Kayode Ogungbenro, Gunnar Schütz, Steven Sourbron, and Aleksandra Galetin</em></p> <p><br /> ACS Mol. Pharmaceutics 2021, 18, 8, 2997-3009; <a href="https://doi.org/10.1021/acs.molpharmaceut.1c00206">doi:10.1021/acs.molpharmaceut.1c00206</a></p> <p>Abstract</p> <p>Physiologically based pharmacokinetic (PBPK) models are increasingly used in drug development to simulate changes in both systemic and tissue exposures that arise as a result of changes in enzyme and/or transporter activity. Verification of these model-based simulations of tissue exposure is challenging in the case of transporter-mediated drug–drug interactions (tDDI), in particular as these may lead to differential effects on substrate exposure in plasma and tissues/organs of interest. Gadoxetate, a promising magnetic resonance imaging (MRI) contrast agent, is a substrate of organic-anion-transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). In this study, we developed a gadoxetate PBPK model and explored the use of liver-imaging data to achieve and refine in vitro–in vivo extrapolation (IVIVE) of gadoxetate hepatic transporter kinetic data. In addition, PBPK modeling was used to investigate gadoxetate hepatic tDDI with rifampicin i.v. 10 mg/kg. In vivo dynamic contrast-enhanced (DCE) MRI data of gadoxetate in rat blood, spleen, and liver were used in this analysis. Gadoxetate in vitro uptake kinetic data were generated in plated rat hepatocytes. Mean (%CV) in vitro hepatocyte uptake unbound Michaelis–Menten constant (<i>K</i><sub>m,u</sub>) of gadoxetate was 106 μM (17%) (<i>n</i> = 4 rats), and active saturable uptake accounted for 94% of total uptake into hepatocytes. PBPK–IVIVE of these data (bottom-up approach) captured reasonably systemic exposure, but underestimated the in vivo gadoxetate DCE–MRI profiles and elimination from the liver. Therefore, in vivo rat DCE–MRI liver data were subsequently used to refine gadoxetate transporter kinetic parameters in the PBPK model (top-down approach). Active uptake into the hepatocytes refined by the liver-imaging data was one order of magnitude higher than the one predicted by the IVIVE approach. Finally, the PBPK model was fitted to the gadoxetate DCE–MRI data (blood, spleen, and liver) obtained with and without coadministered rifampicin. Rifampicin was estimated to inhibit active uptake transport of gadoxetate into the liver by 96%. The current analysis highlighted the importance of gadoxetate liver data for PBPK model refinement, which was not feasible when using the blood data alone, as is common in PBPK modeling applications. The results of our study demonstrate the utility of organ-imaging data in evaluating and refining PBPK transporter IVIVE to support the subsequent model use for quantitative evaluation of hepatic tDDI.</p> <div></div> </div> </div> </div> </div> </div> </div> </div> </div> <div>PBPK Modelling of Gadoxetate in Rat Liver</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/121" hreflang="en">Liver</a></div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> </div> </div> Thu, 19 Aug 2021 07:24:38 +0000 gunnar.schuetz 406 at https://www.imi-tristan.eu Liver T1 Mapping with vFA https://www.imi-tristan.eu/node/396 <span>Liver T1 Mapping with vFA</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-05-15T12:00:00Z">15.05.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Bias, repeatability and reproducibility of liver T1 mapping with variable flip angles</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-a5f92d00-8fc3-446c-9a2f-d7d6be976580 coh-component-instance-a5f92d00-8fc3-446c-9a2f-d7d6be976580 ssa-instance-2910546535 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-382c3026-cf9e-4466-9dcd-c0e19a73f282 coh-component-instance-382c3026-cf9e-4466-9dcd-c0e19a73f282 ssa-instance-4203109745 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Liver T1 Mapping with vFA</h2> <div class="page-head"> <p><strong>Bias, repeatability and reproducibility of liver T1 mapping with variable flip angles</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Sirisha Tadimalla, Daniel Wilson, David Shelley, Gavin Bainbridge, Margaret Saysell, Iosif A Mendichovszky, Martin Graves, Geoff JM Parker, Steven Sourbron</em></p> <p><br /> ISMRM Conference 2021</p> <p>Abstract</p> <p>A multi-centre, multi-vendor study in 8 travelling healthy volunteers was conducted for technical validation of variable flip angle (VFA) T1 mapping in the liver across 6 scanners (3 vendors and 2 field strengths). The 95% CI was 28 ± 8% for the bias in liver T1, 10 ± 3% for the intra-scanner repeatability CV and 28 ± 6% for the inter-scanner reproducibility CV. These values are comparable to literature values for B1+-corrected VFA T1 in prostate, brain, breast, and phantoms. Any proposed refinement of the VFA method in the liver should demonstrate a significant improvement on those benchmarks before it can be recommended as a future standard.</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Liver T1 Mapping with vFA</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/121" hreflang="en">Liver</a></div> </div> </div> Tue, 22 Jun 2021 19:22:30 +0000 gunnar.schuetz 396 at https://www.imi-tristan.eu Population AIF for lung perfusion https://www.imi-tristan.eu/node/391 <span>Population AIF for lung perfusion</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-05-15T12:00:00Z">15.05.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Population Arterial Input Function for Lung Perfusion Imaging</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-942070bf-526b-422e-8a38-0d9942da0ac5 coh-component-instance-942070bf-526b-422e-8a38-0d9942da0ac5 ssa-instance-2812284738 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-46a6975b-b9ea-4ce0-9f51-b053b4a9f019 coh-component-instance-46a6975b-b9ea-4ce0-9f51-b053b4a9f019 ssa-instance-314637869 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Population AIF for lung perfusion</h2> <div class="page-head"> <p><strong>Population Arterial Input Function for Lung Perfusion Imaging</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Marta Tibiletti, Jo Naish, John C Waterton, Paul JC Hughes, James A Eaden, James M Wild, Geoff JM Parker</em></p> <p><br /> ISMRM Conference 2021</p> <p>Abstract</p> <p>Introduction: T1-weighted contrast agent (CA)-based perfusion imaging can be used to characterize the first pass of a CA bolus through the lung, allowing for the measurement of blood flow, relative blood volume and mean transit time. <br /> One of the method’s challenges is the accurate extraction of the Arterial Input Function (AIF), the concentration of CA in a feeding artery. Some of the issues that may arise are: curve sampling at too low temporal resolution for the rapidly changing curve; errors in the peak height due to signal saturation at high CA concentrations; incomplete spoiling; partial volume and inflow effects; and motion. <br /> Previous investigators have used  consensus or population-based arterial input functions (AIFs) in the analysis of extended dynamic contrast-enhanced MR data. However it is not known whether population-based AIFs are also useful in perfusion imaging based on first-pass DCEMRI.<br /> In this work, we explore the possibility of extracting a population AIF for lung perfusion imaging, detailing the first pass of the CA bolus at high temporal resolution in the pulmonary arteries (PA). The results of the analysis using a measured AIF and the population AIF are compared.<br /> Comments:<br /> A population AIF was obtained from the PA. While there is significant variation among the GV fitting from which the population AIF was obtained, the variation is not related to dose but the AUC is linearly related to dose. When comparing the results of the perfusion analysis within our patient population, the only significant difference was observed in in BV, which is lower when using a population AIF. This is probably due to some of the measured AIF presenting too low AUC.</p> <p>Conclusion:<br /> In this work, we have derived a population AIF for perfusion quantification in the lung. This AIF may be of use in settings where measured AIF quality is insufficient to allow reliable quantification.<br />  </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Population AIF for lung perfusion</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/136" hreflang="en">Lung</a></div> </div> </div> Tue, 22 Jun 2021 19:17:20 +0000 gunnar.schuetz 391 at https://www.imi-tristan.eu Gadoxetate MRI to assess rifampicin effect https://www.imi-tristan.eu/node/386 <span>Gadoxetate MRI to assess rifampicin effect</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-03-15T12:00:00Z">15.03.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Acute and chronic rifampicin effect on gadoxetate uptake in rats using gadoxetate DCE-MRI</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-ea814786-f1b7-49d4-a54c-4ea6770631b6 coh-component-instance-ea814786-f1b7-49d4-a54c-4ea6770631b6 ssa-instance-2051510954 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-f85090e4-eb46-4e9c-94b2-c39b069a6ea7 coh-component-instance-f85090e4-eb46-4e9c-94b2-c39b069a6ea7 ssa-instance-4185094668 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Gadoxetate MRI to assess rifampicin effect</h2> <div class="page-head"> <p><strong>Acute and chronic rifampicin effect on gadoxetate uptake in rats using gadoxetate DCE-MRI</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Mikael Montelius, Steven Sourbron, Nicola Melillo, Daniel Scotcher, Aleksandra Galetin, Gunnar Schuetz, Claudia Green, Edvin Johansson, John Waterton, Paul D. Hockings</em></p> <p><br /> ISMRM Conference 2021</p> <p>Abstract</p> <p>Non-invasive biomarkers for Drug Induced Liver Injury, which cause liver failure and impede drug development, and Drug-Drug Interactions affecting pharmacokinetics of drugs when combined are needed. We used gadoxetate DCE-MRI to measure clinical and high dose rifampicin effects on hepatocellular uptake in acute and chronic settings in rats. At high dose, uptake was significantly reduced after acute dosing, and returned to baseline after chronic dosing. Similar but non-significant effects was seen at clinical dose levels. We thus demonstrated the potential of gadoxetate DCE-MRI to non-invasively assess drug-induced inhibition of hepatocellular transport and DDIs. <br /> .</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Gadoxetate MRI to assess rifampicin effect</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/121" hreflang="en">Liver</a></div> </div> </div> Tue, 22 Jun 2021 19:11:14 +0000 gunnar.schuetz 386 at https://www.imi-tristan.eu Assess Liver Transporter Kinetics and DDI from Imaging Data https://www.imi-tristan.eu/node/381 <span>Assess Liver Transporter Kinetics and DDI from Imaging Data</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-01-19T12:00:00Z">19.01.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Insights on hepatobiliary transporter kinetics and DDIs from tissue imaging data: Lessons from PBPK modelling of gadoxetate</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-0c6ca766-d990-445d-8f62-241964f07efd coh-component-instance-0c6ca766-d990-445d-8f62-241964f07efd ssa-instance-4151809505 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-71a71283-918d-4c29-8cc5-a3cb4f98a94c coh-component-instance-71a71283-918d-4c29-8cc5-a3cb4f98a94c ssa-instance-4228699789 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Assess Liver Transporter Kinetics and DDI from Imaging Data</h2> <div class="page-head"> <p><strong>Insights on hepatobiliary transporter kinetics and DDIs from tissue imaging data: Lessons from PBPK modelling of gadoxetate</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Daniel Scotcher</em></p> <p>2021 Drug Metabolism Discussion Group and Swedish Academy of Pharmaceutical Sciences Online Joint Meeting</p> <p>Abstract</p> <p>Physiologically-based pharmacokinetic (PBPK) modelling provides a framework for in vitro-in vivo extrapolation (IVIVE) of drug disposition. Quantitative prediction of transporter-mediated processes and tissue permeation remains challenging due to the lack of available in vivo tissue data for model validation. Gadoxetate is a magnetic resonance imaging (MRI) contrast agent and substrate of organic anion transporting polypeptide 1B1 (OATP1B1) and multidrug resistance-associated protein 2 (MRP2). Gadoxetate is being explored as a novel imaging biomarker for hepatic transporter function in context of evaluation of drug-drug interactions and drug induced liver injury. The in vitro uptake kinetics of gadoxetate in plated rat hepatocytes were assessed, and transporter kinetic parameters derived using a mechanistic cell model. Subsequently, a novel PBPK model was developed for gadoxetate in rat, where liver uptake and cellular binding were informed by IVIVE. Gadoxetate in vivo blood, spleen and liver data obtained in the presence and absence of a single 10 mg/kg intravenous dose of rifampicin were used for PBPK model refinement. The PBPK model successfully predicted gadoxetate concentrations in systemic blood and spleen and corresponding increase in gadoxetate systemic exposure in the presence of rifampicin, whereas liver concentrations were under-predicted. Refinement of the PBPK model using the dynamic contrast agent enhanced (DCE)-MRI data enabled recovery of the liver profile. The current study demonstrates utility of tissue imaging data in validating and refining PBPK models for prediction of transporter-mediated disposition.<br />  </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Assess Liver Transporter Kinetics and DDI from Imaging Data</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/121" hreflang="en">Liver</a></div> </div> </div> Tue, 22 Jun 2021 19:04:24 +0000 gunnar.schuetz 381 at https://www.imi-tristan.eu Imaging of DDI risk with liver transporters https://www.imi-tristan.eu/node/376 <span>Imaging of DDI risk with liver transporters</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-03-12T12:00:00Z">12.03.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>In vivo imaging and evaluation of drug-drug interaction risk arising via hepatobiliary transporters</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-99d6b889-6dda-4cd6-b156-26133c37caab coh-component-instance-99d6b889-6dda-4cd6-b156-26133c37caab ssa-instance-1136428565 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-bcd61b80-82c3-4e43-9900-74b37cc4e9a3 coh-component-instance-bcd61b80-82c3-4e43-9900-74b37cc4e9a3 ssa-instance-2654790208 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <h2>Imaging of DDI risk with liver transporters</h2> <div class="page-head"> <p><strong>In vivo imaging and evaluation of drug-drug interaction risk arising via hepatobiliary transporters</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>J. Gerry Kenna, Claudia Green, Catherine D. G. Hines Iina Laitinen, Aleksandra Galetin, Paul D. Hockings,  Nicola Melillo, Mikael Montelius,  Daniel Scotcher, Steven Sourbron, John C. Watertone, Gunnar Schütz</em><br />  </p> <p>Virtual 2021 Annual Meeting of the US Society of Toxicology and ToxExpo</p> <p>Abstract</p> <p>Inhibition of transporters that mediate hepatic drug uptake and/or biliary excretion may cause clinically relevant drug-drug interactions (DDIs) leading to potentiated or reduced efficacy, and/or increased or reduced toxicity to liver or other tissues. These DDIs are difficult to assess, since accurate prediction of changes in tissue exposure in vivo based on in vitro transport interaction data is challenging. Dynamic contract enhanced magnetic resonance imaging (DCE-MRI) enables in vivo visualisation of hepatic transporter mediated uptake and efflux of the contrast agent gadoxetate. When analysed using a compartmental kinetic model of gadoxetate disposition, gadoxetate DCE-MRI studies provide quantitative rate constants for hepatic gadoxetate uptake (khe) and biliary excretion (kbh). These processes are mediated primarily by Organic Anion Transport Polypeptides (OATPs) and Multidrug Resistance Protein Type 2 (MRP2), respectively. To evaluate drug effects on hepatic gadoxetate khe and kbh, DCE-MRI studies were undertaken in adult male Wistar rats (approx. 250g body weight) dosed intravenously (iv) with single doses of <br /> drugs (rifampicin, asunaprevir, bosentan, cyclosporin, ketoconazole, pioglitazone) that inhibited rat oatp, and human OATP, activities in vitro. Drug doses were selected, via pharmacokinetic modelling and simulation, to achieve rat peripheral blood plasma concentrations following iv administration that were equivalent to steady-state human blood plasma concentrations. Simulations predicted that the selected doses of rifampicin and cyclosporin reduced liver gadoxetate exposure in vivo, whereas the other tested drugs did not. Gadoxetate khe values were determined 20 min after iv administration of dose vehicle and then, in the same animals, after a minimum 48 hr washout interval and following drug administration (n=6 per group). Gadoxetate khe (min-1) was reduced (p &lt; 0.01) following administration of rifampicin at 2 mg/kg (mean +SD, dose: 0.44+0.06; vehicle: 0.92+0.17) or cyclosporin at 5 mg/kg (mean+SD, dose: 0.08+0.02; vehicle: 1.00+0.24); but not after dosing of asunaprevir at 5 mg/kg, bosentan at 2 mg/kg, ketoconazole at 3 mg/kg or pioglitazone at 0.4 mg/kg. These results indicate that gadoxetate DCE-MRI may aid assessment of hepatic transporter-mediated DDI risk.</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Imaging of DDI risk with liver transporters</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/121" hreflang="en">Liver</a></div> </div> </div> Tue, 22 Jun 2021 18:57:26 +0000 gunnar.schuetz 376 at https://www.imi-tristan.eu 129Xe-MRI to Differentiate Fibrosis and Inflammation https://www.imi-tristan.eu/node/371 <span>129Xe-MRI to Differentiate Fibrosis and Inflammation</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2021-01-21T12:00:00Z">21.01.2021</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Hyperpolarised 129-xenon MRI in differentiating between fibrotic and inflammatory interstitial lung disease and assessing longitudinal change</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-07127dbe-b14e-4698-82b2-782928ac5228 coh-component-instance-07127dbe-b14e-4698-82b2-782928ac5228 ssa-instance-3663716253 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-fe1567f7-d194-4732-a868-35ee297aa923 coh-component-instance-fe1567f7-d194-4732-a868-35ee297aa923 ssa-instance-1356952160 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>129Xe-MRI to Differentiate Fibrosis and Inflammation</h2> <div class="page-head"> <p><strong>Hyperpolarised 129-xenon MRI in differentiating between fibrotic and inflammatory interstitial lung disease and assessing longitudinal change</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>by Irma Mahmutovic Persson, Nina Fransén Pettersson, Jian Liu, Hanna Falk Håkansson, Anders Örbom, René JA Eaden, GJ Collier, G Norquay, H-F Chan, PJC Hughes, ND Weatherley, S Rajaram, A Swift, CT Leonard, S Skeoch, N Chaudhuri, GJM Parker, SM Bianchi, JM Wild</em></p> <p><br /> Thorax 2021;76:A46-A47. doi: <a href="http://dx.doi.org/10.1136/thorax-2020-BTSabstracts.80">10.1136/thorax-2020-BTSabstracts.80</a></p> <p>Abstract</p> <p>Introduction and Objectives: Apparent diffusion coefficient (ADC) and mean diffusive length scale (LmD) are diffusion-weighted (DW) MRI measurements of alveolar gas diffusion, providing novel lung microstructure information. Hyperpolarised 129-xenon (<sup>129</sup>Xe) MR spectroscopy is a quantitative marker of gas exchange, using the ratio of uptake of <sup>129</sup>Xe in red blood cells to tissue/plasma (RBC:TP).</p> <p>The objective was to evaluate hyperpolarised <sup>129</sup>Xe MRI in differentiating between fibrotic and inflammatory ILD and assessing longitudinal change.</p> <p>Methods: A prospective, multicentre study of ILD patients including connective tissue disease ILD (CTD-ILD), drug induced ILD (DI-ILD), hypersensitivity pneumonitis (HP), idiopathic non-specific interstitial pneumonia (iNSIP) and idiopathic pulmonary fibrosis (IPF). Hyperpolarised <sup>129</sup>Xe MRI was performed on a 1.5T scanner. Baseline HRCT scan was performed within a year prior to the MRI scan. Semi-quantitative visual CT analysis was performed by two consultant chest radiologists. In the non-IPF subtypes, a ground glass opacity score &lt;2 and ≥2 was used to define fibrotic and inflammatory ILD respectively. All IPF subjects were classified as fibrotic.</p> <p>Results: To date, 34 patients (5 CTD-ILD, 9 DI-ILD, 7 HP, 2 iNSIP, 11 IPF) have complete MRI scan data for two separate visits (6 weeks apart for DI-ILD/HP/iNSIP and 6 months apart for CTD-ILD/IPF). There were 18 patients in the fibrotic group and 16 in the inflammatory group. At baseline visit there was no significant difference in mean RBC:TP between the fibrotic and inflammatory groups (0.17 vs 0.14; p=0.083), but a significant difference between the fibrotic and inflammatory groups in mean ADC (0.048 vs 0.043; p=0.030) (figure 1a) and mean LmD(261.3 vs 243.4; p=0.017) (figure 1b). In longitudinal change, there was a significant difference in mean RBC:TP between the fibrotic and inflammatory groups (-0.026 vs 0.0016; p=0.023), but no significant difference between the fibrotic and inflammatory groups in mean ADC (0.00089 vs -0.00025; p=0.25) and mean LmD (2.1 vs -0.19; p=0.39).</p> <p>Conclusions: <sup>129</sup>Xe DW-MRI could have a role in differentiating changes in the airway microstructure between fibrotic and inflammatory ILD. <sup>129</sup>Xe RBC:TP has sensitivity to longitudinal change with a decline in gas exchange observed in the fibrotic group but not in the inflammatory group.<br />  </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>129Xe-MRI to Differentiate Fibrosis and Inflammation</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/136" hreflang="en">Lung</a></div> </div> </div> Tue, 22 Jun 2021 18:47:34 +0000 gunnar.schuetz 371 at https://www.imi-tristan.eu Profiling of DIILD in a Bleomycin Rat Model https://www.imi-tristan.eu/node/366 <span>Profiling of DIILD in a Bleomycin Rat Model</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2020-09-10T12:00:00Z">10.09.2020</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Gene expression and cellular profiling in a rat bleomycin model of drug-induced interstitial lung disease (DIILD)</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-5192fdf4-9cf1-4827-bc75-eff60e417c9c coh-component-instance-5192fdf4-9cf1-4827-bc75-eff60e417c9c ssa-instance-736751224 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-79ccdbf8-320f-426d-8098-fccc7fdcc175 coh-component-instance-79ccdbf8-320f-426d-8098-fccc7fdcc175 ssa-instance-258829805 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Profiling of DIILD in a Bleomycin Rat Model</h2> <div class="page-head"> <p><strong>Gene expression and cellular profiling in a rat bleomycin model of drug-induced interstitial lung disease (DIILD)</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Irma Mahmutovic Persson, Nina Fransén Pettersson, Jian Liu, Hanna Falk-Håkansson, Lars E. Olsson and Karin von Wachenfeldt - on behalf of the TRISTAN Consortium</em></p> <p><br /> ESR Conference 2020</p> <p>Abstract</p> <p>A large number of frequently prescribed drugs have the potential to cause DIILD. We have characterized a rat model of bleomycin-triggered DIILD, by gene profiling combined with flow cytometric characterization of immune cell populations in lungs over 28 days.</p> <p><br /> Methods &amp; Results: Sprague-Dawley rats received a single dose of intratracheal bleomycin. Longitudinal imaging was performed (MRI and <sup>18</sup>F-FDG-PET/CT) and BAL fluid, blood, lungs and spleen collected. Lung homogenates were used for analysis of gene expression (RT-qPCR), assessment of hydroxyproline content and for flow cytometric analysis of immune cell populations in lung. Early time points were dominated by pro-inflammatory gene expression. Interestingly, fibrosis related genes, such as Gremlin1, CTGF and TGFβs, were also up-regulated (p&lt;0.001) during the inflammatory phase (d3-7). In addition, at later time points during the fibrosis phase (d14-28) inflammatory related genes such as CCL3 (p&lt;0.01) and TNFα stayed up-regulated. Some genes, such as IL-4 and IL-5, revealed dual peaks at d7 and at d28. Animals identified by MRI to have more severe disease demonstrated a different gene profile compared to those with less disease.  Analysis of immune cell populations during the different stages of the disease showed increased numbers of eosinophils, neutrophils and NK cells at the early stages. Neutrophils and macrophages also showed up in a second cell-peak at d28.</p> <p><br /> Conclusion: Linking the pathological changes observed by imaging to gene expression patterns and immune cell profiles in the lung, has provided an increasing understanding of how biomarkers can be implemented to develop improved DIILD- and lung injury models.</p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Profiling of DIILD in a Bleomycin Rat Model</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/136" hreflang="en">Lung</a></div> </div> </div> Tue, 22 Jun 2021 18:28:01 +0000 gunnar.schuetz 366 at https://www.imi-tristan.eu Uptake of Pembrolizumab in lymphoid organs https://www.imi-tristan.eu/node/361 <span>Uptake of Pembrolizumab in lymphoid organs </span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2020-10-05T12:00:00Z">05.10.2020</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>89Zr-pembrolizumab biodistribution is influenced by PD-1-mediated uptake in lymphoid organs</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-b747f95d-1905-49ef-8be2-c0df232af726 coh-component-instance-b747f95d-1905-49ef-8be2-c0df232af726 ssa-instance-1212901738 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-5b05abde-5265-41c6-83b0-19bff4fbe60c coh-component-instance-5b05abde-5265-41c6-83b0-19bff4fbe60c ssa-instance-3915271382 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Uptake of Pembrolizumab in lymphoid organs </h2> <div class="page-head"> <p><strong>89Zr-pembrolizumab biodistribution is influenced by PD-1-mediated uptake in lymphoid organs</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Elly L van der Veen, Danique Giesen, Linda Pot-de Jong, Annelies Jorritsma-Smit, Elisabeth G E De Vries, and Marjolijn N Lub-de Hooge</em></p> <p> </p> <p><em>J Immunother Cancer. 2020; 8(2): e000938. doi: </em><a href="https://dx.doi.org/10.1136%2Fjitc-2020-000938" target="_blank" rel="noreferrer noopener">10.1136/jitc-2020-000938</a></p> <p>Abstract</p> <p>Background<br /> To better predict response to immune checkpoint therapy and toxicity in healthy tissues, insight in the in vivo behavior of immune checkpoint targeting monoclonal antibodies is essential. Therefore, we aimed to study in vivo pharmacokinetics and whole-body distribution of zirconium-89 (<sup>89</sup>Zr) labeled programmed cell death protein-1 (PD-1) targeting pembrolizumab with positron-emission tomography (PET) in humanized mice.</p> <p>Methods<br /> Humanized (huNOG) and non-humanized NOG mice were xenografted with human A375M melanoma cells. PET imaging was performed on day 7 post <sup>89</sup>Zr-pembrolizumab (10 µg, 2.5 MBq) administration, followed by ex vivo biodistribution studies. Other huNOG mice bearing A375M tumors received a co-injection of excess (90 µg) unlabeled pembrolizumab or <sup>89</sup>Zr-IgG4 control (10 µg, 2.5 MBq). Tumor and spleen tissue were studied with autoradiography and immunohistochemically including PD-1.</p> <p>Results<br /> PET imaging and biodistribution studies showed high <sup>89</sup>Zr-pembrolizumab uptake in tissues containing human immune cells, including spleen, lymph nodes and bone marrow. Tumor uptake of <sup>89</sup>Zr-pembrolizumab was lower than uptake in lymphoid tissues, but higher than uptake in other organs. High uptake in lymphoid tissues could be reduced by excess unlabeled pembrolizumab. Tracer activity in blood pool was increased by addition of unlabeled pembrolizumab, but tumor uptake was not affected. Autoradiography supported PET findings and immunohistochemical staining on spleen and lymph node tissue showed PD-1 positive cells, whereas tumor tissue was PD-1 negative.</p> <p>Conclusion<br /><sup>89</sup>Zr-pembrolizumab whole-body biodistribution showed high PD-1-mediated uptake in lymphoid tissues, such as spleen, lymph nodes and bone marrow, and modest tumor uptake. Our data may enable evaluation of <sup>89</sup>Zr-pembrolizumab whole-body distribution in patients.<br />  </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Uptake of Pembrolizumab in lymphoid organs </div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/141" hreflang="en">Biologics-Pet</a></div> </div> </div> Tue, 22 Jun 2021 18:18:07 +0000 gunnar.schuetz 361 at https://www.imi-tristan.eu Bimodal PET/NIRF imaging of HER-2 tumors https://www.imi-tristan.eu/node/356 <span>Bimodal PET/NIRF imaging of HER-2 tumors</span> <span><span lang="" about="/user/276" typeof="schema:Person" property="schema:name" datatype="">gunnar.schuetz</span></span> <span>22.06.2021</span> <div> <div>Private</div> <div>Public</div> </div> <div><time datetime="2020-08-26T12:00:00Z">26.08.2020</time> </div> <div> <div> <article about="/taxonomy/term/131"> <div> <div class="coh-container ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-style-article-teaser---type-1---sgm ssa-instance-2481043932 coh-ce-cpt_article_teaser_type_1-7c69df1" > <div class="coh-container text-wrapper" > <h4 class="coh-heading headline "> <b>Article Title and Summary</b> </h4> <div class="coh-wysiwyg description"> <p>Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat.</p> </div> <a href="/#" class="coh-link ssa-component coh-component ssa-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 coh-component-instance-f0598579-1399-4f64-8cf9-8ba150a93307 read-more enable-basic-hover ssa-instance-664298994 coh-ce-cpt_read_more_button-34304a6b" title="Read more" target="_self" data-analytics-layer="[{&quot;trigger&quot;:&quot;click&quot;,&quot;value&quot;:&quot;gaGenericEvent&quot;,&quot;key&quot;:&quot;event&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventCategory&quot;,&quot;value&quot;:&quot;CTA&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventLabel&quot;,&quot;value&quot;:&quot;www.imi-tristan.eu/#&quot;},{&quot;trigger&quot;:&quot;click&quot;,&quot;key&quot;:&quot;eventAction&quot;,&quot;value&quot;:&quot;Read more&quot;}]" > <span class="coh-inline-element">Read more</span> </a> </div> </div> </div> </article> </div> </div> <div><p><strong>Site-specific, platform-based dual-labeled immunoconjugate for bimodal PET/NIRF imaging of HER2-positive tumors</strong></p> </div> <div><ul class="coh-style-approval-code-list"><li class="coh-approval-code coh-page-approval-code">123</li></ul></div> <div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-89a7df07-c73f-4fa1-b3de-0e99a50db6ea coh-component-instance-89a7df07-c73f-4fa1-b3de-0e99a50db6ea ssa-instance-786351430 coh-ce-cpt_text_component-109d695a"> <div id="head-box"><div class="container head-box sub" title="Publication" style="background-image:url(&quot;/sites/g/files/vrxlpx12716/files/2020-12/background-header-publications.jpg&quot;);"><div class="row"><div class="headline transparent-box-black"><h1 class="hind-light p-md-5"><span class="green-font hind-semibold">Publications</span><br />Take a look</h1></div></div></div></div> </div> <div class="coh-wysiwyg ssa-component coh-component ssa-component-instance-bd9a6bed-754b-4c6a-a228-9b69df5f00cb coh-component-instance-bd9a6bed-754b-4c6a-a228-9b69df5f00cb ssa-instance-2666646343 coh-ce-cpt_text_component-109d695a"> <div class="container publication-section"> <div class="spacer"> <div class="row"> <div class="col-sm-12 col-lg-12 p-md-5"> <div class="blog-post"> <div> <h2>Biomodal PET/NIRF Imaging of her-2 tumors</h2> <div class="page-head"> <p><strong>Site-specific, platform-based dual-labeled immunoconjugate for bimodal PET/NIRF imaging of HER2-positive tumors</strong></p> </div> <div> <div class="paragraph" style="clear:both;"> <div class="paragraph-box-text"> <p><em>Pierre Adumeau, René Raavé, Milou Boswinkel, Sandra Heskamp, Mathieu Moreau, Claire Bernhard, Laurène Da Costa, Victor Goncalves, Franck Denat</em></p> <p><br /> EMIM Conference 2020</p> <p>Abstract</p> <p>Introduction <br /> Immuno-PET/NIRF imaging is very promising for cancer therapy, as it allows non-invasive localization of the tumor and its image-guided resection. The mostly used strategy to synthesize such dual-labeled conjugates relies on a double, sequential random conjugation of the fluorophore and the radionuclide/chelator with the antibody. However, the random conjugation leads to high heterogeneity and potential loss of bioactivity and these phenomena are exponentially amplified by sequential modifications. Therefore, there is a need for a better dual-labeling strategy for PET/NIRF imaging.</p> <p>Results/Discussion <br /> The trivalent platform BCN-DFO-IR800 was obtained in a five steps synthetic route with a global yield of 5%. Trastuzumab-N3, obtained through chemoenzymatic glycoengineering, was efficiently conjugated with the trivalent platform, leading to trastss-DFO/IR800 with a degree of labeling (DOL) of 2.0 (theoretical maximum). Trastrd-DFO/IR800 was synthesized with comparable DOL for the sake of comparison.<br /> Radiolabeling of the conjugates with <sup>89</sup>Zr yielded the radioconjugates with high yield, purity and specific activity (RCY &gt;95%, RCP &gt;99%, SA &gt;50 MBq/mg).<br /> The site-specific conjugate displayed lesser aggregation over time than its random cousin (after 7 days in PBS: 5.0±0.1 % vs 12.7±5.2 % for trastss-DFO/IR800 and trastrd-DFO/IR800, respectively). Fluorescence intensity of the site-specific conjugate also showed an improved stability compared to the random conjugate, the first displaying 90±1 % of the initial fluorescence intensity after 7 days in PBS, with only 25±3 % for trastrd-DFO/IR800.</p> <p>Conclusion <br /> This is the first example of a platform-based, site-specific PET/NIRF conjugate. This strategy gives complete control over the dual-labeling of antibody. The preliminary results have demonstrated the in vitro superiority of our conjugate over the classical random bimodal conjugate. We expect these results to translate into a superior in vivo behavior of the site-specific conjugate. In vivo experiment results will be presented at the conference.<br />  </p> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> </div> <div>Bimodal PET/NIRF Imaging of HER-2 Tumors</div> <div> <div>Article categories</div> <div> <div><a href="/taxonomy/term/126" hreflang="en">Publications</a></div> <div><a href="/taxonomy/term/141" hreflang="en">Biologics-Pet</a></div> </div> </div> Tue, 22 Jun 2021 18:08:01 +0000 gunnar.schuetz 356 at https://www.imi-tristan.eu