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</style><style id="font-style-tag"></style></div><div class="navigator s-navbar-section" id="s-header"><div class="s-bg-image s-bg-light-text strikingly-fixed" id="s-header-bg" parentbinding="[object Object]" image="[object Object]" videohtml="" videourl="" datasrc="https://static-assets.strikinglycdn.com/images/themes/profile/bg.jpg" textcolor="light" style="background-repeat: no-repeat; background-size: cover; background-color: transparent; background-position: 49.5% 0%; background-image: url("https://static-assets.strikinglycdn.com/images/themes/profile/bg.jpg");"></div><div class="s-bg-image s-bg-light-text container" id="s-header-banner" no-logo="!image1.hasContentOrIsEditMode()" parentbinding="[object Object]" image="[object Object]" datasrc="//uploads.striking.ly/page/images/backgrounds/banners/banner1.jpg" textcolor="light" style="background-repeat: no-repeat; background-size: cover; background-color: transparent; background-position: 50% 50%; background-image: url("//uploads.striking.ly/page/images/backgrounds/banners/banner1.jpg");"><div class="video-bg-wrap"></div><div class="logo ib"><div class="s-component s-image"><div><div class="s-component-content"><div><img src="./index_files/xiawkzii6ht4v3vgmnsy.png" alt="" title="" class="crop-default" data-description=""></div></div></div></div></div><h1 class="header-title"><div class="s-component s-text"><div class="s-component-content s-font-title"><p><span class="s-text-color-black"><strong>OpenVax</strong></span></p></div></div></h1><h3 class="header-subtitle"><div class="s-component s-text"><div class="s-component-content s-font-heading"><p><span class="s-text-color-gray">Research group at the Icahn School of Medicine at Mount Sinai</span></p></div></div></h3></div><div id="s-nav-placeholder"><div class="container" style="display: none; height: 56px;"></div></div><div class="strikingly-fixed" id="s-nav" style="width: 1766px; top: 0px;"><div class="container"><ul class="s-nav"><li><a class="s-font-body s-nav-item selected" href="https://www.openvax.org/#research">Research</a></li><li><a class="s-font-body s-nav-item" href="https://www.openvax.org/#clinical-trials">Clinical Trials</a></li><li><a class="s-font-body s-nav-item" href="https://www.openvax.org/#publications">Publications</a></li><li><a class="s-font-body s-nav-item" href="https://www.openvax.org/#software">Software</a></li><li><a class="s-font-body s-nav-item" href="https://www.openvax.org/#members">Members</a></li><li><a class="s-font-body s-nav-item" href="https://www.openvax.org/#blog">Blog</a></li><div id="loginContainer"></div><li id="s-ecommerce-nav-shopping-cart-wrapper" class="s-ecommerce-nav-shopping-cart-wrapper hidden"></li><li class="nav-item"><a class="s-font-body s-nav-item site-search" href="https://www.openvax.org/search"><span class="fa fa-search"></span></a></li></ul></div></div></div><div class="s-navbar-container"><div class="navbar-drawer-bar strikingly-nav-transition"><div class="drawer-container"><a class="navbar" href="javascript:void(0);"><div class="navbar-icons"><span></span><span></span><span></span></div></a>
<div class="mobile-cart-icon" id="s-mobile-shopping-cart-new"></div><div class="navbar-drawer-title-container"></div></div></div><div id="navbar-drawer-mask"></div><div class="navbar-drawer strikingly-drawer bottom-border strikingly-nav-transition"><ul id="nav-drawer-list"><span><li><a class="navbar-drawer-item s-font-body selected" href="https://www.openvax.org/#1">Research</a></li></span><span><li><a class="navbar-drawer-item s-font-body" href="https://www.openvax.org/#2">Clinical Trials</a></li></span><span><li><a class="navbar-drawer-item s-font-body" href="https://www.openvax.org/#3">Publications</a></li></span><span><li><a class="navbar-drawer-item s-font-body" href="https://www.openvax.org/#4">Software</a></li></span><span><li><a class="navbar-drawer-item s-font-body" href="https://www.openvax.org/#5">Members</a></li></span><span><li><a class="navbar-drawer-item s-font-body" href="https://www.openvax.org/#6">Blog</a></li></span><span><li><a class="navbar-drawer-dropdown navbar-drawer-item s-font-body site-search" href="https://www.openvax.org/search"><span class="fa fa-search"></span>
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<div class=" background-image lazyloaded s-new-text-section s-section s-text-section background-image" data-react-style="{}"><div class="container"><div class="clearfix"><div class="columns sixteen"><div class="s-title-group "><div class="s-title "><div class="s-component s-text"><h1 class="s-component-content s-font-title"><p>Research</p></h1></div></div></div></div></div><div class="">
<div class="s-mh s-repeatable"><div><div data-sorting-index="0" class="eight columns no-float s-repeatable-item s-last-row"><div class="s-mhi" style="min-height: 314px;"><div class="s-item-text-group "><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p style="text-align: center;">Neoantigens</p></h3></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>A neoantigen is a determinant of immune-mediated killing which has not been previously encountered by the adaptive immune system. We are particularly interested in neoantigens arising from somatic mutations in tumor cells, since these provide an attractive target for cancer immunotherapies. You can learn more from Schumacher & Schreiber's review paper <a href="http://science.sciencemag.org/content/348/6230/69.full">Neoantigens in cancer immunotherapy</a>.</p><p> </p><p>The OpenVax group develops open source software and machine learning models for predicting different steps of the adaptive immune response to mutated tumor antigens.</p></div></div></div><div class=""></div></div></div></div><div data-sorting-index="1" class="eight columns no-float s-repeatable-item s-last-row"><div class="s-mhi" style="min-height: 314px;"><div class="s-item-text-group "><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p style="text-align: center;">Personalized cancer vaccines</p></h3></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Personalized therapeutic cancer vaccines are a form of cancer immunotherapy which instruct a patient’s immune system to target his or her particular tumor. Early phase I trials have shown some success (<a href="https://doi.org/10.1038/nature23003">Sahin et al. 2017</a>, <a href="https://doi.org/10.1038/nature22991">Ott et al. 2017</a>) and many new pharmaceutical companies are forming around these vaccines.</p><p> </p><p>The OpenVax group is helping initiate and run several clinical trials of personalized cancer vaccines at the Mount Sinai Hospital, in collaboration with <a href="http://labs.icahn.mssm.edu/bhardwajlab/">Dr. Nina Bhardwaj</a>, <a href="https://www.mountsinai.org/profiles/adilia-hormigo">Dr. Adilia Hormigo</a>, <a href="https://www.mountsinai.org/profiles/matthew-galsky">Dr. Matthew Galsky</a>, and Mount Sinai's <a href="http://labs.icahn.mssm.edu/sabadolab/">Vaccine and Cell Therapy Lab</a>. </p></div></div></div><div class=""></div></div></div></div></div></div>
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</div></li><li class="slide s-section-2" id="section-f_69a25535-0c67-4a2c-a476-a176b6a0e65b"><div class="waypoint"></div><a class="section-anchor" style="top: -56px;"></a><div>
<div class=" background-image lazyloaded s-new-media-section s-section s-rows-section background-image" data-react-style="{}"><div class="container"><div class="columns sixteen"><div class="s-title-group "><div class="s-title "><div class="s-component s-text"><h2 class="s-component-content s-font-title"><p>Clinical Trials</p></h2></div></div><div class="s-subtitle"><div class="s-component s-text"><h4 class="s-component-content s-font-heading"><p>Personalized cancer vaccine trials at Mount Sinai using our software</p></h4></div></div></div></div>
<div class="s-media-right s-layout-mediaRight s-repeatable"><div><div data-sorting-index="0" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://clinicaltrials.gov/ct2/show/NCT02721043">Safety and Immunogenicity of Personalized Genomic Vaccine to Treat Malignancies</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"><h6 class="s-component-content s-font-body"><p>Principal Investigator: <a href="http://icahn.mssm.edu/profiles/nina-bhardwaj">Nina Bhardwaj</a></p></h6></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Safety & immunogenicity trial for the PGV-001 vaccine, which consists of 10 neoantigenic peptides injected with an adjuvant (poly-ICLC). Broad set of malignancies:<strong> </strong>H&N, NSCLC, breast, ovarian, bladder, SCC, multiple myeloma. Patients must be disease-free when beginning treatment with PGV-001, so this trial is most applicable following a complete resection.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="1" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://clinicaltrials.gov/ct2/show/NCT03223103">Safety and Immunogenicity of Personalized Genomic Vaccine and Tumor Treating Fields (TTFields) to Treat Glioblastoma </a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"><h6 class="s-component-content s-font-body"><p>Principal Investigator: <a href="http://www.mountsinai.org/profiles/adilia-hormigo">Adilia Hormigo</a></p></h6></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>The PGV-001 neoantigen peptide vaccine in combination with standard-of-care temozolomide and Novocure's "<a href="https://www.novocure.com/our-therapy/">tumor treating fields</a>" for glioblastoma.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="2" class="s-repeatable-item s-last-row"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://clinicaltrials.gov/ct2/show/NCT03359239">Atezolizumab Given in Combination With a Personalized Vaccine in Patients With Urothelial Cancer</a><a href="https://clinicaltrials.gov/ct2/show/NCT03359239"> (NCT03359239)</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"><h6 class="s-component-content s-font-body"><p>Principal Investigator:<a href="http://www.mountsinai.org/profiles/matthew-galsky"> Matt Galsky</a></p></h6></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>The PGV-001 neoantigen peptide vaccine in combination with an anti-PD-L1 checkpoint agent (atezolizumab) for bladder cancer.</p></div></div></div><div class=""></div></div></div></div></div></div></div></div>
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<div class=" background-image lazyloaded s-new-media-section s-section s-rows-section background-image" data-react-style="{}"><div class="container"><div class="columns sixteen"><div class="s-title-group "><div class="s-title "><div class="s-component s-text s-animation-page-slide_in"><h2 class="s-component-content s-font-title"><p>Publications</p></h2></div></div></div></div>
<div class="s-media-right s-layout-mediaRight s-repeatable"><div><div data-sorting-index="0" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="s-item-media-wrapper six columns s-right-in-row right"><div class="s-item-media-group"><div class="s-component s-media s-animation-page-slide_in"><div><div class="s-component-content"><div><div class="s-ratio-box" style="max-width: 720px; max-height: 687px;"><div class="s-ratio-fill" style="padding-bottom: 95.42%;"></div><div><img alt="" title="" class="crop-default lazyloaded" data-description="" width="720" height="687" src="./index_files/PGV_Pipeline_-_Figure_2_vteaxn.jpg" data-src="//user-images.strikinglycdn.com/res/hrscywv4p/image/upload/c_limit,fl_lossy,h_1440,w_720,f_auto,q_auto/1302745/PGV_Pipeline_-_Figure_2_vteaxn.jpg"></div></div></div></div></div></div></div></div><div class="ten columns s-left-in-row right"><div class="s-item-text-group half-offset-right s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"> <a href="https://www.frontiersin.org/articles/10.3389/fimmu.2017.01807/abstract">Computational pipeline for the PGV-001 neoantigen vaccine trial</a> </h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>This paper describes the sequencing protocol and computational pipeline for the PGV-001 personalized vaccine trial. PGV-001 is a therapeutic peptide vaccine targeting neoantigens identified from patient tumor samples. Peptides are selected by a computational pipeline which identifies mutations from tumor/normal exome sequencing and ranks mutant sequences by a combination of predicted Class I MHC affinity and abundance estimated from tumor RNA. The PGV pipeline is modular and consists of independently usable tools and software libraries. We hope that the functionality of these tools may extend beyond the specifics of the PGV-001 trial and enable other research groups in their own neoantigen investigations.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="1" class="s-repeatable-item s-last-row"><div class="clearfix"><div class=""><div class="s-item-media-wrapper six columns s-right-in-row right"><div class="s-item-media-group"><div class="s-component s-media s-animation-page-slide_in"><div><div class="s-component-content"><div><div class="s-ratio-box" style="max-width: 260px; max-height: 266px;"><div class="s-ratio-fill" style="padding-bottom: 102.31%;"></div><div><img alt="" title="" class="crop-default lazyloaded" data-description="" width="260" height="266" src="./index_files/f031a8c7-0188-44bd-9474-45f26c5dd62b_unc1qa.jpg" data-src="//user-images.strikinglycdn.com/res/hrscywv4p/image/upload/c_limit,fl_lossy,h_1440,w_720,f_auto,q_auto/1302745/f031a8c7-0188-44bd-9474-45f26c5dd62b_unc1qa.jpg"></div></div></div></div></div></div></div></div><div class="ten columns s-left-in-row right"><div class="s-item-text-group half-offset-right s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://www.cell.com/cell-systems/fulltext/S2405-4712(18)30232-1">MHCflurry: Open-Source Class I MHC Binding Affinity Prediction</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Predicting the binding affinity of major histocompatibility complex I (MHC I) proteins and their peptide ligands is important for vaccine design. We introduce an open-source package for MHC I binding prediction, MHCflurry. The software implements allele-specific neural networks that use a novel architecture and peptide encoding scheme. When trained on affinity measurements, MHCflurry outperformed the standard predictors NetMHC 4.0 and NetMHCpan 3.0 overall and particularly on non-9-mer peptides in a benchmark of ligands identified by mass spectrometry. The released predictor, MHCflurry 1.2.0, uses mass spectrometry datasets for model selection and showed competitive accuracy with standard tools, including the recently released NetMHCpan 4.0, on a small benchmark of affinity measurements. MHCflurry's prediction speed exceeded 7,000 predictions per second, 396 times faster than NetMHCpan 4.0. MHCflurry is freely available to use, retrain, or extend, includes Python library and command line interfaces, may be installed using package managers, and applies software development best practices.</p></div></div></div><div class=""></div></div></div></div></div></div></div></div>
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</div></li><li class="slide s-section-4" id="section-f_24b8929b-3d87-40e3-a6fe-debb5eea483d"><div class="waypoint"></div><a class="section-anchor" style="top: -56px;"></a><div>
<div class=" background-image lazyloaded s-new-media-section s-section s-rows-section background-image" data-react-style="{}"><div class="container"><div class="columns sixteen"><div class="s-title-group "><div class="s-title "><div class="s-component s-text s-animation-page-slide_in"><h2 class="s-component-content s-font-title"><p>Open Source Software</p></h2></div></div></div></div>
<div class="s-media-right s-layout-mediaRight s-repeatable"><div><div data-sorting-index="0" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://github.com/openvax/vaxrank">Vaxrank</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Generates a ranked list of personalized cancer vaccine peptides from somatic mutations and tumor RNA sequencing data. The most distinctive feature relative to other similar tools (MuPeXi, pVacSeq) is phasing of adjacent somatic/germline variants using a mutant coding sequence assembled from RNA reads.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="1" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://github.com/openvax/topiary">Topiary</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Predict mutated peptide MHC ligands from somatic variants. Strictly a subset of the functionality of Vaxrank.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="2" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://github.com/openvax/mhcflurry">MHCflurry</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Allele-specific Class I MHC binding predictor.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="3" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a target="_blank" href="https://github.com/openvax/isovar">Isovar</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Determine mutant protein sequence by assembling RNA reads which overlap and support somatic variants. Useful for correctly incorporating other adjacent variants (phasing) as well as mutation associated splicing differences (intron retention).</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="4" class="s-repeatable-item"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a target="_blank" href="https://github.com/openvax/varcode">Varcode</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Tool for predicting mutant protein sequences from DNA variants with a friendly Python API.</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="5" class="s-repeatable-item s-last-row"><div class="clearfix"><div class=""><div class="sixteen columns s-left-in-row right"><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a target="_blank" href="https://github.com/openvax/varcode">P</a><a target="_blank" href="https://github.com/openvax/pyensembl">yEnsembl</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>Python library for accessing reference genome sequences and annotations from the Ensembl genome database.</p></div></div></div><div class=""></div></div></div></div></div></div></div></div>
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</div></li><li class="slide s-section-5" id="section-f_97a5a562-5ff0-41a9-92f5-aa2cdeadfd0c"><div class="waypoint"></div><a class="section-anchor" style="top: -56px;"></a><div>
<div class=" background-image s-new-media-section s-section s-columns-section background-image lazyloaded" data-react-style="{}"><div class="container"><div class="columns sixteen"><div class="s-title-group "><div class="s-title "><div class="s-component s-text s-animation-page-slide_in"><h2 class="s-component-content s-font-title"><p>Members</p></h2></div></div></div></div>
<div class="s-mh s-repeatable"><div><div data-sorting-index="0" class="third columns no-float s-repeatable-item s-last-row"><div class="clearfix"><div class=""><div class="s-item-media-wrapper s-mhi " style="min-height: 218px;"><div class="s-item-media-group"><div class="s-component s-media s-animation-page-slide_in"><div><div class="s-component-content"><div class="s-mh-nudge" style="padding-top: 9px;"><div class="s-ratio-box" style="max-width: 200px; max-height: 200px;"><div class="s-ratio-fill" style="padding-bottom: 100%;"></div><div><img alt="" title="" class="crop-default lazyloaded" data-description="" width="200" height="200" src="./index_files/jk_jhnvks.jpg" data-src="//user-images.strikinglycdn.com/res/hrscywv4p/image/upload/c_limit,fl_lossy,h_1440,w_720,f_auto,q_auto/1302745/jk_jhnvks.jpg"></div></div></div></div></div></div></div></div><div class=""><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://scholar.google.com/citations?user=MTOVa-AAAAAJ&hl=en">Julia Kodysh</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>B.Sc. in Computer Science from MIT<br>M.Eng. in Computer Science from MIT</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="1" class="third columns no-float s-repeatable-item s-last-row"><div class="clearfix"><div class=""><div class="s-item-media-wrapper s-mhi " style="min-height: 218px;"><div class="s-item-media-group"><div class="s-component s-media s-animation-page-slide_in"><div><div class="s-component-content"><div class="s-mh-nudge" style="padding-top: 9px;"><div class="s-ratio-box" style="max-width: 200px; max-height: 200px;"><div class="s-ratio-fill" style="padding-bottom: 100%;"></div><div><img alt="" title="" class="crop-default lazyloaded" data-description="" width="200" height="200" src="./index_files/to_us2qyp.png" data-src="//user-images.strikinglycdn.com/res/hrscywv4p/image/upload/c_limit,fl_lossy,h_1440,w_720,f_auto,q_auto/1302745/to_us2qyp.png"></div></div></div></div></div></div></div></div><div class=""><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://scholar.google.com/citations?user=mlCWcdwAAAAJ&hl=en">Tim O'Donnell</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>B.Sc. in Math & Computer Science from Brown</p><p>Enrolled in Ph.D. program at Mount Sinai</p></div></div></div><div class=""></div></div></div></div></div></div><div data-sorting-index="2" class="third columns no-float s-repeatable-item s-last-row"><div class="clearfix"><div class=""><div class="s-item-media-wrapper s-mhi " style="min-height: 218px;"><div class="s-item-media-group"><div class="s-component s-media s-animation-page-slide_in"><div><div class="s-component-content"><div><div class="s-ratio-box" style="max-width: 200px; max-height: 218px;"><div class="s-ratio-fill" style="padding-bottom: 109%;"></div><div><img alt="" title="" class="crop-default lazyloaded" data-description="" width="200" height="218" src="./index_files/580472_897684.png" data-src="//user-images.strikinglycdn.com/res/hrscywv4p/image/upload/c_limit,fl_lossy,h_1440,w_720,f_auto,q_auto/1302745/580472_897684.png"></div></div></div></div></div></div></div></div><div class=""><div class="s-item-text-group s-animation-page-slide_in"><div class="s-item-title"><div class="s-component s-text"><h3 class="s-component-content s-font-heading"><p><a href="https://scholar.google.com/citations?user=7Use2dsAAAAJ&hl=en">Alex Rubinsteyn</a></p></h3></div></div><div class="s-item-subtitle"><div class="s-component s-text"></div></div><div class="s-item-text"><div class="s-component s-text"><div class="s-component-content s-font-body"><p>B.Sc. in Neuroscience from UIUC<br>M.Sc. in Computer Science from NYU</p><p>Ph.D. in Computer Science from NYU</p></div></div></div><div class=""></div></div></div></div></div></div></div></div>
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</div></li><li class="slide s-section-6" id="section-f_d0e7fe6f-76c6-43b5-b39d-f91691f06111"><div class="waypoint"></div><a class="section-anchor" style="top: -56px;"></a><div class=" background-image s-blog-section s-section background-image lazyloaded" data-react-style="{}"><div class="waypoint"></div><div class="container last"><div class="columns no-float sixteen"><div class="s-title-group "><div class="s-title "><div class="s-component s-text s-animation-page-slide_in"><h2 class="s-component-content s-font-title"><p style="font-size: 160%;">Blog</p></h2></div></div><div class="s-subtitle"><div class="s-component s-text s-animation-page-slide_in"><h4 class="s-component-content s-font-heading"><p>Thoughts and research snippets</p></h4></div></div></div></div><div class=""><div><div class="s-component s-blog columns sixteen s-animation-page-slide_in"><div class="s-blog-wrapper"><div class="s-blog-col-placeholder clearfix"><div class="s-blog-col-body s-blog-no-posts"><div class="s-blog-posts "><div class="s-blog-entry s-layout-row s-avatar-circle"><div class="s-blog-entry-inner"><div class="s-blog-entry-left s-blog-avatar-container"><a target="_self" href="https://www.openvax.org/blog/computational-pipeline-for-neoantigen-vaccine-trials-at-mount-sinai"><div class="s-blog-avatar" style="background-image: url("//assets.strikingly.com/static/backgrounds/blur/6.jpg");"></div></a></div><div class="s-blog-entry-right"><div class="s-blog-details"><div class="s-blog-details-head"><div class="s-blog-title s-font-heading"><a target="_self" href="https://www.openvax.org/blog/computational-pipeline-for-neoantigen-vaccine-trials-at-mount-sinai">Computational Pipeline for Neoantigen Vaccine Trials at Mount Sinai</a></div><div class="s-blog-info s-font-body"><span class="s-blog-date">August 3, 2018</span></div></div><div class="s-blog-details-blurb s-font-body s-blog-row">Cancer immunotherapy aims to recruit the body's own immune system to attack a tumor, which...</div></div></div></div></div><div class="s-blog-entry s-layout-row s-avatar-circle"><div class="s-blog-entry-inner"><div class="s-blog-entry-left s-blog-avatar-container"><a target="_self" href="https://www.openvax.org/blog/gliph-tcr-clustering"><div class="s-blog-avatar" style="background-image: url("//assets.strikingly.com/static/backgrounds/blur/3.jpg");"></div></a></div><div class="s-blog-entry-right"><div class="s-blog-details"><div class="s-blog-details-head"><div class="s-blog-title s-font-heading"><a target="_self" href="https://www.openvax.org/blog/gliph-tcr-clustering">GLIPH & TCR clustering</a></div><div class="s-blog-info s-font-body"><span class="s-blog-date">June 27, 2018</span><span class="dot"> · </span><span class="s-blog-tags"><span class="s-blog-tag last">immunology</span></span></div></div><div class="s-blog-details-blurb s-font-body s-blog-row">Uri Laserson organized a delightful class at Mount Sinai called Applications of DNA Sequencing...</div></div></div></div></div></div></div></div></div></div></div></div></div><div class="container layers" style="left: 3px; 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You can learn more from Schumacher \u0026amp; Schreiber's review paper \u003ca href=\"http:\/\/science.sciencemag.org\/content\/348\/6230\/69.full\"\u003eNeoantigens in cancer immunotherapy\u003c\/a\u003e.\u003c\/p\u003e\u003cp\u003e\u00a0\u003c\/p\u003e\u003cp\u003eThe OpenVax group develops open source software and machine learning models for predicting different steps of the adaptive immune response to mutated tumor antigens.\u003c\/p\u003e","backupValue":null,"version":1},"button1":{"type":"Button","id":"f_d44cf2a0-88d4-4e53-8098-4cae2de7ca4e","defaultValue":true,"text":"","link_type":null,"page_id":null,"section_id":null,"url":"","new_target":null}}},{"type":"RepeatableItem","id":"f_a26418e9-1ef0-440d-b71a-b581637e1c06","defaultValue":true,"components":{"text1":{"type":"RichText","id":"f_472fda60-a870-4fa4-8d62-b1e8fcdc64ac","defaultValue":false,"value":"\u003cp style=\"text-align: center;\"\u003ePersonalized cancer vaccines\u003c\/p\u003e","backupValue":null,"version":1},"text2":{"type":"RichText","id":"f_29393e51-95a1-4507-8409-e4e7042092ed","defaultValue":false,"value":"\u003cp\u003ePersonalized therapeutic cancer vaccines are a form of cancer immunotherapy which instruct a patient\u2019s immune system to target his or her particular tumor. Early phase I trials have shown some success (\u003ca href=\"https:\/\/doi.org\/10.1038\/nature23003\"\u003eSahin et al. 2017\u003c\/a\u003e, \u003ca href=\"https:\/\/doi.org\/10.1038\/nature22991\"\u003eOtt et al. 2017\u003c\/a\u003e) and many new pharmaceutical companies are forming around these vaccines.\u003c\/p\u003e\u003cp\u003e\u00a0\u003c\/p\u003e\u003cp\u003eThe OpenVax group is helping initiate and run several clinical trials of personalized cancer vaccines at the Mount Sinai Hospital, in collaboration with \u003ca href=\"http:\/\/labs.icahn.mssm.edu\/bhardwajlab\/\"\u003eDr. Nina Bhardwaj\u003c\/a\u003e, \u003ca href=\"https:\/\/www.mountsinai.org\/profiles\/adilia-hormigo\"\u003eDr. Adilia Hormigo\u003c\/a\u003e, \u003ca href=\"https:\/\/www.mountsinai.org\/profiles\/matthew-galsky\"\u003eDr. Matthew Galsky\u003c\/a\u003e, and Mount Sinai's \u003ca href=\"http:\/\/labs.icahn.mssm.edu\/sabadolab\/\"\u003eVaccine and Cell Therapy Lab\u003c\/a\u003e.\u00a0\u00a0\u00a0\u003c\/p\u003e","backupValue":null,"version":1},"button1":{"type":"Button","id":"f_442592e4-6f6c-41fa-a6ed-72b3fe662eb2","defaultValue":true,"text":"","link_type":null,"page_id":null,"section_id":null,"url":"","new_target":null}}}],"components":{"text1":{"type":"RichText","id":"f_cde37959-d176-401e-822c-ece6e8d92a27","defaultValue":true,"value":"Title Text","backupValue":null,"version":null},"text2":{"type":"RichText","id":"f_037b54cd-1386-435d-821e-061003c11b16","defaultValue":true,"value":"Use a text section to describe your values, or show more info, or summarize a topic, or tell a story. 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Broad set of malignancies:\u003cstrong\u003e \u003c\/strong\u003eH\u0026amp;N, NSCLC, breast, ovarian, bladder, SCC, multiple myeloma. 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href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT03223103\"\u003eSafety and Immunogenicity of Personalized Genomic Vaccine and Tumor Treating Fields (TTFields) to Treat Glioblastoma \u003c\/a\u003e\u003c\/p\u003e","backupValue":null,"version":1},"text2":{"type":"RichText","id":"f_b86dba6d-5d73-4faf-90ae-54b5939a9c50","defaultValue":false,"value":"\u003cp\u003ePrincipal Investigator: \u003ca href=\"http:\/\/www.mountsinai.org\/profiles\/adilia-hormigo\"\u003eAdilia Hormigo\u003c\/a\u003e\u003c\/p\u003e","backupValue":null,"version":1},"text3":{"type":"RichText","id":"f_a536e785-036a-4af6-bc43-b2d6e35ad091","defaultValue":false,"value":"\u003cp\u003eThe PGV-001 neoantigen peptide vaccine in combination with standard-of-care temozolomide and Novocure's \"\u003ca href=\"https:\/\/www.novocure.com\/our-therapy\/\"\u003etumor treating fields\u003c\/a\u003e\" for 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href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT03359239\"\u003eAtezolizumab Given in Combination With a Personalized Vaccine in Patients With Urothelial Cancer\u003c\/a\u003e\u003ca href=\"https:\/\/clinicaltrials.gov\/ct2\/show\/NCT03359239\"\u003e (NCT03359239)\u003c\/a\u003e\u003c\/p\u003e","backupValue":null,"version":1},"text2":{"type":"RichText","id":"f_5666925c-08ce-4c89-af79-31064da166a8","defaultValue":false,"value":"\u003cp\u003ePrincipal Investigator:\u003ca href=\"http:\/\/www.mountsinai.org\/profiles\/matthew-galsky\"\u003e Matt Galsky\u003c\/a\u003e\u003c\/p\u003e","backupValue":null,"version":1},"text3":{"type":"RichText","id":"f_b0729af5-1005-461d-a599-fb7e8076dbc7","defaultValue":false,"value":"\u003cp\u003eThe PGV-001 neoantigen peptide vaccine in combination with an anti-PD-L1 checkpoint agent (atezolizumab) for bladder 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