MatTek is presenting at the 2017 AAPS Annual Meeting and Exposition

Posted on November 10, 2017 |
Categories Posters, Meetings


Dr. Seyoum Ayehunie will be the presenting author for three abstracts submitted to the 2017 American Association of Pharmaceutical Scientists Annual Meeting and Exposition in San Diego, CA. The meeting will take place at the San Diego Convention Center November 12-15, 2017. 

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Poster Forum 7 – Monday 11/13 2:00 PM – 3:00 PM

M6101 – Reproducibility of Three Dimensional Small Intestinal Tissue Model for Drug Permeability and Drug-Drug Interaction Studies

Authors: Seyoum Ayehunie1, Zachary Stevens1, Timothy Landry1, Ezhilarasi Perumal2, Giovanni Pauletti2, Alex Armento1, Mitchell Klausner1, and Patrick Hayden1. 1MatTek Corporation, Ashland, MA and 2University of Cincinnati, Academic Health Center, Cincinnati, OH.

Abstract: The purpose of this study is to evaluate the lot-to-lot reproducibility of a biologically relevant organotypic small intestinal (SMI) tissue model to predict intestinal drug permeation/bioavailability of orally administered drugs. A 96-well format primary human cell-based full-thickness small intestinal (SMI) 3D tissue model that recapitulate in vivo counterpart phenotypically, structurally and functionally will be a relevant testing model for high throughput therapeutic drug screening and drug-drug interaction studies. Currently used cell-line based assays are not physiological and do not mimic the in vivo microenvironment.

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M6102 – Detecting GI Toxicity Earlier Than in Dog: Developing the First In Vitro Assay to Predict Clinical Diarrhea

Authors: Seyoum Ayehunie1, Matt Peters2, Maria Hubinska1&3, Alex Armento1, James Lu2, Timothy Landry1, Pradeep Sharma2, Clay Scott2, Patrick Hayden1, Mitchell Klausner1. 1MatTek Corporation, Ashland MA, 2AstraZeneca, Waltham, MA, and 3MatTek In Vitro Laboratories, Bratislava, Slovakia.

Abstract: GI toxicity is a common adverse effect (AE) across therapy areas. For oncotherapeutics it can prevent efficacy as monotherapy and limits combination partners. There are no in vitro models that provide sufficiently predictive data to guide drug design or to drive in silico modeling of clinical dose scheduling. Preclinical testing in dog (but not rat) is highly predictive but throughput limits application during drug design. After exploring organoids, we focused on a 3D microtissue that replicates the structure of GI epithelium with villi comprised of mature enterocytes which are continually renewed from adult stem cells located in crypts. This jejunum microtissue demonstrated robust barrier function as measured by transepithelial electrical resistance. Since compromised barrier function is associated with diarrhea, we assessed predictivity using drugs with low (<3%) or high (>40%) incidence of clinical diarrhea. Testing under blinded conditions revealed excellent performance: 80% positive predictivity and 83% negative predictivity. Simcyp modeling is being used to match in vitro concentrations with clinical exposure at the enterocytes after oral dosing. The flexibility to re-read daily for >42 days is consistent with supporting dose schedule modeling for oncology drug combinations. By coupling clinical PK with human 3D GI microtissue, this predictive model should provide an engine for designing drugs and treatment plans with better therapeutic windows. Here, we develop a 3D human Intestinal tissue for GI toxicity that predicts clinical diarrhea with 82% accuracy.

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Poster Forum 5 – Tuesday 11/14 12:00 PM – 1:00 PM

T4033 – Hyperposmolal Vaginal Lubricant Formulations Markedly Increase Epithelial Damage in 3D Vaginal Epithelial Tissue Model

Authors: Seyoum Ayehunie1, Ying-Ying Wang2, Stephanie Bogojevic1, Tim Landry1, Richard A. Cone2. 1MatTek Corporation, Ashland, MA and 2Johns Hopkins University, Baltimore, MD.

Abstract:  The overall aim of this investigation was to use one of the best characterized in vitro vaginal tissue models to detect disruption of epithelial barrier functions caused by widely available lubricants following a single topical exposure as a function of their osmolality.

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