# Validation of an in vitro model of progressive fibrosis that mimics Idiopathic Pulmonary Fibrosis > **NIH NIH U01** · UNIVERSITY OF CALIFORNIA LOS ANGELES · 2022 · $630,424 ## Abstract Abstract We have developed a 3D bioengineered human induced pluripotent stem cell (iPSC) derived model of IPF that displays progressive fibrosis and closely phenocopies several characteristics associated with IPF. This model is an extension of our 2D model of progressive fibrosis (Vijayaraj et al., Cell Reports – in press). To make our progressive fibrosis model specific to IPF, we have developed it into a model system that utilizes the lung 3D architecture and specific cell types. Our 3D model displays additional features of IPF such as airway epithelial cell (AEC) apoptosis, epithelial-mesenchymal transition (EMT) and replacement of alveolar architecture. Our proposal aims to improve and validate this 3D model such that it will be amenable to a high throughput drug discovery platform in a patient specific manner for precision medicine. Our project aims to use our unique stem/progenitor cell models of IPF to increase our understanding of the disease and for drug discovery. Specific Aim 1. To improve and validate the 3D bioengineered human iPSC derived model of IPF A. To validate the 3D model of IPF by performing extensive characterization of the model compared to human IPF lung tissue. B. To characterize the heterogeneity of IPF seen across different patients. C. To characterize the 3D IPF model by known genetic risk factors. Specific Aim 2 – To use our 3D bioengineered iPSC-derived model to study cellular plasticity in IPF To profile cellular plasticity of AECs in our 3D model of IPF and compare it to human IPF tissue using single cell RNA sequencing. Specific Aim 3 – To develop and standardize a high throughput drug screening (HTS) platform to identify new anti-fibrotic therapies using the 3D model of IPF A. To develop a HTS using the 3D model of IPF. B. To develop robust, image analysis pipelines that employ a combination of advanced deep learning techniques and traditional image processing methods to generate quantitative measures of tissue health. C. To develop and run a pilot HTS to identify small molecules that will perform one or more of the following a) prevent apoptosis of AEC; b) enhance apoptosis of mesenchymal cells; c) decrease expression of -SMA. Our team includes international experts who study lung biology (Gomperts, UCLA), biology of fibrosis (Vijayaraj, UCLA), an IPF clinician and researcher (Belperio, UCLA), lung pathologist (Wallace, USC), iPSC airway epithelial cell differentiation (Spence, Michigan), single cell RNA seq and analysis (Plath, UCLA), and high throughput drug discovery (Damoiseaux, UCLA) with machine learning algorithms for analysis (Shattuck, UCLA). We are a highly collaborative team that is working together using innovative, patient relevant research approaches to tackle the challenges of modeling IPF to identify new therapies. ## Key facts - **NIH application ID:** 10350549 - **Project number:** 5U01HL153000-02 - **Recipient organization:** UNIVERSITY OF CALIFORNIA LOS ANGELES - **Principal Investigator:** JOHN A BELPERIO - **Activity code:** U01 (R01, R21, SBIR, etc.) - **Funding institute:** NIH - **Fiscal year:** 2022 - **Award amount:** $630,424 - **Award type:** 5 - **Project period:** 2021-02-15 → 2025-01-31 ## Primary source NIH RePORTER: https://reporter.nih.gov/project-details/10350549 ## Citation > US National Institutes of Health, RePORTER application 10350549, Validation of an in vitro model of progressive fibrosis that mimics Idiopathic Pulmonary Fibrosis (5U01HL153000-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10350549. Licensed CC0. --- *[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*