SBIR/STTR Research Award

A D osteoarthritis model targeting patient populations with high risk genetic polymorphisms

Award identifier 312e51073ef9f528743b5175360d703a8846da81edeb5501902098d9ac6bc18dAwarding agency Department of Health and Human Services · National Institutes of Health

Award amount

$225,000

Program and phase

SBIR · Phase I

Award year

2017

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Award details

Awarding agency
Department of Health and Human Services
Branch
National Institutes of Health
Recipient company
Cytex Therapeutics, Inc.
Proposal award date
2017-09-01
Contract end date
2019-08-31
UEI
G9RMDCWJYGL3
Solicitation number
AR17-005
Topic code
NIAMS

Research abstract

Abstract Osteoarthritis OA is a degenerative joint disease that affects an estimated million adults in the United States and results in an economic burden of over $ billion per year Although the burden of OA is immense current non surgical treatments are only palliative and no disease modifying OA drugs DMOADs presently exist to address the problem This lack of success in identifying DMOADs is frequently attributed to the variable causes of OA initiation and the dearth of human cartilage available for screening potential DMOADs To increase the likelihood of identifying DMOADs we propose to study a segmented OA population based on defined genetic predisposition to OA development To produce a nearly unlimited source of human cartilage for use in DMOAD screening we will use induced pluripotent stem cells iPSCs as a cell source for cartilage tissue engineering The goal of this project is to create a platform screening technology to identify the therapeutic requirements of OA associated genetic risk factors Our approach is to create a three dimensional in vitro model of OA which utilizes iPSC lines that have been modified to contain defined genetic variations In Aim we will employ genome editing technology to generate OA associated single nucleotide polymorphisms SNPs in the genome of hiPSCs Engineered cartilage formed from these edited cells will be characterized using biochemical and micromechanical assays and then treated with inflammatory cytokines to induce OA like changes in the cartilage The resulting in vitro OA model will be validated by measuring matrix degradation loss of mechanical properties and production of inflammatory mediators In Aim our iPSC based model of OA will be transferred to a well plate format to facilitate the development of an OA drug screening platform A set of model therapeutics known to inhibit inflammatory degradation will be used to validate the sensitivity of the model and to define high throughput readouts of OA progression Finally two libraries of novel bioactive compounds will be screened for their ability to slow OA associated degradation in our in vitro model This proposal will help elucidate the mechanism by which genetic variants result in increased risk for OA and will catalyze the development of tailored OA therapeutics by providing a platform technology for identifying therapeutic effectiveness based on defined risk factors Narrative Osteoarthritis OA is a common cause of pain and disability but unfortunately there are no drugs available to slow or stop progression of the disease This project will develop a bench top model of arthritis for rapid drug testing based on a patient s genetic risk factors The long term goal is to identify effective drugs that can be targeted to specific populations of OA patients

Technology keywords

Not reported

Other awards by this recipient

Verified by the same UEI. These are other public SBIR/STTR award pages, not a merged company record.

Awards with the same topic code

Verified by an exact topic code match. This is not a text-similarity match.

Research funding history

22 SBIR/STTR records share this UEI (2007–2023). Reported award amounts total $18,271,228. Reported amounts are not federal obligations.

Phases: Phase I, Phase II, Phase II – Direct to Phase II

Agencies: Department of Health and Human Services, National Science Foundation

Agency intelligence

Department of Health and Human Services

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