# Statistical optimization of self-assembled biosynthetic cornea implants

> **NIH NIH R01** · JOHNS HOPKINS UNIVERSITY · 2020 · $392,537

## Abstract

The overall vision of the proposed research is to create an effective, scalable, and affordable
biomimetic corneal substitute suitable for clinical translation. Damage to the cornea, the outermost
tissue of the eye, causes loss of vision, which profoundly impacts quality of life. Cornea transplantation
is the gold standard for treatment, but slowly progressing rejection, short supply of donor tissue, and
the small number of failures that lead to devastating consequences, remain key challenges. Artificial
corneal substitutes have thus far failed to recapitulate the native tissue structure and function. An
effective biosynthetic replacement that mimics the native cornea would offer a transformational new
option for corneal injury patients. Our prior work has opened a novel route to fully functional synthetic
corneas. We previously developed a collagen vitrification process that increases the mechanical
strength of collagen gels. To achieve the necessary transparency in full thickness implants, we needed
to further control collagen spacing and lamellae orthogonality. We recapitulated cornea development
and organization in vitro using synthetic cyclic proteoglycan molecules, cyclodextrins (CD). Preliminary
data with CD and collagen vitrification produced materials with aligned fibrillar architecture and
orthogonally organized lamellae similar to the native cornea. Furthermore, cells were able to grow on
the materials and implants were suturable and biocompatible in a rabbit corneal defect. Our objective is
to replicate the native cornea ultrastructure, including structure (collagen fibril size, alignment and
lamella) and function (transparency and mechanical strength). We hypothesize that the CD molecules
interact specifically with collagen to control fiber spacing and assembly during vitrification, enabling a
fully functional corneal replacement material. To achieve these goals, we propose the following specific
aims:
Specific Aim 1: Develop a library of CD-Collagen biomaterials using statistical optimization. A CD-Col
material library will be synthesized with varying forms of α, β, and γ CDs using multiphase statistical
optimization Design of Experiments (DOE) will be used to define and optimize corneal biomimetic
structure.
Specific Aim 2: Characterize physical properties of CD-Collagen biomaterials. Formulations from Aim
1 that achieve minimum clarity and mechanics for corneal implantation will be characterized and
compared to the native cornea and standard collagen implants.
Specific Aim 3: Translate the biomimetic CD-Collagen material to a corneal defect model.

## Key facts

- **NIH application ID:** 9913555
- **Project number:** 5R01EY029055-03
- **Recipient organization:** JOHNS HOPKINS UNIVERSITY
- **Principal Investigator:** JENNIFER H ELISSEEFF
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $392,537
- **Award type:** 5
- **Project period:** 2018-05-01 → 2022-04-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9913555

## Citation

> US National Institutes of Health, RePORTER application 9913555, Statistical optimization of self-assembled biosynthetic cornea implants (5R01EY029055-03). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/9913555. Licensed CC0.

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