Enhancing the Precision of CRISPR-Based Gene Editing
A new interdisciplinary project at Lehigh University aims to leverage AI and advanced modeling to refine CRISPR gene editing, enhancing safety and expanding its medical applications
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Researchers at Lehigh University are embarking on an innovative project to enhance the safety and efficacy of CRISPR gene editing technologies. Funded by the National Science Foundation, this initiative, led by bioengineering professor Tomas Gonzalez-Fernandez, focuses on developing predictive models using artificial intelligence and deep learning.
CRISPR, a revolutionary tool for genome editing, enables precise modifications to DNA. However, as Gonzalez-Fernandez noted in a recent press release, “CRISPR is very powerful, but it comes with side effects.” Altering one gene can inadvertently affect multiple others, leading to unintended outcomes. To address this, Gonzalez-Fernandez has assembled an interdisciplinary team, including faculty from bioengineering and computer science, alongside PhD student Joshua Graham, who is integrating machine learning techniques into the project.
“This is the first time it’s being used to create a surrogate genome model,” said Gonzalez-Fernandez. This model will allow researchers to simulate the effects of gene modifications on the entire genome, facilitating the identification of suitable genetic targets while avoiding adverse consequences. “If we have a specific therapeutic application, but we don’t know what gene to modify, the model will help us identify different candidates,” he explained.
Their work has significant implications for various medical fields, including cancer treatment and regenerative medicine. For instance, they aim to enhance the differentiation of induced pluripotent stem cells into cancer-fighting cells and improve the development of cartilage cells for treating osteoarthritis.
Additionally, the project addresses the delivery mechanism for CRISPR components through nanoparticle vehicles, which can negatively impact cell viability. The team will utilize computer modeling to predict and mitigate these effects.
Gonzalez-Fernandez emphasized the collaborative nature of the research, which merges computer science, genetic engineering, and molecular biology to tackle the complex challenges posed by CRISPR technology. With this work, the team aspires to unlock new therapeutic applications, making CRISPR a safer and more reliable tool for treating a variety of diseases.
Note: This news summary was generated by AI based on a published press release, followed by a review from human editors.