CRISPR Meets Zebrafish: Accelerating the Discovery of New Therapeutic Targets

We propose that zebrafish, with the use of CRISPR/Cas9 tools, could streamline functional genomic processes to bring biologically relevant knowledge on diseases.

Davide Rubbini 1Carles Cornet 1Javier Terriente 1Vincenzo Di Donato 1

ABSTRACT

Bringing a new drug to the market costs an average of US$2.6 billion and takes more than 10 years from discovery to regulatory approval. Despite the need to reduce cost and time to increase productivity, pharma companies tend to crowd their efforts in the same indications and drug targets. This results in the commercialization of drugs that share the same mechanism of action (MoA) and, in many cases, equivalent efficacies among them—an outcome that helps neither patients nor the balance sheet of the companies trying to bring therapeutics to the same patient population. Indeed, the discovery of new therapeutic targets, based on a deeper understanding of the disease biology, would likely provide more innovative MoAs and potentially greater drug efficacies. It would also bring better chances for identifying appropriate treatments according to the patient’s genetic stratification. Nowadays, we count with an enormous amount of unprocessed information on potential disease targets that could be extracted from omics data obtained from patient samples. In addition, hundreds of pharmacological and genetic screenings have been performed to identify innovative drug targets. Traditionally, rodents have been the animal models of choice to perform functional genomic studies. The high experimental cost, combined with the low throughput provided by those models, however, is a bottleneck for discovering and validating novel genetic disease associations. To overcome these limitations, we propose that zebrafish, in conjunction with the use of CRISPR/Cas9 genome-editing tools, could streamline functional genomic processes to bring biologically relevant knowledge on innovative disease targets in a shorter time frame.


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