The discovery and development of orphan drugs and gene therapies for rare diseases face many challenges, including: insufficient knowledge regarding the underlying disease mechanisms, the lack of clinically relevant humanized animal disease models, insufficient AAV vector productivity and targeted delivery in gene therapy development, and more. In light of the challenges faced with orphan drug development, bioinformatics and artificial intelligence (AI) tools have become essential for researchers, biotechs, and pharmaceutical companies developing rare disease therapies to accelerate drug discovery and vastly reduce time to clinical trials.
The Rare Disease Data Center (RDDC) provides interfaces for the interactive visualization and exploration of biomedical data alongside several gene diagnosis tools based on the sophisticated AI and machine learning models. The RDDC is consistently developing new tools to meet the rapidly evolving demands of rare disease scientific research. For example, the RDDC RNA Splicing Tool is based on deep neural network (DNN) strategy and bioinformatics that predict splicing by analyzing the splicing abnormalities that have a greater effect on protein coding translation, and eventually finds out the causes of genetic diseases at the base mutation level. By combining conventional bioinformatics analysis and AI models, we can screen the loci of interest before heading onto validation experiments.
For AAV-mediated gene therapy approaches, Cyagen has produced substantial experimental data for AI model training and developed proprietary machine learning algorithms to accelerate the AAV capsid identification and optimization processes compared to traditional directed evolution methods. Utilizing AI and single-cell RNA-sequencing technologies, Cyagen’s high-throughput AAV vector discovery platform helps overcome the present limitations of gene therapy R&D by quickly identifying next-generation AAV capsids that have enhanced tissue targeting capability, tissue specificity, and productivity.
Even with the available data resources and AI tools, researchers often face difficulties in acquiring clinically relevant models of a rare disease. The Humanized Model Project has developed genetic humanization models of rare disease for preclinical research, with a focus on ophthalmology and neurology applications. These clinically relevant humanized models are readily available to researchers worldwide via Cyagen’s repository, which can also perform downstream services as a part of their comprehensive gene therapy research solution platform.
Join our expert, Dr. Kugeng (KG) Huo, for a discussion on how you can use the Rare Disease Data Center (RDDC) resources and Cyagen’s one-stop CRO platform to accelerate your research and development of effective gene therapies for rare diseases.
