“When you talk about precision medicine every disease can become somewhat of a rare disease because you’re going to increasingly segment down the different subtypes of that disease.”
That’s host Simon Smith’s takeaway from the inaugural episode of BenchSci’s Artificial Intelligence in Drug Discovery podcast, a show offering knowledge and inspiration from leaders in the healthcare, tech, and pharma industries.
This episode featured FDNA’s CEO, Dekel Gelbman, who discussed the application of current technologies (like FDNA’s Face2Gene) to identify disease-causing genetic variants and disease mechanisms when genomic data alone can fall short of a definitive diagnosis. The abundance of available data can provide better insights and transform care, but no human alone could ever effectively analyze and decipher that level of information. “Genetics really needs this type of technology as a complementary technology in genetic analysis and variant analysis,” Dekel explained.
“Using deep learning and facial analysis, clinicians have improved workflows that allow them to better treat disease,” he went on to say, “and can provide insights to possible diseases that they may have traditionally never considered.”
Through a better understanding of AI and how it can be used in a targeted way, companies can more easily collect and interpret data, ultimately leading to earlier diagnosis of disease and discovery of new ones. With this information, pharmaceutical companies have the ability to research and develop more precise treatments for these diseases and improve the quality of life for patients all over the world. From machine learning to biomedical research, digital health and pharma companies are using AI to speed discovery and cut costs, transforming drug development with data and algorithms.
“Once you understand the biological mechanisms, once you understand what is causing a particular phenotype, we’re in a much better position to try and match those diseases with specific biological approaches.”