AI Platform Achieves Novel Drug Discovery in Under 18 Months
Insilico Medicine successfully uses artificial intelligence to discover a new drug target and molecule for idiopathic pulmonary fibrosis, cutting costs and time significantly compared to traditional methods.
Insilico Medicine achieves a major biopharma milestone by using artificial intelligence to discover a novel drug target and molecule in under 18 months. This world-first accomplishment costs just over $2 million, which represents only ten percent of the expense of a conventional drug discovery program. The company now makes this validated technology available to large pharmaceutical partners to help modernize research and development.
The company relies on two interconnected AI platforms called PandaOmics and Chemistry42 to navigate the complex biology of drug discovery. For their validation project targeting idiopathic pulmonary fibrosis, Insilico trains deep neural networks on omics and clinical data to predict tissue-specific fibrosis. The PandaOmics system then identifies viable targets through deep feature selection, causality inference, and pathway reconstruction.
Applying deep learning to biology presents a significantly greater challenge than analyzing images or text, but Insilico overcomes this hurdle through years of dedicated research. The company documents its progress in over 120 peer-reviewed papers before successfully linking its target discovery platform with its generative chemistry tools. This integrated approach proves that AI drastically accelerates the delivery of preclinical drug candidates while reducing financial risks.