Potential IPF Treatment, Found Using AI, May Move Into Trial, Insilico Says


Insilico Medicine announced that it has found a new therapeutic target and potential therapy candidate for idiopathic pulmonary fibrosis (IPF) using artificial intelligence (AI), a company specialty.

The potential therapy, a small molecule inhibitor, has been validated in preclinical tests in human tissue and animal models of IPF. Work here showed both efficacy and safety, potentially supporting a request to test the molecule in a clinical trial, Insilico said in a press release.

“To my knowledge this is the first case where AI identified a novel target and designed a preclinical candidate for a very broad disease indication. It is a major milestone for us as … and we need to have many enabling AI technologies that help us understand and manipulate human biology in other chronic diseases,” said Alex Zhavoronkov, PhD, founder and CEO of Insilico Medicine.

The IPF candidate treatment, which was not further identified in the release, demonstrated “great in vitro and in vivo efficacy in preclinical studies for idiopathic pulmonary fibrosis, and [a] good safety profile in the 14-day repeated mouse dose range finding study,” the company reported.

It is planning to launch a Phase 1 clinical trial in the candidate therapy in December, Insilico reported on a webpage.

A team of 20 scientists with expertise in therapy development, based in Shanghai, will be in charge both of bringing treatment candidates into clinical testing and with creating a portfolio of other potential treatment. The team will be led by Insilico’s chief science officer Feng Ren, a PhD who joined the Hong Kong-based company in February.

Insilico platform for target discovery and therapy design is known as Pharma.AI , which it claims allows researchers “to discover signatures of diseases and identify the most promising targets” with speed and cost-effectiveness.

“By creating the first universal system linking all of the areas of drug development from target identification, small molecule design, and soon clinical trial outcomes prediction, Insilico’s AI platform will be capable of supporting every step of pharmaceutical [research and development],” Zhavoronkov said.

“Speed is everything in drug development. At least 90 percent of the costs associated with getting a drug approved for human use is in the late stage clinical trials,” said Charles Cantor, PhD, a professor emeritus at Boston University and member of Insilico’s science advisory board.

Aisha Abdullah received a B.S. in biology from the University of Houston and a Ph.D. in neuroscience from Weill Cornell Medical College, where she studied the role of microRNA in embryonic and early postnatal brain development. Since finishing graduate school, she has worked as a science communicator making science accessible to broad audiences.

Joana holds a BSc in Biology, a MSc in Evolutionary and Developmental Biology and a PhD in Biomedical Sciences from Universidade de Lisboa, Portugal. Her work has been focused on the impact of non-canonical Wnt signaling in the collective behavior of endothelial cells — cells that made up the lining of blood vessels — found in the umbilical cord of newborns.

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