News Release

Combining AI and live cell assays to develop drugs for "undruggable" cancer targets

Business Announcement

InSilico Medicine

Igor Stagljar, PhD, University of Toronto biochemist and molecular geneticist


The Stagljar Lab is a global leader in proteomics and chemical genomics, specializing in unraveling protein-protein interactions of human membrane proteins. Pivotal in cancer and rare genetic diseases, their research aims to map the integral membrane protein interactions and their projects use artificial intelligence for drug screening.

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Credit: Stagljar Lab

University of Toronto biochemist and molecular geneticist professor Igor Stagljar, PhD, has partnered with clinical stage artificial intelligence (AI)-driven drug discovery company Insilico Medicine to test the effectiveness of Insilico’s AI-designed molecules against what are known as “undruggable” targets – or disease targets that have been out of reach of conventional therapeutics. 

Using live cell-based assays developed in professor Stagljar’s lab, researchers will test 15-20 undruggable targets as a part of the collaboration. As many as 85% of all human proteins are thought to be “undruggable,” with smooth surfaces that lack easy pockets for small molecule drugs to bind, making rational drug design a huge challenge. 

The Stagljar lab specializes in cancer, a disease with many “undruggable” targets. Among the most well-known is KRAS, the most frequently mutated cancer-causing gene (or oncogene), across all cancer types, including high fatality cancers such as lung, colorectal and pancreatic. In particular, his lab focuses on protein-protein interactions (PPIs), identifying aberrant interactions among proteins that result in various diseases. 

Using Insilico’s end-to-end Pharma.AI platform, researchers will design novel small molecule drugs with desired properties such as metabolic stability, potency, novelty and diversity that can target these problem areas in order to stop disease progression. They can then quickly test the validity of these molecules in inhibiting or stimulating a target using professor Stagljar’s assays. 

“We are excited to move this collaboration forward and explore how we can further advance the testing and development of our AI-designed drugs using these novel assays, particularly for undruggable cancer targets,” says Petrina Kamya, PhD, Head of AI Platforms and President of Insilico Medicine Canada. 

The two assays to be used are called MaMTH-DS, a live-cell drug screening platform designed for the identification and monitoring of PPIs in cellular membranes; and SIMPL, a new technology that uses a split intein (a type of protein with unique properties that occurs naturally in many cells) as a sensor for PPI detection and can be applied to virtually any human protein in any cell line. Both were recently published in journals belonging to the Nature publishing group.

Stagljar says it was only over the last few years that live cell assays have become a viable alternative to in vitro, or test tube, testing – thanks to both technological improvements and greater insights about these hard-to-drug targets. And live cell assays have a distinct advantage over test tubes, providing data about how well a small molecule binds in a biological setting, as well as its cellular permeability and toxicity to the cell. 

“Using these novel assays, we can monitor how drugs inhibit key proteins associated with many human diseases,” he says. “Within a short time frame we can now easily determine  whether a small molecule developed by AI inhibits a particular protein target.” He adds that the assays are cheap to produce and capable of screening up to 10,000 molecules per week. 

Once the molecules are tested, they can be further improved using AI, retested, and ultimately readied for preclinical studies. Using these live assays, the process of drug validation for a molecule has the potential to be reduced from 4-5 years to a matter of months, Stagljar says.


About Insilico Medicine

Insilico Medicine, a global clinical stage biotechnology company powered by generative AI, is connecting biology, chemistry, and clinical trials analysis using next-generation AI systems. The company has developed AI platforms that utilize deep generative models, reinforcement learning, transformers, and other modern machine learning techniques for novel target discovery and the generation of novel molecular structures with desired properties. Insilico Medicine is developing breakthrough solutions to discover and develop innovative drugs for cancer, fibrosis, immunity, central nervous system diseases, infectious diseases, autoimmune diseases, and aging-related diseases. 


About the Stagljar Lab

The Stagljar Lab, based at the University of Toronto's Donnelly Centre, is a global leader in proteomics and chemical genomics, specializing in unraveling protein-protein interactions of human membrane proteins. Pivotal in cancer and rare genetic diseases, their research aims to map the integral membrane protein interactions, shaping healthy and diseased cells. Focused on lung, colon, breast, and pancreatic cancer, their projects use artificial intelligence for drug screening.  In close collaboration with medicinal chemists and clinical investigators, the Stagljar Lab delves into the molecular mechanisms behind challenging and sometimes unexplained observations related to drugs and pathological events. 

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