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AI Helps Identify New Therapeutic Directions for ALS

Image Credits: HKSTP, Press Release

A partner company of Hong Kong Science and Technology Parks Corporation (HKSTP) that specialises in end-to-end artificial intelligence (AI)-driven drug discovery, announced that the company’s Hong Kong team has identified multiple potential therapeutic targets for the fatal and incurable amyotrophic lateral sclerosis (ALS), using its proprietary biology AI platform, PandaOmics™. The research was in collaboration with Answer ALS, the largest and most comprehensive ALS research project ever. The findings were published in the June 28 issue of Frontiers in Aging Neuroscience.

The team of researchers leveraged massive datasets to find genes relevant to disease, which could serve as potential targets for new therapeutics. The target discovery engine helped analyse the expression profiles of central nervous system (CNS) samples from public datasets, and direct iPSC-derived motor neurons (diMN) from Answer ALS.

AI can greatly accelerate the early stage of drug discovery; the time from target discovery to clinical stage can be shortened from 5-6 years to 30 months. Image Credits: HKSTP, Press Release

The study resulted in the identification of 17 high-confidence and 11 novel therapeutic targets from CNS and diMN samples. These targets were further validated in the c9ALS Drosophila model, mimicking the most common genetic cause of ALS, of which 18 targets (64%) have been validated to have functional correlations to ALS. Notably, eight unreported genes, including KCNB2, KCNS3, ADRA2B, NR3C1, P2RY14, PPP3CB, PTPRC, and RARA, strongly rescued neurodegeneration through their suppression. All the potential therapeutic targets were disclosed in the paper and at ALS.AI.

The Director, Robert Packard Center for ALS Research and Answer ALS stated that he is excited to see the Answer ALS data being used to identify possible ALS disease-causing pathways and candidate drugs. The work done by the HKSTP partner company is how this unprecedented program was envisioned to help change the course of ALS.

A Professor at Tsinghua University and Founder of 4B Technologies stated that from AI-powered target discovery based on massive datasets to biological validation by multiple model systems (fly, mouse, human iPS cells), to rapid clinical testing through investigator-initiated trials (IIT), this represents a new trend that may dramatically reduce the costs and duration and more importantly the success rate of developing medicines, especially for neurodegenerative diseases.

The Co-CEO and CSO of an end-to-end AI-driven drug discovery firm stated that this demonstrates the power of their biology AI platform, PandaOmics, in target discovery. It is impressive that around 70% of targets identified by AI were validated in a preclinical animal model.

The team is now working with collaborators to progress some targets toward clinical trials for ALS, while also further expanding the utilisation of the drug discovery engine to identify new targets for other disease areas including oncology, immunology, and fibrosis.

The Head of the Institute for Translational Research at HKSTP noted, “We are thrilled to witness Insilico Medicine Hong Kong team’s breakthrough in the application of AI-powered drug discovery and development in ALS.”

The global study led by multidisciplinary experts in ALS and AI has revealed new aspects of our understanding of the disease and opens a new window of opportunities for developing potentially new treatment options, demonstrating the importance of a collaborative approach and the potential of AI with deep insights in addressing clinical unmet needs, she said.

She added that HKSTP will continue to build a thriving I&T ecosystem for accelerating and commercialising innovative solutions and nurturing local and global I&T talent.

The HKSTP partner firm has been conducting research on ALS target discovery and drug repurposing with other interested parties using PandaOmics™ since 2016. This study further validates the drug discovery engine as an AI tool capable of identifying therapeutic targets with potential roles in ALS neurodegeneration and creating new avenues for drug discovery and a better understanding of this rare and fatal neuromuscular disease.

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