Researchers from Klick Applied Sciences have developed an artificial intelligence framework capable of swiftly identifying novel applications for existing therapeutics, as revealed in the recent NeurIPS conference.
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The breakthrough, presented on Friday, holds significant promise for enhancing the drug repurposing process and revolutionizing the pharmaceutical sector.
The unveiled algorithm, named LOVENet, or Large Optimized Vector Embeddings Network, combines two state-of-the-art AI technologies: large language model (LLM) and structured knowledge graph technology. This innovative approach mathematically represents the connections between drugs and diseases, providing a fresh perspective on potential therapeutic uses.
Drug repurposing, the exploration of new therapeutic applications for established drugs, has garnered attention due to the time and cost constraints associated with conventional drug development. Approximately 30 to 40% of new drugs and biologics approved by the US Food and Drug Administration (FDA) are estimated to be repurposed or repositioned products.
Jouhyun Jeon, the Lead Scientist and Principal Investigator at Klick Applied Sciences, explained that LOVENet is designed to tackle these challenges by seamlessly integrating advanced machine-learning techniques with extensive biological and clinical datasets.
The research team demonstrated LOVENet's success in identifying associations between drugs and other confirmed disease states documented in scientific literature. For instance, they highlighted a drug initially approved for treating heart rhythm disturbances, which has also proven effective in addressing seizures.
The usual path for developing new medicines can take more than a decade. By using AI to speed up the repurposing process, we hope to shave years off current timelines, identify more uses for existing drugs, and ultimately provide physicians and patients with more treatment options across a wide range of therapeutic areas.
Jouhyun Jeon, Principal Investigator, Klick Applied Sciences
Klick’s EVP of Data Science Alfred Whitehead said, “LOVENet is an important first step in a new era of drug discovery. We think it holds amazing promise to lower development costs while increasing time efficiency and risk mitigation. It could also greatly assist in streamlining regulatory pathways, expanding market opportunities while addressing unmet medical needs.”
Journal Reference:
Krishnamurthy, N., et al. (2023) Drug repurposing: a systematic review on root causes, barriers and facilitators. BMC Health Services Research. doi.org/10.1186%2Fs12913-022-08272-z.
Source: https://www.klick.com/