LG Group has decided to embark on joint AI research and development with The Jackson Laboratory, a world-renowned genome research institution based in the United States, to unlock the secrets of Alzheimer’s disease and cancer.
LG AI Research and The Jackson Laboratory have signed a recent contract following their partnership agreement in December last year. Both entities plan to develop AI models capable of analyzing the causes and progression of Alzheimer’s disease and cancer, and predicting the effectiveness of treatments. This effort aims to lay the groundwork for personalized treatment research.
Both LG’s generative AI, known as EXAONE, and The Jackson Laboratory’s research data on the genetic characteristics and life cycle of Alzheimer’s disease will be integrated. The plan is to train EXAONE with this data to analyze the disease’s causes and enhance treatment effectiveness.
In particular, The Jackson Laboratory possesses a vast amount of research data on various genetic variations and mutations associated with diseases such as Alzheimer’s and cancer as a specialized research institution in genomics capable of designing and producing genetically modified mice. It is expected that there will be significant synergy when combined with LG’s AI technology.
LG AI Research and The Jackson Laboratory are also collaborating on the development of AI models for use in cancer diagnosis and treatment.
Both entities have embarked on developing new generative AI models: a multimodal generative AI model capable of swiftly diagnosing cancer and predicting treatment outcomes solely based on pathological images without the need for expensive and specialized tests. Additionally, they are developing a new conversational generative AI model that proposes personalized treatment options for cancer based on individual genomic information to healthcare professionals.
Both entities anticipate that AI will significantly reduce the development timeline from discovering potential drug candidates to preclinical and clinical trials in the field of cancer, thereby increasing the success rate.
Furthermore, they envision that the AI models developed through their collaboration will play a pivotal role in ushering in a precision medicine era where personalized treatments based on individual genetic mutations become possible.