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    Home > Active Ingredient News > Antitumor Therapy > Professor Lu Shun: AI multi-omics deep learning predicts the efficacy of lung cancer immunity PD-1/PD-L1

    Professor Lu Shun: AI multi-omics deep learning predicts the efficacy of lung cancer immunity PD-1/PD-L1

    • Last Update: 2021-03-20
    • Source: Internet
    • Author: User
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    A few days ago, the results of a "prediction of the clinical benefit of single-drug PD-1/PD-L1 immunotherapy for advanced non-small cell lung cancer based on multi-omics sequence deep learning " was officially released in the American Journal of Translation Research.


    immunity

    Yang,Y.


    PMID: 33594323.


    In the process of lung cancer immunotherapy (PD-1/PD-L1), it is very important to predict the clinical benefit of patients, and it is also facing huge challenges.


     This study retrospectively analyzed 1633 CT imaging data of 200 patients with advanced NSCLC who were treated with mAb PD-1/PD-L1 in the Chest Hospital of Shanghai Jiaotong University from April 2016 to December 2019 .


    NSCLC

     

    Serial deep learning model for response to PD-1/PD-L1 inhibitor in NSCLC 3

    3

     The results of the study found that the prediction model based on the 90-day deep learning showed good detection performance in distinguishing drug response, and the area under the curve (AUC) reached 0.


    Figure1

    Before immunotherapy, the model was used to divide patients into high-risk and low-risk non-responders.


    Figure2

    An exploratory predictive analysis of 93 patients with stable disease (SD) also showed that low-risk patients and higher-risk patients had longer PFS and OS (11.


    Figure3

    Therefore, SimTA-based multi-omics series deep learning provides a method with great potential for predicting the response of patients with advanced NSCLC to PD-1/PD-L1 monotherapy.


    4

    Professor Lu Shun

    Professor Lu Shun

    Chief physician, doctoral supervisor, second-level professor

    Leading talent in Shanghai, outstanding academic leader in Shanghai, chief expert of national key special project

    Enjoy the special allowance of the State Council

    Director of Shanghai Chest Hospital of Shanghai Jiaotong University, Shanghai Lung Cancer Clinical Medicine Center

    Director of China Anti-Cancer Association, Chairman of Lung Cancer Professional Committee

    Chinese Society of Clinical Oncology (CSCO) executive director, Xi Sike fund will be vice president

    fund

    Chairman of Shanghai Medical Association Oncology Society

    Member of Oncology Society of Chinese Medical Association, Chairman of Lung Cancer Professional Committee

    Vice President of the Oncology Branch of Shanghai Medical Doctor Association, leader of the specialist training group

    Deputy Editor-in-Chief of Journal of Thoracic Oncology, the official journal of the International Association for the Study of Lung Cancer 

    Executive Director of Shanghai Anti-Cancer Association

    Vice Chairman of the Precision Medicine Branch ofChina Medical Biotechnology Association

    Precise

    As the person in charge, presided over 1 international cooperation project of the Ministry of Science and Technology; 1 major national new drug innovation project, 2 sub-projects of 863 major project; 1 general project of the National Natural Science Foundation of China

     About point

    Diannei Technology was established in April 2016.


    Diannei Technology uses machine deep learning to carry out independent research and development of a number of exclusive technologies such as "non-invasive prediction of pathological infiltration typing", and cooperates with top domestic experts and hospitals for clinical verification.


    The company's core team members have an average of more than 10 years of medical artificial intelligence technology research and development, product research and development and industry market experience.
    At present, the technology service cooperation in the site has covered 58 provinces, cities, and prefecture-level administrative regions across the country, benefiting millions of people.
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