创腾科技很荣幸受邀参加本次研讨会，作为合作伙伴我们将带来三大创新科技平台，分别是iLabPower研发创新平台、SDH科学数据基因组平台和MaXFlow分子模拟与人工智能平台。这些产品及解决方案代表了我们在药物研发领域的最新科技成果，旨在帮助企业降低成本、提高效率，并加速新药的研发与上市进程。我们诚挚地邀请企业新药研发人员、药物投资者以及各大高校的研究人员参会。

张弛 博士  新靶点发现总监

国药中生上海生物制品研究所 

报告时间：4月12日（周五）15:50-16:15

报告题目：An AI-driven approachtowards the discovery of neoantigen-based therapeutic cancer vaccines

本次演讲探讨胞苷脱氨酶介导的突变在肿瘤进化和新抗原生成中的作用。将重点讲述如何借助AI方法识别胞苷脱氨酶催化所产生的突变热点以及新抗原预测及验证方法。这些方法将组成一个有效开发肿瘤治疗性疫苗的技术平台。

个人简介：

本科毕业于中山大学药学院，硕士毕业于英国剑桥大学生物化学系，2015年博士毕业于英国伦敦大学癌症研究所肿瘤学专业，师从英国皇家科学院院士Paul Workman教授。2015-2021年历任英国伦敦大学癌症研究所博士后与研究员。2021年加入上海生物制品研究所任药物靶点研发总监。2022年入选国家高层次人才计划和上海市“浦江人才计划”，担任发展中国家生物制药联盟(EBPMN)科学顾问和上海生物工程学会理事。曾主持英国Wellcome Trust资助新药发现研究课题一项；主持英国Cancer Research UK资助的药物早期研发课题一项。作为主要完成人参与英国Cancer Research UK资助的研究课题两项。发表SCI科研论文13篇。主要科学发现在英国推动了I期临床实验一项；推动新靶点药物研发项目进入先导化合物优化阶段并获得A轮资助一项。

报告摘要：

The quest for efficacious therapeutic cancer vaccines hinges on the identification of neoantigens that elicit robust immune responses. This study introduces an AI-driven framework for discovering neoantigen-based therapeutic targets by identifying and evaluating Differential Variants (DVs) mediated by the cytidine deamination enzymes (CDEs), a class of key players in immune response modulation and tumorigenesis. Utilizing a novel artificial intelligence methodology, we systematically analyze CDEs-mediated DVs in breast cancer, identifying potential neoantigens through sophisticated computational predictions of immunogenicity.

Our approach begins with the mapping of CDEs-mediated DNA or RNA editing sites using breast cancer cell models, coupled with next-generation sequencing to identify DVs. Leveraging AI algorithms, we then sift through these DVs to pinpoint novel candidates with potential immunogenic mutations. Predictive modeling of mutant peptides derived from these DVs allows for the prioritization based on their immunogenic potential, focusing on those most likely to be recognized by the host immune system.

Validation of the AI-derived DVs through experimental assays confirms their capacity to generate genuine neoantigens, substantiating the predictive power of our AI framework. By employing a combination of identifying DVs at both genomic and transcriptomic levels, we ensure a comprehensive analysis, thereby uncovering a wide array of potential neoantigens.

The study not only showcases the application of artificial intelligence in the nuanced identification of cancer neoantigens but also sets a precedent for the integration of AI in the design of personalized cancer immunotherapies. The results underscore the significance of CDE-mediated base editing as a source of neoantigens and demonstrate the feasibility of an AI-driven approach in predicting and validating neoantigenicity. This methodology promises to streamline the discovery of therapeutic cancer vaccines, potentially transforming the landscape of cancer treatment through personalized immunotherapy strategies.

欢迎莅临创腾科技展位（4号），一同探讨如何在药物研发中有效应用这些先进的技术，实现研发流程的优化和创新。

我们期待与您面对面交流，拓展合作机会，共同探索科技在药物研发中的无限可能，推动药物研发领域的进步。