论文标题
行业尺度精心策划的联合学习毒品发现
Industry-Scale Orchestrated Federated Learning for Drug Discovery
论文作者
论文摘要
为了将联邦学习应用于药物发现，我们在欧洲创新药品计划（IMI）项目Melloddy（Grant N°831472）的背景下开发了一个新颖的平台，该计划由10家制药公司，学术研究实验室，大型工业公司和初创公司组成。 Melloddy平台是第一个实现全球联合药物发现模型的行业规模平台，而无需共享单个合作伙伴的机密数据集。在平台上，通过在每次训练迭代后以密码，安全的方式汇总所有贡献合作伙伴的梯度，在平台上进行了培训。该平台部署在Amazon Web服务（AWS）的多门数架构上，以私有子网运行Kubernetes群集。在组织中，不同合作伙伴的角色被编码为平台上的不同权利和权限，并以分散的方式管理。 Melloddy平台产生了新的科学发现，这些发现在同伴论文中进行了描述。
To apply federated learning to drug discovery we developed a novel platform in the context of European Innovative Medicines Initiative (IMI) project MELLODDY (grant n°831472), which was comprised of 10 pharmaceutical companies, academic research labs, large industrial companies and startups. The MELLODDY platform was the first industry-scale platform to enable the creation of a global federated model for drug discovery without sharing the confidential data sets of the individual partners. The federated model was trained on the platform by aggregating the gradients of all contributing partners in a cryptographic, secure way following each training iteration. The platform was deployed on an Amazon Web Services (AWS) multi-account architecture running Kubernetes clusters in private subnets. Organisationally, the roles of the different partners were codified as different rights and permissions on the platform and administrated in a decentralized way. The MELLODDY platform generated new scientific discoveries which are described in a companion paper.
