目前新药研发高投入高失败率的“反摩尔定律(Eroom′s Law)”提示,现有药物研发将复杂人体系统简化为可研究模型(还原论方法)到最终回归复杂人体系统验证效果(系统论方法)存在转化研究上的巨大鸿沟。近年来全球创新药研发策略发生了两...目前新药研发高投入高失败率的“反摩尔定律(Eroom′s Law)”提示,现有药物研发将复杂人体系统简化为可研究模型(还原论方法)到最终回归复杂人体系统验证效果(系统论方法)存在转化研究上的巨大鸿沟。近年来全球创新药研发策略发生了两个重大变化:一是希望将表型药物发现(phenotypic drug discovery,PDD)和靶点药物发现(target-based drug discovery,TDD)结合起来以加速创新药研发,二是更加关注多靶点药物设计(multi-target drug design,MTDD)及其对疾病动态网络系统调节的重要性。研究发现,中医方剂及其组成药物衍生的方剂纳米体(formula-derived nanoparticles of TCM,FDN),包括中药外泌体(TCM-Exo)、中药汤剂体(TCM-Deco)、中药碳量子点(TCM-CDs)、中药成分本草体(TCM-Benc)等自组装纳米聚集体,可作为中药多成分药效物质递送的理想方式或载体,进而实现对疾病动态网络多靶点多层次立体靶向调控。笔者提出的方剂纳米体药物发现(formula-derived nanoparticles drug discovery,FDD),创新融合传统中医方剂配伍理论和现代纳米技术方法,可实现PDD和TDD的优势结合,为多靶点药物技术创新与新药发现提供新策略和新方案,有助于大幅度提高多靶点复方药物研发的成功率。展开更多
The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the...The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the pilot training and/or CsI feedback stage.In fact,the downlink communication generally includes three stages,i.e.,pilot training,CsI feedback,and data transmission.These three stages are mutually related and jointly determine the overall system performance.Unfortunately,there exist few studies on the reduction of csIT acquisition overhead from the global point of view.In this paper,we integrate the Minimum Mean Square Error(MMSE)channel estimation,Random Vector Quantization(RVQ)based limited feedback and Maximal Ratio Combining(MRC)precoding into a unified framework for investigating the resource allocation problem.In particular,we first approximate the covariance matrix of the quantization error with a simple expression and derive an analytical expression of the received Signal-to-Noise Ratio(SNR)based on the deterministic equivalence theory.Then the three performance metrics(the spectral efficiency,energy efficiency,and total energy consumption)oriented problems are formulated analytically.With practical system requirements,these three metrics can be collaboratively optimized.Finally,we propose an optimization solver to derive the optimal partition of channel coherence time.Experiment results verify the benefits of the proposed resource allocation schemes under three different scenarios and illustrate the tradeoff of resource allocation between three stages.展开更多
文摘目前新药研发高投入高失败率的“反摩尔定律(Eroom′s Law)”提示,现有药物研发将复杂人体系统简化为可研究模型(还原论方法)到最终回归复杂人体系统验证效果(系统论方法)存在转化研究上的巨大鸿沟。近年来全球创新药研发策略发生了两个重大变化:一是希望将表型药物发现(phenotypic drug discovery,PDD)和靶点药物发现(target-based drug discovery,TDD)结合起来以加速创新药研发,二是更加关注多靶点药物设计(multi-target drug design,MTDD)及其对疾病动态网络系统调节的重要性。研究发现,中医方剂及其组成药物衍生的方剂纳米体(formula-derived nanoparticles of TCM,FDN),包括中药外泌体(TCM-Exo)、中药汤剂体(TCM-Deco)、中药碳量子点(TCM-CDs)、中药成分本草体(TCM-Benc)等自组装纳米聚集体,可作为中药多成分药效物质递送的理想方式或载体,进而实现对疾病动态网络多靶点多层次立体靶向调控。笔者提出的方剂纳米体药物发现(formula-derived nanoparticles drug discovery,FDD),创新融合传统中医方剂配伍理论和现代纳米技术方法,可实现PDD和TDD的优势结合,为多靶点药物技术创新与新药发现提供新策略和新方案,有助于大幅度提高多靶点复方药物研发的成功率。
基金supported by the foundation of National Key Laboratory of Electromagnetic Environment(Grant No.JCKY2020210C 614240304)Natural Science Foundation of ZheJiang province(LQY20F010001)+1 种基金the National Natural Science Foundation of China under grant numbers 82004499State Key Laboratory of Millimeter Waves under grant numbers K202012.
文摘The performance of massive MIMO systems relies heavily on the availability of Channel State Information at the Transmitter(CSIT).A large amount of work has been devoted to reducing the CSIT acquisition overhead at the pilot training and/or CsI feedback stage.In fact,the downlink communication generally includes three stages,i.e.,pilot training,CsI feedback,and data transmission.These three stages are mutually related and jointly determine the overall system performance.Unfortunately,there exist few studies on the reduction of csIT acquisition overhead from the global point of view.In this paper,we integrate the Minimum Mean Square Error(MMSE)channel estimation,Random Vector Quantization(RVQ)based limited feedback and Maximal Ratio Combining(MRC)precoding into a unified framework for investigating the resource allocation problem.In particular,we first approximate the covariance matrix of the quantization error with a simple expression and derive an analytical expression of the received Signal-to-Noise Ratio(SNR)based on the deterministic equivalence theory.Then the three performance metrics(the spectral efficiency,energy efficiency,and total energy consumption)oriented problems are formulated analytically.With practical system requirements,these three metrics can be collaboratively optimized.Finally,we propose an optimization solver to derive the optimal partition of channel coherence time.Experiment results verify the benefits of the proposed resource allocation schemes under three different scenarios and illustrate the tradeoff of resource allocation between three stages.
