For many multigene or multifactorial diseases,the one-drug therapy for inhibiting a defined molecular target is often less effective than combined treatments.Typically,drug combination therapies are multitargeted,so t...For many multigene or multifactorial diseases,the one-drug therapy for inhibiting a defined molecular target is often less effective than combined treatments.Typically,drug combination therapies are multitargeted,so the mechanisms or even interactions are often complementary.These drug-drug interactions may promote alteration of pharmacokinetic or pharmacodynamic activities of one drug by another drug.Other interactions may change the expected effect of medications through polymorphisms that alter the expression or activity of the drug-mediated enzyme and the cell signaling cascade,such as drug-gene interactions and drug-drug-gene interactions.The number of possible existing interactions requires appropriate methods of study.In this review,we summarized combination therapies for cancer,as well as for viral,cardiovascular,and neurological diseases.Here,we also highlight known methodologies,such as in vitro methods based on Loewe’s and Bliss’s pioneer models and in silico methods based on online available data.With more elaborate methods and reliable results,multitarget therapies through drug combinations may increasingly benefit patients suffering from complex diseases.展开更多
After the initiation of Human Microbiome Project in 2008,various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies.In this review an...After the initiation of Human Microbiome Project in 2008,various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies.In this review and perspective,we discuss the research and statistical hypotheses in gut microbiome studies,focusing on mechanistic concepts that underlie the complex relationships among host,microbiome,and environment.We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models.Given the current challenges and limitations in biostatistic approaches and tools,we discuss the future direction in developing statistical methods and models for the microbiome studies.展开更多
文摘For many multigene or multifactorial diseases,the one-drug therapy for inhibiting a defined molecular target is often less effective than combined treatments.Typically,drug combination therapies are multitargeted,so the mechanisms or even interactions are often complementary.These drug-drug interactions may promote alteration of pharmacokinetic or pharmacodynamic activities of one drug by another drug.Other interactions may change the expected effect of medications through polymorphisms that alter the expression or activity of the drug-mediated enzyme and the cell signaling cascade,such as drug-gene interactions and drug-drug-gene interactions.The number of possible existing interactions requires appropriate methods of study.In this review,we summarized combination therapies for cancer,as well as for viral,cardiovascular,and neurological diseases.Here,we also highlight known methodologies,such as in vitro methods based on Loewe’s and Bliss’s pioneer models and in silico methods based on online available data.With more elaborate methods and reliable results,multitarget therapies through drug combinations may increasingly benefit patients suffering from complex diseases.
基金We would like to acknowledge the NIDDK/National Institutes of Health grant R01 DK105118 to Jun Sun and UIC Cancer Center for supporting her research.
文摘After the initiation of Human Microbiome Project in 2008,various biostatistic and bioinformatic tools for data analysis and computational methods have been developed and applied to microbiome studies.In this review and perspective,we discuss the research and statistical hypotheses in gut microbiome studies,focusing on mechanistic concepts that underlie the complex relationships among host,microbiome,and environment.We review the current available statistic tools and highlight recent progress of newly developed statistical methods and models.Given the current challenges and limitations in biostatistic approaches and tools,we discuss the future direction in developing statistical methods and models for the microbiome studies.
