Michael Neely – författare

Individualized Drug Therapy for Patients: Basic Foundations, Relevant Software and Clinical Applications focuses on quantitative approaches that maximize the precision with which dosage regimens of potentially toxic drugs can hit a desired therapeutic goal. This book highlights the best methods that enable individualized drug therapy and provides specific examples on how to incorporate these approaches using software that has been developed for this purpose.

The book discusses where individualized therapy is currently and offers insights to the future. Edited by Roger Jelliffe, MD and Michael Neely, MD, renowned authorities in individualized drug therapy, and with chapters written by international experts, this book provides clinical pharmacologists, pharmacists, and physicians with a valuable and practical resource that takes drug therapy away from a memorized ritual to a thoughtful quantitative process aimed at optimizing therapy for each individual patient.

2018 PROSE Awards - Honorable Mention, Clinical Medicine: Association of American Publishers Uses pharmacokinetic approaches as the tools with which therapy is individualized Provides examples using specific software that illustrate how best to apply these approaches and to make sense of the more sophisticated mathematical foundations upon which this book is based Incorporates clinical cases throughout to illustrate the real-world benefits of using these approaches Focuses on quantitative approaches that maximize the precision with which dosage regimens of potentially toxic drugs can hit a desired therapeutic goal

Individualized Drug Therapy for Patients: Basic Foundations, Relevant Software and Clinical Applications focuses on quantitative approaches that maximize the precision with which dosage regimens of potentially toxic drugs can hit a desired therapeutic goal. This book highlights the best methods that enable individualized drug therapy and provides specific examples on how to incorporate these approaches using software that has been developed for this purpose.The book discusses where individualized therapy is currently and offers insights to the future. Edited by Roger Jelliffe, MD and Michael Neely, MD, renowned authorities in individualized drug therapy, and with chapters written by international experts, this book provides clinical pharmacologists, pharmacists, and physicians with a valuable and practical resource that takes drug therapy away from a memorized ritual to a thoughtful quantitative process aimed at optimizing therapy for each individual patient.- 2018 PROSE Awards - Honorable Mention, Clinical Medicine: Association of American Publishers- Uses pharmacokinetic approaches as the tools with which therapy is individualized- Provides examples using specific software that illustrate how best to apply these approaches and to make sense of the more sophisticated mathematical foundations upon which this book is based- Incorporates clinical cases throughout to illustrate the real-world benefits of using these approaches- Focuses on quantitative approaches that maximize the precision with which dosage regimens of potentially toxic drugs can hit a desired therapeutic goal

This text presents a modern theory of analysis, control, and optimization for dynamic networks. Mathematical techniques of Lyapunov drift and Lyapunov optimization are developed and shown to enable constrained optimization of time averages in general stochastic systems. The focus is on communication and queueing systems, including wireless networks with time-varying channels, mobility, and randomly arriving traffic. A simple drift-plus-penalty framework is used to optimize time averages such as throughput, throughput-utility, power, and distortion. Explicit performance-delay tradeoffs are provided to illustrate the cost of approaching optimality. This theory is also applicable to problems in operations research and economics, where energy-efficient and profit-maximizing decisions must be made without knowing the future. Topics in the text include the following: - Queue stability theory - Backpressure, max-weight, and virtual queue methods - Primal-dual methods for non-convex stochasticutility maximization - Universal scheduling theory for arbitrary sample paths - Approximate and randomized scheduling theory - Optimization of renewal systems and Markov decision systems Detailed examples and numerous problem set questions are provided to reinforce the main concepts. Table of Contents: Introduction / Introduction to Queues / Dynamic Scheduling Example / Optimizing Time Averages / Optimizing Functions of Time Averages / Approximate Scheduling / Optimization of Renewal Systems / Conclusions