It has been believed that the better optimization can be achieved by tile P＋＋ optimization strategy since the P＋ curve shows a rather shallow maximum. In this paper, the P＋＋ optimization strategy has been verifie...It has been believed that the better optimization can be achieved by tile P＋＋ optimization strategy since the P＋ curve shows a rather shallow maximum. In this paper, the P＋＋ optimization strategy has been verified by evaluating （intensity-modulated radiation therapy, IMRT） plans for a T4 stage NPC patient in the situation where diffieuh compromise has to be made between probabilities for tumor control and normal tissue injuh＇y. The results showed that including the biological objective gEUD into the plan optimization couht decrease the mean dose of OAR. Theoretically, P＋＋ optimization strategy could be helpfnl to find the refined optimization solution for radiation therapy planning. However, in clinical radiotherapy practice, disease situations will form restrictions to use the biological evaluation only. More factors including both physical and biological models should be considered in a planning evaluation process to aehieve a best clinical solution.展开更多
Finding the optimal dose combination in two-agent dose-finding trials is challenging due to limited sample sizes and the extensive range of potential doses.Unlike traditional chemotherapy or radiotherapy,which primari...Finding the optimal dose combination in two-agent dose-finding trials is challenging due to limited sample sizes and the extensive range of potential doses.Unlike traditional chemotherapy or radiotherapy,which primarily focuses on identifying the maximum tolerated dose(MTD),therapies involving targeted and immune agents facilitate the identifica-tion of an optimal biological dose combination(OBDC)by simultaneously evaluating both toxicity and efficacy.Cur-rently,most approaches to determining the OBDC in the literature are model-based and require complex model fittings,making them cumbersome and challenging to implement.To address these challenges,we developed a novel model-as-sisted approach called uTPI-Comb.This approach refines the established utility-based toxicity probability interval design by integrating a strategically devised zone-based local and global candidate set searching strategy,which can effectively optimize the decision-making process for two-agent dose escalation or de-escalation in drug combination trials.Extensive simulation studies demonstrate that the uTPI-Comb design speeds up the dose-searching process and provides substantial improvements over existing model-based methods in determining the optimal biological dose combinations.展开更多
Introduction:Vaccines are a cornerstone of global health,with their efficacy and safety dependent on appropriate dosage determination.Early-phase vaccination trials face significant challenges due to minimal toxicity ...Introduction:Vaccines are a cornerstone of global health,with their efficacy and safety dependent on appropriate dosage determination.Early-phase vaccination trials face significant challenges due to minimal toxicity and nonmonotonic dose response curves,creating a major obstacle in vaccine development.To address this gap,we propose a novel Bayesian phase I/II trial design for dose response curves exhibiting plateau or unimodal patterns to identify the optimal biological dose(OBD),effectively balancing efficacy and toxicity.Methods:We employ a logistic dose-efficacy design that makes dose-escalation and de-escalation decisions while simultaneously considering both efficacy and safety parameters.Extensive simulation studies evaluate the performance of this design.Results:Comparative analyses with commonly used vaccine dose-finding designs demonstrate that our method excels in identifying the optimal toxicityefficacy trade-off,offering both simplicity and accuracy.Sensitivity analyses across various prior settings confirm the robustness and efficiency of our approach.Additionally,our design provides a userfriendly framework for clinicians,with superior operating performance compared to existing designs,particularly in terms of accuracy and robustness.Discussion:Our innovative Bayesian design represents a significant advancement in addressing the inherent challenges of early-phase vaccination clinical trials,offering improved accuracy and efficacy in vaccine dosage determination.展开更多
Atomizers were designed with different atomization parameters to obtain droplets that satisfy optimal particle size requirements for an impinging-type low-speed centrifugal atomizing sprayer.The main factors affecting...Atomizers were designed with different atomization parameters to obtain droplets that satisfy optimal particle size requirements for an impinging-type low-speed centrifugal atomizing sprayer.The main factors affecting droplet size are turntable speed,the number of teeth and the tooth shape of the toothed disc.Winner318 software was used to evaluate droplet sizes for different structures and the working parameters of the atomizer.The response surface method and Design-Expert were used to analyze the effect of each factor.The response surface analysis of the effect of structural and working parameters of the atomizer on the interaction between the volume medium diameter of the droplet and the spectral width of the droplet size was used to establish the atomizer droplet Granular spectrum prediction model.Optimal design fitting formulas are obtained,and the droplet sizes required for pesticides to control flying insect pests,to control the growth of reptile larvae,and the use of spraying fungicides to prevent crop damage were determined.This research provides a product not only similar to those in the market,but also the theoretical basis and references for innovation,development,and optimization of centrifugal atomization technology.展开更多
文摘It has been believed that the better optimization can be achieved by tile P＋＋ optimization strategy since the P＋ curve shows a rather shallow maximum. In this paper, the P＋＋ optimization strategy has been verified by evaluating （intensity-modulated radiation therapy, IMRT） plans for a T4 stage NPC patient in the situation where diffieuh compromise has to be made between probabilities for tumor control and normal tissue injuh＇y. The results showed that including the biological objective gEUD into the plan optimization couht decrease the mean dose of OAR. Theoretically, P＋＋ optimization strategy could be helpfnl to find the refined optimization solution for radiation therapy planning. However, in clinical radiotherapy practice, disease situations will form restrictions to use the biological evaluation only. More factors including both physical and biological models should be considered in a planning evaluation process to aehieve a best clinical solution.
基金This work was supported by the Natural Science Foundation of Anhui Province(2022AH050703)the National Natural Science Foundation of China(11671375).
文摘Finding the optimal dose combination in two-agent dose-finding trials is challenging due to limited sample sizes and the extensive range of potential doses.Unlike traditional chemotherapy or radiotherapy,which primarily focuses on identifying the maximum tolerated dose(MTD),therapies involving targeted and immune agents facilitate the identifica-tion of an optimal biological dose combination(OBDC)by simultaneously evaluating both toxicity and efficacy.Cur-rently,most approaches to determining the OBDC in the literature are model-based and require complex model fittings,making them cumbersome and challenging to implement.To address these challenges,we developed a novel model-as-sisted approach called uTPI-Comb.This approach refines the established utility-based toxicity probability interval design by integrating a strategically devised zone-based local and global candidate set searching strategy,which can effectively optimize the decision-making process for two-agent dose escalation or de-escalation in drug combination trials.Extensive simulation studies demonstrate that the uTPI-Comb design speeds up the dose-searching process and provides substantial improvements over existing model-based methods in determining the optimal biological dose combinations.
基金Supported by the National Natural Science Foundation of China(Project Nos.82404383 to Mengyi Lu,82173620 and 82373690 to Yang Zhao,82204156 to Dongfang You,and 82473732 to Fang Shao).
文摘Introduction:Vaccines are a cornerstone of global health,with their efficacy and safety dependent on appropriate dosage determination.Early-phase vaccination trials face significant challenges due to minimal toxicity and nonmonotonic dose response curves,creating a major obstacle in vaccine development.To address this gap,we propose a novel Bayesian phase I/II trial design for dose response curves exhibiting plateau or unimodal patterns to identify the optimal biological dose(OBD),effectively balancing efficacy and toxicity.Methods:We employ a logistic dose-efficacy design that makes dose-escalation and de-escalation decisions while simultaneously considering both efficacy and safety parameters.Extensive simulation studies evaluate the performance of this design.Results:Comparative analyses with commonly used vaccine dose-finding designs demonstrate that our method excels in identifying the optimal toxicityefficacy trade-off,offering both simplicity and accuracy.Sensitivity analyses across various prior settings confirm the robustness and efficiency of our approach.Additionally,our design provides a userfriendly framework for clinicians,with superior operating performance compared to existing designs,particularly in terms of accuracy and robustness.Discussion:Our innovative Bayesian design represents a significant advancement in addressing the inherent challenges of early-phase vaccination clinical trials,offering improved accuracy and efficacy in vaccine dosage determination.
基金This work was financially supported by National Key Research and Development Program of China(2017YFD0200303)China Agriculture Research System(CARS-25).
文摘Atomizers were designed with different atomization parameters to obtain droplets that satisfy optimal particle size requirements for an impinging-type low-speed centrifugal atomizing sprayer.The main factors affecting droplet size are turntable speed,the number of teeth and the tooth shape of the toothed disc.Winner318 software was used to evaluate droplet sizes for different structures and the working parameters of the atomizer.The response surface method and Design-Expert were used to analyze the effect of each factor.The response surface analysis of the effect of structural and working parameters of the atomizer on the interaction between the volume medium diameter of the droplet and the spectral width of the droplet size was used to establish the atomizer droplet Granular spectrum prediction model.Optimal design fitting formulas are obtained,and the droplet sizes required for pesticides to control flying insect pests,to control the growth of reptile larvae,and the use of spraying fungicides to prevent crop damage were determined.This research provides a product not only similar to those in the market,but also the theoretical basis and references for innovation,development,and optimization of centrifugal atomization technology.
