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High Dimensional Statistical Inference in Flexible Response Surface Models for Product Formulation

产品配方灵活响应面模型中的高维统计推断

基本信息

批准号：
1634878
负责人：
Enrique Del Castillo
金额：
$ 27.06万
依托单位：
Pennsylvania State Univ University Park
依托单位国家：
美国
项目类别：
Standard Grant
财政年份：
2016
资助国家：
美国
起止时间：
2016-08-15 至 2020-07-31
项目状态：
已结题

来源：
https://www.nsf.gov/awardsearch/showAward?AWD_ID=1634878&HistoricalAwards=false
关键词：
Dimensional Statistical Inference Flexible Response

项目摘要

Over the last few decades, multicomponent drugs have proved beneficial in the treatment of the most severe of diseases, e.g., anti-Cancer agents or antiviral agents. More generally, a multicomponent product formulation problem requires the determination of not only the component proportions and their amounts (or doses) but also the manufacturing process conditions that accompany the production of such formulation. With the introduction of new regulations by the Food and Drug Administration, pharmaceutical companies gained additional flexibility to make changes in their formulations and process operations. A key guideline in these regulations is that companies must specify a design space for their product/process for approval, i.e., a region of formulation and process operating conditions that guarantees quality. How to determine such design space poses several statistical inference challenges and is the goal of this research. This research also has important broader impacts in Biology. Experiments in animals vary the components and amounts of diets and measure surrogates of "fitness" and lifetime. These experiments have a similar structure as some of the experiments in drug development and they too require flexible models. Collaboration with researchers from the pharmaceutical sector and biologists in academia will consider these broader impacts.The overall goal of this research is to contribute new statistical methodology for computing frequentist and bayesian regions for the location of optima of flexible, supervised learning models that will aid in defining a design for product formulation. The research will study methods for finding confidence regions for optima of nonparametric models which are functions in a high-dimensional space without recourse to any distributional assumption. A very general Reproducible Kernel Hilbert Space construction will be adopted, which will find design spaces based on many different models used in practice. This research will also extend the theory of bootstrapping functions of parameters to the vector function case. The research includes an investigation of the data depth notion used to generate valid, unbiased, and small high dimensional confidence regions for the parameters, which in turn will be used to find the desired design region.

在过去的几十年里，多组分药物已被证明在治疗最严重的疾病中是有益的，例如，抗癌剂或抗病毒剂。更一般地，多组分产品配方问题不仅需要确定组分比例及其量（或剂量），而且还需要确定伴随这种配方生产的制造工艺条件。随着美国食品和药物管理局新法规的出台，制药公司获得了更大的灵活性，可以对其配方和工艺操作进行更改。这些法规中的一个关键准则是，公司必须为其产品/工艺指定一个设计空间以供批准，即，保证质量的配方和工艺操作条件区域。如何确定这样的设计空间提出了一些统计推断的挑战，是本研究的目标。这项研究在生物学领域也有重要的广泛影响。动物实验改变了饮食的成分和数量，并测量了“健康”和寿命的替代品。这些实验与药物开发中的一些实验具有类似的结构，它们也需要灵活的模型。与制药部门的研究人员和学术界的生物学家的合作将考虑这些更广泛的影响。本研究的总体目标是为计算灵活的监督学习模型的最优位置的频率论和baidu区域提供新的统计方法，这将有助于定义产品配方的设计。该研究将研究在高维空间中不依赖任何分布假设的非参数模型的最优值的置信区域的确定方法。将采用一个非常通用的可再生核希尔伯特空间构造，它将基于实践中使用的许多不同模型找到设计空间。本研究亦将参数自举函数理论推广至向量函数。该研究包括用于生成有效的，无偏的，小的高维置信区域的参数，这反过来又将被用来找到所需的设计区域的数据深度概念的调查。

项目成果

期刊论文数量（4）

专著数量（0）

科研奖励数量（0）

会议论文数量（0）

专利数量（0）

The Geometry of Nutrient Space-Based Life-History Trade-Offs: Sex-Specific Effects of Macronutrient Intake on the Trade-Off between Encapsulation Ability and Reproductive Effort in Decorated Crickets

DOI：
10.1086/696147
发表时间：
2018-04-01
期刊：
AMERICAN NATURALIST
影响因子：
2.9
作者：
Rapkin, James;Jensen, Kim;Hunt, John
通讯作者：
Hunt, John

Confidence regions for the location of response surface optima: the R package OptimaRegion

DOI：
10.1080/03610918.2020.1823412
发表时间：
2020-09-29
期刊：
COMMUNICATIONS IN STATISTICS-SIMULATION AND COMPUTATION
影响因子：
0.9
作者：
del Castillo, Enrique;Chen, Peng;Rapkin, James
通讯作者：
Rapkin, James

Multivariate stabilizing sexual selection and the evolution of male and female genital morphology in the red flour beetle*

红粉甲虫的多变量稳定性选择和雄性和雌性生殖器形态的进化*

DOI：
10.1111/evo.13912
发表时间：
2020
期刊：
Evolution
影响因子：
3.3
作者：
House, Clarissa;Tunstall, Philip;Rapkin, James;Bale, Mathilda J.;Gage, Matthew;Castillo, Enrique;Hunt, John
通讯作者：
Hunt, John

The geometry of nutritionally based life-history trade-offs: sex differences in the effect of macronutrient intake on the trade-off between immune function and reproductive effort in decorated crickets

基于营养的生活史权衡的几何形状：大量营养素摄入对装饰蟋蟀免疫功能和繁殖努力之间权衡影响的性别差异