Elucidating Sensorial and Functional Characteristics of Topical Formulations

摘要 除了由产品中的活性药物引起的明确疗效外，还有安慰剂和， 潜在的，与该产品相关的NOCEBO效应。在外用产品中，后一种效应可能解释了 对一些产品的总体反应的30%到50%。他们还可以解释为什么一些特效产品带有 明显相同的生物利用度与不同的患者结局相关。此应用程序旨在 解决以下问题：局部产品中细微的赋形剂和生产工艺的改变何时会导致 受试者的感官知觉，即产品的“感觉”在产品发生变化之前和/或之后发生变化 适用于人类皮肤。第二个问题是产品在使用前和使用后的“感觉” 可以通过仪器流变学、摩擦学和织构分析方法来量化，而这些方法反过来， 可能与报告的感官行为有关。我们将生产外用配方，系统地 在第一季度、第二季度和/或第三季度属性上存在差异，并存在较大且接近的感知差异。到时候我们会的 使用一系列流变学、摩擦学和质构分析方法以及 干燥速度、颗粒和球粒大小的表征。同时，这些产品将通过以下机构进行评估 感知测试的焦点小组，有对照，关于他们的感官特性或产品的“感觉”。我们会 然后将这些感官发现与配方性质、成分和制造的变化联系起来，以及 他们的仪器性测试结果。我们的目标是，首先了解产品之间的关系 自然，仪器发现和感官分析，第二，得出仪器测试的标准， 指出受试者建议的产品组成没有不同，不确定它们是否不同，并且确实不同 感官行为。预计我们可以定义最简单、最健壮、准确和稳健的测试 与感官知觉相一致。一系列统计方法，包括(可能)复杂的机器 然后将使用学习和深度学习工具来对最合适的工具分析进行建模， 以合理的信心预测感知属性。一个关键的结果是一个潜在的监管指南 主张仿制药应表现出与参考上市药品类似的感官行为， 给出流变学、摩擦学和织构分析的边界，由Q1、Q2和Q3差异定义 局部产品之间的感官行为可能会有所不同。

Abstract In addition to the defined therapeutic effect caused by an active drug in a product, there is also a placebo and, potentially, a nocebo effect associated with that product. In topical products, these latter effects may account for 30% to 50% of the overall response for some products. They may also explain why some topical products with apparently identical bioavailability are associated with different patient outcomes. This application seeks to address the question of when do subtle excipient and manufacturing changes in a topical product cause a sensorial perception by subjects such that the “feel” of a product has changed either before and/or after it is applied to human skin. A second question is whether the “feel” of a product both before and after application can be quantified by instrumental rheology, tribology and texture analysis methods and whether these, in turn, can be related to the reported sensorial behaviour. We will manufacture topical formulations that systematically vary in Q1, Q2, and/or Q3 attributes and have large and borderline perceptive differences. We will then characterize these products using a range of rheology, tribology and texture analysis methods along with characterization of rate of drying, particle and globule size. In parallel, these products will be evaluated by perceptive testing focus groups, with controls, for their sensory properties or the ‘feel’ of the products. We will then relate these sensorial findings with the variations in formulation nature, composition and manufacture, and their resulting instrumental test results. Our goals are, firstly, to understand the relationships between product nature, instrumental findings and sensorial analyses and, secondly, to derive criteria for instrument tests that indicate what product composition subjects suggest do not differ, uncertain if they differ and do differ in their sensorial behaviour. It is anticipated that we can define the simplest, robust test that accurately and robustly aligns with sensory perceptions. A range of statistical methods, including (potentially) sophisticated, machine learning and deep learning tools will then be used to model the most appropriate instrumental analysis that can, with reasonable confidence predict perceptive attributes. A key outcome is a potential regulatory guideline advocating that generic products should exhibit similar sensorial behaviour as a reference listed drug product, giving boundaries in rheology, tribology and texture analysis as defined by Q1, Q2 and Q3 differences when sensorial behaviour between topical products is likely to be different.