Elucidating Sensorial and Functional Characteristics of Topical Formulations

摘要 除了由产品中的活性药物引起的确定的治疗作用外，还有安慰剂， 潜在的反安慰剂效应。在局部产品中，这些后一种效应可以解释 对于某些产品，总体响应的30%至50%。他们也可以解释为什么一些局部产品， 显然相同的生物利用度与不同的患者结果相关。本申请旨在 解决了局部产品中的细微赋形剂和制造变化何时会导致 受试者的感觉感知，使得产品的“感觉”在其被施用之前和/或之后已经改变。 适用于人体皮肤。第二个问题是产品在使用前后的“感觉”是否 可以通过仪器流变学、摩擦学和质地分析方法来量化，反过来， 可能与报告的感官行为有关。我们将生产局部配方， Q1、Q2和/或Q3属性不同，并且具有大的和边界感知差异。然后我们将 使用一系列流变学、摩擦学和质地分析方法以及沿着 干燥速率、颗粒和小球尺寸的表征。与此同时，这些产品将由 感知测试重点小组，与控制，为他们的感官特性或'感觉'的产品。我们将 然后将这些感官发现与制剂性质、组成和制造的变化联系起来， 仪器测试结果。我们的目标是，首先，了解产品之间的关系， 性质，仪器发现和感官分析，其次，得出仪器测试的标准， 指出受试者建议的产品成分没有差异，不确定它们是否不同， 感官行为预计我们可以定义最简单的，稳健的测试，准确和稳健 与感官知觉一致一系列统计方法，包括（潜在的）复杂的，机器 然后，学习和深度学习工具将用于对最合适的仪器分析进行建模， 以合理的置信度预测感知属性。一个关键的成果是一个潜在的监管指南 提倡仿制药应表现出与参考上市药品相似的感觉行为， 在流变学、摩擦学和质地分析中给出由Q1、Q2和Q3差异定义的边界， 局部产品之间的感觉行为可能不同。

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.