Development of a web-based platform implementing novel Predictor of Skin Sensitization for Medical Devices (PreSS/MD)

开发基于网络的平台，实施新型医疗器械皮肤过敏预测器 (PreSS/MD)

基本信息

批准号：
10079701
负责人：
YVES RIBEILL
金额：
$ 16.79万
依托单位：
PREDICTIVE, LLC
依托单位国家：
美国
项目类别：
财政年份：
2020
资助国家：
美国
起止时间：
2020-09-09 至 2021-11-30
项目状态：
已结题

来源：
https://reporter.nih.gov/project-details/10079701
关键词：
Acute Address Advanced Development Allergic Contact Dermatitis Animal Testing Animals Bayesian Method Bayesian Modeling Biological Assay Cavia Chemical Structure Chemicals Computer Models Computer software Consumption Contact Dermatitis Data Data Set Databases Detection Development Devices Economics Evaluation Feedback Generations Human Immune response Instruction Interagency Coordinating Committee on the Validation of Alternative Methods International Knowledge Lead Medical Medical Care Costs Medical Device Methods Modeling Modernization Mus Occupational Online Systems Pathway interactions Phase Poison Prevalence Prostheses and Implants Public Health Publishing Pythons Quantitative Structure-Activity Relationship Reaction Reporting Resources Safety Skin Small Business Innovation Research Grant Structure Test Result Testing Time Toxic effect Toxin United States Food and Drug Administration Validation Workers&apos Compensation Workplace adverse outcome chemical release cost experience in silico in vitro Assay in vivo innovation knowledge graph lymph nodes machine learning algorithm model development novel novel strategies occupational hazard operation phase 1 study response skin patch software as a service success systemic toxicity tool web portal web server

项目摘要

PROJECT SUMMARY Medical devices have been documented to contain toxic chemicals that can leach and cause acute contact dermatitis (ACD) after repeated exposure or prolonged contact of the skin to these toxins. ACD is credited for 10-15% of all occupational illnesses and is also the second highest reported occupational hazard. Given its prevalence, ACD is also a great public health burden with combined yearly costs of up to $1 billion, which spans including medical costs, worker’s compensation and lost working time due to workplace absence. To this end, the U.S. Food and Drug Administration has mandated that all medical devices must be evaluated for possible skin sensitization using in vivo animal assays, which includes the Guinea pig maximization test (GPMT). Although GPMT tests provide valuable data on the skin sensitization effects of potential toxins, these assays are time-consuming and expensive. Moreover, the Interagency Coordinating Committee on the Validation of Alternative Methods (ICCVAM) recently published a Strategic Roadmap, calling for the development of alternative approaches to reduce animal testing of chemical and medical agents. Thus, there is a stated need to modernize safety evaluation of medical devices to reduce animal testing and shorten the regulatory review time, which would ultimately bring safer devices to the market faster. To address this unmet need, the key objectives of our FDA Phase I SBIR project are to (i) produce rigorously validated computational models for the GPMT assay integrating data obtained in human, mouse, and in vitro assays; and (ii) integrate these models into a software product termed PreSS/MD (Predictor of Skin Sensitization for Medical Devices). Our specific aims for this study include: 1) collecting, curating, and integrating the largest publicly available dataset for GMPT; 2) creating and validating novel computational models for GMPT data; 3) developing the PreSS/MD web server to allow users to make predictions of skin sensitization potential in medical devices. We will also develop a model for mixtures, including compounds tested jointly in different concentrations, using an approach that we developed previously. Finally, we will implement novel approaches to help users of our PreSS/MD platform interpret the developed models in terms of key chemical features responsible for skin sensitization. In addition, we will employ biomedical knowledge graphs to elucidate Adverse Outcome Pathways (AOPs) for skin sensitizers. Successful execution of this Phase I project will yield in the development of PreSS/MD as a centralized resource to evaluate the skin sensitization potential for medical devices. We expect this software-as-a-service web server platform will be of great value for companies and sponsors seeking regulatory approval of medical devices.

项目概要据记录，医疗设备含有有毒化学物质，可能会渗出并导致急性接触皮肤反复接触或长时间接触这些毒素后会出现皮炎 (ACD)。占所有职业病的 10-15%，也是报告的第二高职业危害。流行率，ACD 也是一个巨大的公共卫生负担，每年的综合成本高达 10 亿美元，涵盖包括医疗费用、工人赔偿和因缺勤而损失的工作时间。美国食品和药物管理局强制要求所有医疗器械必须接受可能的评估使用体内动物测定进行皮肤过敏，其中包括豚鼠最大化试验（GPMT）。尽管 GPMT 测试提供了有关潜在毒素对皮肤致敏作用的宝贵数据，但这些测定方法此外，机构间协调委员会的验证工作既耗时又昂贵。替代方法（ICCVAM）最近发布了战略路线图，呼吁开发因此，有必要采取替代方法来减少化学和药物的动物试验。实现医疗器械安全性评价现代化，减少动物试验并缩短监管审查时间，这最终将更快地将更安全的设备推向市场。为了解决这一未满足的需求，关键目标是。 FDA 第一阶段 SBIR 项目的目标是 (i) 为 GPMT 测定整合在人类、小鼠和体外测定中获得的数据；以及 (ii) 整合这些数据；模型转化为名为 PreSS/MD（医疗器械皮肤过敏预测器）的软件产品。我们这项研究的具体目标包括：1）收集、整理和整合最大的公开可用的 GMPT 数据集；2) 创建和验证 GMPT 数据的新颖计算模型； PreSS/MD 网络服务器允许用户预测医疗设备中的皮肤过敏潜力。还将开发一个混合物模型，包括在不同浓度下联合测试的化合物，使用最后，我们将实施新的方法来帮助我们的用户。 PreSS/MD 平台根据皮肤的关键化学特征解释开发的模型此外，我们将利用生物医学知识图来阐明不良结果途径。皮肤致敏剂（AOP）的成功执行第一阶段项目将产生以下成果：我们期望 PreSS/MD 作为评估医疗器械皮肤致敏潜力的集中资源。这个软件即服务网络服务器平台对于寻求帮助的公司和赞助商来说具有巨大的价值医疗器械的监管审批。