PAASPort: A web-based tool for nonclinical research quality assessment and risk of bias management to advance development of innovative medications

PAASPort：一种基于网络的工具，用于非临床研究质量评估和偏倚风险管理，以促进创新药物的开发

• 批准号: 9886100
• 负责人: ANDRE DER-AVAKIAN
• 金额: $ 22.33万
• 依托单位: PAASP US, LLC
• 依托单位国家: 美国
• 财政年份: 2020
• 资助国家: 美国
• 起止时间: 2020-02-01 至 2020-08-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9886100
• 关键词: Academia; Address; Advanced Development; Area; Automatic Information Processing; Automation; Biomedical Research; Businesses; Capital; Categories; Certification; Clinical; Clinical Research; Clinical Treatment; Code; Computer Simulation; Costs and Benefits; Data; Data Analyses; Decision Making; Development; Disease; Early identification; Economics; Elements; Employee; Evaluation; Evaluation Research; FAIR principles; Feedback; Foundations; Funding; Generations; Goals; Guidelines; Human; Individual; Industry; Investments; Laboratories; Link; Manuals; Measures; Modeling; Neurons; Neurosciences; Online Systems; Outcome; Pharmaceutical Preparations; Pharmacologic Substance; Phase; Privatization; Probability; Process; Quality Control; Questionnaires; Records; Reporting; Research; Research Design; Research Support; Resources; Risk; Risk Assessment; Risk Factors; Science; Scientist; Secure; Services; Substance Use Disorder; Targeted Research; Testing; Therapeutic; Time; Training; Translating; Translations; Validation; Visit; Weight; base; computerized data processing; cost; cost effective; data format; data integrity; design; digital; drug discovery; improved; innovation; interest; model design; novel; pressure; protective factors; prototype; research and development; research in practice; research to practice; response; tool; translational approach; web app; web-based tool

PROJECT SUMMARY / ABSTRACT Robust nonclinical data is an absolute requirement for building an effective translational strategy and developing clinically safe and effective medications. Most current efforts to facilitate generation of robust nonclinical research data focus on producing guidelines and checklists pertaining to study design and data analysis, but: a) do so only from a reporting perspective; b) do not consider processes other than study design and data analysis, such as compliance of data records with FAIR principles; and c) are at risk of triggering normative responses, whereby scientists simply satisfy the guidelines at a time when it is too late to take corrective actions. In this regard, and in line with RFA-DA-19-031, the current application proposes to develop, validate and introduce into common practice a novel web-based tool called PAASPort for early identification of potential risks of bias and support of decision making related to nonclinical research practice. PAASPort consists of a web application with proprietary analytics supporting project-specific and research unit-specific certification. In Phase 1, we will (Aim 1) convert the existing PAASPort prototype, which is currently a questionnaire in Microsoft Word format where data are manually organized and analyzed by a PAASP employee, into a web- based, interactive digital tool that can be accessed online at the research unit’s convenience and data will be automatically processed and prepared to provide feedback to the PAASPort customer (e.g., foundations, private investors, VCs, pharma); (Aim 2) enhance the commercial value of PAASPort by asking different groups of private investors how they value the different aspects of bias in research practice related to 1) study design and conduct, 2) data integrity, 3) quality culture, and 4) organizational and individual factors. In Phase 2, we will: (Aim 1) implement analytical mechanisms to support semi-automated processing of information collected from the online assessment; (Aim 2) minimize normative responses to the online assessment by introducing onsite audit-based feedback control, and (Aim 3) demonstrate economic benefits of improved nonclinical research practice quality assessments for private investors. The tool will be developed and validated with neuroscience and, more specifically, substance use disorder drug discovery in focus, but it can be extrapolated to other disease indications and therapeutic areas. The most immediate impact of the proposed tool is to avoid normative responses to emerging standards in research quality. However, given that PAASPort-supported data are expected to be more robust, the ultimate goal is to facilitate decision making, industry-academia partnerships, and the advancement of fundamental discoveries into commercial development.

项目概要/摘要 稳健的非临床数据是建立有效转化策略的绝对要求 开发临床安全有效的药物。当前为促进稳健生成而做出的大多数努力 非临床研究数据侧重于制定与研究设计和研究相关的指南和清单 数据分析，但是： a) 仅从报告角度进行分析； b) 不考虑除 研究设计和数据分析，例如数据记录是否符合公平原则； c) 位于 触发规范性反应的风险，即科学家只需满足准则即可 采取纠正措施为时已晚。在这方面，根据 RFA-DA-19-031，当前 应用程序建议开发、验证一种新颖的基于网络的工具并将其引入普遍实践 称为 PAASPort，以便及早识别潜在的偏见风险并支持相关决策 非临床研究实践。 PAASPort 由具有专有分析功能的 Web 应用程序组成 支持特定项目和特定研究单位的认证。 在第一阶段，我们将（目标 1）转换现有的 PAASPort 原型，该原型目前是一个调查问卷 Microsoft Word 格式，其中数据由 PAASP 员工手动组织和分析，并存储到网络中 基于交互式数字工具，可以在研究单位方便时在线访问，数据将 自动处理并准备向 PAASPort 客户提供反馈（例如基金会、 私人投资者、风险投资公司、制药公司）； （目标2）通过提出不同的要求来提升PAASPort的商业价值 私人投资者群体如何评价与 1) 研究相关的研究实践中不同方面的偏见 设计和行为，2) 数据完整性，3) 质量文化，以及 4) 组织和个人因素。同相 2、我们将：（目标1）实施分析机制以支持信息的半自动化处理 从在线评估中收集； （目标 2）最大限度地减少对在线评估的规范性反应 引入基于现场审核的反馈控制，以及（目标 3）展示改进后的经济效益 私人投资者的非临床研究实践质量评估。该工具将被开发并 经神经科学验证，更具体地说，重点是物质使用障碍药物发现，但它可以 可以推断到其他疾病适应症和治疗领域。此次事件最直接的影响 拟议的工具是避免对新兴研究质量标准做出规范性反应。然而，鉴于 PAASPort支持的数据预计会更加稳健，最终目标是方便决策， 产学合作伙伴关系，以及将基本发现转化为商业 发展。