The RATIOS Study: Risk/benefit AssessmenT by IRB review of Phase One Studies

项目概要/摘要 第一阶段试验的道德行为取决于潜在试验之间存在合理的比例 风险和收益以及在研究期间向研究候选人提供有关该潜力的关键信息 知情同意过程。 IRB 必须仔细评估支持评估的科学信息 满足这些条件的潜在风险和收益。有几个障碍阻碍了这种评估。同时 FDA 仔细审查与 1 期试验相关的临床前安全数据，但临床前试验的情况并非如此 需要功效数据来支持潜在的益处。此外，IRB 没有收到有关以下方面的具体指导： 在临床前疗效数据中寻找什么，或者他们应该如何审查有关第一阶段的科学主张 方式。鉴于大量研究记录了以下特征，这种缺乏指导令人不安 许多临床前疗效研究使得很难对新药是否有效做出可靠的推论 治疗方式最终可能能够证明临床疗效。这样的推论是 当涉及采用新颖研究技术的临床前疗效研究时，尤其具有挑战性 CRISPR-Cas9 和脑类器官。了解可以可靠地对潜在功效做出哪些推论 关于采用新型临床前工具的新治疗方式将是我们项目的主要重点。这些 如果 IRB 能够确定存在合理的比率，则需要进行这些推论 使用新承诺技术的第一阶段试验的收益和风险之间的关系。在这个充满挑战的 在这种情况下，IRB 可以从结构化的风险/收益评估方法中受益。该项目旨在 制定并试点这样的方法。为此，我们将进行定量和定性研究以了解 关于当前 IRB 审查第一阶段研究的优点和缺点。我们将完成全国调查 IRB 主席。然后我们将进行 3 组半结构化访谈：(a) 过去的第一阶段试验 研究者，(b) 审查第一阶段试验申请的 IRB 成员，以及 (c) 过去的参与者或其合法参与者 第一阶段试验的代表。我们将利用这些发现来完善现有的概念框架 评估临床前研究中疗效数据的质量和可靠性。从这个精致的概念 框架中，我们将制定 IRB 和研究者清单，旨在 (a) 促进高度结构化的称量 IRB 在第一阶段试验中的潜在益处和风险，并 (b) 协助第一阶段研究人员提交更多 道德上健全的第一阶段试验申请。我们还将开发一种新颖的数据分析和决策支持 交互式软件平台，帮助第一阶段调查人员和 IRB 成员评估证据背景 围绕给定的第一阶段试验。这些决策辅助工具还将用于识别有关以下方面的关键披露： 第一阶段试验研究候选者的潜在风险和益处。看看我们的决策辅助工具是否会产生 这些预期的好处，在我们项目的最后一年，我们将与第一阶段研究人员和 IRB 一起进行试点 成员。

PROJECT SUMMARY/ABSTRACT The ethical conduct of Phase 1 trials is conditioned on both there being a reasonable ratio between potential risks and benefits and research candidates being provided with key information about that potential during the informed consent process. IRBs must carefully assess the scientific information supporting the assessment of potential risks and benefits in order to meet these conditions. Several hurdles hinder such assessment. While the FDA carefully vets preclinical safety data that relate to Phase 1 trials, the same is not true for the preclinical efficacy data needed to support the potential for benefit. Further, IRBs receive no specific guidance regarding what to look for in preclinical efficacy data or how they should vet scientific claims made about Phase 1 modalities. This lack of guidance is disconcerting given extensive research documenting characteristics of many preclinical efficacy studies that make it difficult to make reliable inferences about whether a new treatment modality might eventually be capable of demonstrating clinical efficacy. Such inferences are especially challenging when it comes to preclinical efficacy studies that employ novel research techniques like CRISPR-Cas9 and brain organoids. Knowing what inferences about potential efficacy can reliably be made about new treatment modalities employing novel preclinical tools will be the primary focus of our project. These are the very inferences that are required if IRBs are to be able to determine that there is a reasonable ratio between benefits and risks in Phase 1 trials employing new promissory technologies. In this challenging setting, IRBs could benefit from a structured approach to risk/benefit assessments. This project is designed to develop and pilot such an approach. To do this, we will conduct quantitative and qualitative research to learn about current strengths and weaknesses in IRB review of Phase 1 studies. We will complete a national survey of IRB chairs. Then we will conduct 3 sets of semi-structured interviews with: (a) past Phase 1 trial investigators, (b) IRB members who review Phase 1 trial applications, and (c) past participants or their legal representatives of Phase 1 trials. We will use these findings to refine an existing conceptual framework for assessing the quality and reliability of efficacy data in preclinical studies. From this refined conceptual framework, we will develop IRB and investigator checklists designed to (a) promote highly-structured weighing of potential benefits and risks by IRBs in Phase 1 trials and (b) assist Phase 1 investigators to submit more ethically robust Phase 1 trial applications. We will also develop a novel data analytics and decision-support interactive software platform to help Phase 1 investigators and IRB members evaluate the evidentiary context surrounding a given Phase 1 trial. These decision aids will also be used to identify critical disclosures about potential risks and benefits to Phase 1 trial research candidates. To see if our decision aids might produce these desired benefits, in the final year of our project we will pilot them with Phase 1 investigators and IRB members.