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首页> 外文期刊>Birth defects research, Part B. Developmental and reproductive toxicology >Goldilocks' Determination of What New In Vivo Data are 'Just Right' for Different Common Drug Development Scenarios, Part 1
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Goldilocks' Determination of What New In Vivo Data are 'Just Right' for Different Common Drug Development Scenarios, Part 1

机译:Goldilocks确定哪些新的体内数据对于不同的常见药物开发方案是“正确的”,第1部分

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摘要

As alternative models and scientific advancements improve the ability to predict developmental toxicity, the challenge is how to best use this information to support safe use of pharmaceuticals in humans. While in vivo experimental data are often expected, there are other important considerations that drive the impact of developmental toxicity data to human risk assessment and product labeling. These considerations include three key elements: (1) the drug's likelihood of producing off-target toxicities, (2) risk tolerance of adverse effects based on indication and patient population, and (3) how much is known about the effects of modulating the target in pregnancy and developmental biology. For example, there is little impact or value of a study in pregnant monkeys to inform the risk assessment for a highly specific monoclonal antibody indicated for a life-threatening indication against a target known to be critical for pregnancy maintenance and fetal survival. In contrast, a small molecule to a novel biological target for a chronic lifestyle indication wouldwarrant more safety data than simply in vitro studies and a literature review. Rather than accounting for innumerable theoretical possibilities surrounding each potential submission's profile, we consolidated most of the typical situations into eight possible scenarios across these three elements, and present a discussion of these scenarios here. We hope that this framework will facilitate a rational approach to determining what new information is required to inform developmental toxicity risk of pharmaceuticals in context of the specific needs of each program while reducing animal use where possible.
机译:随着替代模型和科学进步提高了预测发育毒性的能力,挑战在于如何最好地利用这些信息来支持人类安全使用药物。尽管通常需要体内实验数据,但还有其他重要考虑因素会影响发育毒性数据对人类风险评估和产品标签的影响。这些考虑因素包括三个关键要素:(1)药物产生脱靶毒性的可能性;(2)基于适应症和患者人群的不良反应风险承受能力;(3)关于调节靶点的作用了解多少在怀孕和发育生物学中。例如,对怀孕的猴子进行的一项研究没有什么影响或价值,无法告知高特异性单克隆抗体的风险评估,该单克隆抗体针对已知对维持妊娠和胎儿存活至关重要的靶标,可能威胁生命。相比之下,针对新的生物靶标的小分子可用于长期生活方式的指示,将比简单的体外研究和文献综述提供更多的安全性数据。我们没有考虑围绕每个潜在提交者的个人资料的无数理论可能性,而是将大多数典型情况合并为横跨这三个要素的八个可能情况,并在此处介绍了这些情况。我们希望该框架将有助于采取一种合理的方法来确定需要哪些新信息以根据每个程序的特定需求来告知药物的发育毒性风险,同时尽可能减少动物的使用。

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