High-quality dose predictions based on a good understanding of target engagement is one of the main translational goals in drug development. Here, we systematically evaluate active human dose predictions for 15 Merck KGaA/EMD Serono assets spanning several modalities and therapeutic areas. Using case studies, we illustrate the value of adhering to the translational best practices of having an exposure–response relationship in an appropriate animal model; having validated, translatable pharmacodynamic (PD) biomarkers measurable in Phase I populations in the right tissue; having a deeper understanding of biology; and capturing uncertainties in predictions. Given the gap in publications on the subject, we believe that the learnings from this unique diverse data set, which are generic to the industry, will trigger actions to improve future predictions.

基于对靶点参与的良好理解的高质量剂量预测是药物开发的主要转化目标之一。在这里，我们系统地评估了 15 种 Merck KGaA/EMD Serono 资产的活性人体剂量预测，这些资产跨越多种模式和治疗领域。通过案例研究，我们说明了在适当的动物模型中遵循具有暴露-反应关系的转化最佳实践的价值；具有经过验证的、可翻译的药效学 (PD) 生物标志物，可在正确组织的 I 期人群中进行测量；对生物学有更深入的了解；并捕捉预测中的不确定性。鉴于有关该主题的出版物存在差距，我们相信从这一行业通用的独特多样数据集中学到的知识将触发改进未来预测的行动。