Abstract：
Late-stage clinical trial failures increase the overall cost and risk of bringing new drugs to market. Determining the pharmacokinetic (PK) drivers of toxicity and efficacy in preclinical studies and early clinical trials supports quantitative optimization of drug schedule and dose through computational modeling. Additionally, this approach permits prioritization of lead candidates with better PK properties early in development. Mylotarg is an antibody-drug conjugate (ADC) that attained U.S. Food and Drug Administration (FDA) approval under a fractionated dosing schedule after 17 years of clinical trials, including a 10-year period on the market resulting in hundreds of fatal adverse events. Although ADCs are often considered lower risk for toxicity due to their targeted nature, off-target activity and liberated payload can still constrain dosing and drive clinical failure. Under its original schedule, Mylotarg was dosed infrequently at high levels, which is typical for ADCs because of their long half-lives. However, our PK modeling suggests that these regimens increase maximum plasma concentration (Cmax)-related toxicities while producing suboptimal exposures to the target receptor. Our analysis demonstrates that the benefits of dose fractionation for Mylotarg tolerability should have been obvious early in the drug\'s clinical development and could have curtailed the proliferation of ineffective Phase III studies. We also identify schedules likely to be even more efficacious without compromising on tolerability. Alternatively, a longer-circulating Mylotarg formulation could obviate the need for dose fractionation, allowing superior patient convenience. Early-stage PK optimization through quantitative modeling methods can accelerate clinical development and prevent late-stage failures.
摘要：
后期临床试验失败会增加新药上市的总体成本和风险。在临床前研究和早期临床试验中确定毒性和功效的药代动力学（PK）驱动因素支持通过计算模型定量优化药物方案和剂量。此外,这种方法允许在开发早期对具有更好PK特性的先导候选物进行优先排序.Mylotarg是一种抗体-药物偶联物（ADC），经过17年的临床试验，在分次给药方案下获得了美国食品和药物管理局（FDA）的批准。包括市场上的10年期限，导致数百起致命的不良事件。尽管ADC由于其靶向性质而通常被认为具有较低的毒性风险，脱靶活性和释放的有效载荷仍然可以限制给药和驱动临床失败。根据其最初的时间表，Mylotarg的剂量很少高，这是典型的ADC，因为它们的半衰期长。然而,我们的PK模型表明,这些方案增加了与最大血浆浓度(Cmax)相关的毒性,同时产生对靶受体的次优暴露.我们的分析表明，剂量分割对Mylotarg耐受性的益处应该在药物临床开发的早期就很明显，并且可能会减少无效的III期研究的增殖。我们还确定了在不损害耐受性的情况下可能更有效的时间表。或者，循环时间较长的Mylotarg制剂可以避免剂量分级的需要，允许优越的病人方便。通过定量建模方法进行早期PK优化可以加速临床发展并防止后期失败。
