Imaging, Dosimetry and Radiobiology for α-particle Emitter Radiopharmaceutical Therapy

对几乎所有转移性癌症患者的治疗已经成为一种平衡，既要处理通常严重的， 治疗引起的毒性和预防癌症进展。进展导致毒性越来越大 联合方案，直到患者屈服于治疗毒性或疾病进展。 放射药物治疗(RPT)是一种将辐射传递到靶细胞的新兴治疗方式。 阿尔法粒子发射器RPT(αRPT)是一种新的、从根本上不同的治疗方式，可以打破这一点 周而复始。这是唯一一种可以将高度有效的α颗粒输送到播散性癌症转移的方式。 从根本上说，它是一种辐射传递方式。所提供的辐射类型对 耐药机制或生物(或途径抑制)治疗观察到的意外副作用 化疗。尽管存在这些关键差异，αRPT仍在以延长的多周期方案进行管理 这严重损害了这种治疗方式的潜在疗效。在很大程度上，这是因为严格， 目前尚不存在用于α发射体的经验证的剂量学方法。这样的方法将使投射潜力成为可能。 对个别患者的正常器官毒性，这样就不需要为了毒性而延长治疗时间 评估。我们的主要目标是：1)开发和测试能够实现精确的剂量测量方法 以药物/治疗计划为基础的αRPT用于癌症治疗；2)获得所需的理解 优化涉及αRPT的联合疗法。支持这项计划项目赠款的假设如下 1.αRPT是一种特别适用于靶向转移的全身癌症治疗方式 癌症；它不太容易受到传统耐药机制的影响。它也可以由剂量学驱动 治疗计划。2.按照目前的执行情况，α可再生能源技术没有发挥其潜力。剂量学驱动的治疗 对RPT的计划已被证明可显著提高长期存活率。3.没有人对癌症进行治疗 治疗方式是治愈的，患者的潜在治疗反应和毒性有所不同。有希望的代理人是 不可避免地与其他疗法相结合。尽管机械论的研究被用来指向理性 在组合方面，临床试验继续在很大程度上是经验性的，就每个组合的顺序和数量而言 用药的。剂量学和放射生物学驱动的方法将极大地缩小人类 实验。考虑到这些假设，我们的总体目标是开发方法和 研究如何最好地将RPT实施从“放射化疗范例”转变为 一项与放射治疗计划更密切一致的计划。这些基本假设激发了 这项计划项目中提出的工作。简单地说：剂量学已被证明可以改善 RPT试剂，但阿尔法辐射源的剂量测定很困难。对该计划项目的五年支持将使αRPT 剂量学足够容易广泛实施，从而提高目前无法治愈的癌症的存活率。

Treatment for almost all patients with metastatic cancer has become a balance between managing often severe, treatment-induced toxicity and preventing cancer progression. Progression leads to increasingly toxic combination regimens until the patient succumbs either to treatment toxicity or to disease progression. Radiopharmaceutical therapy (RPT) is an emerging treatment modality that delivers radiation to targeted cells. Alpha-particle-emitter RPT (αRPT) is a new and fundamentally different therapeutic modality that can break this cycle. It is the only modality that can deliver highly potent, α-particles to disseminated cancer metastases. Fundamentally, it is a radiation delivery modality. The radiation type delivered is far less susceptible to the resistance mechanisms or unanticipated side-effects observed with biologic (or pathway inhibition) therapy and chemotherapy. Despite these key differences, αRPT is being administered in a prolonged multi-cycle scheme that severely compromises the potential efficacy of this treatment modality. In large part, this is because rigorous, validated dosimetry methods for α-emitters do not exist. Such methods would make it possible to project potential normal organ toxicity for individual patients so that treatment need not be prolonged for the sake of toxicity evaluation. Our primary objectives are: 1) to develop and test dosimetry methodologies that will enable precision medicine/treatment-planning-based αRPT for cancer therapy and 2) to gain the understanding needed to optimize combination therapies involving αRPT. The hypotheses underpinning this program project grant are as follows: 1. αRPT is a systemic cancer therapy modality that is particularly applicable to targeting metastatic cancer; it is far less susceptible to conventional resistance mechanisms. It is also amenable to dosimetry-driven treatment planning. 2. As currently implemented αRPT is not achieving its potential. Dosimetry-driven treatment planning for RPT has been demonstrated to substantially improve long-term survival. 3. No one cancer treatment modality is curative, and patients differ in their potential therapeutic response and toxicity. Promising agents are inevitably combined with other therapeutics. Although mechanistic studies are used to point towards rational combinations, clinical trials continue to be largely empirical in terms of the sequencing and amount of each administered drug. A dosimetry and radiobiology-driven approach will substantially reduce the scope of human experimentation. Considering these hypotheses, our overall objective is to develop methodologies and investigate how best to transition RPT implementation from that of a “radioactive chemotherapy paradigm” to one more closely aligned with treatment planning for radiation delivery. These foundational hypotheses motivate the work proposed in this program project. Put very simply: dosimetry has been proven to improve outcome for RPT agents but dosimetry for alpha-emitters is hard. Five years support of this program project will make αRPT dosimetry easy enough to implement widely and thereby improve survival for currently incurable cancers.