Smith Mitchell R, Cronin John F, Weiss Robert F
George Washington Cancer Center, 1255 25th St NW, Suite 932, Washington, D.C., 20037, USA.
Back Bay Biosciences, Boston, MA, USA.
Leuk Res. 2021 Nov;110:106663. doi: 10.1016/j.leukres.2021.106663. Epub 2021 Jul 6.
In silico simulation of pre-clinical and clinical data may accelerate pre-clinical and clinical trial advances, leading to benefits for therapeutic outcomes, toxicity and cost savings. Combining this with clonal architecture data may permit truly personalized therapy. Chronic lymphocytic leukemia (CLL) exhibits clonal diversity, evolution and selection, spontaneously and under treatment pressure. We apply a dynamic simulation model to published CLL clonal architecture data to explore alternative therapeutic strategies, focusing on BTK inhibition. By deriving parameters of clonal growth and death behavior we model continuous vs time-limited ibrutinib therapy, and find that, despite persistence of disease, time to clinical progression may not differ. This is a testable hypothesis. We model IgVH-mutated CLL vs unmutated CLL by varying proliferation and find, based on the limited available data about clonal dynamics after such therapy, that there are differences predicted in response to anti-CD20 efficacy. These models can suggest potential clinical trials, and also indicate what additional data are needed to improve predictions. Ongoing work will expand modeling to agents such as venetoclax and to T cell therapies.
临床前和临床数据的计算机模拟可能会加速临床前和临床试验的进展，为治疗效果、毒性和成本节约带来益处。将其与克隆结构数据相结合可能会实现真正的个性化治疗。慢性淋巴细胞白血病（CLL）在自发状态下以及治疗压力下会表现出克隆多样性、进化和选择。我们将动态模拟模型应用于已发表的CLL克隆结构数据，以探索替代治疗策略，重点关注布鲁顿酪氨酸激酶（BTK）抑制。通过推导克隆生长和死亡行为的参数，我们对连续与限时伊布替尼治疗进行建模，发现尽管疾病持续存在，但临床进展时间可能并无差异。这是一个可检验的假设。我们通过改变增殖来对免疫球蛋白重链可变区（IgVH）突变的CLL与未突变的CLL进行建模，并基于此类治疗后关于克隆动力学的有限可用数据发现，预测抗CD20疗效存在差异。这些模型可以提出潜在的临床试验建议，还能指出为改善预测还需要哪些额外数据。正在进行的工作将把建模扩展到维奈托克等药物以及T细胞疗法。
