We present the EVONANO platform for the evolution of nanomedicines with application to anti-cancer treatments. EVONANO includes a simulator to grow tumours, extract representative scenarios, and then simulate nanoparticle transport through these scenarios to predict nanoparticle distribution. The nanoparticle designs are optimised using machine learning to efficiently find the most effective anti-cancer treatments. We demonstrate our platform with two examples optimising the properties of nanoparticles and treatment to selectively kill cancer cells over a range of tumour environments.
翻译:我们提出了纳米医学进化的EVONANO平台,用于抗癌治疗。 EVONANNO包含一个模拟器,以模拟肿瘤生长,提取具有代表性的设想情景,然后通过这些假设情景模拟纳米粒子迁移,以预测纳米粒子的分布。纳米粒子设计优化了利用机器学习来高效地找到最有效的抗癌治疗。我们用两个例子展示了我们的平台,优化纳米粒子的特性和治疗,以便在一系列肿瘤环境中选择性地杀死癌症细胞。