Computational models constitute a fundamental asset for cancer research and drug R$\&D$, as they provide controlled environments for testing of hypotheses and are characterized by the total knowledge of the system. These features are particularly useful for 3D cell culture models where a complex interaction among cells and their environments ensues.

In this work, we present a programmable simulator capable of reproducing the behavior of cells cultured in 3D scaffolds and their response to pharmacological treatment. This system will be shown to be able to accurately describe the temporal evolution of the density of a population of MDA-MB-231 cells following their treatment with different concentrations of doxorubicin, together with a newly described drug-resistance mechanism and potential re-sensitization strategy. An extensive technical description of this model will be coupled to its experimental validation and to an analysis aimed at identifying which variables and behaviors account for differences in the response to treatment.

Comprehensively, this work contributes to the growing field of integrated in-silico/in-vitro analysis of biological processes which has great potential for both the increase of our scientific knowledge and the development of novel, more effective treatments.

计算模型是癌症研究和药物研发的基本资产$和d$，因为它们提供了用于检验假设的受控环境，并且具有系统的整体知识。这些功能对于3D细胞培养模型特别有用，在3D细胞培养模型中，需要进行细胞及其环境之间的复杂相互作用。

在这项工作中，我们提出了一个可编程的模拟器，该模拟器能够再现在3D支架中培养的细胞的行为及其对药理处理的反应。该系统将被证明能够准确描述MDA-MB-231细胞群在用不同浓度的阿霉素处理后的密度随时间的演变，以及新描述的耐药机制和潜在的再敏化战略。该模型的广泛技术描述将与它的实验验证以及旨在识别哪些变量和行为解释对治疗反应差异的分析相结合。

总的来说，这项工作为生物过程的硅/体外综合分析领域的发展做出了贡献，这既有增加我们的科学知识，又有开发新颖，更有效的治疗方法的巨大潜力。