1 Vivia Biotech, Tres Cantos, Madrid, Spain.
2 Hematology Service, Hospital 12 de Octubre, Madrid, Spain.
SLAS Technol. 2017 Jun;22(3):325-337. doi: 10.1177/2472630317700346. Epub 2017 Mar 24.
Functional ex vivo assays that predict a patient's clinical response to anticancer drugs for guiding cancer treatment have long been a goal, but few have yet proved to be reliable. To address this, we have developed an automated flow cytometry platform for drug screening that evaluates multiple endpoints with a robust data analysis system that can capture the complex mechanisms of action across different compounds. This system, called PharmaFlow, is used to test peripheral blood or bone marrow samples from patients diagnosed with hematological malignancies. Functional assays that use the whole sample, retaining all the microenvironmental components contained in the sample, offer an approach to ex vivo testing that may give results that are clinically relevant. This new approach can help to predict the patients' response to existing treatments or to drugs under development, for hematological malignancies or other tumors. In addition, relevant biomarkers can be identified that determine the patient's sensitivity, resistance, or toxicity to a given treatment. We propose that this approach, which better recapitulates the human microenvironment, constitutes a more predictive assay for personalized medicine and preclinical drug discovery.
长期以来,能够预测患者对癌症治疗药物的临床反应的功能性体外检测一直是一个目标,但迄今为止,很少有检测被证明是可靠的。为了解决这个问题,我们开发了一种用于药物筛选的自动化流式细胞仪平台,该平台使用强大的数据分析系统评估多个终点,可以捕捉不同化合物作用的复杂机制。该系统称为 PharmaFlow,用于测试被诊断患有血液系统恶性肿瘤的患者的外周血或骨髓样本。使用整个样本的功能检测,保留样本中包含的所有微环境成分,为体外检测提供了一种方法,可能会提供具有临床相关性的结果。这种新方法可以帮助预测患者对现有治疗方法或正在开发的药物的反应,适用于血液系统恶性肿瘤或其他肿瘤。此外,还可以确定相关的生物标志物,这些标志物决定了患者对特定治疗的敏感性、耐药性或毒性。我们提出,这种更好地模拟人类微环境的方法,构成了一种更具预测性的个性化医疗和临床前药物发现的检测方法。