Department of Pediatrics, Medical University of South Carolina, Charleston, SC, USA.
Int J Hyperthermia. 2022;39(1):998-1009. doi: 10.1080/02656736.2022.2086303.
Thermosensitive liposomes (TSL) and other triggered drug delivery systems (DDS) are promising therapeutic strategies for targeted drug delivery. However, successful designs with candidate drugs depend on many variables, including nanoparticle formulation, drug properties, and cancer cell properties. We developed a computational model based on experimental data to predict the potential efficacies of drugs when used with triggered DDS, such as TSL.
A computer model based on the Krogh cylinder was developed to predict uptake and cell survival with four anthracyclines when delivered by intravascular triggered DDS (e.g., TSL): doxorubicin (DOX), idarubicin (IDA), pirarubicin (PIR), and aclarubicin (ACLA). We simulated three tumor types derived from SVR angiosarcoma, LLC lung cancer, or SCC-1 oral carcinoma cells. cellular drug uptake and cytotoxicity data were obtained experimentally and incorporated into the model.
For all three cell lines, ACLA and IDA had the fastest cell uptake, with slower uptake for DOX and PIR. Cytotoxicity was highest for IDA and lowest for ACLA. The computer model predicted the highest tumor drug uptake for ACLA and IDA, resulting from their rapid cell uptake. Overall, IDA was most effective and produced the lowest tumor survival fraction, with DOX being the second best. Perivascular drug penetration was reduced for drugs with rapid cell uptake, potentially limiting delivery to cancer cells distant from the vasculature.
Combining simple experiments with a computer model could provide a powerful screening tool to evaluate the potential efficacy of candidate investigative drugs preceding TSL encapsulation and studies.
热敏脂质体（TSL）和其他触发式药物递送系统（DDS）是靶向药物递送的有前途的治疗策略。然而，候选药物的成功设计取决于许多变量，包括纳米颗粒制剂、药物特性和癌细胞特性。我们开发了一种基于实验数据的计算模型，用于预测在使用触发式 DDS（如 TSL）时药物的潜在疗效。
基于 Krogh 圆柱的计算机模型被开发出来，用于预测四种蒽环类抗生素（如 DOX、IDA、PIR 和 ACLA）经血管内触发式 DDS（如 TSL）给药时的摄取和细胞存活率。我们模拟了三种源自 SVR 血管肉瘤、LLC 肺癌或 SCC-1 口腔癌的肿瘤类型。细胞药物摄取和细胞毒性数据是通过实验获得的，并纳入到模型中。
对于所有三种细胞系，ACLA 和 IDA 的细胞摄取最快，而 DOX 和 PIR 的摄取较慢。IDA 的细胞毒性最高，ACLA 的细胞毒性最低。计算机模型预测 ACLA 和 IDA 的肿瘤药物摄取最高，这是由于它们的快速细胞摄取。总的来说，IDA 是最有效的，产生的肿瘤存活分数最低，其次是 DOX。快速细胞摄取的药物会降低血管周围的药物渗透，可能会限制药物输送到远离血管的癌细胞。
将简单的实验与计算机模型相结合，可以为评估候选研究性药物在 TSL 封装和研究之前的潜在疗效提供一种强大的筛选工具。
