Selecting ideal drugs for encapsulation in thermosensitive liposomes and other triggered nanoparticles

Abstract

Objective: 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. Methods: 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. In vitro cellular drug uptake and cytotoxicity data were obtained experimentally and incorporated into the model. Results: 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. Conclusion: Combining simple in vitro experiments with a computer model could provide a powerful screening tool to evaluate the potential efficacy of candidate investigative drugs preceding TSL encapsulation and in vivo studies.