Data demonstrating the in vivo anti-tumor efficacy of thermosensitive liposome formulations of a drug combination in pre-clinical models of breast cancer.

Thermosensitive liposomes in combination with localized mild hyperthermia can improve the delivery of drug to solid tumor sites. For this reason, thermosensitive liposome formulations of a range of chemotherapy drugs have been designed. Our group previously developed and characterized a thermosensitive liposome formulation of the heat shock protein 90 inhibitor alvespimycin as a companion therapeutic to a thermosensitive liposome formulation equivalent in composition to ThermoDox (i.e., ThermoDXR), with the goal of increasing the therapeutic index of doxorubicin as the combination was revealed to be highly synergistic in a panel of human breast cancer cell lines including MDA-MB-231 (Dunne et al., 2019). The data presented here further describes the effect of the doxorubicin (DXR) and alvespimycin (ALV) combination in vitro and in vivo. Specifically, the combination effect in mouse breast cancer 4T1 cells and the in vivo efficacy of this heat-activated chemotherapy combination in both immunocompromised (MDA-MB-231 tumor bearing female SCID mice) and immunocompetent (4T1 tumor bearing female BALB/c mice) models of breast cancer.

Harnessing immunotherapy to enhance the systemic anti-tumor effects of thermosensitive liposomes.

Chemotherapy plays an important role in debulking tumors in advance of surgery and/or radiotherapy, tackling residual disease, and treating metastatic disease. In recent years many promising advanced drug delivery strategies have emerged that offer more targeted delivery approaches to chemotherapy treatment. For example, thermosensitive liposome-mediated drug delivery in combination with localized mild hyperthermia can increase local drug concentrations resulting in a reduction in systemic toxicity and an improvement in local disease control. However, the majority of solid tumor-associated deaths are due to metastatic spread. A therapeutic approach focused on a localized target area harbors the risk of overlooking and undertreating potential metastatic spread. Previous studies reported systemic, albeit limited, anti-tumor effects following treatment with thermosensitive liposomal chemotherapy and localized mild hyperthermia. This work explores the systemic treatment capabilities of a thermosensitive liposome formulation of the vinca alkaloid vinorelbine in combination with mild hyperthermia in an immunocompetent murine model of rhabdomyosarcoma. This treatment approach was found to be highly effective at heated, primary tumor sites. However, it demonstrated limited anti-tumor effects in secondary, distant tumors. As a result, the addition of immune checkpoint inhibition therapy was pursued to further enhance the systemic anti-tumor effect of this treatment approach. Once combined with immune checkpoint inhibition therapy, a significant improvement in systemic treatment capability was achieved. We believe this is one of the first studies to demonstrate that a triple combination of thermosensitive liposomes, localized mild hyperthermia, and immune checkpoint inhibition therapy can enhance the systemic treatment capabilities of thermosensitive liposomes.

Triggered release from thermosensitive liposomes improves tumor targeting of vinorelbine.

Triggered drug delivery strategies have been shown to enhance drug accumulation at target diseased sites in comparison to administration of free drug. In particular, many studies have demonstrated improved targetability of chemotherapeutics when delivered via thermosensitive liposomes. However, most studies continue to focus on encapsulating doxorubicin while many other drugs would benefit from this targeted and localized delivery approach. The proposed study explores the therapeutic potential of a thermosensitive liposome formulation of the commonly used chemotherapy drug vinorelbine in combination with mild hyperthermia (39-43 °C) in a murine model of rhabdomyosarcoma. Rhabdomyosarcoma, the most common soft tissue sarcoma in children, is largely treated using conventional chemotherapy which is associated with significant adverse long-term sequelae. In this study, mild hyperthermia was pursued as a non-invasive, non-toxic means to improve the efficacy and safety profiles of vinorelbine. Thorough assessment of the pharmacokinetics, biodistribution, efficacy and toxicity of vinorelbine administered in the thermosensitive liposome formulation was compared to administration in a traditional, non-thermosensitive liposome formulation. This study shows the potential of an advanced formulation technology in combination with mild hyperthermia as a means to target an untargeted therapeutic agent and result in a significant improvement in its therapeutic index.

Turning down the heat: The case for mild hyperthermia and thermosensitive liposomes.

"A single disappointing study does not mean an end to the future of ThermoDox®", writes Michael Tardugno (CEO of Celsion Corporation), after announcing the termination of Celsion's second Phase III clinical trial. The OPTIMA trial, as it was known, evaluated their thermosensitive liposome (TSL) formulation of doxorubicin (ThermoDox®) in combination with radiofrequency ablation for the treatment of hepatocellular carcinoma (HCC). The purpose of this perspective is to review the case of ThermoDox and to address questions related to its clinical translation. Specifically, what has prevented the clinical translation of this once highly regarded breakthrough technology? Is this the end of TSLs? What can we learn from the challenges faced in the clinical development of this multi-modal therapy? As formulation scientists working in the field, we continue to believe that heat-triggered drug delivery platforms have tremendous potential as chemotherapy. Herein, we highlight potential limitations in the design of many of the Thermodox clinical trials, and we propose that despite these setbacks, TSLs have the potential to become an effective component of cancer therapy.

Heat-activated nanomedicine formulation improves the anticancer potential of the HSP90 inhibitor luminespib in vitro.

The heat shock protein 90 inhibitor, luminespib, has demonstrated potent preclinical activity against numerous cancers. However, clinical translation has been impeded by dose-limiting toxicities that have necessitated dosing schedules which have reduced therapeutic efficacy. As such, luminespib is a prime candidate for reformulation using advanced drug delivery strategies that improve tumor delivery efficiency and limit off-target side effects. Specifically, thermosensitive liposomes are proposed as a drug delivery strategy capable of delivering high concentrations of drug to the tumor in combination with other chemotherapeutic molecules. Indeed, this work establishes that luminespib exhibits synergistic activity in lung cancer in combination with standard of care drugs such as cisplatin and vinorelbine. While our research team has previously developed thermosensitive liposomes containing cisplatin or vinorelbine, this work presents the first liposomal formulation of luminespib. The physico-chemical properties and heat-triggered release of the formulation were characterized. Cytotoxicity assays were used to determine the optimal drug ratios for treatment of luminespib in combination with cisplatin or vinorelbine in non-small cell lung cancer cells. The formulation and drug combination work presented in this paper offer the potential for resuscitation of the clinical prospects of a promising anticancer agent.

Machine learning directed drug formulation development.

Machine learning (ML) has enabled ground-breaking advances in the healthcare and pharmaceutical sectors, from improvements in cancer diagnosis, to the identification of novel drugs and drug targets as well as protein structure prediction. Drug formulation is an essential stage in the discovery and development of new medicines. Through the design of drug formulations, pharmaceutical scientists can engineer important properties of new medicines, such as improved bioavailability and targeted delivery. The traditional approach to drug formulation development relies on iterative trial-and-error, requiring a large number of resource-intensive and time-consuming in vitro and in vivo experiments. This review introduces the basic concepts of ML-directed workflows and discusses how these tools can be used to aid in the development of various types of drug formulations. ML-directed drug formulation development offers unparalleled opportunities to fast-track development efforts, uncover new materials, innovative formulations, and generate new knowledge in drug formulation science. The review also highlights the latest artificial intelligence (AI) technologies, such as generative models, Bayesian deep learning, reinforcement learning, and self-driving laboratories, which have been gaining momentum in drug discovery and chemistry and have potential in drug formulation development.