Colloidal drug aggregates have been a nuisance in drug screening, yet, because they inherently comprise drug-rich particles, they may be useful in vivo if issues of stability can be addressed. As the first step toward answering this question, we optimized colloidal drug aggregate formulations using a fluorescence-based assay to study fulvestrant colloidal formation and stability in high (90%) serum conditions in vitro. We show, for the first time, that the critical aggregation concentration of fulvestrant depends on media composition and increases with serum concentration. Excipients, such as polysorbate 80, stabilize fulvestrant colloids in 90% serum in vitro for over 48 h. Using fulvestrant and an investigational pro-drug, pentyloxycarbonyl-( p-aminobenzyl) doxazolidinylcarbamate (PPD), as proof-of-concept colloidal formulations, we demonstrate that the in vivo plasma half-life for stabilized colloids is greater than their respective monomeric forms. These studies demonstrate the potential of turning the nuisance of colloidal drug aggregation into an opportunity for drug-rich formulations.

Background

Leiomyosarcoma (LMS) is a common type of soft tissue sarcoma that responds poorly to standard chemotherapy. Thus the goal of this study was to identify novel selective therapies that may be effective in leiomyosarcoma by screening cell lines with a small molecule library comprised of 480 kinase inhibitors to functionally determine which signalling pathways may be critical for LMS growth.

Methods

LMS cell lines were screened with the OICR kinase library and a cell viability assay was used to identify potentially effective compounds. The top 10 % of hits underwent secondary validation to determine their EC50 and immunoblots were performed to confirm selective drug action. The efficacy of combination drug therapy with doxorubicin (Dox) in vitro was analyzed using the Calcusyn program after treatment with one of three dosing schedules: concurrent treatment, initial treatment with a selective compound followed by Dox, or initial treatment with Dox followed by the selective compound. Single and combination drug therapy were then validated in vivo using LMS xenografts.

Results

Compounds that targeted PI3K/AKT/mTOR pathways (52 %) were most effective. EC50s were determined to validate these initial hits, and of the 11 confirmed hits, 10 targeted PI3K and/or mTOR pathways with EC50 values <1 μM. We therefore examined if BEZ235 and BKM120, two selective compounds in these pathways, would inhibit leiomyosarcoma growth in vitro. Immunoblots confirmed on-target effects of these compounds in the PI3K and/or mTOR pathways. We next investigated if there was synergy with these agents and first line chemotherapy doxorubicin (Dox), which would allow for earlier introduction into patient care. Only combined treatment of BEZ235 and Dox was synergistic in vitro. To validate these findings in pre-clinical models, leiomyosarcoma xenografts were treated with single agent and combination therapy. BEZ235 treated xenografts (n = 8) demonstrated a decrease in tumor volume of 42 % whereas combining BEZ235 with Dox (n = 8) decreased tumor volume 68 % compared to vehicle alone.

Conclusions

In summary, this study supports further investigation into the use of PI3K and mTOR inhibitors alone and in combination with standard treatment in leiomyosarcoma patients.

One aspirational goal of computational chemistry is to predict potent and drug-like binders for any protein, such that only those that bind are synthesized. In this Roadmap, we describe the launch of Critical Assessment of Computational Hit-finding Experiments (CACHE), a public benchmarking project to compare and improve small molecule hit-finding algorithms through cycles of prediction and experimental testing. Participants will predict small molecule binders for new and biologically relevant protein targets representing different prediction scenarios. Predicted compounds will be tested rigorously in an experimental hub, and all predicted binders as well as all experimental screening data, including the chemical structures of experimentally tested compounds, will be made publicly available, and not subject to any intellectual property restrictions. The ability of a range of computational approaches to find novel binders will be evaluated, compared, and openly published. CACHE will launch 3 new benchmarking exercises every year. The outcomes will be better prediction methods, new small molecule binders for target proteins of importance for fundamental biology or drug discovery, and a major technological step towards achieving the goal of Target 2035, a global initiative to identify pharmacological probes for all human proteins.