Extending the boundaries of cancer therapeutic complexity with literature text mining.

Drug combination therapy is a main pillar of cancer therapy. As the number of possible drug candidates for combinations grows, the development of optimal high complexity combination therapies (involving 4 or more drugs per treatment) such as RCHOP-I and FOLFIRINOX becomes increasingly challenging due to combinatorial explosion. In this paper, we propose a text mining (TM) based tool and workflow for rapid generation of high complexity combination treatments (HCCT) in order to extend the boundaries of complexity in cancer treatments. Our primary objectives were: (1) Characterize the existing limitations in combination therapy; (2) Develop and introduce the Plan Builder (PB) to utilize existing literature for drug combination effectively; (3) Evaluate PB's potential in accelerating the development of HCCT plans. Our results demonstrate that researchers and experts using PB are able to create HCCT plans at much greater speed and quality compared to conventional methods. By releasing PB, we hope to enable more researchers to engage with HCCT planning and demonstrate its clinical efficacy.

Polydopamine Copolymers for Stable Drug Nanoprecipitation.

Polydopamine (PDA), a biomaterial inspired by marine mussels, has attracted interest in cancer nanomedicine due to its photothermal properties, nanoparticle coating, and pi-pi stacking-based drug encapsulation abilities. Despite numerous one-pot and post-polymerization modifications, PDA copolymers have not been sufficiently studied in the context of stabilizing hydrophobic drugs in the process of nanoprecipitation. In this study, we tested combinatorial panels of comonomers with PDA to optimize drug loading efficiency, particle size and stability of nano formulations made via drug nanoprecipitation. As a selection criterion for optimal comonomers, we used drug aggregation-induced emission (AIE). We identified 1,1,2-Trimethyl-3-(4-sulfobutyl)benz[e]indolium (In820) as a novel and highly useful comonomer for catecholamines and optimized the conditions for its incorporation into PDA copolymers used for drug nanoprecipitation. Surprisingly, it was superior to polyethylene glycol modifications in every aspect. The leading copolymer, poly(dopamine)-poly(L-dopa)-co-In820 (PDA-PDO-In820 1:1:1), was shown to be a good stabilizer for several hydrophobic drugs. The resulting nanoparticles showed stability for up to 15 days, high encapsulation efficiency of at least 80%, low toxicity, and high antitumor efficacy in vitro. Nanoprecipitation of hydrophobic drugs can be greatly enhanced by the use of PDA copolymers containing In820, which are easy-to-prepare and highly effective stabilizers.