Automated discovery of nanomaterials via drug aggregation induced emission

• Published in: Biomaterials Vol. 289; p. 121800
• Main Authors: Harris, Yuval, Sason, Hagit, Niezni, Danna, Shamay, Yosi
• Format: Journal Article
• Language: English
• Published: Elsevier Ltd 01.10.2022
• Subjects: Aggregation induced emission; Automated discovery; Drug delivery; KRAS; Nanomedicine; KRAS; Drug delivery; Aggregation induced emission; Automated discovery; Nanomedicine
• ISSN: 0142-9612; 1878-5905
• DOI: 10.1016/j.biomaterials.2022.121800

Nanoformulations of small molecule drugs are essential to effectively deliver them and treat a wide range of diseases. They are normally complex to develop, lack predictability, and exhibit low drug loading. Recently, nanoparticles made via co-assembly of hydrophobic drugs and organic dyes, exhibited drug-loading of up to 90% with high predictability from the drug structure. However, these particles have relatively short stability and can formulate only a small fraction of the drug space. Here, we developed an automated workflow to synthesize and select novel dye stabilizers, based on their ability to inhibit drug aggregation-induced emission (AIE). We first screened and identified 10 drugs with previously unknown strong AIE activity and exploited this trait to automatically synthesize and select a new ultra-stabilizer named R595. Interestingly, it shares several synthetic similarities and advantages with polydopamine. We found that R595 is superior to myriad types of excipients and solubilizers such as cyclodextrins, poloxamers, albumin, and previously published organic dyes, in both long-term stability and drug compatibility. We investigated the biodistribution, pharmacokinetics, safety and efficacy of the AIEgenic MEK inhibitor trametinib-R595 nanoparticles in vitro and in vivo and demonstrated that they are non-toxic and effective in KRAS driven colon and lung cancer models. [Display omitted]