RT Journal Article
SR Electronic
T1 Computationally guided high-throughput design of self-assembling drug nanoparticles
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 786251
DO 10.1101/786251
A1 Daniel Reker
A1 Yulia Rybakova
A1 Ameya R. Kirtane
A1 Ruonan Cao
A1 Jee Won Yang
A1 Natsuda Navamajiti
A1 Apolonia Gardner
A1 Rosanna M. Zhang
A1 Tina Esfandiary
A1 Johanna L’Heureux
A1 Thomas von Erlach
A1 Elena M. Smekalova
A1 Dominique Leboeuf
A1 Kaitlyn Hess
A1 Aaron Lopes
A1 Jaimie Rogner
A1 Joy Collins
A1 Siddartha M. Tamang
A1 Keiko Ishida
A1 Paul Chamberlain
A1 DongSoo Yun
A1 Abigail Lytoon-Jean
A1 Christian K. Soule
A1 Jaime H. Cheah
A1 Alison M. Hayward
A1 Robert Langer
A1 Giovanni Traverso
YR 2019
UL http://biorxiv.org/content/early/2019/09/30/786251.abstract
AB Nanoformulations are transforming our capacity to effectively deliver and treat a myriad of conditions. However, many nanoformulation approaches still suffer from high production complexity and low drug loading. One potential solution relies on harnessing co-assembly of drugs and small molecular excipients to facilitate nanoparticle formation through solvent exchange without the need for chemical synthesis, generating nanoparticles with up to 95% drug loading. However, there is currently no understanding which of the millions of possible combinations of small molecules can result in the formation of these nanoparticles. Here we report the development of a high-throughput screening platform coupled to machine learning to enable the rapid evaluation of such nanoformulations. Our platform identified 101 novel self-assembling drug nanoparticles from 2.1 million pairings derived from 788 candidate drugs with one of 2686 excipients, spanning treatments for multiple diseases and often harnessing well-known food additives, vitamins, or approved drugs as carrier materials – with potential for accelerated approval and translation. Given their long-term stability and potential for clinical impact, we further characterize novel sorafenib-glycyrrhizin and terbinafine-taurocholic acid nanoparticles ex vivo and in vivo. We anticipate that this platform could accelerate the development of safer and more efficacious nanoformulations with high drug loadings for a wide range of therapeutics.