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Novel computational method for identification of Drug Candidates for Liposomal Reformulation

Goldblum Amiram, HUJI, School of Medicine - IMRIC, School of Pharmacy- Institute for Drug Research
Barenholz Yechezkel, HUJI, School of Medicine - IMRIC, Biochemistry and Molecular Biology
CERN Ahuva, HUJI, School of Medicine - IMRIC

Background

  • Most active pharmaceutical ingredients (APIs) are not suitable for “passive” loading into nano-liposomes. The desired concentration in the nano-liposomes is hard to achieve. Consequently, the therapeutic efficacy in humans is not sufficient.
  • Remote drug loading into nano-liposomes is in most cases the best method for achieving high concentrations of API per nano-liposome that enables therapeutically viable API-loaded nano-liposomes, referred to as nano-drugs.

Our innovation

The inventors constructed computational methods to identify APIs that can achieve the desired high concentrations in nano-liposomes by remote loading.

Advantages

  • Controlled drug release
  • Stable upon storage

Applications for use:

The technology entails modeling structural drug descriptors for loading and leakage properties of liposomal drugs for the rational identification of new liposomal drug candidates

This group of molecules, having diverse pharmacological activities, may be the basis for future liposomal drug development.

Contact for more information:

Mel Larrosa
VP Business Development Healthcare
+972-2-6586692