A major problem in drug discovery is the need to predict candidates with optimal disposition properties in animals. Good oral absorption is often a key property, and the Caco-2 intestinal cell model, routinely used for predicting human oral availability of drugs, has disadvantages. These include the need for cell culture and sterile conditions, use of radiolabel or other sensitive compound-specific detection method, and lack of adaptability to large scale screening of compounds. A cell-free model, PAMPA (Parallel Artificial Membrane Permeation Assay), has certain advantages, but does not utilize a true membrane bilayer, is slow, and is limited to compounds with UV or fluorescence absorption properties. We propose to develop a novel method, the """"""""Fluorosome(TM) Technique"""""""" that can measure drug permeability through membrane bilayer vesicles and drug:membrane partition coefficients. This in vitro, cell-free method is rapid and inexpensive, and is applicable to a wide range of molecules. It requires only micromolar concentrations, employs no animals or living cells, does not require sterile conditions, and uses no radiolabel. It is adaptable to robotics and complementary to other tools used in the early screening of drugs. During phase I we will improve assay conditions and demonstrate the validity of the Fluorosome(TM) Technique to measure drug permeabilities and partition coefficients. We will compare the results of the Fluorosome(TM) Technique with published results for the Caco-2 and PAMPA models for a set of 15 drugs with known human oral absorption values. Additionally, we will examine a set of 36 synthetic antibiotic candidate compounds using the Fluorosome(TM) Technique and the Caco-2 model to measure permeabilities and compare each methods ability to predict oral absorption. Adaptation of this technique to high-throughput screening of drug molecules will be accomplished in phase II.
We propose the commercial development of a cell-free method for rapidly and accurately determining drug permeabilities and partition coefficients. This technique will be of significant interest to pharmaceutical companies for the early screening of drug candidates and drug delivery vehicles.
