Analysis on Parallel Artificial Membrane Permeation Assay


Posted August 15, 2020 by Bonnibelle

The Parallel Artificial Membrane Permeation Assay (PAMPA) is a non-cell based assay designed to predict passive, trans- cellular permeability of drugs in early drug discovery.

 
The Parallel Artificial Membrane Permeation Assay (PAMPA) is a non-cell based assay designed to predict passive, trans- cellular permeability of drugs in early drug discovery. In this assay, we will discuss the major concerns related to PAMPA.

PAMPA analysis measures the permeability of artificial membranes that provides an in vitro model of passive diffusion. Passive diffusion is an important factor that determines transport through the gastrointestinal tract, penetration of the blood-brain barrier, and transport across cell membranes. Permeability may also be affected by several other mechanisms, including paracellular transport and active uptake or efflux not evaluated in PAMPA. Therefore, PAMPA can provide a simplified permeability method by measuring a single mechanism which avoids the complexity of active transport/outflow and enables compounds to be ordered by a single permeability.

Generally, PAMPA is used as the main permeability barrier, in which a simple measurement of passive diffusion is required. However, separation using PAMPA may misunderstand the true understanding of permeability in vivo. Cell-based analysis (e.g. Caco-2) evaluates permeability through passive diffusion across cells and active and paracellular transport. Therefore, Caco-2 permeability screen can provide more detailed mechanical information.

What is the relationship between Caco-2 and PAMPA?
PAMPA measures permeability only by passive diffusion, while the Caco-2 permeability assay also evaluates active uptake/efflux and paracellular transport. Therefore, if the compound only passes through the membrane by passive diffusion, a good correlation is observed between the Caco-2 permeability measurement and PAMPA. If the compound is an active substrate, PAMPA will overestimate the permeability, if the compound undergoes active uptake or paracellular absorption, PAMPA will underestimate the permeability. The relationship between Caco-2 permeability and PAMPA permeability can be used to diagnose the penetration mechanism.

The penetration of these compounds is dominated by passive diffusion, unrelated compounds are divided into two subsets. A subset has a higher PAMPA permeability than the cell monolayer permeability and is composed of compounds affected by secretion mechanisms: efflux of alkali or reduced passive diffusion under Caco-2 when operating under a pH gradient. The cell monolayer permeability of the other subset is higher than that of PAMPA, and consists of compounds with an absorption mechanism: when running under a pH gradient, the absorption of acid under the Caco-2 is increased by the paracellular uptake, active transport or passive diffusion. In view of the characteristics of these two methods, these studies show how to synergistically apply PAMPA and Caco-2 to the rapid and effective study of the penetration mechanism in drug discovery.

In the early discovery process, PAMPA can be used to quickly screen all compounds at low and neutral pH to evaluate passive diffusion permeability to indicate the potential of gastrointestinal tract and cells to measure penetration. In the middle of the discovery process, selected compounds can also be analyzed by Caco-2, which goes to the outside of the basal. This result, combined with PAMPA data, shows sensitivity to other penetration mechanisms (secretion and absorption). During the mid- to late-stage discovery, selected candidates can be examined in detail through multiple targeted Caco-2 experiments and transporter inhibitors to fully characterize the penetration mechanism. All compounds can be quickly screened using PAMPA at low and neutral pH to assess passive diffusion permeability to indicate the potential of the gastrointestinal tract and cells to measure penetration.
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Issued By https://dda.creative-bioarray.com/
Country United States
Categories Biotech
Last Updated August 15, 2020