PAMPA—critical factors for better predictions of absorption
Abstract
PAMPA, log P(OCT), and Caco-2 are useful tools in drug discovery for the prediction of oral absorption, brain penetration and for the development of structure-permeability relationships. Each approach has its advantages and limitations. Selection criteria for methods are based on many different factors: predictability, throughput, cost and personal preferences (people factor). The PAMPA concerns raised by Galinis-Luciani et al. (Galinis-Luciani et al., 2007, J Pharm Sci, this issue) are answered by experienced PAMPA practitioners, inventors and developers from diverse research organizations. Guidelines on how to use PAMPA are discussed. PAMPA and PAMPA-BBB have much better predictivity for oral absorption and brain penetration than log P(OCT) for real-world drug discovery compounds. PAMPA and Caco-2 have similar predictivity for passive oral absorption. However, it is not advisable to use PAMPA to predict absorption involving transporter-mediated processes, such as active uptake or efflux. Measurement of PAMPA is much more rapid and cost effective than Caco-2 and log P(OCT). PAMPA assay conditions are critical in order to generate high quality and relevant data, including permeation time, assay pH, stirring, use of cosolvents and selection of detection techniques. The success of using PAMPA in drug discovery depends on careful data interpretation, use of optimal assay conditions, implementation and integration strategies, and education of users.
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PAMPA is a robust, versatile method for predicting passive permeability of compounds through the gastrointestinal tract, the blood-brain barrier, and skin.
“PAMPA has become a robust, versatile method for predicting passive permeability of compounds through the gastrointestinal (GI) track, the BBB, and skin [37,38].”
From Polyphenol Microbial Metabolites Exhibit Gut and Blood–Brain Barrier Permeability and Protect Murine Microglia against LPS-Induced Inflammation (2019) · cites this paper as [37]
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- Authors
- Avdeef, A., Bendels, S., Di, L. I., Faller, B., Kansy, M., Sugano, K., & Yamauchi, Y.
- Affiliations
- F. Hoffmann-La Roche AG (CH)
- Wyeth (US)
- Novartis (Switzerland) (CH)
- Pfizer (Japan) (JP)
- Corresponding author
- Avdeef, Alex
- Venue
- Journal of Pharmaceutical Sciences
- Publisher
- Elsevier BV
- Published
- 2007-11
- Volume
- 96
- Issue
- 11
- Pages
- 2893-2909
- ISSN
- 0022-3549 (ISSN-L)
- OpenAlex
- W2168642149
- Cited by
- 240
- References
- 56
- Citations by year
- 2026: 8 · 2025: 13 · 2024: 12 · 2023: 6 · 2022: 11 · 2021: 12 · 2020: 10 · 2019: 13 · 2018: 9 · 2017: 13 · 2016: 19 · 2015: 14 · 2014: 11 · 2013: 19 · 2012: 16
- FWCI
- 11.07
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Journal of Pharmaceutical Sciences (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Life Sciences › Pharmacology, Toxicology and Pharmaceutics › Pharmaceutical Science › Drug Solubulity and Delivery Systems
- Health Sciences › Medicine › Oncology › Drug Transport and Resistance Mechanisms
- Physical Sciences › Computer Science › Computational Theory and Mathematics › Computational Drug Discovery Methods
- Keywords
- Pampas, Caco-2 cells, brain penetration, structure-permeability relationship, passive diffusion, assay conditions, cosolvents, drug discovery
- MeSH terms
- Pharmaceutical Preparations, Humans, Hydrogen-Ion Concentration, Intestinal Absorption, Jejunum, Membranes, Artificial, Pharmacokinetics, Structure-Activity Relationship, Caco-2 Cells
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