A quantitative approach to probe the dependence and correlation of food-effect with aqueous solubility, dose/solubility ratio, and partition coefficient (LogP) for orally active drugs administered as immediate-release formulations

Singh, Brahma N.

doi:10.1002/ddr.20008

Cited by 62 publications

(32 citation statements)

References 153 publications

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“…0 -2 range. This theoretical finding is in good agreement with the physicochemical property -food effect relationship in [65] [66].…”

Section: General Absorption Equationsupporting

confidence: 90%

Computational Oral Absorption Simulation for Low‐Solubility Compounds

Sugano

2009

Chemistry & Biodiversity

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Bile micelles play an important role in oral absorption of low-solubility compounds. Bile micelles can affect solubility, dissolution rate, and permeability. For the pH-solubility profile in bile micelles, the Henderson-Hasselbalch equation should be modified to take bile-micelle partition into account. For the dissolution rate, in the Nernst-Brunner equation, the effective diffusion coefficient in bile-micelle media should be used instead of the monomer diffusion coefficient. The diffusion coefficient of bile micelles is 8- to 18-fold smaller than that of monomer molecules. For permeability, the effective diffusion coefficient in the unstirred water layer adjacent to the epithelial membrane, and the free fraction at the epithelial membrane surface should be taken into account. The importance of these aspects is demonstrated here using several in vivo and clinical oral-absorption data of low-solubility model compounds. Using the theoretical equations, the food effect on oral absorption is further discussed.

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“…0 -2 range. This theoretical finding is in good agreement with the physicochemical property -food effect relationship in [65] [66].…”

Section: General Absorption Equationsupporting

confidence: 90%

Computational Oral Absorption Simulation for Low‐Solubility Compounds

Sugano

2009

Chemistry & Biodiversity

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“…Singh compared whether aqueous solubility, dose/solubility ratio and Log P could be correlated to human fed/fasted AUC through the analysis of over 100 structurally diverse compounds (12). Aqueous solubility and lipophilicity played a "predominant role" in anticipating human food effect.…”

Section: In Silico Methods For Predicting Food Effectmentioning

confidence: 99%

Current Methods for Predicting Human Food Effect

Lentz

2008

AAPS J

145

106

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Abstract. Food can impact the pharmacokinetics of a drug product through several mechanisms, including but not limited to, enhancement in drug solubility, changes in GI physiology, or direct interaction with the drug. Significant food effects complicate development of new drugs, especially when clinical plans require control and/or monitoring of food intake in relation to dosing. The prediction of whether a drug or drug product will show a human food effect is challenging. In vitro models which consider physical-chemical properties can classify the potential for a compound to demonstrate a positive, negative or no food effect, and may be appropriate for screening compounds at early stages of drug discovery. When comparing various formulations, dissolution tests in biorelevant media can serve as a predictor of human drug performance under fasted and fed conditions. Few in vivo models exist which predict the magnitude of change in pharmacokinetic parameters in humans when dosing in the presence of food, with the dog appearing to be the most studied species for this purpose. Control of gastric pH, as well as the amount and composition of the fed state in dogs are critical parameters to improving the predictability of the dog overall as a food effect model. No single universal model is applicable for all drugs at all stages of drug development. One or more models may be required depending whether the goal is to assess potential for a food effect, determine the magnitude of change in pharmacokinetic parameters in the fed/fasted state, or whether formulation efforts have the ability to mitigate an observed food effect.

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“…F o o d c a n i n fl u e n c e t h e r a t e o f absorption (through altered Cmax and Tmax) and extent of absorption (AUC). As AUC is the most commonly used PK parameter of overall FE (7,8,14), and the fact that food induced changes to the rate of absorption may not reflect a change in extent of absorption (2,24), AUC is used as the primary parameter in this article.…”

Section: Reporting Of Clinical Food-effect Resultsmentioning

confidence: 99%

“…5) is similar to the correlation reported by Singh (8) when statistically analyzing the physicochemical properties of 100 oral administered compounds. In that study, compounds with Log P>2 were spread across a wide range of human FE AUC ratio from 0.5 to about 5 (8). Compounds with a Log P≥3 were more likely to benefit from increased bioavailability with food.…”

Section: Case Studies On Fe Mechanismsmentioning

confidence: 89%

“…The experimental approaches can broadly be classified as statistical or mechanistic in nature. Statistical approaches examine a large number of compounds to provide a qualitative assessment of the risk and recommend threshold physicochemical parameters that influence the correlation (6)(7)(8). They pull-out trends in large data sets, but don't provide information on the mechanism behind the rate-limiting steps for a compound of interest.…”

Section: Introductionmentioning

confidence: 99%

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Food Effect in Humans: Predicting the Risk Through In Vitro Dissolution and In Vivo Pharmacokinetic Models

Mathias

Yang

Vig

et al. 2015

AAPS J

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Abstract. In vitro and in vivo experimental models are frequently used to assess a new chemical entity's (NCE) biopharmaceutical performance risk for food effect (FE) in humans. Their ability to predict human FE hinges on replicating key features of clinical FE studies and building an in vitro-in vivo relationship (IVIVR). In this study, 22 compounds that span a wide range of physicochemical properties, Biopharmaceutics Classification System (BCS) classes, and food sensitivity were evaluated for biorelevant dissolution in fasted-and fed-state intestinal media and the dog fed/fasted-state pharmacokinetic model. Using the area under the curve (AUC) as a performance measure, the ratio of the fed-to-fasted AUC (FE ratio) was used to correlate each experimental model to FE ratio in humans. A linear correlation was observed for the in vitro dissolution-human IVIVR (R 2 =0.66, % mean square error 20.7%). Similarly, the dog FE ratio correlated linearly with the FE ratio in humans (R 2 =0.74, % mean square error 16.25%) for 15 compounds. Data points near the correlation line indicate dissolution-driven mechanism for food effect, while deviations from the correlation line shed light on unique mechanisms that can come into play such as GI physiology or unusual physicochemical properties. In summary, fed/fasted dissolution studies and dog PK studies show a reasonable correlation to human FE, hence are useful tools to flag high-risk NCEs entering clinical development. Combining kinetic dissolution, dog FE model and in silico modeling one can study FE mechanism and formulation strategies to mitigate the FE risk.KEY WORDS: biorelevant dissolution; dog food effect model; food effect; in vitro-in vivo relationship.

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A quantitative approach to probe the dependence and correlation of food-effect with aqueous solubility, dose/solubility ratio, and partition coefficient (LogP) for orally active drugs administered as immediate-release formulations

Cited by 62 publications

References 153 publications

Computational Oral Absorption Simulation for Low‐Solubility Compounds

Computational Oral Absorption Simulation for Low‐Solubility Compounds

Current Methods for Predicting Human Food Effect

Food Effect in Humans: Predicting the Risk Through In Vitro Dissolution and In Vivo Pharmacokinetic Models

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