Food Effect on Oral Bioavailability: Old and New Questions

Effect of High-Fat Food on the Pharmacokinetic Profile and Safety of SAF-189s, an ALK/ROS1 Inhibitor, in Healthy Chinese Adults

BACKGROUND AND OBJECTIVES

This study was conducted to investigate the effect of high-fat meals on the pharmacokinetics (PK) and safety profile of SAF-189s, a novel ALK/ROS1 inhibitor.

METHODS

This was a single-center, phase I, open-label, crossover study in which healthy adults (≥18 years) were randomized (1:1) to two sequences of SAF-189s administration (fasted-fed or fed-fasted) separated by a 14-day washout. After a ≥10-h overnight fast, volunteers received SAF-189s 160 mg orally in a fasted state or 30 min after a high-fat, high-calorie meal. Similarity of pharmacokinetic parameters was concluded if the 90% CI for the geometric mean ratio (GMR) between the fed and fasted group fell within the predefined range of 0.80-1.25.

RESULTS

In total, 24 subjects were enrolled and 23 completed the study. SAF-189s maximum plasma concentration (Cmax; GMR: 109.1% [90% CI 103.1-115.4]) was comparable under fed (high-fat meal, n = 24) versus fasted (n = 23) conditions, with no effect on area under the plasma concentration-time curve from time 0 to t (AUC0-t; GMR: 105.1% [90% CI 100.3-110.2]) and AUC from time 0 to infinity (AUC0-∞; GMR: 105.5% [90% CI, 100.6-110.6]). In both groups, the median time to maximum plasma concentration (tmax) was around 6 h and mean plasma half-life (t½) was around 35 h. Fed administration led to a lower incidence of treatment-emergent adverse events (TEAEs; 29.2% vs 54.2%), including gastrointestinal disorders (4.2% vs 41.7%) and headache (0.0% vs 12.5%), versus fasted administration.

CONCLUSIONS

A high-fat meal had minimal effect on the pharmacokinetic profile of SAF-189s compared with a fasted state following a single dose of 160 mg. Administration with a high-fat meal led to a lower incidence of TEAEs.

Analysis of the interplay of physiological response to food intake and drug properties in food-drug interactions

The effect of food on oral drug absorption is determined by the complex interplay among gut physiological factors and drug properties. The currently used dissolution testing and classification systems (biopharmaceutics classification system, BCS or biopharmaceutics drug disposition classification system, BDDCS) do not account for dynamic changes in gastrointestinal physiology caused by food intake. This study aimed to identify key drug properties that influence food effect (FE) using supervised machine learning approaches. The analysis showed that drugs with high logP, dose number, and extraction ratio have a higher probability of positive FE, while drugs with low permeability and high efflux saturation index have a greater likelihood of negative FE. Weakly acidic drugs also showed a greater probability of positive FE, particularly at pKa >4.3. The importance of drug properties in predicting FE was ranked as logP, dose number, extraction ratio, pKa, and permeability. The accuracy of FE prediction using the models was compared with BCS and extended clearance classification system (ECCS). Overall, the likelihood or magnitude of FE depends on physiological changes to food intake such as altered bile acid secretion rate, intestinal metabolism, transport kinetics, and gastric emptying time, which should be considered along with drug properties (e.g., solubility, logP, and ionization) in predicting FE of orally administered drugs.

Evaluation of Potential Food Effects and Drug Interactions With Lansoprazole in Healthy Adult Volunteers Receiving Futibatinib

Futibatinib, an oral, irreversible fibroblast growth factor receptor (FGFR) 1-4 inhibitor, is being evaluated for FGFR-aberrant tumors. Two open-label phase 1 studies evaluated the effects of high-fat, high-calorie food and concomitant proton pump inhibitors (PPIs; lansoprazole) on single-dose futibatinib (20 mg) pharmacokinetics and safety in healthy adults. In the food effect study (N  =  17), subjects received futibatinib under fed and fasted conditions, separated by a 7-day washout. In the PPI study (N  =  20), subjects received futibatinib alone, underwent a 2-day washout, and then received lansoprazole 60 mg once daily for 5 days, with futibatinib also administered on day 5. Under fed versus fasted conditions, futibatinib bioavailability was 11.2% lower (area under the plasma concentration-time curve from time 0 to infinity geometric mean ratio 88.8%; 90% confidence interval, 79.8%-98.9%), and median time to maximum plasma concentration was significantly delayed (4.0 vs 1.5 hours; P < .0001). There were no significant differences in futibatinib exposure between futibatinib plus lansoprazole and futibatinib alone. No serious adverse events occurred in either study. These findings suggest that food and PPIs are unlikely to have clinically meaningful impacts on futibatinib bioavailability. Thus, futibatinib may be used with or without food and concomitantly with acid-reducing agents.

Evaluation of a Low-Fat Low-Calorie Meal on the Relative Bioavailability of Trametinib and Dabrafenib: Results From a Randomized, Open-Label, 2-Part Study in Healthy Participants

In this randomized, open-label, 2-part, 2 × 2 crossover, phase 1 study, the effect of a low-fat low-calorie (LFLC) meal on the relative bioavailability of a trametinib 2-mg tablet or dabrafenib 150-mg capsule was evaluated in healthy participants. Trametinib adjusted geometric mean ratios (90%CI) of fed : fasted for area under the concentration-time curve (AUC) from time 0 to the last quantifiable concentration and AUC from time 0 extrapolated to infinity were 0.76 (0.71-0.82) and 0.82 (0.77-0.88), respectively. For dabrafenib, the adjusted geometric mean ratios of AUC from time 0 to the last quantifiable concentration and AUC from time 0 extrapolated to infinity (90%CI) for fed:fasted were 0.85 (0.79-0.91) and 0.86 (0.80-0.92), respectively. Consumption of an LFLC meal delayed trametinib and dabrafenib absorption, with an increase in time to maximum concentration of ≈15 and ≈30 minutes, respectively, compared to the fasted state. These findings indicate that consumption of an LFLC meal reduced the bioavailability and delayed the absorption of trametinib and dabrafenib, supporting current recommendations to administer both drugs in the fasting state; however, an occasional LFLC meal is unlikely to affect the pharmacokinetics of the drugs once steady state is reached and, by consequence, not likely to alter the overall intended efficacy.

Phase 1 Studies to Evaluate the Food Effect and Relative Bioavailability of Tablet and Capsule Formulations of Belumosudil in Healthy Adult Subjects

Belumosudil is a selective Rho-associated coiled-coil containing protein kinase 2 inhibitor. A capsule formulation was used during early clinical development of belumosudil; it was later replaced by a tablet formulation, which mimicked the capsule's release properties and facilitated manufacturing scalability. To assess belumosudil's pharmacokinetics, including potential food effects, and evaluate the relative bioavailability of the 2 formulations, 2 phase 1 clinical trials were conducted. Administration of both belumosudil tablets and capsules with food increased exposure ≈2× as compared to the fasted state and delayed time to maximum concentration by 0.5 hour, indicating a decrease in the rate but increase in the extent of absorption with fed administration. Relative bioavailability was slightly higher when belumosudil was administered as tablets vs capsules, although the difference was not clinically meaningful. Safety and tolerability were generally consistent with the known safety profile of belumosudil. The results of these studies support administration of belumosudil with food.

The Effects of Feed Intake and Water Hardness on Fluralaner Pharmacokinetics in Layer Chickens

Background

Fluralaner is a novel drug belonging to the isoxazoline class that acts on external parasites of domestic animals. It is used systemically via drinking water, especially against red poultry mite in layer chickens. Fluralaner is frequently used in layers infected with D. gallinae. However, no study to date has investigated the effects of feed intake and water hardness.

Objectives

This study aimed to investigate the effects of variable water hardness and feed intake on the pharmacokinetic profile of fluralaner.

Methods

Layer chickens were divided into four groups (n = 8): fed + purified water (Group 1), feed restricted + purified water (Group 2), feed restricted + hard water (Group 3), and feed restricted + soft water (Group 4). After administering a single dose of the drug with drinking water, the blood samples were collected for 21 days. Fluralaner concentrations in plasma samples were determined by liquid chromatography/tandem mass spectrometry. The maximum plasma concentration (C_max), time to reach maximum plasma concentration (t_max), area under the concentration–time curve values (AUC_0-21d), half-life (t_1/2), and other pharmacokinetic parameters were calculated.

Results

Although the highest maximum plasma concentration (C_max) was determined in Group 1 (fed + purified water), no statistically significant difference was found in the C_max, t_max, t_1/2, MRT_{0-inf_obs}, Vz/F_obs, and Cl/F_{_obs} parameters between the experimental groups.

Conclusions

It was concluded that the feed intake or water hardness did not change the pharmacokinetic profile of fluralaner in layer chickens. Therefore, fluralaner could be used before or after feeding with the varying water hardness in poultry industry.

Machine learning methods for prediction of food effects on bioavailability: A comparison of support vector machines and artificial neural networks

Despite countless advances in recent decades across various in vitro, in vivo and in silico tools, anticipation of whether a drug will show a human food effect (FE) remains challenging. One means to predict potential FE involves probing any dependence between FE and drug properties. Accordingly, this study explored the potential for two machine learning (ML) algorithms to predict likely FE. Using a collated database of drugs licensed from 2016-2020, drugs were classified into three groups; positive, negative or no FE. Greater than 250 drug properties were predicted for each drug which were used to train predictive models using Support Vector Machine (SVM) and Artificial Neural Network (ANN) algorithms. When compared, ANN outperformed SVM for FE classification upon training (82%, 72%) and testing (72%, 69%). Both models demonstrated higher FE prediction accuracy than the Biopharmaceutics Classification System (BCS) (46%). This exploratory work provided new insights into the connection between FE and drug properties as the Octanol Water Partition Coefficient (S+logP), Number of Hydrogen Bond Donors (HBD), Topological Polar Surface Area (T_PSA) and Dose (mg) were all significant for prediction. Overall, this study demonstrated the utility of ML to facilitate early anticipation of likely FE in pre-clinical development using four well-known drug properties.

The influence of feeding and gastroprotectant medications on the Factor Xa inhibitory activity of orally administered rivaroxaban in normal dogs

OBJECTIVE

Rivaroxaban is a new anticoagulant option for dogs, yet its reported oral bioavailability is as low as 60%. The objective of this study was to examine the influence of feeding and gastroprotectant medications on the bioactivity (anti-Xa activity) of rivaroxaban in healthy dogs.

DESIGN

Prospective experimental study.

SETTING

University research laboratory.

ANIMALS

Five healthy neutered male purpose-bred Beagles.

INTERVENTIONS

Dogs were administered a median dose of 1.8 mg/kg rivaroxaban (range, 1.6-1.8 mg/kg) orally once daily for 2 consecutive days with either (1) no food, (2) food, (3) sucralfate 30 minutes before rivaroxaban, or (4) omeprazole at the same time as rivaroxaban. Blood was collected from preplaced jugular catheters immediately before and at 6 time points after rivaroxaban administration (2, 4, 8, 24, 36, and 48 hours). A rivaroxaban calibrated anti-Xa activity assay (RIVA) was used to monitor anticoagulant effect.

MEASUREMENTS AND MAIN RESULTS

Rivaroxaban administration resulted in significant increases in RIVA (P = 0.02), with peak activities occurring 2 to 4 hours after dosingduring each study arm. No feeding was associated with significantly higher RIVA at the 36-hour time point compared to all other treatment arms (P < 0.0001), and feeding resulted in high RIVA at the 48-hour time point compared with sucralfate administration (P = 0.003). No significant changes in RIVA were otherwise identified with respect to feeding or gastroprotectant administration (P = 0.2).

CONCLUSIONS AND CLINICAL IMPORTANCE

Although administration without food demonstrated an apparent increase in RIVA 36 hours after drug administration, clinically relevant differences among treatment groups were not identified in combined analyses of time points. Based on these results, dogs treated with rivaroxaban do not require special modification of feeding practices or gastroprotectant drug administration.

Effect of Food on the Pharmacokinetics of Quizartinib

Quizartinib is an oral, highly potent, and selective type II FMS‐like tyrosine kinase 3 inhibitor in development for acute myeloid leukemia. This parallel‐group study evaluated potential food effects on quizartinib absorption in healthy subjects who received a single 30‐mg dose after overnight fasting (n = 34) or a high‐fat, high‐calorie meal (n = 30). Blood samples were collected through 504 hours after dosing, and pharmacokinetic parameters calculated were maximum observed concentration (C_max) and area under plasma concentration–time curve from time 0 to last quantifiable concentration (AUC_last) and from time 0 to infinity (AUC_inf). Mean quizartinib pharmacokinetic profiles were similar under fasted and fed conditions. The geometric least squares means ratios (%) for fed/fasted and associated 90% confidence intervals (CIs) for C_max, AUC_last, and AUC_inf were 91.58 (82.15‐102.08), 105.39 (90.79‐122.35), and 108.39 (91.54‐128.34), respectively. The 90%CI for the ratio fell within the 80% to 125% limits for C_max and AUC_last, with 90%CI for AUC_inf slightly outside the limits (ie, 128%). Food delayed quizartinib time to C_max by 2 hours. All adverse events were either mild or moderate; no discontinuations due to adverse events occurred. Based on these results, quizartinib can be administered without regard to food.

Food for thought: formulating away the food effect - a PEARRL review

OBJECTIVES

Co-ingestion of oral dosage forms with meals can cause substantial changes in bioavailability relative to the fasted state. Food-mediated effects on bioavailability can have significant consequences in drug development, regulatory and clinical settings. To date, the primary focus of research has focused on the ability to mechanistically understand the causes and predict the occurrence of these effects.

KEY FINDINGS

The current review describes the mechanisms underpinning the occurrence of food effects, sheds new insights on the relative frequency for newly licensed medicines and describes the various methods by which they can be overcome. Analysis of oral medicines licensed by either the EMA or FDA since 2010 revealed that over 40% display significant food effects. Due to altered bioavailability, these medicines are often required to be dosed, rather restrictively, in either the fed or the fasted state, which can hinder clinical usefulness.

SUMMARY

There are clinical and commercial advantages to predicting the presence of food effects early in the drug development process, in order to mitigate this risk of variable food effect bioavailability. Formulation approaches aimed at reducing variable food-dependent bioavailability, through the use of bio-enabling formulations, are an essential tool in addressing this challenge and the latest state of the art in this field are summarised here.