Predicting effect of food on extent of drug absorption based on physicochemical properties

Playing Hide-and-Seek with Tyrosine Kinase Inhibitors: Can We Overcome Administration Challenges?

Tyrosine kinase inhibitors (TKIs) have demonstrated significant efficacy against various types of cancers through molecular targeting mechanisms. Over the past 22 years, more than 100 TKIs have been approved for the treatment of various types of cancer indicating the significant progress achieved in this research area. Despite having significant efficacy and ability to target multiple pathways, TKIs administration is associated with challenges. There are reported inconsistencies between observed food effect and labeling administration, challenges of concomitant administration with acid-reducing agents (ARA), pill burden and dosing frequency. In this context, the objective of present review is to visit administration challenges of TKIs and effective ways to tackle them. We have gathered data of 94 TKIs approved in between 2000 and 2022 with respect to food effect, ARA impact, administration schemes (food and PPI restrictions), number of pills per day and administration frequency. Further, trend analysis has been performed to identify inconsistencies in the labeling with respect to observed food effect, molecules exhibiting ARA impact, in order to identify solutions to remove these restrictions through novel formulation approaches. Additionally, opportunities to reduce number of pills per day and dosing frequency for better patient compliance were suggested using innovative formulation interventions. Finally, utility of physiologically based pharmacokinetic modeling (PBPK) for rationale formulation development was discussed with literature reported examples. Overall, this review can act as a ready-to-use-guide for the formulation, biopharmaceutics scientists and medical oncologists to identify opportunities for innovation for TKIs.

Evaluating Utilization of Tiny-TIM to Assess the Effect of Food on the Absorptions of Oral Drugs and Its Application on Biopharmaceutical Modeling

Safety and efficacy are the most critical factors for the development of modern medications. For oral drugs, evaluating drug exposure under various conditions is one of the most important outcomes for clinical trials. These data will help to better understand the safety and efficacy of new drugs. Studies involving potential drug-drug interactions, proton pump inhibitors, and intake of food are often conducted to assess the above. Among the above, the influence of food on exposure to the drug is one of the key data sets for regulatory submission. Since food may have either a positive or negative effect on drug exposure, it is important to obtain an early assessment of the food effect. To better forecast and plan for clinical studies, substantial efforts have been made in the industry to develop modeling and in-vitro and in-vivo assays. Despite the efforts, predicting the effect of food on exposure without integrating the dynamic of the gastrointestinal tract in the assessment remains challenging. In this study, we evaluated the utilization of the dynamic Gastro-Intestinal Model (Tiny-TIM) for the food effect of over 20 drugs/formulations in development or on the market that covers all BCS classes. In general, the Tiny-TIM predicted food effects were in good agreement with the reported data in humans. This suggests that Tiny-TIM can successfully capture the impact of physicochemical properties on absorption under the influence of food.

Bridging population pharmacokinetic and semimechanistic absorption modeling of APX3330

APX3330 ((2E)-2-[(4,5-dimethoxy-2-methyl-3,6-dioxo-1,4-cyclohexadien-1-yl)methylene]-undecanoic acid), a selective inhibitor of APE1/Ref-1, has been investigated in treatment of hepatitis, cancer, diabetic retinopathy, and macular edema. APX3330 is administered orally as a quinone but is rapidly converted to the hydroquinone form. This study describes the pharmacokinetics of APX3330 and explores effect of food on absorption. Total plasma quinone concentrations of APX3330 were obtained following oral administration from studies in healthy Japanese male subjects (single dose-escalation; multiple-dose; food-effect) and patients with cancer patients. Nonlinear mixed effects modeling was performed using Monolix to estimate pharmacokinetic parameters and assess covariate effects. To further evaluate the effect of food on absorption, a semi-physiologic pharmacokinetic model was developed in Gastroplus to delineate effects of food on dissolution and absorption. A two-compartment, first order absorption model with lag time best described plasma concentration-time profiles from 49 healthy Japanese males. Weight was positively correlated with apparent clearance (CL/F) and volume. Administration with food led to an 80% higher lag time. CL/F was 41% higher in the cancer population. The semi-physiologic model indicates a switch from dissolution-rate control of absorption in the fasted-state to gastric emptying rate determining absorption rate in the fed-state. Oral clearance of APX3330 is higher in patients with cancer than healthy Japanese males, possibly due to reduced serum albumin in patients with cancer. Delayed APX3330 absorption with food may be related to higher conversion to the more soluble but less permeable hydroquinone form in the gastrointestinal tract. Future work should address pharmacokinetic differences between APX3330 quinone and hydroquinone forms.

Comparative Impact of Various Fasting Periods on the Welfare of Sprague-Dawley Rats With or Without Supplementation

In nonclinical toxicology studies, lab animals are fasted typically overnight, to reduce variability in some clinical pathology parameters. However, fasting adds undue stress, and this is particularly concerning in rodents given their fast metabolic rates. Furthermore, as rodents are nocturnal animals, an overnight fasting may cause a protracted negative metabolic state even when the fasting has technically ended, given their minimal activity and food consumption during the day. Therefore, to evaluate the impacts of different fasting durations (±DietGel supplementation) on rats' welfare, we assessed the traditional and ancillary clinical pathology parameters in Sprague-Dawley rats, along with body weight, organ weight, and histopathology. Although most endpoints were comparable between the different fasting durations (±DietGel supplementation), the long fasting times (≥8 hr) without DietGel supplementation caused significant decreases in body weight, liver weight, liver glycogen content, serum glucose, triglyceride, and creatinine concentrations-all findings suggestive of a negative energy balance that could impact animal welfare and consequently, data quality; while the short fasting time (4 hr) and DietGel supplementation were associated with higher triglycerides variability. Hence, we propose that short fasting time should be adequate for most toxicology studies in rats, and long fasting times should only be accommodated with scientific justification.

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.

Exploratory Food Effect Assessment in Patients in Early Clinical Development of Oncology Drugs

Instructions for administration with regard to food are a key aspect of how patients experience oral drugs. Through potential effects on pharmacokinetics, the food condition can influence safety and efficacy, and thereby is one of many dimensions of dose optimization. Regulatory guidance from major health authorities advocates for the early investigation of food effect (FE) in clinical development. In oncology, exploratory FE (eFE) evaluation is often incorporated into the first-in-human (FIH) studies in patients to inform food condition of later clinical studies. However, the design aspects of such exploratory assessments are generally under-reported and barely described, and yet complex, due to uniqueness of FIH study design and drug development process in oncology. Herein, we review literature of eFE assessment study design in oncology in patients, and present the Novartis experience in the design, execution, and impact of eFE in FIH oncology studies from 2014 to 2021. Based on this, we propose a roadmap for eFE assessment in early clinical drug development for oncology drugs in patients, including a framework for common study design options with a focus on study- and patient-level timing for typical scenarios. We also provide a broad spectrum of decision-making factors which should be evaluated to drive the design and implementation of eFE assessment, spanning from clinical development strategy, FIH study design, to compound-specific features.

Reduced Fasting Duration in Cynomolgus Monkeys Enhances Animal Welfare During Toxicology Studies

During toxicology studies, fasting animals prior to clinical pathology blood collection is believed to reduce variability in some clinical chemistry analytes. However, fasting adds stress to animals that are already stressed from the administration of potentially toxic doses of the test article. The purpose of this study was to assess the impacts of different fasting durations on cynomolgus monkeys' welfare during toxicology studies. To this end, we assessed the cynomolgus monkeys traditional and ancillary clinical pathology endpoints at different fasting times. We showed that most clinical pathology endpoints were largely comparable between different fasting times suggesting that cynomolgus monkeys could be fasted for as little as 4 hours for toxicology studies, as longer fasting times (up to 20 hours) resulted in stress, dehydration, and significant decreases in blood glucose- changes that impacts animal welfare. Shorter fasting times were associated with higher triglycerides variability among individual animals. Therefore, we propose that shorter fasting time (i.e., 4 hours) should be adequate for most toxicology studies except when: (1) parameters that could be affected by non-fasting conditions are important for safety and pharmacodynamic assessments (i.e., glucose and lipids) and (2) fasting would be needed for the bioavailability of an orally administered test article.

Development and Validation of an Explainable Machine Learning-Based Prediction Model for Drug-Food Interactions from Chemical Structures

Possible drug-food constituent interactions (DFIs) could change the intended efficiency of particular therapeutics in medical practice. The increasing number of multiple-drug prescriptions leads to the rise of drug-drug interactions (DDIs) and DFIs. These adverse interactions lead to other implications, e.g., the decline in medicament's effect, the withdrawals of various medications, and harmful impacts on the patients' health. However, the importance of DFIs remains underestimated, as the number of studies on these topics is constrained. Recently, scientists have applied artificial intelligence-based models to study DFIs. However, there were still some limitations in data mining, input, and detailed annotations. This study proposed a novel prediction model to address the limitations of previous studies. In detail, we extracted 70,477 food compounds from the FooDB database and 13,580 drugs from the DrugBank database. We extracted 3780 features from each drug-food compound pair. The optimal model was eXtreme Gradient Boosting (XGBoost). We also validated the performance of our model on one external test set from a previous study which contained 1922 DFIs. Finally, we applied our model to recommend whether a drug should or should not be taken with some food compounds based on their interactions. The model can provide highly accurate and clinically relevant recommendations, especially for DFIs that may cause severe adverse events and even death. Our proposed model can contribute to developing more robust predictive models to help patients, under the supervision and consultants of physicians, avoid DFI adverse effects in combining drugs and foods for therapy.

Current State and Challenges of Physiologically Based Biopharmaceutics Modeling (PBBM) in Oral Drug Product Development

Physiologically based biopharmaceutics modeling (PBBM) emphasizes the integration of physicochemical properties of drug substance and formulation characteristics with system physiological parameters to predict the absorption and pharmacokinetics (PK) of a drug product. PBBM has been successfully utilized in drug development from discovery to postapproval stages and covers a variety of applications. The use of PBBM facilitates drug development and can reduce the number of preclinical and clinical studies. In this review, we summarized the major applications of PBBM, which are classified into six categories: formulation selection and development, biopredictive dissolution method development, biopharmaceutics risk assessment, clinically relevant specification settings, food effect evaluation and pH-dependent drug-drug-interaction risk assessment. The current state of PBBM applications is illustrated with examples from published studies for each category of application. Despite the variety of PBBM applications, there are still many hurdles limiting the use of PBBM in drug development, that are associated with the complexity of gastrointestinal and human physiology, the knowledge gap between the in vitro and the in vivo behavior of drug products, the limitations of model interfaces, and the lack of agreed model validation criteria, among other issues. The challenges and essential considerations related to the use of PBBM are discussed in a question-based format along with the scientific thinking on future research directions. We hope this review can foster open discussions between the pharmaceutical industry and regulatory agencies and encourage collaborative research to fill the gaps, with the ultimate goal to maximize the applications of PBBM in oral drug product development.

Prediction of Oral Drug Absorption in Rats from In Vitro Data

PURPOSE

In drug discovery, rats are widely used for pharmacological and toxicological studies. We previously reported that a mechanism-based oral absorption model, the gastrointestinal unified theoretical framework (GUT framework), can appropriately predict the fraction of a dose absorbed (Fa) in humans and dogs. However, there are large species differences between humans and rats. The purpose of the present study was to evaluate the predictability of the GUT framework for rat Fa.

METHOD

The Fa values of 20 model drugs (a total of 39 Fa data) were predicted in a bottom-up manner. Based on the literature survey, the bile acid concentration (C_bile) and the intestinal fluid volume were set to 15 mM and 4 mL/kg, respectively, five and two times higher than in humans. LogP, pK_a, molecular weight, intrinsic solubility, bile micelle partition coefficients, and Caco-2 permeability were used as input data.

RESULTS

The Fa values were appropriately predicted for highly soluble drugs (absolute average fold error (AAFE) = 1.65, 18 Fa data) and poorly soluble drugs (AAFE = 1.57, 21 Fa data). When the species difference in C_bile was ignored, Fa was over- and under-predicted for permeability and solubility limited cases, respectively. High C_bile in rats reduces the free fraction of drug molecules available for epithelial membrane permeation while increasing the solubility of poorly soluble drugs.

CONCLUSION

The Fa values in rats were appropriately predicted by the GUT framework. This result would be of great help for a better understanding of species differences and model-informed preclinical formulation development.

Food effects on gastrointestinal physiology and drug absorption

Food ingestion affects the oral absorption of many drugs in humans. In this review article, we summarize the physiological factors in the gastrointestinal (GI) tract that affect the in vivo performance of orally administered solid dosage forms in fasted and fed states in humans. In particular, we discuss the effects of food ingestion on fluid characteristics (pH, bile concentration, and volume) in the stomach and small intestine, GI transit of water and dosage forms, and microbiota. Additionally, case examples of food effects on GI physiology and subsequent changes in oral drug absorption are provided. Furthermore, the effects of food, especially fruit juices (e.g., grapefruit, orange, apple) and green tea, on transporter-mediated permeation and enzyme-catalyzed metabolism of drugs in intestinal epithelial cells are also summarized comprehensively.

Applications of bio-predictive dissolution tools for the development of solid oral dosage forms: Current industry experience

Development and optimization of orally administered drug products often require bio-predictive tools to help with informing formulation and manufacturing decisions. Reliable bio-predictive dissolution toolkits not only allow rational development of target formulations without having to conduct excessive in vivo studies but also help in detecting critical material attributes (CMAs), critical formulation variables (CFVs), or critical process parameters (CPPs) that could impact a drug's in vivo performance. To provide early insights for scientists on the development of a bio-predictive method for drug product development, this review summarizes current phase-appropriate bio-predictive dissolution approaches applicable to address typical concerns on solubility-limited absorption, food effect, achlorhydria, development of extended-release formulation, clinically relevant specification, and biowaiver. The selection of an in vitro method which can capture the key rate-limiting step(s) of the in vivo dissolution and/or absorption is considered to have a better chance to produce a meaningful in vitro-in vivo correlation (IVIVC) or in vitro-in vivo relationship (IVIVR).

Machine learning predicts the effect of food on orally administered medicines

Food-mediated changes to drug absorption, termed the food effect, are hard to predict and can have significant implications for the safety and efficacy of oral drug products in patients. Mimicking the prandial states of the human gastrointestinal tract in preclinical studies is challenging, poorly predictive and can produce difficult to interpret datasets. Machine learning (ML) has emerged from the computer science field and shows promise in interpreting complex datasets present in the pharmaceutical field. A ML-based approach aimed to predict the food effect based on an extensive dataset of over 311 drugs with more than 20 drug physicochemical properties, referred to as features. Machine learning techniques were tested; including logistic regression, support vector machine, k-Nearest neighbours and random forest. First a standard ML pipeline using a 80:20 split for training and testing was tried to predict no food effect, negative food effect and positive food effect, however this lead to specificities of less than 40%. To overcome this, a strategic ML pipeline was devised and three tasks were developed. Random forest achieved the strongest performance overall. High accuracies and sensitivities of 70%, 80% and 70% and specificities of 71%, 76% and 71% were achieved for classifying; (i) no food effect vs food effect, (ii) negative food vs positive food effect and (iii) no food effect vs negative food effect vs positive food effect, respectively. Feature importance using random forest ranked the features by importance for building the predictive tasks. The calculated dose number was the most important feature. Here, ML has provided an effective screening tool for predicting the food effect, with the potential to select lead compounds with no food effect, reduce the number of animal studies, and accelerate oral drug development studies.

Interactions between Food and Drugs, and Nutritional Status in Renal Patients: A Narrative Review

Drugs and food interact mutually: drugs may affect the nutritional status of the body, acting on senses, appetite, resting energy expenditure, and food intake; conversely, food or one of its components may affect bioavailability and half-life, circulating plasma concentrations of drugs resulting in an increased risk of toxicity and its adverse effects, or therapeutic failure. Therefore, the knowledge of these possible interactions is fundamental for the implementation of a nutritional treatment in the presence of a pharmacological therapy. This is the case of chronic kidney disease (CKD), for which the medication burden could be a problem, and nutritional therapy plays an important role in the patient’s treatment. The aim of this paper was to review the interactions that take place between drugs and foods that can potentially be used in renal patients, and the changes in nutritional status induced by drugs. A proper definition of the amount of food/nutrient intake, an adequate definition of the timing of meal consumption, and a proper adjustment of the drug dosing schedule may avoid these interactions, safeguarding the quality of life of the patients and guaranteeing the effectiveness of drug therapy. Hence, a close collaboration between the nephrologist, the renal dietitian, and the patient is crucial. Dietitians should consider that food may interact with drugs and that drugs may affect nutritional status, in order to provide the patient with proper dietary suggestions, and to allow the maximum effectiveness and safety of drug therapy, while preserving/correcting the nutritional status.

Exploring the Relationship of Drug BCS Classification, Food Effect, and Gastric pH-Dependent Drug Interactions

Food effect (FE) and gastric pH-dependent drug-drug interactions (DDIs) are both absorption-related. Here, we evaluated if Biopharmaceutics Classification System (BCS) classes may be correlated with FE or pH-dependent DDIs. Trends in FE data were investigated for 170 drugs with clinical FE studies from the literature and new drugs approved from 2013 to 2019 by US Food and Drug Administration. A subset of 38 drugs was also evaluated to determine whether FE results can inform the need for a gastric pH-dependent DDI study. The results of FE studies were defined as no effect (AUC ratio 0.80-1.25), increased exposure (AUC ratio ≥1.25), or decreased exposure (AUC ratio ≤0.8). Drugs with significantly increased exposure FE (AUC ratio ≥2.0; N=14) were BCS Class 2 or 4, while drugs with significantly decreased exposure FE (AUC ratio ≤0.5; N=2) were BCS Class 1/3 or 3. The lack of FE was aligned with the lack of a pH-dependent DDI for all 7 BCS Class 1 or 3 drugs as expected. For the 13 BCS Class 2 or 4 weak base drugs with an increased exposure FE, 6 had a pH-dependent DDI (AUC ratio ≤0.8). Among the 16 BCS Class 2 or 4 weak base drugs with no FE, 6 had a pH-dependent DDI (AUC ratio ≤0.8). FE appears to have limited correlation with BCS classes except for BCS Class 1 drugs, confirming that multiple physiological mechanisms can impact FE. Lack of FE does not indicate absence of pH-dependent DDI for BCS Class 2 or 4 drugs. Graphical Abstract.

Comparison of Predictions by BCS, rDCS and Machine Learning for the Effect of Food on Oral Drug Absorption Based on Features Calculated In silico

In this study, observed food effects of 473 drugs were categorized into positive, negative, or no effects and compared with the predictions made by machine learning (ML), the Biopharmaceutics Classification System (BCS) and refined Developability Classification System (rDCS). All methods used primarily in silico estimates for prediction, and for ML, four algorithms were evaluated using nested cross-validation to select important information from 371 features calculated based on the chemical structure. Approximately 18 features, including estimated solubility in biorelevant media, were selected as important, and the random forest classifier was the best among four algorithms with 36.6% error rate (ER) and 10.8% opposite prediction rate (OPR). The prediction by rDCS utilizing solubility in a biorelevant medium was somewhat inferior, but not by much; 41.0% ER and 11.4% OPR. Compared with these two methods, the prediction by BCS was inferior; 54.5% ER and 21.4% OPR. ER was improved modestly by using measured features instead of in silico estimates when BCS was applied to a subset of 151 drugs (46.4% from 55.0%). ML and rDCS predicted the food effects of the same subset using in silico estimates with ERs of 37.7% and 42.4%, respectively, suggesting that the predictions by ML and rDCS using in silico features are similar or more accurate than those by BCS using measured features. These results suggest that ML was useful in revealing essential features from complex information and, together with rDCS, is effective in predicting food effects during drug development, including early drug discovery.

Formulation strategies to improve the efficacy of intestinal permeation enhancers. Adv Drug Deliv Rev 2021;177:113925. [PMID: 34418495 DOI: 10.1016/j.addr.2021.113925]

The use of chemical permeation enhancers (PEs) is the most widely tested approach to improve oral absorption of low permeability active agents, as represented by peptides. Several hundred PEs increase intestinal permeability in preclinical bioassays, yet few have progressed to clinical testing and, of those, only incremental increases in oral bioavailability (BA) have been observed. Still, average BA values of ~1% were sufficient for two recent FDA approvals of semaglutide and octreotide oral formulations. PEs are typically screened in static in vitro and ex-vivo models where co-presentation of active agent and PE in high concentrations allows the PE to alter barrier integrity with sufficient contact time to promote flux across the intestinal epithelium. The capacity to maintain high concentrations of co-presented agents at the epithelium is not reached by standard oral dosage forms in the upper GI tract in vivo due to dilution, interference from luminal components, fast intestinal transit, and possible absorption of the PE per se. The PE-based formulations that have been assessed in clinical trials in either immediate-release or enteric-coated solid dosage forms produce low and variable oral BA due to these uncontrollable physiological factors. For PEs to appreciably increase intestinal permeability from oral dosage forms in vivo, strategies must facilitate co-presentation of PE and active agent at the epithelium for a sustained period at the required concentrations. Focusing on peptides as examples of a macromolecule class, we review physiological impediments to optimal luminal presentation, discuss the efficacy of current PE-based oral dosage forms, and suggest strategies that might be used to improve them.

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.

A phase I study of high dose camostat mesylate in healthy adults provides a rationale to repurpose the TMPRSS2 inhibitor for the treatment of COVID-19

Camostat mesylate, an oral serine protease inhibitor, is used to treat chronic pancreatitis and reflux esophagitis. Recently, camostat mesylate and its active metabolite 4-(4-guanidinobenzoyloxy)phenylacetic acid (GBPA) were reported to inhibit the infection of cells by severe acute respiratory syndrome coronavirus 2 by inhibiting type II transmembrane serine protease. We conducted a phase I study to investigate high-dose camostat mesylate as a treatment for coronavirus disease 2019. Camostat mesylate was orally administered to healthy adults at 600 mg 4 times daily under either of the following conditions: fasted state, after a meal, 30 min before a meal, or 1 h before a meal, and the pharmacokinetics and safety profiles were evaluated. In addition, the time of plasma GBPA concentration exceeding the effective concentration was estimated as the time above half-maximal effective concentration (EC50 ) by using pharmacokinetic/pharmacodynamic modeling and simulation. Camostat mesylate was safe and tolerated at all dosages. Compared with the fasted state, the exposure of GBPA after a meal and 30 min before a meal was significantly lower; however, no significant difference was observed at 1 h before a meal. The time above EC50 was 11.5 h when camostat mesylate 600 mg was administered 4 times daily in the fasted state or 1 h before a meal. Based on the results of this phase I study, we are currently conducting a phase III study.

Pharmacokinetic and Bioequivalence Evaluation of 2 Tadalafil Tablets in Healthy Male Chinese Subjects Under Fasting and Fed Conditions

Tadalafil is an effective, reversible, and competitive phosphodiesterase 5 inhibitor mainly used to treat erectile dysfunction. This study investigated the bioequivalence of generic and marketed formulations of 10-mg tadalafil tablets under fasted and fed conditions. This open-label, randomized, single-dose, 2-period crossover study included 53 healthy Chinese men (aged 20-43 years). Plasma samples were collected from 0.5 hours before treatment to 72 hours after each dose and analyzed using ultra-high-performance liquid chromatography coupled with tandem mass spectrometry. Pharmacokinetic parameters were calculated using noncompartmental analysis. Safety assessments were performed throughout the study. For the fasted state, the 90% confidence intervals of the geometric mean ratios between the generic and marketed formulations were 86.1% to 99.1% for the maximum plasma concentration and 88.4% to 100.3% for the area under the plasma concentration-time curve from time 0 to infinity, and the corresponding values under the fed state were and 99.9% to 108.4% and 95.7% to 104.3%, respectively. All data were within the accepted bioequivalence range of 80% to 125%. After consuming high-fat, high-calorie meals in the fed condition, the time to the maximum plasma concentration was similar between the formulations, and area under the plasma concentration-time curve from time 0 to infinity and maximum plasma concentration were 10.2% and 6.55% higher, respectively, for the marketed formulation. Thus, food had no clinically relevant effect on tadalafil exposure following a single oral dose in healthy Chinese men. No serious adverse reactions were reported. These results indicated that the analyzed generic and marketed tadalafil tablets were bioequivalent with similar safety profiles.

Single- and Multiple-Dose Pharmacokinetics and Pharmacodynamics of PN-943, a Gastrointestinal-Restricted Oral Peptide Antagonist of α4β7, in Healthy Volunteers

PN‐943 is an orally stable, gastrointestinal‐restricted peptide that binds specifically to α4ß7 integrin on leukocytes, blocking leukocyte trafficking to and activation in the gut, inhibiting colon inflammation and reducing signs and symptoms of active ulcerative colitis. Two pharmacokinetic/pharmacodynamic studies were conducted in healthy volunteers. Study 1 was a first‐in‐human study with 40 male subjects receiving PN‐943, 100 to 1400 mg or placebo, as single doses and 57 male subjects receiving PN‐943, 100 to 1000 mg or placebo, as multiple doses. Study 2 was a randomized, crossover study comparing multiple doses of 450‐mg PN‐943 twice daily as a liquid solution and as an immediate‐release tablet in 10 subjects. No subjects discontinued due to treatment‐emergent adverse events. Consistent with the gastrointestinal‐restricted nature of the peptide, systemic exposure was minimal; there was an approximate dose‐proportional increase in area under the plasma concentration–time curve. There was minimal accumulation with once‐daily dosing and an absence of time‐dependent changes in pharmacokinetics. Administration of PN‐943 after a high‐fat meal reduced peak plasma concentration and area under the plasma concentration–time curve. There was minimal (<0.1%) urinary excretion of intact drug, and there was a dose‐related increase in fecal excretion of intact PN‐943. Dose‐dependent increases in blood receptor occupancy and reduction in blood receptor expression were observed, supporting target engagement. Twice‐daily dosing resulted in sustained receptor occupancy with low plasma fluctuations (143%). PN‐943 was generally well tolerated following single and multiple oral doses with low systemic exposure. Twice‐daily dosing resulted in sustained pharmacokinetics and pharmacodynamics, supporting further investigation in efficacy studies.

Influence of food matrix and food processing on the chemical interaction and bioaccessibility of dietary phytochemicals: A review

Consumption of phytochemicals-rich foods shows the health effect on some chronic diseases. However, the bioaccessibility of these phytochemicals is extremely low, and they are often consumed in the diet along with the food matrix. The food matrix can be described as a complex assembly of various physical and chemical interactions that take place between the compounds present in the food. Some studies indicated that the physiological response and the health benefits of phytochemicals are resultant in these interactions. Some food substrates inhibit the absorption of phytochemicals via this interaction. Moreover, processing technologies have been developed to facilitate the release and/or to increase the accessibility of phytochemicals in plants or breakdown of the food matrix. Food processing processes may disrupt the activity of phytochemicals or reduce bioaccessibility. Enhancement of functional and sensorial attributes of phytochemicals in the daily diet may be achieved by modifying the food matrix and food processing in appropriate ways. Therefore, this review concisely elaborated on the mechanism and the influence of food matrix in different parts of the digestive tract in the human body, the chemical interaction between phytochemicals and other compounds in a food matrix, and the various food processing technologies on the bioaccessibility and chemical interaction of dietary phytochemicals. Moreover, the enhancing of phytochemical bioaccessibility through food matrix design and the positive/negative of food processing for dietary phytochemicals was also discussed in this study.

Assessing Food Effects on Oral Drug Absorption Based on the Degree of Renal Excretion

Food intake influences the pharmacokinetics of orally administered drugs by altering drug absorption, metabolism, and excretion. A drug which is mainly excreted into urine as parent drug is usually highly water-soluble and metabolically stable. Food intake is not expected to significantly affect its extent of oral absorption, metabolism, and excretion. Therefore, we hypothesize that an orally administered drug with significant renal excretion should not have a dramatic food effect (FE). To test our hypothesis, we summarized the FE for orally administered immediate-release (IR) and modified-release (MR) formulations approved by the US FDA from 1998 to 2019, focusing on drugs undergoing significant renal excretion. Totally, 98 active pharmaceutical ingredients (APIs) in IR formulations and 34 APIs in MR formulations were selected. The results demonstrate that the area-under-the-curve (AUC) for IR drug products with f_{ur_unchanged_po} > 10% is unlikely to be affected by food, although the peak plasma concentration (C_max) may increase or decrease by up to 50%. Compared with IR drug products with f_{ur_unchanged_po} > 10%, MR drug products with f_{ur_unchanged_po} > 10% tend to have more significant FE. Although our proposed approach cannot substitute a clinical FE study, it could be a useful addition to early drug development to get an initial sense of the potential for FE for a drug candidate.

Enteral Medication for the Tube-Fed Patient: Making This Route Safe and Effective

The administration of medication through an enteral access device requires important forethought. Meeting a patient's therapeutic needs requires achieving expected drug bioavailability without increasing the risk for toxicity, therapeutic failure, or feeding tube occlusion. Superimposing gut dysfunction, critical illness, or enteral nutrition-drug interaction further increases the need for a systematic approach to prescribing, evaluating, and preparing a drug for administration through an enteral access device. This review will explain the fundamental factors involved in drug bioavailability through the gut, address the influencing considerations for the enterally fed patient, and describe best practices for enteral drug preparation and administration.

Phase I, First-in-Human, Single and Multiple Ascending Dose- and Food-Effect Studies to Assess the Safety, Tolerability and Pharmacokinetics of a Novel Anti-hepatitis B Virus Drug, Bentysrepinine (Y101), in Healthy Chinese Subjects

BACKGROUND AND OBJECTIVE

Bentysrepinine (Y101), a derivative of repensine (a compound isolated from Dichondra repens Forst), is a novel phenylalanine dipeptide currently under development for the treatment of hepatitis B virus (HBV). The objectives of these studies were to assess the safety, tolerability and pharmacokinetics of bentysrepinine in healthy Chinese subjects.

METHODS

Two randomised, double-blind, placebo-controlled trials evaluated a single oral dose (50-900 mg, study 01) and multiple doses (300 mg and 600 mg, study 02), and a randomised, open, crossover food-effect study (600 mg, study 03) of bentysrepinine was established. Safety and tolerability were assessed by adverse event (AE) reporting, clinical laboratory tests, physical examinations, vital sign monitoring and electrocardiogram (ECG). Plasma, urine and faecal samples were analysed using validated liquid chromatography tandem mass spectrometry (LC-MS/MS) methods to investigate the pharmacokinetics of bentysrepinine.

RESULTS

Ninety-four subjects were enrolled, and bentysrepinine was well tolerated. Mild and reversible AEs occurred for single and multiple oral doses between 50 and 900 mg. The most common adverse effects were increased alanine aminotransferase (ALT) and aspartate transaminase (AST). Other clinically significant AEs included nausea and elevated urine leukocytes, urine red blood cells, transaminase, creatine kinase, total cholesterol, triglycerides, and low-density cholesterol. There were no clinically significant changes in the ECG, vital signs or laboratory assessments during the studies. The maximum tolerated dose (MTD) was not reached in the dose escalation study. Bentysrepinine was rapidly absorbed and metabolised with a mean time to reach maximum concentration (T_max) between 1-2 h and a mean terminal elimination half-life (t_1/2) of approximately 1-3 h. In the single ascending dose study, the exposure including the area under the concentration-time curve (AUC) and the maximum plasma concentration (C_max) of bentysrepinine generally increased in a dose-dependent but not dose-proportional manner in the 50-900 mg dose range. The urinary excretion and faecal excretion of unchanged bentysrepinine were 2.98% and 4.58% of the total dose, respectively. In the multiple-dose study, no accumulation was found after repeated administration at the 300 mg and 600 mg dose levels. The food-effect study using a 600 mg single dose showed that food intake has an obvious effect on the absorption of bentysrepinine from tablets. No experimental differences were found based on sex.

CONCLUSION

Bentysrepinine exhibited acceptable safety and tolerability in healthy subjects in the dose range of 50-900 mg in both single- and multiple-dose studies. The drug did not exhibit linear pharmacokinetic characteristics. No accumulation was observed after the administration of multiple 300 and 600 mg doses. Bentysrepinine is extensively metabolised in the body. Food may increase its bioavailability.

TRIALS REGISTRATION

CFDA registration numbers CTR20160096, CTR20160094, and CTR20140543 (www.chinadrugtrials.org.cn).

Development of LC-MS/MS method for simultaneous determination of Canagliflozin and Metformin in human plasma and its pharmacokinetic application in Indian population under fast and fed conditions

A novel, selective and sensitive method is developed for simultaneous estimation of canagliflozin and metformin and successfully applied to fast and fed pharmacokinetic studies in healthy Indian volunteers. The current study reports the development, optimization, and validation of liquid chromatography-mass spectrometry (LC-MS/MS) method for simultaneous quantification of canagliflozin and metformin in human plasma using deuterated canagliflozin D4 and metformin D6 as an internal standard (IS). The solid-phase extraction technique was employed where strata X polymeric reverse phase (30 mg-1 cc) SPE cartridges were used for the extraction of analytes and IS from plasma. The ACE 5 C18 column (50 × 4.6 mm, 5µ) was used to chromatograph the prepared samples. The mobile phase consisted of methanol and 5 mM ammonium trifluoroacetate in water, pH 5 (50:50, v/v) at a flow rate of 0.8 mL/min. Detection was performed by positive ion Turbo ion spray in Multiple reaction monitoring (MRM) mode, monitoring the transitions m/z 461.9 → m/z 191.1 and m/z 461.9 → m/z 267.2, for quantification of canagliflozin. The response of canagliflozin fragments m/z 461.9 → m/z 191.1 and m/z 461.9 → m/z 267.2 was combined. Also, for metformin transitions were monitored at m/z 130.0 → m/z 71.1. Full validation of the method was performed according to the United States Food and Drugs Administration (USFDA) guidelines. Linearity was in the range of 24.95-2806.55 ng/mL for canagliflozin and 24.99-3400.72 ng/mL for metformin. The mean extraction recovery of canagliflozin, canagliflozin D4, metformin, and metformin D6 was 77.240, 84.663, 66.747, and 67.449, respectively across four QC levels. This rapid method with the run time of 2.80 min allows the analysis of more than 400 plasma samples per day.

Use of Physiologically Based Pharmacokinetic (PBPK) Modeling for Predicting Drug-Food Interactions: an Industry Perspective

The effect of food on pharmacokinetic properties of drugs is a commonly observed occurrence affecting about 40% of orally administered drugs. Within the pharmaceutical industry, significant resources are invested to predict and characterize a clinically relevant food effect. Here, the predictive performance of physiologically based pharmacokinetic (PBPK) food effect models was assessed via de novo mechanistic absorption models for 30 compounds using controlled, pre-defined in vitro, and modeling methodology. Compounds for which absorption was known to be limited by intestinal transporters were excluded in this analysis. A decision tree for model verification and optimization was followed, leading to high, moderate, or low food effect prediction confidence. High (within 0.8- to 1.25-fold) to moderate confidence (within 0.5- to 2-fold) was achieved for most of the compounds (15 and 8, respectively). While for 7 compounds, prediction confidence was found to be low (> 2-fold). There was no clear difference in prediction success for positive or negative food effects and no clear relationship to the BCS category of tested drug molecules. However, an association could be demonstrated when the food effect was mainly related to changes in the gastrointestinal luminal fluids or physiology, including fluid volume, motility, pH, micellar entrapment, and bile salts. Considering these findings, it is recommended that appropriately verified mechanistic PBPK modeling can be leveraged with high to moderate confidence as a key approach to predicting potential food effect, especially related to mechanisms highlighted here.

Biliary Excretion-Mediated Food Effects and Prediction

Many orally administered drugs with negative food effects (i.e., lower exposure under fed conditions) are often primarily or partially eliminated by biliary excretion. The aim of this study is to assess the potential correlation between a negative food effect and biliary excretion. Correlation analysis was conducted using a training dataset containing 27 drugs which met the following criteria: (1) immediate-release formulations, (2) shows a negative food effect, (3) > 10% biliary clearance, and (4) does not undergo extensive metabolism. A correlation between fed-state biliary clearance (CL_b,fed) and fasted-state biliary clearance (CL_b,fast) (y = 1.81*x, R² = 0.68) was observed. The 1.8-fold increase in biliary clearance was then used as a correction factor to improve physiologically based pharmacokinetic (PBPK) prediction of food effects for 12 test drugs. The mean deviations of predicted fed/fasting AUC ratio and C_max ratio from clinically observed values were reduced from 32.4 to 17.2% and from 63.3 to 54.3%, respectively. In contrast to the positive food effects on most biopharmaceutics classification system (BCS) class II drugs for which food-stimulated bile flow increases drug solubility and absorption, our results suggest that the elimination of biliary excreted drugs is increased by food-stimulated bile flow, resulting in negative food effects.

Prediction of negative food effect induced by bile micelle binding on oral absorption of hydrophilic cationic drugs

The purpose of the present study was to quantitatively predict the negative food effect induced by bile micelle binding on the oral absorption of hydrophilic cationic drugs. The intrinsic membrane permeability and bile micelle unbound fraction of 12 model drugs (7 tertiary amines, 3 quaternary ammoniums, and 2 neutral drugs) were calculated from the experimental Caco-2 permeability data (P_app) under fasted and fed conditions. From these input data, the fraction of a dose absorbed (Fa) was predicted using the gastrointestinal unified theoretical framework, a mechanism-based oral absorption model. The predicted Fa ratio (fed/fasted) was then compared with the in vivo fed/fasted area under the plasma concentration-time curve ratio (AUCr). The AUCr values of tertiary amines and neutral drugs were appropriately predicted (absolute average fold error (AAFE) = 1.19), whereas those of quaternary ammoniums were markedly underestimated (AAFE = 4.70). The P_app ratio (fed/fasted) predicted AUCr less quantitatively (AAFE = 1.30 for tertiary amines and neutral drugs). The results of the present study would lead to a better understanding of negative food effect on oral drug absorption.

The Bioequivalence of Two Peficitinib Formulations, and the Effect of Food on the Pharmacokinetics of Peficitinib: Two-Way Crossover Studies of a Single Dose of 150 mg Peficitinib in Healthy Volunteers

The marketed tablet formulation of peficitinib differs from the tablet used during the clinical trials. The bioequivalence of the marketed formulation and developmental tablet, and the food effect on the marketed formulation, were analyzed in 2 Japanese open‐label, randomized, 2‐way crossover studies in healthy male volunteers. Volunteers received a single oral dose of the marketed 150‐mg peficitinib tablet under fasted conditions (bioequivalence), and under fed or fasted conditions (food effect). Bioequivalence was compared with the developmental 150‐mg tablet. Samples for pharmacokinetic analysis were collected before dose and ≤72 hours after dose. Safety assessments included adverse events, vital signs, and laboratory variables. In total, 40 and 18 subjects were randomized to the bioequivalence and food effect studies, respectively. The 2 peficitinib formulations were bioequivalent (90% confidence intervals of the geometric mean ratios for C_max and AUC_t of peficitinib were within predefined limits of 0.8 to 1.25). The AUC_last and the C_max of the marketed tablet were 36.8% and 56.4% higher, respectively, under fed versus fasted conditions. Peficitinib was well tolerated. The marketed 150‐mg tablet formulation of peficitinib was bioequivalent to the developmental 150‐mg formulation, with no discernible safety differences. Bioavailability increased under fed conditions with the marketed tablet formulation.

Optimal drug administration manner would rescue partial virological response in chronic hepatitis B patients with entecavir or tenofovir treatment

Not all treatment-naïve patients receiving entecavir (ETV) or tenofovir disoproxil fumarate (TDF) therapy can achieve complete virological response, and many factors may be related with the outcome of partial virological response. This study aimed to determine whether the manner of drug administration affects the antiviral efficacy of ETV/TDF monotherapy. All eligible patients were divided into complete or partial response cohorts based on their virological response following 24-week therapy. Factors related with partial response were evaluated. Patients with partial response were further grouped depending on whether they later adjusted the manner of drug administration, and the antiviral efficacy was compared between the two groups during prolonged treatment. A total of 518 patients were enrolled. Suboptimal drug administration (OR 77.511, P = .000), positive-HBeAg (OR 3.191, P = .000) and ETV treatment (OR 2.537, P = .001) were identified as independent risk factors for partial response. Among patients with partial response, 213 were in the adjusted group and 76 were in the unadjusted group. The percentages of patients with undetectable serum HBV DNA (78.9% vs 31.6%, P < .001) and with normal alanine aminotransferase (ALT) (88.7% vs 68.4%, P < .001) were both higher in the adjusted group than that in unadjusted group following a further 6-month therapy. In conclusion, the manner of drug administration is an important factor influencing the efficacy of ETV/TDF therapy, and optimal drug administration manner can help to increase antiviral efficacy and rescue patients with partial response.

Sustained Release Ziprasidone Microparticles Prepared by Spray Drying with Soluplus® and Ethyl Cellulose to Eliminate Food Effect and Enhance Bioavailability

The purpose of this study was to develop and evaluate a new formulation of ziprasidone (ZIP) for improved fasted state absorption and sustained drug release. ZIP solid dispersions were produced via spray drying using Soluplus®, an amphiphilic polymer, as the solubility enhancer. Physicochemical analysis proved that ZIP presented at amorphous state in the spray-dried microparticles and the dissolution rate of ZIP from the Soluplus®-ZIP composite microparticles was significantly increased compared with that of the physical mixtures. Commonly used encapsulation materials including Eudragit® RL, Eudragit® S100 and Ethyl Cellulose were incorporated into the solid dispersions to regulate the drug release kinetics. The formulation containing ethyl cellulose provided the most sustained release behaviors. Pharmacokinetic studies in beagle dogs confirmed that there was no significant difference in oral bioavailability of the microparticles under fasted and fed states, and a prolonged T_max value was simultaneously achieved compared with the commercial ZIP capsules.

An Investigation into the Factors Governing Drug Absorption and Food Effect Prediction Based on Data Mining Methodology

Drug absorption is a complex process governed by a number of interrelated physicochemical, biopharmaceutical, and pharmacokinetic factors. In order to explore complex relationships among these factors, multivariate exploratory analysis was performed on the dataset of drugs with diverse bioperformance. The investigated dataset included subset of drugs for which bioequivalence between solid dosage form and oral solution has been reported, and subset of drugs described in the literature as low solubility/low permeability compounds. Discriminatory power of hierarchical clustering on principal components was somewhat higher when applied on the data subsets of drugs with similar bioperformance, while analysis of the integrated dataset indicated existence of two groups of drugs with the boundaries reflected in P_eff value of approximately 2 × 10^-4 cm/s and Fa and Fm values higher than 85% and 50%, respectively. Majority of the investigated drugs within the integrated dataset were grouped within their initial subset indicating that overall drug bioperformance is closely related to its physicochemical, biopharmaceutical and pharmacokinetic properties. Classification models constructed using the random forest (RF) and support vector machine with polynomial kernel function were able to predict food effect based on drug dose/solubility ratio (D/S), effective permeability (P_eff), percent of dose metabolized (Fm), and elimination half-life (τ_1/2). Although both models performed well during training and testing, only RF kept satisfying performance when applied on the external dataset (kappa value > 0.4). The results obtained indicate that data mining can be employed as useful tool in biopharmaceutical drug characterization which merits further investigation.

Relationship between the effects of food on the pharmacokinetics of oral antineoplastic drugs and their physicochemical properties

Background

Food is known to affect drug absorption by delaying gastric emptying time, altering gastrointestinal pH, stimulating bile flow, increasing splanchnic blood flow, or physically interacting with drugs. Although food is known to affect the pharmacokinetics of oral antineoplastic drugs, the relationship between the effects of food and the physicochemical properties of drugs remains unclear.

Methods

In this study, we surveyed the literature on three kinds of pharmacokinetic changes, AUC ratio, C_max ratio and T_max ratio, in the fasted and fed state for 72 oral antineoplastic drugs that were listed on the drug price standard in May 2018 in Japan. We further predicted the physicochemical properties from the 2D chemical structure of the antineoplastic drugs using in silico predictions.

Results

As a result of analyzing the relationship between the effects of food and physicochemical properties, we found that compounds that show increased absorption in the fed state had higher logP and lower solubility in fasted-state simulated intestinal fluid (FaSSIF). However, compounds with delayed absorption had higher solubility in FaSSIF. Furthermore, as a result of decision tree analysis, it was classified as AUC increase with logP ≥4.34. We found that an AUC increase in the fed state did not occur with compounds with low lipid solubilities (logP < 1.59). From these results, it is predicted that 7 compounds out of the 24 compounds for which the effects of food are unknown are at risk for increased absorption in the fed state and that no increase in absorption would occur in 13 compounds.

Conclusion

In this study, we found that drugs that will show increased absorption in the fed state and drugs for which absorption is not dependent on food can generally be predicted by logP. These results suggest that logP can be a useful parameter for predicting the effects of food on drug absorption.

Dissolution Enhancement of Atorvastatin Calcium by Cocrystallization

Purpose: To enhance the dissolution rate of the poorly soluble drug atorvastatin calcium (ATC) by cocrystallization with selected coformers. Enhancement of the dissolution rate and solubility of the drug, which is classified as Class II of the Biopharmaceutical Classification System (BCS), is expected to enhance the bioavailability.

Methods: Two methods were used for preparing the cocrystals, solvent drop grinding (SDG) and solvent evaporation (SE) method using 1:1, 1:3, and 1:10 drug-coformer molar ratios. Glucosamine hydrochloride (GluN) and nicotinamide (NIC) were investigated as coformers. The cocrystals, their physical mixtures, and the raw ATC were characterized by fourier transform infrared (FTIR spectroscopy), differential scanning calorimetry (DSC), powder X-ray diffraction (PXRD), mass spectroscopy (MS), scanning electron microscopy (SEM), solubility, and dissolution rate studies.

Results: SDG and SE were effective in improving the dissolution rate of ATC with both coformers. Drug: coformer ratio 1:3 was optimum. The solubility values for ATC, GluN-, and NIC-cocrystals were 26, to 35 and 50 µg/mL, respectively. The dissolution rate of ATC from cocrystals was > 90% after 5 minutes, compared to 41% untreated ATC.

Conclusion: Cocrystallization significantly improved the solubility and dissolution, in comparison to the untreated ATC.

In-vitro–in-silico investigation of the negative food effect of zolpidem when administered as immediate-release tablets

Objectives

The main objective of the present work was to combine in-vitro and in-silico tools to better understand the in-vivo behavior of the immediate release (IR) formulation of zolpidem in the fasted and fed states.

Methods

The dissolution of zolpidem was evaluated using biorelevant media simulating the gastric and intestinal environment in the fasted and fed states. Additionally, the influence of high viscosity and high fat content on the release of zolpidem under fed state conditions was investigated. The in-vitro results were combined with a physiologically based pharmacokinetic (PBPK) model constructed with Simcyp® to simulate the zolpidem pharmacokinetic profile in both prandial states.

Key findings

In vitro biorelevant dissolution experiments representing the fasted and fed states, combinedwith PBPKmodelling, were able to simulate the plasma profiles from the clinical food effect studies well. Experiments reflecting the pH and fat content of themeal led to a good prediction of the zolpidem plasma profile in the fed state, whereas increasing the viscosity of the gastricmedia led to an under-prediction.

Conclusions

This work demonstrates that the combination of biorelevant dissolution testing and PBPK modelling is very useful for understanding the in-vivo behavior of zolpidem in the fasted and fed states. This approach could be implemented in the development of other drugs exhibiting negative food effects, saving resources and bringing new drug products to the market faster.

Toward the establishment of a standardized pre-clinical porcine model to predict food effects - Case studies on fenofibrate and paracetamol

A preclinical porcine model that reliably predicts human food effect of fenofibrate was developed. Fenofibrate was administered to pigs as model compound with a positive food effect. Two different types of fed conditions were explored: a FDA style breakfast and a standard pig pellet feed. In order to assess if complete stomach emptying had been achieved under the employed fasting protocol, the amount of gastric and intestinal content was evaluated post-mortem. In addition, the protocol was designed to evaluate gastric emptying in the pre- and postprandial state using paracetamol as a marker. The study confirmed that micronized fenofibrate displayed a positive food effect with a similar fold difference to humans in FDA style fed state. Post-mortem assessment of stomach and intestinal content confirmed significantly lower content in the fasted compared to the pig pellet fed state. In the case of paracetamol, a delayed gastric emptying in the fed state was not observed, which may suggest that the Magenstrasse phenomena reported in humans, may also occur in landrace pigs. The study demonstrated the utility of a food effect protocol in landrace pigs as a pre-clinical approach to predict human food effects and provided new insights into gastric emptying in pigs.

Effect of pH and Ionic Strength on the Solubility of Quinoline: Back-to-Basics

The interest of quinoline as a contaminant agent and as scaffold for the development of new therapeutic agent warrants to revisit the pH-solubility behavior of quinoline (Q) and quinoline derivatives (Q-derivatives) with possible salting-out effect. Q is a weak base with potential hazard upon exposure that may be occupational by inhalation or ingestion of or dermal exposure to particulates in certain industries; or simply by inhalation of cigarette smoke. In contrast, quinoline and its derivatives are useful in diverse therapeutic applications such as anticancer, antiseptic, antipyretic, antiviral, and antimalarial. These claims have raised the possibility of using quinoline motif for the synthesis of new drugs; however, it may act as a pollutant on soil and water as ionizable organic compounds (IOC). The solubility and partitioning behavior of Q may be a critical factor in determining the extent of inhalation and oral absorption or sorption onto soil and water. Studies on the solubility of Q have been reported; however, due to Q-derivatives distinctive usage, it is necessary to revisit and evaluate the solubility profile of Q at different pH levels and ionic strengths. This study reports a simple analytical method for determining the solubility of nitrogen heterocyclic compounds and possible salting-out effect as a function of pH, buffer concentration, and ionic strength. This information can be of value when developing Q-derivatives and to enhance understanding of Q as well as its derivatives behavior in the gastrointestinal tract or when evaluating the presence of Q as an environmental contaminant.

Application of Permeation Enhancers in Oral Delivery of Macromolecules: An Update

The application of permeation enhancers (PEs) to improve transport of poorly absorbed active pharmaceutical ingredients across the intestinal epithelium is a widely tested approach. Several hundred compounds have been shown to alter the epithelial barrier, and although the research emphasis has broadened to encompass a role for nanoparticle approaches, PEs represent a key constituent of conventional oral formulations that have progressed to clinical testing. In this review, we highlight promising PEs in early development, summarize the current state of the art, and highlight challenges to the translation of PE-based delivery systems into safe and effective oral dosage forms for patients.

Impact of P-Glycoprotein on Intestinal Absorption of an Inhibitor of Apoptosis Protein Antagonist in Rats: Mechanisms of Nonlinear Pharmacokinetics and Food Effects

PURPOSE

This study was designed to investigate the effects of P-glycoprotein (P-gp) expressed in the intestine on the nonlinear pharmacokinetics (PK) of T-3256336, an inhibitor of apoptosis protein inhibitor, and food effects on its bioavailability in rats.

METHODS

To investigate the factors that contribute to nonlinear PK of T-3256336 in the intestine and liver, rats double-cannulated in the portal vein and femoral artery (PS rats) were used. F_aF_g (F_a, absorption ratio; F_g, intestinal availability) and hepatic availability (F_h) were simultaneously evaluated based on the difference between the portal and systemic blood area under the concentration-time curve (AUC). Elacridar was used as a P-gp inhibitor to assess the impact of P-gp on the intestinal absorption.

RESULTS

After oral administration of T-3256336 to PS rats at 3 and 30 mg/kg, F_aF_g value increased with dose escalation, whereas F_h value was nearly constant. Moreover, co-administration of elacridar resulted in a 5-fold increase in the F_aF_g value at 3 mg/kg. The AUC value of T-3256336 under fed conditions was 3-fold lower than that under fasted conditions. This food effect on the oral bioavailability (BA) was reduced by concomitant administration of elacridar.

CONCLUSION

P-gp expressed in the intestine would cause nonlinear PK and a food effect on BA of T-3256336 in rats.

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.

Industry Perspective on Standardizing Food-Effect Studies for New Drug Development

Investigating the effect of food on bioavailability during the development of an oral drug product is of prime importance because it has major implications on the study design of the clinical trials and dosing and administration recommendations. For modified-release formulations that exhibit dose dumping when administered with food, this may result in clinical concerns around safety and efficacy. In this article, we provide an overview of the various considerations in our opinion that impact the design and conduct of food-effect studies. We summarize the various recommendations from the different regulatory agencies and provide specific suggestions on study conduct in terms of statistical design, timing of studies, subject selection, and type and caloric content of the meal. We also discuss the role of modeling and simulation. Finally, we present an interpretation of the results of food-effect studies in addition to dosing and labeling recommendations in relation to regulatory guidance documents.

Labrasol® and Salts of Medium-Chain Fatty Acids Can Be Combined in Low Concentrations to Increase the Permeability of a Macromolecule Marker Across Isolated Rat Intestinal Mucosae

In addition to their solubilizing properties, excipients used in lipid-based formulations can improve intestinal permeability of macromolecules. We determined whether admixing of medium-chain fatty acid (MCFA) permeation enhancers with a lipoidal excipient (Labrasol^®) could potentiate transepithelial flux of a poorly permeable macromolecule (fluorescein isothiocyanate dextran 4 kDa [FD4]) across rat intestinal mucosae mounted in Ussing chambers. Low concentrations of sodium caprate (C₁₀), sodium undecylenate (C_11:1), or sodium laurate (C₁₂) combined with Labrasol^® increased the apparent permeability coefficient (P_app) of FD4 to values typically seen with higher concentrations of MCFAs or Labrasol^® alone. For example, combination of C_11:1 (0.5 mg/mL) with Labrasol^® (1 mg/mL) increased the P_app of FD4 by 10- and 11-fold over the respective individual agents at the same concentrations where no enhancement was evident. The increased enhancement ratios seen with the combinations were associated with some perturbation in intestinal histology and with attenuation of an epithelial functional measure, carbachol-stimulated inward short-circuit current. In conclusion, combining three MCFAs separately with Labrasol^® increased the P_app of FD4 to values greater than those seen for MCFAs or Labrasol^® alone. Ultimately, this may permit lower concentrations of MCFA to be used in combination with other excipients in oral formulations of poorly permeable molecules.

Review and analysis of FDA approved drugs using lipid-based formulations

Lipid-based drug delivery systems (LBDDS) are one of the most studied bioavailability enhancement technologies and are utilized in a number of U.S. Food and Drug Administration (FDA) approved drugs. While researchers have used several general rules of thumb to predict which compounds are likely to benefit from LBDDS, formulation of lipid systems is primarily an empiric endeavor. One of the challenges is that these rules of thumb focus in different areas and are used independently of each other. The Developability Classification System attempts to link physicochemical characteristics with possible formulation strategies. Although it provides a starting point, the formulator still has to empirically develop the formulation. This article provides a review and quantitative analysis of the molecular properties of these approved drugs formulated as lipid systems and starts to build an approach that provides more directed guidance on which type of lipid system is likely to be the best for a particular drug molecule.

Physicochemical properties of dietary phytochemicals can predict their passive absorption in the human small intestine

A diet high in phytochemical-rich plant foods is associated with reducing the risk of chronic diseases such as cardiovascular and neurodegenerative diseases, obesity, diabetes and cancer. Oxidative stress and inflammation (OSI) is the common component underlying these chronic diseases. Whilst the positive health effects of phytochemicals and their metabolites have been demonstrated to regulate OSI, the timing and absorption for best effect is not well understood. We developed a model to predict the time to achieve maximal plasma concentration (Tmax) of phytochemicals in fruits and vegetables. We used a training dataset containing 67 dietary phytochemicals from 31 clinical studies to develop the model and validated the model using three independent datasets comprising a total of 108 dietary phytochemicals and 98 pharmaceutical compounds. The developed model based on dietary intake forms and the physicochemical properties lipophilicity and molecular mass accurately predicts Tmax of dietary phytochemicals and pharmaceutical compounds over a broad range of chemical classes. This is the first direct model to predict Tmax of dietary phytochemicals in the human body. The model informs the clinical dosing frequency for optimising uptake and sustained presence of dietary phytochemicals in circulation, to maximise their bio-efficacy for positively affect human health and managing OSI in chronic diseases.