Evaluation of the Use of Göttingen Minipigs to Predict Food Effects on the Oral Absorption of Drugs in Humans

Safety, tolerability and toxicokinetics of the novel mitochondrial drug SUL-138 administered orally to rat and minipig

Noncommunicable Chronic Diseases (NCD) are a socioeconomic burden and considered one of the major health challenges for coming decades. Mitochondrial dysfunction has been implicated mechanistically in their pathophysiology. Therefore, targeting mitochondria holds great promise to improve clinical outcomes in NCDs. SUL-138, an orally bioavailable small molecule efficacious from 0.5 mg/kg, improves mitochondrial function during disease in several preclinical animal models. As preparation for a First-in-Human (FIH) trial, SUL-138 was investigated in 30-day GLP repeated dose toxicity studies in rat and minipig, selected based on their comparability with human metabolism, to determine toxicokinetics, potential toxicity and its reversibility. Rats were allocated to either vehicle, 27, 136 or 682 mg/kg SUL-138 dose groups and minipigs were allocated to either vehicle, 16, 82 or 409 mg/kg. Treatment occurred orally for 30 days followed by a recovery period of 14 days. During these studies clinical observations, toxicokinetic, clinical pathology, necropsy and histopathology evaluations were performed. There was significant systemic exposure to SUL-138 and toxicokinetics was characterized by a rapid absorption and elimination. In the rat, toxicokinetics was dose-proportional and AUC0-tlast ratios in both species indicated that SUL-138 does not accumulate in vivo. No treatment-related adverse effects were observed for dose levels up to 136 and 82 mg/kg/day in rat and minipig respectively. In conclusion, these preclinical studies demonstrate that SUL-138 is well tolerated after repeated administration in rat and minipig, with NOAELs of 136 and 82 mg/kg/day, respectively.

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.

Evaluation and prediction of oral drug absorption and bioequivalence with food-drug interaction

This article reviews the impacts on the in vivo prediction of oral bioavailability (BA) and bioequivalence (BE) based on Biopharmaceutical classification systems (BCS) by the food-drug interaction (food effect) and the gastrointestinal (GI) environmental change. Various in vitro and in silico predictive methodologies have been used to expect the BA and BE of the test oral formulation. Food intake changes the GI physiology and environment, which affect oral drug absorption and its BE evaluation. Even though the pHs and bile acids in the GI tract would have significant influence on drug dissolution and, hence, oral drug absorption, those impacts largely depend on the physicochemical properties of oral medicine, active pharmaceutical ingredients (APIs). BCS class I and III drugs are high soluble drugs in the physiological pH range, food-drug interaction may not affect their BA. On the other hand, BCS class II and IV drugs have pH-dependent solubility, and the more bile acid secretion and the pH changes by food intake might affect their BA. In this report, the GI physiological changes between the fasted and fed states are described and the prediction on the oral drug absorption by food-drug interaction have been introduced.

Bio-enabling strategies to mitigate the pharmaceutical food effect: a mini review

The concomitant administration of oral drugs with food can result in significant changes in bioavailability, leading to variable pharmacokinetics and considerable clinical implications, such as over- or under-dosing. Consequently, there is increasing demand for bio-enabling formulation strategies to reduce variability in exposure between the fasted and fed state and/or mitigate the pharmaceutical food effect. The current review critically evaluates technologies that have been implemented to overcome the positive food effects of pharmaceutical drugs, including, lipid-based formulations, nanosized drug preparations, cyclodextrins, amorphisation and solid dispersions, prodrugs and salts. Additionally, improved insight into preclinical models for predicting the food effect is provided. Despite the wealth of research, this review demonstrates that application of optimal formulation strategies to mitigate the positive food effects and the evaluation in preclinical models is not a universal approach, and improved standardisation of models to predict the food effects would be desirable. Ultimately, the successful reformulation of specific drugs to eliminate the food effect provides a panoply of advantages for patients with regard to clinical efficacy and compliance.

Development of In Vitro Dissolution Testing Methods to Simulate Fed Conditions for Immediate Release Solid Oral Dosage Forms

In vitro dissolution testing is widely used to mimic and predict in vivo performance of oral drug products in the gastrointestinal (GI) tract. This literature review assesses the current in vitro dissolution methodologies being employed to simulate and predict in vivo drug dissolution under fasted and fed conditions, with emphasis on immediate release (IR) solid oral dosage forms. Notable human GI physiological conditions under fasted and fed states have been reviewed and summarized. Literature results showed that dissolution media, mechanical forces, and transit times are key dissolution test parameters for simulating specific postprandial conditions. A number of biorelevant systems, including the fed stomach model (FSM), GastroDuo device, dynamic gastric model (DGM), simulated gastrointestinal tract models (TIM), and the human gastric simulator (HGS), have been developed to mimic the postprandial state of the stomach. While these models have assisted in expanding physiological relevance of in vitro dissolution tests, in general, these models lack the ability to fully replicate physiological conditions/processes. Furthermore, the translatability of in vitro data to an in vivo system remains challenging. Additionally, physiologically based pharmacokinetic (PBPK) modeling has been employed to evaluate the effect of food on drug bioavailability and bioequivalence. Here, we assess the current status of in vitro dissolution methodologies and absorption PBPK modeling approaches to identify knowledge gaps and facilitate further development of in vitro dissolution methods that factor in fasted and fed states. Prediction of in vivo drug performance under fasted and fed conditions via in vitro dissolution testing and modeling may potentially help efforts in harmonizing global regulatory recommendations regarding in vivo fasted and fed bioequivalence studies for solid oral IR products.

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.

Exploring porcine gastric and intestinal fluids using microscopic and solubility estimates: Impact of placebo self-emulsifying drug delivery system administration to inform bio-predictive in vitro tools

Validation and characterisation of in vitro and pre-clinical animal models to support bio-enabling formulation development is of paramount importance. In this work, post-mortem gastric and small intestinal fluids were collected in the fasted, fed state and at five sample-points post administration of a placebo Self-Emulsifying Drug Delivery System (SEDDS) in the fasted state to pigs. Cryo-TEM and Negative Stain-TEM were used for ultrastructure characterisation. Ex vivo solubility of fenofibrate was determined in the fasted-state, fed-state and post-SEDDS administration. Highest observed ex vivo drug solubility in intestinal fluids after SEDDS administration was used for optimising the biorelevant in vitro conditions to determine maximum solubility. Under microscopic evaluation, fasted, fed and SEDDS fluids resulted in different colloidal structures. Drug solubility appeared highest 1 hour post SEDDS administration, corresponding with presence of SEDDS lipid droplets. A 1:200 dispersion of SEDDS in biorelevant media matched the highest observed ex vivo solubility upon SEDDS administration. Overall, impacts of this study include increasing evidence for the pig preclinical model to mimic drug solubility in humans, observations that SEDDS administration may poorly mimic colloidal structures observed under fed state, while microscopic and solubility porcine assessments provided a framework for increasingly bio-predictive in vitro tools.

Oral biopharmaceutics tools: recent progress from partnership through the Pharmaceutical Education and Research with Regulatory Links collaboration

OBJECTIVES

To summarise key contributions of the Pharmaceutical Education and Research with Regulatory Links (PEARRL) project (2016-2020) to the optimisation of existing and the development of new biopharmaceutics tools for evaluating the in vivo performance of oral drug products during the development of new drugs and at the regulatory level.

KEY FINDINGS

Optimised biopharmaceutics tools: Based on new clinical data, the composition of biorelevant media for simulating the fed state conditions in the stomach was simplified. Strategies on how to incorporate biorelevant in vitro data of bio-enabling drug products into physiologically based pharmacokinetic (PBPK) modelling were proposed. Novel in vitro biopharmaceutics tools: Small-scale two-stage biphasic dissolution and dissolution-permeation setups were developed to facilitate understanding of the supersaturation effects and precipitation risks of orally administered drugs. A porcine fasted state simulated intestinal fluid was developed to improve predictions and interpretation of preclinical results using in vitro dissolution studies. Based on new clinical data, recommendations on the design of in vitro methodologies for evaluating the GI drug transfer process in the fed state were suggested. The optimized design of in vivo studies for investigating food effects: A food effect study protocol in the pig model was established which successfully predicted the food-dependent bioavailability of two model compounds. The effect of simulated infant fed state conditions in healthy adults on the oral absorption of model drugs was evaluated versus the fasted state and the fed state conditions, as defined by regulatory agencies for adults. Using PBPK modelling, the extrapolated fasted and infant fed conditions data appeared to be more useful to describe early drug exposure in infants, while extrapolation of data collected under fed state conditions, as defined by regulators for adults, failed to capture in vivo infant drug absorption.

SUMMARY

Substantial progress has been made in developing an advanced suite of biopharmaceutics tools for streamlining drug formulation screening and supporting regulatory applications. These advances in biopharmaceutics were achieved through networking opportunities and research collaborations provided under the H2020 funded PEARRL project.

Characterization of gastrointestinal transit and luminal conditions in pigs using a telemetric motility capsule

Within preclinical research, the pig has become an important model in regulatory toxicology and pharmacokinetics, to assess oral dosage forms and to compare different formulation strategies. In addition, there are emerging application of the pig model to asses clinical dosing conditions in the fasted and fed state. In this study, the gastrointestinal transit conditions in male landrace pigs were studied with a telemetric motility capsule under fasted and postprandial conditions. The whole gut transit time (WGTT) was determined by administering a SmartPill® capsule to four landrace pigs, under both fasted and fed state conditions in a cross-over study design. Overall, this study found that small intestinal transit in landrace pigs ranged from 2.3 - 4.0 h, and was broadly similar to reported human estimates and was not affected by the intake conditions. Gastric emptying was highly variable and prolonged in landrace pigs ranging from 20 - 233 h and up to 264 h in one specific case. Under dynamic conditions pigs have a low gastric pH comparable to humans, however a high variability under fasted conditions could be observed. The comparison of the data from this study with a recent similar study in beagle dogs revealed major differences between gastric maximum pressures observed in landrace pigs and dogs. In the porcine stomach maximum pressures of up to 402 mbar were observed, which are comparable to reported human data. Intestinal maximum pressures in landrace pigs were in the same range as in humans. Overall, the study provides new insights of gastrointestinal conditions in landrace pigs, which can lead to more accurate interpretation of in vivo results obtained of pharmacokinetic studies in preclinical models. While small intestinal transit conditions, GI pH and pressures were similar to humans, the prolonged gastric emptying observed in pigs need to be considered in assessing the suitability of the pig model for assessing in vivo performance of large non-disintegrated oral drug products.

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.

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.

Porcine Prediction of Pharmacokinetic Parameters in People: A Pig in a Poke?

The minipig has become an animal of considerable interest in preclinical drug development. It has been used in toxicology research and in examining/establishing regulatory guidelines as a nonrodent animal model. We have reviewed some basic issues that one would want to consider in the development and testing of any animal model for humans. The pig is a reasonable alternative to the dog, but there are some clear limitations and unexplained disparities in the literature, which require further study; primary among these is the need for standardization in choice of breed and sex and routine protocols. The minipig offers numerous advantages over other established animal models, and it has similarities to the human with regard to anatomy, physiology, and biochemistry. The gastrointestinal tract is structurally and functionally similar to humans. This appears to be true for enzymes and transporters in the gut as well, but more study is needed. One major concern is assessment of oral drug absorption, especially with regard to potential food effects due to gastric emptying differences, yet this does not appear to be a consistent observation. Hepatic metabolism seems to reflect enzymatic patterns in humans, with some differences. Kidney function seems similar to humans but requires further study. We have analyzed literature data that suggest the pig would offer a reasonable model for human oral bioavailability and for allometric predictions of clearance. The minipig appears to be the model for dermal absorption in humans, and we discuss this in terms of literature data and our own in-house experience.

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.

The pig as a preclinical model for predicting oral bioavailability and in vivo performance of pharmaceutical oral dosage forms: a PEARRL review

OBJECTIVES

In pharmaceutical drug development, preclinical tests in animal models are essential to demonstrate whether the new drug is orally bioavailable and to gain a first insight into in vivo pharmacokinetic parameters that can subsequently be used to predict human values. Despite significant advances in the development of bio-predictive in vitro models and increasing ethical expectations for reducing the number of animals used for research purposes, there is still a need for appropriately selected pre-clinical in vivo testing to provide guidance on the decision to progress to testing in humans. The selection of the appropriate animal models is essential both to maximise the learning that can be obtained from such experiments and to avoid unnecessary testing in a range of species.

KEY FINDINGS

The present review, provides an insight into the suitability of the pig model for predicting oral bioavailability in humans, by comparing the conditions in the GIT. It also contains a comparison between the bioavailability of compounds dosed to both humans and pigs, to provide an insight into the relative correlation and examples on why a lack of correlation may be observed.

SUMMARY

While there is a general trend towards predicting human bioavailability from pig data, there is considerable variability in the data set, most likely reflecting species specific differences in individual drug metabolism. Nonetheless, the correlation between pigs vs. humans was comparable to that reported for dogs vs. humans. The presented data demonstrate the suitability of the pig as a preclinical model to predict bioavailability in human.