A New Version of the Tissue Composition-Based Model for Improving the Mechanism-Based Prediction of Volume of Distribution at Steady-State for Neutral Drugs.

In-vitro models are available in the literature for predicting the volume of distribution at steady-state (Vdss) of drugs. The mechanistic model refers to the tissue composition-based model (TCM), which includes important factors that govern Vdss such as drug physiochemistry and physiological data. The recognized TCM published by Rodgers and Rowland (TCM-RR) and a subsequent adjustment made by Simulations Plus Inc. (TCM-SP) have been shown to be generally less accurate with neutral compared to ionized drugs. Therefore, improving these models for neutral drugs becomes necessary. The objective of this study was to propose a new TCM for improving the prediction of Vdss for neutral drugs. The new TCM included two modifications of the published models (i) accentuate the effect of the blood-to-plasma ratio (BPR) that should cover permeated molecules across the biomembranes, which is lacking in these models for neutral compounds, and (ii) use a different approach to estimate the binding in tissues. The new TCM was validated with a large dataset of 202 commercial and proprietary compounds including preclinical and clinical data. All scenario datasets were predicted more accurately with the TCM-New, whereas all statistical parameters indicate that the TCM-New showed significant improvements in terms of accuracy over the TCM-RR and TCM-SP. Predictions of Vdss were frequently more accurate for the TCM-new with 83% within twofold error versus only 50% for the TCM-RR. And more than 95% of the predictions were within threefold error and patient interindividual differences can be predicted with the TCM-New, greatly exceeding the accuracy of the published models. Overall, the new TCM incorporating BPR significantly improved the Vdss predictions in animals and humans for neutral drugs, and, hence, has the potential to better support the drug discovery and facilitate the first-in-human predictions.

Gene expression databases for physiologically based pharmacokinetic modeling of humans and animal species.

In drug research, developing a sound understanding of the key mechanistic drivers of pharmacokinetics (PK) for new molecular entities is essential for human PK and dose predictions. Here, characterizing the absorption, distribution, metabolism, and excretion (ADME) processes is crucial for a mechanistic understanding of the drug-target and drug-body interactions. Sufficient knowledge on ADME processes enables reliable interspecies and human PK estimations beyond allometric scaling. The physiologically based PK (PBPK) modeling framework allows the explicit consideration of organ-specific ADME processes. The sum of all passive and active ADME processes results in the observed plasma PK. Gene expression information can be used as surrogate for protein abundance and activity within PBPK models. The absolute and relative expression of ADME genes can differ between species and strains. This is affecting both, the PK and pharmacodynamics and is therefore posing a challenge for the extrapolation from preclinical findings to humans. We developed an automated workflow that generates whole-body gene expression databases for humans and other species relevant in drug development, animal health, nutritional sciences, and toxicology. Solely, bulk RNA-seq data curated and provided by the Swiss Institute of Bioinformatics from healthy, normal, and untreated primary tissue samples were considered as an unbiased reference of normal gene expression. The databases are interoperable with the Open Systems Pharmacology Suite (PK-Sim and MoBi) and enable seamless access to a central source of curated cross-species gene expression data. This will increase data transparency, increase reliability and reproducibility of PBPK model simulations, and accelerate mechanistic PBPK model development in the future.

Utilization of Physiologically Based Pharmacokinetic Modeling in Pharmacokinetic Study of Natural Medicine: An Overview.

Natural medicine has been widely used for clinical treatment and health care in many countries and regions. Additionally, extracting active ingredients from traditional Chinese medicine and other natural plants, defining their chemical structure and pharmacological effects, and screening potential druggable candidates are also uprising directions in new drug research and development. Physiologically based pharmacokinetic (PBPK) modeling is a mathematical modeling technique that simulates the absorption, distribution, metabolism, and elimination of drugs in various tissues and organs in vivo based on physiological and anatomical characteristics and physicochemical properties. PBPK modeling in drug research and development has gradually been recognized by regulatory authorities in recent years, including the U.S. Food and Drug Administration. This review summarizes the general situation and shortcomings of the current research on the pharmacokinetics of natural medicine and introduces the concept and the advantages of the PBPK model in the study of pharmacokinetics of natural medicine. Finally, the pharmacokinetic studies of natural medicine using the PBPK models are summed up, followed by discussions on the applications of PBPK modeling to the enzyme-mediated pharmacokinetic changes, special populations, new drug research and development, and new indication adding for natural medicine. This paper aims to provide a novel strategy for the preclinical research and clinical use of natural medicine.

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.

Selective Separation and Preconcentration of Caffeine from Natural and Pharmaceutical Products using New Polyurethane Foams

Abstract Two polyurethane foam-based sorbents (PUF) were synthesized by imprinting and grafting techniques and examined for selective separation and preconcentration of caffeine (CAF) in some pharmaceutical products and in black tea. Molecularly imprinted PUF was synthesized based on hydrogen-bonding interactions between CAF and alizarin yellow G (AYG) and subsequent polymerization into PUF. The static experiments indicated optimum sorption conditions at pH=6.5 and 5.5 for imprinted PUF (AY-IPUF) and grafted PUF (AY-GPUF), respectively. In the online experiments, the suitable preconcentration time was found to be 40 and 20s for (AY-IPUF) and (AY-GPUF), respectively, at a flow rate of 1.75 mL.min-1. Desorption of CAF has been affected by passing 500 µL of 0.05, 0.01 mol.L−1 HCl eluent onto (AY-IPUF) and (AY-GPUF), respectively. The online methods have provided satisfactory enrichment factors of 8.4 and 10.5 for (AY-IPUF) and (AY-GPUF), respectively. The time consumed for preconcentartion, elution and determination steps was 1.48 and 1.05 min, thus, the throughput was 42 and 57 h-1, for (AY-IPUF) and (AY-GPUF), respectively. The developed sorbents were studied for the determination of CAF in pharmaceutical samples which will be helpful to minimize caffeinism. Finally, in silico bioactivity, ADMET and drug-likeness predictive computational studies of caffeine were also carried out

Sanguiins-Promising Molecules with Broad Biological Potential.

Compounds of natural origin, an infinite treasure of bioactive chemical entities, persist as an inexhaustible resource for discovering new medicines. In this review, we summarize the naturally occurring ellagitannins, sanguiins, which are bioactive constituents of various traditional medicinal plants, especially from the Rosaceae family. In-depth studies of sanguiin H-6 as an antimicrobial, antiviral, anticancer, anti-inflammatory, and osteoclastogenesis inhibitory agent have led to potent drug candidates. In addition, recently, virtual screening studies have suggested that sanguiin H-6 might increase resistance toward SARS-CoV-2 in the early stages of infection. Further experimental investigations on ADMET (absorption, distribution, metabolism, excretion, and toxicity) supplemented with molecular docking and molecular dynamics simulation are still needed to fully understand sanguiins' mechanism of action. In sum, sanguiins appear to be promising compounds for additional studies, especially for their application in therapies for a multitude of common and debilitating ailments.

Metabolite Identification in the Preclinical and Clinical Phase of Drug Development.

Metabolite identification plays a critical role in the phases during drug development. Drug metabolites can contribute to efficacy, toxicity, and drug-drug interaction. Thus, the correct identification of metabolites is essential to understand the behavior of drugs in humans. Drug administration authorities (e.g., FDA, EMA, and NMPA) emphasize evaluating the safety of human metabolites with exposure higher than 10% of the total drugrelated components. Many previous reviews have summarized the various methods, tools, and strategies for the appropriate and comprehensive identification of metabolites. In this review, we focus on summarizing the importance of identifying metabolites in the preclinical and clinical phases of drug development. Summarized scenarios include the role of metabolites in pharmacokinetics/pharmacodynamics (PK/PD) analysis, disproportional exposure of metabolites that contribute to drug toxicity, changes in metabolite exposure in renal-impaired patients, covalent tyrosine kinase inhibitors (anticancer drugs), and metabolite identification of drug candidates from natural medicines. This review is aimed to provide meaningful insight into the significant role of metabolite identification in drug development.

Neuroprotective potentials of selected natural edible oils using enzyme inhibitory, kinetic and simulation approaches.

BACKGROUND: Edible oils have proven health benefits in the prevention and treatment of various disorders since the establishment of human era. This study was aimed to appraise neuropharmacological studies on the commonly used edible oils including Cinnamomum verum (CV), Zingiber officinale (ZO) and Cuminum cyminum (CC). METHODS: The oils were analyzed via GC-MS for identifications of bioactive compounds. Anti-radicals capacity of the oils were evaluated via 2,2-diphenyl-1-picryl-hydrazyl-hydrate (DPPH) and 2,2'-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid (ABTS) radicals scavenging assays. The samples were also tested against two important acetylcholinesterase (AChE) and butyrylcholinesterase (BChE) which are among the important drug targets in Alzheimer's disease. Lineweaver-Burk plots were constructed for enzyme inhibition studies which correspond to velocity of enzymes (Vmax) against the reciprocal of substrate concentration (Km) in the presence of test samples and control drugs following Michaelis-Menten kinetics. Docking studies on AChE target were also carried out using Molecular Operating Environment (MOE 2016.0802) software. RESULTS: (Gas chromatography-mass spectrometry GC-MS) analysis revealed the presence of thirty-four compounds in Cinnamon oil (Cv.Eo), fourteen in ginger oil (Zo.Eo) and fifty-six in cumin oil (Cc.Eo). In the antioxidant assays, Cv.Eo, Zo.Eo and Cc.Eo exhibited IC50 values of 85, 121, 280 µg/ml sequentially against DPPH radicals. Whereas, in ABTS assay, Cv.Eo, Zo.Eo and Cc.Eo showed considerable anti-radicals potentials with IC50 values of 93, 77 and 271 µg/ml respectively. Furthermore, Cv.Eo was highly active against AChE enzyme with IC50 of 21 µg/ml. Zo.Eo and Cc.Eo exhibited considerable inhibitory activities against AChE with IC50 values of 88 and 198 µg/ml respectively. In BChE assay, Cv.Eo, Zo.Eo and Cc.Eo exhibited IC50 values of 106, 101 and 37 µg/ml respectively. Our results revealed that these oils possess considerable antioxidant and cholinesterase inhibitory potentials. As functional foods these oils can be effective remedy for the prevention and management of neurological disorders including AD. Synergistic effect of all the identified compounds was determined via binding energy values computed through docking simulations. Binding orientations showed that all the compounds interact with amino acid residues present in the peripheral anionic site (PAS) and catalytic anionic site (CAS) amino acid residues, oxyanion hole and acyl pocket via π-π stacking interactions and hydrogen bond interactions.

The impact of catha edulis (vahl) forssk. ex endl. (celestraceae) (khat) on pharmacokinetics of clinically used drugs.

INTRODUCTION: Catha edulis (Vahl) Forssk. ex Endl. (Celestraceae) is used as a recreational drug on daily basis for its euphoric and psychostimulant effects. It is also chewed by individuals who are on medications, raising the possibility of drug-khat interaction. However, limited data are available in the literature, although clinically significant interactions are expected, as khat contains a complex mixture of pharmacologically active constituents. AREAS COVERED: It provides an overview of the phytochemistry, pharmacokinetics, pharmacodynamics, and pharmacogenetics of khat based on the literature mined from PubMed, Google Scholar, and Cochrane databases. It also presents a detailed account of drug-khat interactions with specific examples and their clinical significance. The interactions mainly occur at the pharmacokinetics level and particular attention is paid for the phases of absorption and cytochrome P450 enzyme-mediated metabolism. EXPERT OPINION: Despite the increasing trend of khat chewing with medications among the populace and the potential risk for the occurrence of clinically significant interactions, there is paucity of data in the literature demonstrating the magnitude of the risk. The available data, however, clearly demonstrate that the consequence of drug-khat interaction is dependent on genotype. Genotyping, where feasible, could be used to improve clinical outcome and minimize adverse reactions.

Bioequivalence assessment of pharmaceutical aerosol products through IVIVC.

Many pharmaceutical developers of generic orally inhaled products (OIPs) are facing significant issues in passing the regulatory requirement to show pharmacokinetic (PK) bioequivalence (BE) to the originator product. The core of the issue is that no reliable in vitro-in vivo correlation (IVIVC) is available to guide their development. In this paper, several issues are identified and means to improve the data used for developing an IVIVC are discussed. The article also presents an "IVIVC-free" approach for developing a formulation matching the originator's PK performance.

Chrono-Drug Discovery and Development Based on Circadian Rhythm of Molecular, Cellular and Organ Level.

The paired suprachiasmatic nuclei (SCN) is the circadian pacemaker in mammals. Clock genes ultimately regulates a vast array of circadian rhythms involved in biological, physiological and behavioral process. The clock genes are closely related to sleep disorders, metabolic syndromes, and cancer diseases. Monitoring rhythm, overcoming rhythm disruption, and manipulating rhythm from the perspective of the clock genes play an important role to improve chronopharmacotherapy. Such an approach should be achieved by overcoming the new challenges in drug delivery systems that match the circadian rhythm (Chrono-DDS). Gene and antibody delivery, targeting specific molecules for certain diseases have been focused in recent studies on pharmacotherapy. One of important candidates should also be clock genes. New drugs targeting the molecular clock are being developed to manage diseases in humans. The circadian dynamics of cancer stem cells are controlled by the tumor microenvironment and provide proof for its implication in chronotherapy against triple-negative breast cancer. To examine the relationship between the circadian clock and chronic kidney disease (CKD) exacervation leads to clarify the novel molecular mechanisms causing renal malfunction in mice with CKD. A novel inhibitor of cell cycle regulatory factors has been identified and the inhibitor repressed renal inflammation in a CKD mouse model. Therefore, this review aims to introduce the role of the molecular clock in the time-dependent dosing changes in the therapeutic effect and safety of a drug and the possibility of drug discovery and development based on the molecular clock.

Fast screening of covariates in population models empowered by machine learning.

One of the objectives of Pharmacometry (PMX) population modeling is the identification of significant and clinically relevant relationships between parameters and covariates. Here, we demonstrate how this complex selection task could benefit from supervised learning algorithms using importance scores. We compare various classical methods with three machine learning (ML) methods applied to NONMEM empirical Bayes estimates: random forest, neural networks (NNs), and support vector regression (SVR). The performance of the ML models is assessed using receiver operating characteristic (ROC) curves. The F1 score, which measures test accuracy, is used to compare ML and PMX approaches. Methods are applied to different scenarios of covariate influence based on simulated pharmacokinetics data. ML achieved similar or better F1 scores than stepwise covariate modeling (SCM) and conditional sampling for stepwise approach based on correlation tests (COSSAC). Correlations between covariates and the number of false covariates does not affect the performance of any method, but effect size has an impact. Methods are not equivalent with respect to computational speed; SCM is 30 and 100-times slower than NN and SVR, respectively. The results are validated in an additional scenario involving 100 covariates. Taken together, the results indicate that ML methods can greatly increase the efficiency of population covariate model building in the case of large datasets or complex models that require long run-times. This can provide fast initial covariate screening, which can be followed by more conventional PMX approaches to assess the clinical relevance of selected covariates and build the final model.

Natural soluble epoxide hydrolase inhibitors from Alisma orientale and their potential mechanism with soluble epoxide hydrolase.

Inhibition of soluble epoxide hydrolase (sEH) is considered to be an effective treatment for inflammation-related diseases, and small molecules origin from natural products show promising activity against sEH. Two undescribed protostanes, 3ß-hydroxy-25-anhydro-alisol F (1) and 3ß-hydroxy-alisol G (2) were isolated from Alisma orientale and identified as new sEH inhibitors with IC50 values of 10.06 and 30.45 µM, respectively. Potential lead compound 1 was determined as an uncompetitive inhibitor against sEH, which had a Ki value of 5.13 µM. In-depth molecular docking and molecular dynamics simulations revealed that amino acid residue Ser374 plays an important role in the inhibition of 1, which also provides an idea for the development of sEH inhibitors based on protostane-type triterpenoids.

Advances in Predictions of Oral Bioavailability of Candidate Drugs in Man with New Machine Learning Methodology.

Oral bioavailability (F) is an essential determinant for the systemic exposure and dosing regimens of drug candidates. F is determined by numerous processes, and computational predictions of human estimates have so far shown limited results. We describe a new methodology where F in humans is predicted directly from chemical structure using an integrated strategy combining 9 machine learning models, 3 sets of structural alerts, and 2 physiologically-based pharmacokinetic models. We evaluate the model on a benchmark dataset consisting of 184 compounds, obtaining a predictive accuracy (Q2) of 0.50, which is successful according to a pharmaceutical industry proposal. Twenty-seven compounds were found (beforehand) to be outside the main applicability domain for the model. We compare our results with interspecies correlations (rat, mouse and dog vs. human) using the same dataset, where animal vs. human-correlations (R2) were found to be 0.21 to 0.40 and maximum prediction errors were smaller than maximum interspecies differences. We conclude that our method has sufficient predictive accuracy to be practically useful with applications in human exposure and dose predictions, compound optimization and decision making, with potential to rationalize drug discovery and development and decrease failures and overexposures in early clinical trials with candidate drugs.

Phosphorus-mediated sp2-sp3 couplings for C-H fluoroalkylation of azines.

Fluoroalkyl groups profoundly affect the physical properties of pharmaceuticals and influence almost all metrics associated with their pharmacokinetic and pharmacodynamic profile1-4. Drug candidates increasingly contain trifluoromethyl (CF3) and difluoromethyl (CF2H) groups, and the same trend in agrochemical development shows that the effect of fluoroalkylation translates across human, insect and plant life5,6. New fluoroalkylation reactions have undoubtedly stimulated this shift; however, methods that directly convert C-H bonds into C-CF2X groups (where X is F or H) in complex drug-like molecules are rare7-13. Pyridines are the most common aromatic heterocycles in pharmaceuticals14, but only one approach-via fluoroalkyl radicals-is viable for achieving pyridyl C-H fluoroalkylation in the elaborate structures encountered during drug development15-17. Here we develop a set of bench-stable fluoroalkylphosphines that directly convert the C-H bonds in pyridine building blocks, drug-like fragments and pharmaceuticals into fluoroalkyl derivatives. No preinstalled functional groups or directing groups are required. The reaction tolerates a variety of sterically and electronically distinct pyridines, and is exclusively selective for the 4-position in most cases. The reaction proceeds through initial formation of phosphonium salts followed by sp2-sp3 coupling of phosphorus ligands-an underdeveloped manifold for forming C-C bonds.

A randomized trial to examine the impact of food on pharmacokinetics of 4-phenylbutyrate and change in amino acid availability after a single oral administration of sodium 4-phenylbutyrarte in healthy volunteers.

Urea cycle disorders (UCDs), inborn errors of hepatocyte metabolism, result in the systemic accumulation of ammonia to toxic levels. Sodium 4-phenylbutyrate (NaPB), a standard therapy for UCDs for over 20 years, generates an alternative pathway of nitrogen deposition through glutamine consumption. Administration during or immediately after a meal is the accepted use of NaPB. However, this regimen is not based on clinical evidence. Here, an open-label, single-dose, five-period crossover study was conducted in healthy adults to investigate the effect of food on the pharmacokinetics of NaPB and determine any subsequent change in amino acid availability. Twenty subjects were randomized to one of four treatment groups. Following an overnight fast, NaPB was administered orally at 4.3 g/m2 (high dose, HD) or 1.4 g/m2 (low dose, LD) either 30 min before or just after breakfast. At both doses, compared with post-breakfast administration, pre-breakfast administration significantly increased systemic exposure of PB and decreased plasma glutamine availability. Pre-breakfast LD administration attenuated plasma glutamine availability to the same extent as post-breakfast HD administration. Regardless of the regimen, plasma levels of branched-chain amino acids (BCAA) were decreased below baseline in a dose-dependent manner. In conclusion, preprandial oral administration of NaPB maximized systemic exposure of the drug and thereby its potency to consume plasma glutamine. This finding may improve poor medication compliance because of the issues with odor, taste, and pill burden of NaPB and reduce the risk of BCAA deficiency in NaPB therapy.

Traditional Chinese Medicine Formulas Alleviate Acute Pancreatitis: Pharmacological Activities and Mechanisms.

ABSTRACT: Acute pancreatitis (AP) is a common clinical gastrointestinal disorder with a high mortality rate for severe AP and lacks effective clinical treatment, which leads to considerable comorbidity and financial burden. Traditional Chinese medicine (TCM) has had the unique advantage of treating AP for a long time in China. Clinically, TCM formulas such as Da-cheng-qi decoction, Chai-qin-cheng-qi decoction, Qing-yi decoction, Da-chai-hu decoction, and Da-huang-fu-zi decoction are widely administrated to AP patients. All of these TCM formulas can improve gastrointestinal function, regulate the inflammatory response, and enhance immunity, thus preventing complications, reducing the mortality rate and financial burden. This review will summarize the pharmacological activities and mechanisms of TCM formulas in alleviating AP.

Current development of integrated web servers for preclinical safety and pharmacokinetics assessments in drug development.

In drug development, preclinical safety and pharmacokinetics assessments of candidate drugs to ensure the safety profile are a must. While in vivo and in vitro tests are traditionally used, experimental determinations have disadvantages, as they are usually time-consuming and costly. In silico predictions of these preclinical endpoints have each been developed in the past decades. However, only a few web-based tools have integrated different models to provide a simple one-step platform to help researchers thoroughly evaluate potential drug candidates. To efficiently achieve this approach, a platform for preclinical evaluation must not only predict key ADMET (absorption, distribution, metabolism, excretion and toxicity) properties but also provide some guidance on structural modifications to improve the undesired properties. In this review, we organized and compared several existing integrated web servers that can be adopted in preclinical drug development projects to evaluate the subject of interest. We also introduced our new web server, Virtual Rat, as an alternative choice to profile the properties of drug candidates. In Virtual Rat, we provide not only predictions of important ADMET properties but also possible reasons as to why the model made those structural predictions. Multiple models were implemented into Virtual Rat, including models for predicting human ether-a-go-go-related gene (hERG) inhibition, cytochrome P450 (CYP) inhibition, mutagenicity (Ames test), blood-brain barrier penetration, cytotoxicity and Caco-2 permeability. Virtual Rat is free and has been made publicly available at https://virtualrat.cmdm.tw/.

Characterization and Validation of Canine P-Glycoprotein-Deficient MDCK II Cell Lines for Efflux Substrate Screening.

PURPOSE: We characterized three canine P-gp (cP-gp) deficient MDCKII cell lines. Their relevance for identifying efflux transporter substrates and predicting limitation of brain penetration were evaluated. In addition, we discuss how compound selection can be done in drug discovery by using these cell systems. METHOD: hMDR1, hBCRP-transfected, and non-transfected MDCKII ZFN cells (all with knock-down of endogenous cP-gp) were used for measuring permeability and efflux ratios for substrates. The compounds were also tested in MDR1_Caco-2 and BCRP_Caco-2, each with a double knock-out of BCRP/MRP2 or MDR1/MRP2 transporters respectively. Efflux results were compared between the MDCK and Caco-2 models. Furthermore, in vitro MDR1_ZFN efflux data were correlated with in vivo unbound drug brain-to-plasma partition coefficient (Kp,uu). RESULTS: MDR1 and BCRP substrates are correctly classified and robust transporter affinities with control substrates are shown. Cell passage mildly influenced mRNA levels of transfected transporters, but the transporter activity was proven stable for several years. The MDCK and Caco-2 models were in high consensus classifying same efflux substrates. Approx. 80% of enlisted substances were correctly predicted with the MDR1_ZFN model for brain penetration. CONCLUSION: cP-gp deficient MDCKII ZFN models are reliable tools to identify MDR1 and BCRP substrates and useful for predicting efflux liability for brain penetration.

The Effect of Coffee on Pharmacokinetic Properties of Drugs : A Review.

BACKGROUND: Coffee has been the most commercialized food product and most widely consumed stimulant beverage in the world. It is a major source of caffeine which is the most bioactive component of coffee. Although both the United States Department of Agriculture and European Food Safety Authority consider daily intake of coffee which contains 400 mg of caffeine as safe for health, it causes different clinically significant pharmacokinetic interactions with many drugs. The aim of this work was to review the effect of coffee on the pharmacokinetic properties of drugs. METHOD: This review was done by investigating the in vitro and in vivo research findings, clinical case reports, and expert panels from credible sources including Scopus, PubMed, Hindawi, OVID, Google Scholar, Embase, Cochrane Library, and Web of Science. RESULT: Several studies and medical case reports evidently showed that concomitant consumption of coffee significantly affects the absorption, distribution, metabolism, and excretion of many drugs. These effects of coffee on the pharmacokinetics of drugs could lead to enhanced therapeutic response, therapeutic failure, or toxic reactions. Conclusion and Recommendation. Concomitant use of coffee should be avoided with medications which have a significant interaction with coffee. There should be an appropriate time gap between intake of drugs and coffee based on drug properties. Pharmacists and clinicians should be aware of the potential risks of drug-coffee interaction and advice patients appropriately. Further in vitro and in vivo studies should be done for frequently prescribed drugs to get a strong evidence on the pharmacokinetic interaction with coffee.