Public knowledge and attitude towards drug-food interactions: implications for improved public health safety.

Drug-Food Interaction (DFI) can potentially lead to treatment ineffectiveness and adverse health outcomes. This study investigated knowledge and attitude towards DFI and the associated factors. A validated questionnaire was distributed to 2040 participants across Jordan. The participants had moderate knowledge and attitudes regarding DFIs. Regression results revealed that male gender, lower education level, not working in the healthcare sector, and utilizing non-scientific sources of information about DFIs were associated with lower knowledge about DFI. Furthermore, male gender, being unmarried, having a low or moderate education level, not working in the healthcare sector, not having a family member with chronic disease, and having low knowledge of DFI were significantly associated with negative attitudes towards DFIs. Future health education programs should emphasize using reliable scientific sources to enhance awareness about DFIs'. Additionally, healthcare professionals should counsel patients on avoiding DFIs and provide guidance accordingly.

An annotated corpus from biomedical articles to construct a drug-food interaction database.

MOTIVATION: While drug-food interaction (DFI) may undermine the efficacy and safety of drugs, DFI detection has been difficult because a well-organized database for DFI did not exist. To construct a DFI database and build a natural language processing system extracting DFI from biomedical articles, we formulated the DFI extraction tasks and manually annotated texts that could have contained DFI information. In this article, we introduced a new annotated corpus for extracting DFI, the DFI corpus. RESULTS: The DFI corpus contains 2270 abstracts of biomedical articles accessible through PubMed and 2498 sentences that contain DFI and/or drug-drug information (DDI), a substantial amount of information about drug/food entities, evidence-levels of abstracts and relations between named entities. BERT models pre-trained on the biomedical domain achieved a F1 score 55.0% in extracting DFI key-sentences. To the best of our knowledge, the DFI corpus is the largest public corpus for drug-food interaction. AVAILABILITY AND IMPLEMENTATION: Our corpus is available at https://github.com/ccadd-snu/corpus-for-DFI-extraction.

Intestinal Absorption of Alogliptin Is Mediated by a Fruit-Juice-Sensitive Transporter.

Alogliptin (ALG), an inhibitor of dipeptidylpeptidase-4, is used in the management of type 2 diabetes mellitus, and has a high absorption rate (>60-71%), despite its low lipophilicity (logP=-1.4). Here, we aimed to clarify the mechanism of its intestinal absorption. ALG uptake into Caco-2 cells was time-, temperature-, and concentration-dependent, but was not saturated at concentrations up to 10 mmol/L. The uptake was significantly inhibited by the organic anion transporting polypeptide (OATP) substrate fexofenadine and by the OATP inhibitor 4,4'-diisothiocyanostilbene-2,2'-disulfonic acid (DIDS), but was not inhibited by organic cation transporter (OCT)/organic cation/carnitine transporter (OCTN) or peptide transporter 1 (PEPT1) substrates. Grapefruit, orange, and apple juices and their constituents, which are known to strongly inhibit intestinal OATPs, significantly inhibited ALG uptake into Caco-2 cells. The pH dependence was bell-shaped, indicating the involvement of a pH-sensitive transporter. However, ALG uptake by HEK293 cells overexpressing OATP2B1, a key intestinal OATP transporter of amphiphilic drugs, was not different from that of mock cells. In a rat in vivo study, apple juice reduced systemic exposure to orally administered ALG without changing the terminal half-life. These observations suggest that intestinal absorption of ALG is carrier-mediated, and involves a fruit-juice-sensitive transporter other than OATP2B1.

Inhibitory Effects of Juices Prepared from Individual Vegetables on CYP3A4 Activity in Recombinant CYP3A4 and LS180 Cells.

Human intestinal absorption and drug metabolism vary to a large extent among individuals. For example, CYP3A4 activity has large individual variation that cannot be attributed to only genetic differences. Various flavonoids in vegetables, such as kaempferol and quercetin, possess inhibitory effects, and some vegetable and fruit juices have also been found to inhibit CYP3A4 activity. Therefore, differences in daily intake of flavonoid-containing vegetables may induce individual variation in intestinal bioavailability. To identify a vegetable that strongly inhibits CYP3A4, we investigated the effects of juices, prepared from individual vegetables, on CYP3A4 activity using recombinant CYP3A4 and LS180 cells in this study. Nine vegetable juices (cabbage, Japanese radish, onion, tomato, eggplant, carrot, Chinese cabbage, green pepper, and lettuce), were prepared and recombinant CYP3A4 and LS180 cells were used for evaluation of CYP3A4 activity. Metabolism to 6ß-hydroxytestosterone by recombinant CYP3A4 was strongly inhibited by cabbage, onion, and green pepper juices, and cabbage and green pepper juices significantly inhibited CYP3A4 activity in a preincubation time-dependent manner. In addition, CYP3A4 activity in LS180 cells was significantly inhibited by cabbage and onion juices. In conclusion, this study showed that juices prepared from some individual vegetables could significantly inhibit CYP3A4 activity. Therefore, variation in the daily intake of vegetables such as cabbage and onion may be one of the factors responsible for individual differences in intestinal bioavailability.

Vitamin D deficiency as adverse drug reaction? A cross-sectional study in Dutch geriatric outpatients.

PURPOSE: Adverse drug reactions as well as vitamin D deficiency are issues of public health concern in older people. However, relatively little is known about the impact of drug use on vitamin D status. Our primary aim is to explore associations between drug use and vitamin D status in older people. Furthermore, prevalences of drug use and vitamin D deficiency are estimated. METHODS: In a population of 873 community-dwelling Dutch geriatric outpatients, we explored the cross-sectional relationships of polypharmacy (≥5 medications concomitantly used), severe polypharmacy (≥10 medications), and use of twenty-one specific drug groups, with serum 25-hydroxyvitamin D (25(OH)D) by analysis of covariance. RESULTS: Overall prevalence of polypharmacy was 65 %, of severe polypharmacy 22 %. Depending on the cut-off value, prevalence of vitamin D deficiency was 49 % (<50 nmol/l) or 77 % (<75 nmol/l). Of the patients using a vitamin D supplement, 17 % (<50 nmol/l) or 49 % (<75 nmol/l) were still deficient. In non-users of supplemental vitamin D, after adjustment for age and gender, negative associations were found for severe polypharmacy, metformin, sulphonamides and urea derivatives (SUDs), vitamin K antagonists, cardiac glycosides, loop diuretics, potassium-sparing diuretics, ACE inhibitors, and serotonin reuptake inhibitors; for non-selective monoamine reuptake inhibitors (NSMRIs) the association was positive. The most extreme impacts of drug use on adjusted mean 25(OH)D were -19 nmol/l for SUDs and +18 nmol/l for NSMRIs. CONCLUSION: Drug use should be considered a risk factor for vitamin D deficiency amongst geriatric outpatients.

Enhancing drug-food interaction prediction with precision representations through multilevel self-supervised learning.

Drug-food interactions (DFIs) crucially impact patient safety and drug efficacy by modifying absorption, distribution, metabolism, and excretion. The application of deep learning for predicting DFIs is promising, yet the development of computational models remains in its early stages. This is mainly due to the complexity of food compounds, challenging dataset developers in acquiring comprehensive ingredient data, often resulting in incomplete or vague food component descriptions. DFI-MS tackles this issue by employing an accurate feature representation method alongside a refined computational model. It innovatively achieves a more precise characterization of food features, a previously daunting task in DFI research. This is accomplished through modules designed for perturbation interactions, feature alignment and domain separation, and inference feedback. These modules extract essential information from features, using a perturbation module and a feature interaction encoder to establish robust representations. The feature alignment and domain separation modules are particularly effective in managing data with diverse frequencies and characteristics. DFI-MS stands out as the first in its field to combine data augmentation, feature alignment, domain separation, and contrastive learning. The flexibility of the inference feedback module allows its application in various downstream tasks. Demonstrating exceptional performance across multiple datasets, DFI-MS represents a significant advancement in food presentations technology. Our code and data are available at https://github.com/kkkayle/DFI-MS.

Streamlining Food Effect Assessment - Are Repeated Food Effect Studies Needed? An IQ Analysis.

Current regulatory guidelines on drug-food interactions recommend an early assessment of food effect to inform clinical dosing instructions, as well as a pivotal food effect study on the to-be-marketed formulation if different from that used in earlier trials. Study waivers are currently only granted for BCS class 1 drugs. Thus, repeated food effect studies are prevalent in clinical development, with the initial evaluation conducted as early as the first-in-human studies. Information on repeated food effect studies is not common in the public domain. The goal of the work presented in this manuscript from the Food Effect PBPK IQ Working Group was to compile a dataset on these studies across pharmaceutical companies and provide recommendations on their conduct. Based on 54 studies collected, we report that most of the repeat food effect studies do not result in meaningful differences in the assessment of the food effect. Seldom changes observed were more than twofold. There was no clear relationship between the change in food effect and the formulation change, indicating that in most cases, once a compound is formulated appropriately within a specific formulation technology, the food effect is primarily driven by inherent compound properties. Representative examples of PBPK models demonstrate that following appropriate validation of the model with the initial food effect study, the models can be applied to future formulations. We recommend that repeat food effect studies should be approached on a case-by-case basis taking into account the totality of the evidence including the use of PBPK modeling.

Novel food drug interaction mechanism involving acyclovir, chitosan and endogenous mucus.

Drug absorption from drug products may be affected by pharmaceutical excipients and/or food additives through different mechanisms. Chitosan is a recognized nutraceutical, with potential as an excipient due to its permeability enhancer properties. While chitosan properties have been evaluated in in vitro and pre-clinical models, studies in humans are scarce. Unexpectedly, a controlled clinical trial showed chitosan actually reduced acyclovir bioavailability. The effect seems to be related to an interaction with gastrointestinal mucus that prevents further absorption, although more in depth research is needed to unravel the mechanism. In this paper, we propose a mechanism underlying this excipient effect. The mucus - chitosan interaction was characterized and its effect on acyclovir diffusion, permeation and bioaccessibility was investigated. Further, pharmacokinetic modeling was used to assess the clinical relevance of our findings. Results suggest that in situ coacervation between endogenous mucus and chitosan rapidly entrap 20-30% of acyclovir dissolved dose in the intestinal lumen. This local reduction of acyclovir concentration together with its short absorption window in the small intestine would explain the reduction in acyclovir Cmax and AUC. This study highlights the importance of considering mucus in any biorelevant absorption model attempting to anticipate the effect of chitosan on drug absorption.

A Physiologically Based Pharmacokinetic Model of Ketoconazole and Its Metabolites as Drug-Drug Interaction Perpetrators.

The antifungal ketoconazole, which is mainly used for dermal infections and treatment of Cushing's syndrome, is prone to drug-food interactions (DFIs) and is well known for its strong drug-drug interaction (DDI) potential. Some of ketoconazole's potent inhibitory activity can be attributed to its metabolites that predominantly accumulate in the liver. This work aimed to develop a whole-body physiologically based pharmacokinetic (PBPK) model of ketoconazole and its metabolites for fasted and fed states and to investigate the impact of ketoconazole's metabolites on its DDI potential. The parent-metabolites model was developed with PK-Sim® and MoBi® using 53 plasma concentration-time profiles. With 7 out of 7 (7/7) DFI AUClast and DFI Cmax ratios within two-fold of observed ratios, the developed model demonstrated good predictive performance under fasted and fed conditions. DDI scenarios that included either the parent alone or with its metabolites were simulated and evaluated for the victim drugs alfentanil, alprazolam, midazolam, triazolam, and digoxin. DDI scenarios that included all metabolites as reversible inhibitors of CYP3A4 and P-gp performed best: 26/27 of DDI AUClast and 21/21 DDI Cmax ratios were within two-fold of observed ratios, while DDI models that simulated only ketoconazole as the perpetrator underperformed: 12/27 DDI AUClast and 18/21 DDI Cmax ratios were within the success limits.

Knowledge of Drug-Food Interactions Among Healthcare Professionals Working in Public Hospitals in Ethiopia.

Background: Drug-food interactions can result in unfavorable outcomes during the treatment of patients. Healthcare professionals (HCPs) should advise patients on drug-food interactions. Knowledge of such interactions is crucial to avoid their occurrence. However, there is no information regarding the knowledge of HCPs about drug-food interactions in Harari Regional State. Objective: To assess knowledge of drug-food interactions and associated factors among HCPs working in public hospitals in Harari Regional State, Eastern Ethiopia from April 15 to May 15, 2022. Methods: A cross-sectional study was conducted in public hospitals in Harari Regional State, Eastern Ethiopia, among 251 HCPs. After stratification was done based on profession (pharmacists, nurses, and doctors), the sample size was proportionally allocated for the respective groups. Data were collected using a standardized self-administered questionnaire, entered into Epi-Data 3.1 and analyzed using Statistical Package for Social Sciences 26.0. Descriptive statistics were used to summarize variables. Multivariable logistic regression was done to determine factors associated with knowledge of drug-food interactions. P < 0.05 was used to declare significant association. Results: Among the HCPs who completed the questionnaire, 56 (22.3%), 36 (14.3%), and 159 (63.3%) were doctors, pharmacists, and nurses, respectively. The majority of the HCPs were males (174 (69.3%)). The mean age of the HCPs was 27.6±3.8. The mean knowledge score±SD of the HCPs was 28.6±6.6 out of an overall score of 59. The HCPs poorly identified drug-food interactions and the correct administration time of drugs relative to meals. Being a pharmacist (AOR: 2.8, CI: 1.3-6.4, p-value=0.012), and working at a tertiary hospital (AOR: 3.9, CI: 2.1-7.3, p-value <0.001), were associated with higher knowledge of drug-food interactions. Conclusion: The HCPs in this study had inadequate knowledge of drug-food interactions. Thus, additional educational courses and training should be provided in order to improve knowledge regarding drug-food interaction.

Development and Evaluation of a Physiologically Based Pharmacokinetic Model of Labetalol in Healthy and Diseased Populations.

Labetalol is a drug that exhibits both alpha and beta-adrenergic receptor-blocking properties. The American Heart Association/American Stroke Association (AHA/ASA) has recommended labetalol as an initial treatment option for the management of severe hypertension. The physiologically based pharmacokinetic (PBPK) model is an in silico approach to determining the pharmacokinetics (PK) of a drug by incorporating blood flow and tissue composition of the organs. This study was conducted to evaluate the primary reasons for the difference in PK after intravenous (IV) and oral administration in healthy and diseased (renal and hepatic) populations. A comprehensive literature search was done using two databases, PubMed and Google Scholar. Various PK parameters were screened for the development of the PBPK model utilizing a population-based PK-Sim simulator. Simulations were performed after creating building blocks firstly in healthy individuals and then in diseased patients after IV and oral administration. The disposition of labetalol after IV and oral administration occurring in patients with the hepatic and renal disease was predicted. The model was evaluated by calculating the Robs/pred ratio and average fold error (AFE), which was in the two-fold error range. Moreover, Box-whisker plots were made to compare the overall concentration of the drug in the body at various stages of disease severity. The presented model provides useful quantitative estimates of drug dosing in patients fighting against severe chronic diseases.

Food Effect Study to Assess the Impact on Edaravone Pharmacokinetic Profiles in Healthy Participants.

PURPOSE: The safety and efficacy of intravenous edaravone, a neuroprotectant used for the treatment of amyotrophic lateral sclerosis (ALS), have been shown in clinical trials. An oral suspension of edaravone has been developed, but the food effect on its pharmacokinetic profile has not been evaluated. This study aimed to assess the food effect on the pharmacokinetic profile of edaravone after oral administration and to investigate dosing regimens and administration instructions with different meal intake and timing. METHODS: Data from 3 Phase I clinical studies were used to evaluate the effect of food on the pharmacokinetic profiles of a single dose of edaravone oral suspension. In all 3 studies, participants received a single dose of edaravone with various meal conditions. Healthy Japanese adult male participants (Studies 1, 2, and 3) or female participants (Study 3) aged 20 to 45 years at the time of informed consent were included. FINDINGS: In Study 1, 6 participants were enrolled and 5 completed the study. Nine and 16 participants were treated in Studies 2 and 3, respectively, and all completed the study. The Cmax and AUC0-∞ of edaravone were lower when administered 30 minutes after a high-fat meal compared with those in a fasted condition (Study 1). Lower plasma edaravone concentrations (approximately within the first hour) and subsequent lower Cmax and AUC0-∞ were observed after administration of edaravone 4 hours after a high-fat meal (Study 2) or 2 hours after a low-fat meal (Study 3). The Cmax and AUC0-∞ of oral edaravone were generally similar and not affected when administered 8 hours after a high-fat meal, 4 hours after a low-fat meal, or 2 hours after a light meal relative to the fasted condition. Administration of edaravone 1 hour before a high-fat meal resulted in no effect on Cmax or AUC0-∞ relative to the fasted condition. Administration of edaravone in the fed or fasted conditions resulted in a similar urine pharmacokinetic profile. IMPLICATIONS: Oral administration of edaravone with a meal decreased the plasma concentration of edaravone. Oral administration of edaravone 8 hours after a high-fat meal, 4 hours after a low-fat meal, 2 hours after a light meal, and 1 hour before a high-fat meal showed no effect of food on the PK profile of unchanged edaravone compared with that observed under a fasted condition. CLINICALTRIALS: gov identifiers: NCT04481750, NCT04481789, and NCT05342597.

The Overview on the Pharmacokinetic and Pharmacodynamic Interactions of Triazoles.

Second generation triazoles are widely used as first-line drugs for the treatment of invasive fungal infections, including aspergillosis and candidiasis. This class, along with itraconazole, voriconazole, posaconazole, and isavuconazole, is characterized by a broad range of activity, however, individual drugs vary considerably in safety, tolerability, pharmacokinetics profiles, and interactions with concomitant medications. The interaction may be encountered on the absorption, distribution, metabolism, and elimination (ADME) step. All triazoles as inhibitors or substrates of CYP isoenzymes can often interact with many drugs, which may result in the change of the activity of the drug and cause serious side effects. Drugs of this class should be used with caution with other agents, and an understanding of their pharmacokinetic profile, safety, and drug-drug interaction profiles is important to provide effective antifungal therapy. The manuscript reviews significant drug interactions of azoles with other medications, as well as with food. The PubMed and Google Scholar bases were searched to collect the literature data. The interactions with anticonvulsants, antibiotics, statins, kinase inhibitors, proton pump inhibitors, non-nucleoside reverse transcriptase inhibitors, opioid analgesics, benzodiazepines, cardiac glycosides, nonsteroidal anti-inflammatory drugs, immunosuppressants, antipsychotics, corticosteroids, biguanides, and anticoagulants are presented. We also paid attention to possible interactions with drugs during experimental therapies for the treatment of COVID-19.

A Questionnaire-Based Survey to Assess the Level of Knowledge and Awareness about Drug-Food Interactions among General Public in Western Saudi Arabia.

Introduction: Various drug-food interactions exist that may hinder treatment and can sometimes be lethal. Our aim was to assess the level of public knowledge and awareness in Jeddah city, Western Saudi Arabia, about drug-food interactions, along with the effects of demographics on their knowledge. Methods: A survey questionnaire was administered in this cross-sectional study to participants spread across multiple locations in Jeddah, including in malls and public gatherings. Participants included both males and females. Sample size was calculated through Raosoft® software. Data analysis was executed using IBM Statistic SPSS and the level of statistical significance was set at p < 0.05. Results: A total of 410 people participated in the study and only 92.68% (380) of responses were enrolled in the study; 7.32% (30) were not enrolled due to the exclusion criteria. Surprisingly, only six out of eighteen questions regarding drug-food interactions in the administered questionnaire were correctly answered by 380 participants. Data indicated that the participants had a poor to intermediate level of both knowledge and awareness with respect to drug-food interactions. Furthermore, participants showed moderate to strong awareness of the effects of alcohol and tea generally, and their interaction with medication. Conclusion: Participants in our study showed inadequate knowledge of basic and fundamental information about drug-food interactions, which highlights the dire need to increase awareness.

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.

The involvement of human organic anion transporting polypeptides (OATPs) in drug-herb/food interactions.

Organic anion transporting polypeptides (OATPs) are important transporter proteins that are expressed at the plasma membrane of cells, where they mediate the influx of endogenous and exogenous substances including hormones, natural compounds and many clinically important drugs. OATP1A2, OATP2B1, OATP1B1 and OATP1B3 are the most important OATP isoforms and influence the pharmacokinetic performance of drugs. These OATPs are highly expressed in the kidney, intestine and liver, where they determine the distribution of drugs to these tissues. Herbal medicines are increasingly popular for their potential health benefits. Humans are also exposed to many natural compounds in fruits, vegetables and other food sources. In consequence, the consumption of herbal medicines or food sources together with a range of important drugs can result in drug-herb/food interactions via competing specific OATPs. Such interactions may lead to adverse clinical outcomes and unexpected toxicities of drug therapies. This review summarises the drug-herb/food interactions of drugs and chemicals that are present in herbal medicines and/or food in relation to human OATPs. This information can contribute to improving clinical outcomes and avoiding unexpected toxicities of drug therapies in patients.

Drug use is associated with lower plasma magnesium levels in geriatric outpatients; possible clinical relevance.

BACKGROUND: Hypomagnesemia has been associated with diabetes, cardiovascular disease, and other disorders. Drug use has been suggested as one of the risk factors for low magnesium (Mg) levels. In the elderly population, prone to polypharmacy and inadequate Mg intake, hypomagnesemia might be relevant. Therefore, we aimed to investigate associations between drug use and plasma Mg. METHODS: Cross-sectional data of 343 Dutch geriatric outpatients were analysed by Cox and linear regression, while adjusting for covariates. Drug groups were coded according to the Anatomical Therapeutic Chemical classification system; use was compared to non-use. Hypomagnesemia was defined as plasma Mg < 0.75 mmol/l and <0.70 mmol/l. RESULTS: Prevalence of hypomagnesemia was 22.2% (Mg < 0.75 mmol/l) or 12.2% (Mg < 0.70 mmol/l); 67.6% of the patients used ≥5 medications (polypharmacy). The number of different drugs used was inversely linearly associated with Mg level (beta -0.01; p < 0.01). Fully adjusted Cox regression showed significant associations of polypharmacy with hypomagnesemia (Mg < 0.75 mmol/l) (prevalence ratio (PR) 1.81; 95%CI 1.08-3.14), proton pump inhibitors (PR 1.80; 95%CI 1.20-2.72), and metformin (PR 2.34; 95%CI 1.56-3.50). Moreover, stratified analyses pointed towards associations with calcium supplements (PR 2.26; 95%CI 1.20-4.26), insulins (PR 3.88; 95%CI 2.19-6.86), vitamin K antagonists (PR 2.01; 95%CI 1.05-3.85), statins (PR 2.44; 95%CI 1.31-4.56), and bisphosphonates (PR 2.97; 95%CI 1.65-5.36) in patients <80 years; selective beta blockers (PR 2.01; 95%CI 1.19-3.40) if BMI <27.0 kg/m2; and adrenergic inhalants in male users (PR 3.62; 95%CI 1.73-7.56). Linear regression supported these associations. CONCLUSION: As polypharmacy and several medications are associated with hypomagnesemia, Mg merits more attention, particularly in diabetes, cardiovascular disease, and in side-effects of proton pump inhibitors and calcium supplements.

Inhibitory kinetics of fruit components on CYP2C19 activity.

It has been suggested that the fruit components resveratrol (RSV), 6', 7'-dihydroxybergamottin (DHB), and bergamottin (BG) might inhibit cytochrome P450 2C19 (CYP2C19) activity, but the mode and potency of such inhibition are yet to be investigated. This study aimed to investigate the mode and kinetics of the inhibition of CYP2C19-based omeprazole metabolism by RSV or grapefruit juice components (DHB or BG). RSV and DHB reduced CYP2C19 activity in a preincubation time-dependent manner, suggesting that they inactivated CYP2C19 via mechanism-based inhibition (MBI). Although BG inactivated CYP2C19 in a preincubation time- and concentration-dependent manner, suggesting that both MBI and reversible inhibition contributed to these effects, the concentration required to achieve 50% inhibition was 26-fold higher for reversible inhibition than for MBI (0.859 and 0.0331 µM, respectively), indicating that the inhibition of CYP2C19 by BG is primarily attributable to MBI. Based on the estimated intestinal concentrations of these components, it is considered that >90% of CYP2C19 would be inactivated after the consumption of normal amounts of grapefruit juice or RSV-containing substances. In conclusion, these findings suggest that food containing these components has the potential to evoke drug-food interactions caused by the MBI of intestinal CYP2C19 activity in the clinical setting.

Drug-Drug Interaction Assessment and Identification in the Primary Care Setting.

BACKGROUND: Drug-drug interactions (DDIs) are ubiquitous, harmful and a leading cause of morbidity and mortality. With an aging population, growth in polypharmacy, widespread use of supplements, and the rising opioid abuse epidemic, primary care physicians (PCPs) are increasingly challenged with identifying and preventing DDIs. We set out to evaluate current clinical practices related to identifying and treating DDIs and to determine if opportunities to increase prevention of DDIs and their adverse events could be identified. METHODS: In a nationally representative sample of 330 board-certified family and internal medicine practitioners, we evaluated whether PCPs assessed DDIs in the care they provided for three simulated patients. The patients were taking common prescription medications (e.g. opioids and psychiatric medications) along with other common ingestants (e.g. supplements and food) and presented with symptoms of DDIs. Physicians were scored on their ability to inquire about the patient's medications, investigate possible DDIs, evaluate the patient, and provide treatment recommendations. We scored the physicians' care recommendations against evidence-based criteria, including overall care quality and treatment for DDIs. RESULTS: Average overall quality of care score was 50.5% ± 12.0%. Despite >99% self-reported use of medication reconciliation practices and tools, physicians identified DDIs in only 15.3% of patients, with 15.5% ± 20.3% of DDI-specific treatment by the physicians. CONCLUSIONS: PCPs in this study did not recognize or adequately treat DDIs. Better methods are needed to screen for DDIs in the primary care setting.

Clinical Utility of Definitive Drug⁻Drug Interaction Testing in Primary Care.

Drug⁻drug interactions (DDIs) are a leading cause of morbidity and mortality. New tools are needed to improve identification and treatment of DDIs. We conducted a randomized controlled trial to assess the clinical utility of a new test to identify DDIs and improve their management. Primary care physicians (PCPs) cared for simulated patients presenting with DDI symptoms from commonly prescribed medications and other ingestants. All physicians, in either control or one of two intervention groups, cared for six patients over two rounds of assessment. Intervention physicians were educated on the DDI test and given access to these test reports when caring for their patients in the second round. At baseline, we saw no significant differences in making the DDI diagnosis (p = 0.071) or DDI-related treatment (p = 0.640) between control and intervention arms. By round two, providers who accessed the DDI test performed significantly better in making the DDI diagnosis (+41.6%) and performing DDI-specific treatment (+12.2%) than in the previous round, and were 9.8 and 20.4 times more likely to diagnose and identify the DDI (p < 0.001 for all). The introduction of a definitive DDI test significantly increased identification, appropriate management, and counseling of DDIs among PCPs, which has the potential to improve clinical care.