Extending the DIDEO ontology to include entities from the natural product drug interaction domain of discourse

Abstract

Background

Prompted by the frequency of concomitant use of prescription drugs with natural products, and the lack of knowledge regarding the impact of pharmacokinetic-based natural product-drug interactions (PK-NPDIs), the United States National Center for Complementary and Integrative Health has established a center of excellence for PK-NPDI. The Center is creating a public database to help researchers (primarly pharmacologists and medicinal chemists) to share and access data, results, and methods from PK-NPDI studies. In order to represent the semantics of the data and foster interoperability, we are extending the Drug-Drug Interaction and Evidence Ontology (DIDEO) to include definitions for terms used by the data repository. This is feasible due to a number of similarities between pharmacokinetic drug-drug interactions and PK-NPDIs.

Methods

To achieve this, we set up an iterative domain analysis in the following steps. In Step 1 PK-NPDI domain experts produce a list of terms and definitions based on data from PK-NPDI studies, in Step 2 an ontology expert creates ontologically appropriate classes and definitions from the list along with class axioms, in Step 3 there is an iterative editing process during which the domain experts and the ontology experts review, assess, and amend class labels and definitions and in Step 4 the ontology expert implements the new classes in the DIDEO development branch. This workflow often results in different labels and definitions for the new classes in DIDEO than the domain experts initially provided; the latter are preserved in DIDEO as separate annotations.

Results

Step 1 resulted in a list of 344 terms. During Step 2 we found that 9 of these terms already existed in DIDEO, and 6 existed in other OBO Foundry ontologies. These 6 were imported into DIDEO; additional terms from multiple OBO Foundry ontologies were also imported, either to serve as superclasses for new terms in the initial list or to build axioms for these terms. At the time of writing, 7 terms have definitions ready for review (Step 2), 64 are ready for implementation (Step 3) and 112 have been pushed to DIDEO (Step 4). Step 2 also suggested that 26 terms of the original list were redundant and did not need implementation; the domain experts agreed to remove them. Step 4 resulted in many terms being added to DIDEO that help to provide an additional layer of granularity in describing experimental conditions and results, e.g. transfected cultured cells used in metabolism studies and chemical reactions used in measuring enzyme activity. These terms also were integrated into the NaPDI repository.

Conclusion

We found DIDEO to provide a sound foundation for semantic representation of PK-NPDI terms, and we have shown the novelty of the project in that DIDEO is the only ontology in which NPDI terms are formally defined.

Risk of Clinically Relevant Pharmacokinetic-Based Drug-Drug Interactions with Drugs Approved by the U.S. Food and Drug Administration Between 2013 and 2016

Drug Metab Dispos. 2018 Jun; 46(6): 835-845.
Published online 2018 Mar 23

Abstract

A total of 103 drugs (including 14 combination drugs) were approved by the U.S. Food and Drug Administration from 2013 to 2016. Pharmacokinetic-based drug interaction profiles were analyzed using the University of Washington Drug Interaction Database, and the clinical relevance of these observations was characterized based on information from new drug application reviews. CYP3A was involved in approximately two-thirds of all drug-drug interactions (DDIs). Transporters (alone or with enzymes) participated in about half of all interactions, but most of these were weak-to-moderate interactions. When considered as victims, eight new molecular entities (NMEs; cobimetinib, ibrutinib, isavuconazole, ivabradine, naloxegol, paritaprevir, simeprevir, and venetoclax) were identified as sensitive substrates of CYP3A, two NMEs (pirfenidone and tasimelteon) were sensitive substrates of CYP1A2, one NME (dasabuvir) was a sensitive substrate of CYP2C8, one NME (eliglustat) was a sensitive substrate of CYP2D6, and one NME (grazoprevir) was a sensitive substrate of OATP1B1/3 (with changes in exposure greater than 5-fold when coadministered with a strong inhibitor). Approximately 75% of identified CYP3A substrates were also substrates of P-glycoprotein. As perpetrators, most clinical DDIs involved weak-to-moderate inhibition or induction. Only idelalisib showed strong inhibition of CYP3A, and lumacaftor behaved as a strong CYP3A inducer. Among drugs with large changes in exposure (≥5-fold), whether as victim or perpetrator, the most-represented therapeutic classes were antivirals and oncology drugs, suggesting a significant risk of clinical DDIs in these patient populations.

Intestinal Drug Interactions Mediated by OATPs: A Systematic Review of Preclinical and Clinical Findings

J Pharm Sci. 2017 Sep; 106(9); 2312-2325
Published online 2017 Apr 13

Abstract

In recent years, an increasing number of clinical drug-drug interactions (DDIs) have been attributed to inhibition of intestinal organic anion-transporting polypeptides (OATPs); however, only a few of these DDI results were reflected in drug labels. This review aims to provide a thorough analysis of intestinal OATP-mediated pharmacokinetic-based DDIs, using both in vitro and clinical investigations, highlighting the main mechanistic findings and discussing their clinical relevance. On the basis of pharmacogenetic and clinical DDI results, a total of 12 drugs were identified as possible clinical substrates of OATP2B1 and OATP1A2. Among them, 3 drugs, namely atenolol, celiprolol, and fexofenadine, have emerged as the most sensitive substrates to evaluate clinical OATP-mediated intestinal DDIs when interactions with P-glycoprotein by the test compound can be ruled out. With regard to perpetrators, 8 dietary or natural products and 1 investigational drug, ronacaleret (now terminated), showed clinical intestinal inhibition attributable to OATPs, producing ≥20% decreases in area under the plasma concentration-time curve of the co-administered drug. Common juices, such as apple juice, grapefruit juice, and orange juice, are considered potent inhibitors of intestinal OATP2B1 and OATP1A2 (decreasing exposure of the co-administered substrate by ∼85%) and may be adequate prototype inhibitors to investigate intestinal DDIs mediated by OATPs.

What Can Be Learned From Recent New Drug Applications? A Systematic Review of Drug Interaction Data for Drugs Approved by the US FDA in 2015

Drug Metab Dispos. 2017 Jan; 45(1); 86-108.
Published online 2016 Nov 7

Abstract

As a follow up to previous reviews, the aim of the present analysis was to systematically examine all drug metabolism, transport, pharmacokinetics (PK), and drug-drug interaction (DDI) data available in the 33 new drug applications (NDAs) approved by the Food and Drug Administration (FDA) in 2015, using the University of Washington Drug Interaction Database, and to highlight the significant findings. In vitro, a majority of the new molecular entities (NMEs) were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. In vivo, 95 clinical DDI studies displayed positive PK interactions, with an area under the curve (AUC) ratio ≥ 1.25 for inhibition or ≤ 0.8 for induction. When NMEs were considered as victim drugs, 21 NMEs had at least one positive clinical DDI, with three NMEs shown to be sensitive substrates of CYP3A (AUC ratio ≥ 5 when coadministered with strong inhibitors): cobimetinib, isavuconazole (the active metabolite of prodrug isavuconazonium sulfate), and ivabradine. As perpetrators, nine NMEs showed positive inhibition and three NMEs showed positive induction, with some of these interactions involving both enzymes and transporters. The most significant changes for inhibition and induction were observed with rolapitant, a moderate inhibitor of CYP2D6 and lumacaftor, a strong inducer of CYP3A. Physiologically based pharmacokinetics simulations and pharmacogenetics studies were used for six and eight NMEs, respectively, to inform dosing recommendations. The effects of hepatic or renal impairment on the drugs’ PK were also evaluated to support drug administration in these specific populations.

Investigating ABCB1-Mediated Drug-Drug Interactions: Considerations for In Vitro and In Vivo Assay Design

Abstract

Background

ABCB1 is a key ABC efflux transporter modulating the pharmacokinetics of a large percentage of drugs. ABCB1 is also a site of transporter mediated drug-drug interactions (tDDI). It is the transporter most frequently tested for tDDIs both in vitro and in the clinic.

Objective

Understanding the limitations of various in vitro and in vivo models, therefore, is crucial. In this review we cover regulatory aspects of ABCB1 mediated drug transport as well as inhibition and the available models and methods. We also discuss protein structure and mechanistic aspects of transport as ABCB1 displays complex kinetics that involves multiple binding sites, potentiation of transport and probe-dependent IC50 values.

Results

Permeability of drugs both passive and mediated by transporters is also a covariate that modulates apparent kinetic values. Levels of expression as well as lipid composition of the expression system used in in vitro studies have also been acknowledged as determinates of transporter activity. ABCB1-mediated clinical tDDIs are often complex as multiple transporters as well as metabolic enzymes may play a role. This complexity often masks the role of ABCB1 in tDDIs.

Conclusion

It is expected that utilization of in vitro data will further increase with the refinement of simulations. It is also anticipated that transporter humanized preclinical models have a significant impact and utility.

Key Findings From Preclinical and Clinical Drug Interaction Studies Presented in New Drug and Biological License Applications Approved by the Food and Drug Administration in 2014

Drug Metab Dispos. 2016 Jan; 44(1); 83-101.
Published online 2015 Sep 30

Abstract

Regulatory approval documents contain valuable information, often not published, to assess the drug-drug interaction (DDI) profile of newly marketed drugs. This analysis aimed to systematically review all drug metabolism, transport, pharmacokinetics, and DDI data available in the new drug applications and biologic license applications approved by the U.S. Food and Drug Administration in 2014, using the University of Washington Drug Interaction Database, and to highlight the significant findings. Among the 30 new drug applications and 11 biologic license applications reviewed, 35 new molecular entities (NMEs) were well characterized with regard to drug metabolism, transport, and/or organ impairment and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. In vivo, when NMEs were considered as victim drugs, 16 NMEs had at least one in vivo DDI study with a clinically significant change in exposure (area under the time-plasma concentration curve or Cmax ratio ≥2 or ≤0.5), with 6 NMEs shown to be sensitive substrates of cytochrome P450 enzymes (area under the time-plasma concentration curve ratio ≥5 when coadministered with potent inhibitors): paritaprevir and naloxegol (CYP3A), eliglustat (CYP2D6), dasabuvir (CYP2C8), and tasimelteon and pirfenidone (CYP1A2). As perpetrators, seven NMEs showed clinically significant inhibition involving both enzymes and transporters, although no clinically significant induction was observed. Physiologically based pharmacokinetic modeling and pharmacogenetics studies were used for six and four NMEs, respectively, to optimize dosing recommendations in special populations and/or multiple impairment situations. In addition, the pharmacokinetic evaluations in patients with hepatic or renal impairment provided useful quantitative information to support drug administration in these fragile populations.

Physiologically Based Pharmacokinetic (PBPK) Modeling and Simulation Approaches: A Systematic Review of Published Models, Applications, and Model Verification

Drug Metab Dispos. 2015 Nov; 43(11); 1823-37.
Published online 2015 Aug 21

Abstract

Modeling and simulation of drug disposition has emerged as an important tool in drug development, clinical study design and regulatory review, and the number of physiologically based pharmacokinetic (PBPK) modeling related publications and regulatory submissions have risen dramatically in recent years. However, the extent of use of PBPK modeling by researchers, and the public availability of models has not been systematically evaluated. This review evaluates PBPK-related publications to 1) identify the common applications of PBPK modeling; 2) determine ways in which models are developed; 3) establish how model quality is assessed; and 4) provide a list of publically available PBPK models for sensitive P450 and transporter substrates as well as selective inhibitors and inducers. PubMed searches were conducted using the terms “PBPK” and “physiologically based pharmacokinetic model” to collect published models. Only papers on PBPK modeling of pharmaceutical agents in humans published in English between 2008 and May 2015 were reviewed. A total of 366 PBPK-related articles met the search criteria, with the number of articles published per year rising steadily. Published models were most commonly used for drug-drug interaction predictions (28%), followed by interindividual variability and general clinical pharmacokinetic predictions (23%), formulation or absorption modeling (12%), and predicting age-related changes in pharmacokinetics and disposition (10%). In total, 106 models of sensitive substrates, inhibitors, and inducers were identified. An in-depth analysis of the model development and verification revealed a lack of consistency in model development and quality assessment practices, demonstrating a need for development of best-practice guidelines.

Organ Impairment-Drug-Drug Interaction Database: A Tool for Evaluating the Impact of Renal or Hepatic Impairment and Pharmacologic Inhibition on the Systemic Exposure of Drugs

CPT Pharmacometrics Syst Pharmacol. 2015 Aug; 4(8); 489-94.
Published online 2015 Jul 14

Abstract

The organ impairment and drug-drug interaction (OI-DDI) database is the first rigorously assembled database of pharmacokinetic drug exposure data from publicly available renal and hepatic impairment studies presented together with the maximum change in drug exposure from drug interaction inhibition studies. The database was used to conduct a systematic comparison of the effect of renal/hepatic impairment and pharmacologic inhibition on drug exposure. Additional applications are feasible with the public availability of this database.

Drug Disposition and Drug-Drug Interaction Data in 2013 FDA New Drug Applications: A Systematic Review

Drug Metab Dispos. 2014 Dec; 42(12); 1991-2001.
Published online 2014 Sep 30

Abstract

The aim of the present work was to perform a systematic review of drug metabolism, transport, pharmacokinetics, and DDI data available in the NDAs approved by the FDA in 2013, using the University of Washington Drug Interaction Database, and to highlight significant findings. Among 27 NMEs approved, 22 (81%) were well characterized with regard to drug metabolism, transport, or organ impairment, in accordance with the FDA drug interaction guidance (2012) and were fully analyzed in this review. In vitro, a majority of the NMEs were found to be substrates or inhibitors/inducers of at least one drug metabolizing enzyme or transporter. However, in vivo, only half (n = 11) showed clinically relevant drug interactions, with most related to the NMEs as victim drugs and CYP3A being the most affected enzyme. As perpetrators, the overall effects for NMEs were much less pronounced, compared with when they served as victims. In addition, the pharmacokinetic evaluation in patients with hepatic or renal impairment provided useful information for further understanding of the drugs’ disposition.

Importance of multi-p450 Inhibition in Drug-Drug Interactions: Evaluation of Incidence, Inhibition Magnitude, and Prediction From in Vitro Data

Chem Res Toxicol. 2012 Nov 19;25(11; 2285-300. Published online 2013 Sep 27

Abstract

Drugs that are mainly cleared by a single enzyme are considered more sensitive to drug-drug interactions (DDIs) than drugs cleared by multiple pathways. However, whether this is true when a drug cleared by multiple pathways is coadministered with an inhibitor of multiple P450 enzymes (multi-P450 inhibition) is not known. Mathematically, simultaneous equipotent inhibition of two elimination pathways that each contribute half of the drug clearance is equal to equipotent inhibition of a single pathway that clears the drug. However, simultaneous strong or moderate inhibition of two pathways by a single inhibitor is perceived as an unlikely scenario. The aim of this study was (i) to identify P450 inhibitors currently in clinical use that can inhibit more than one clearance pathway of an object drug in vivo and (ii) to evaluate the magnitude and predictability of DDIs caused by these multi-P450 inhibitors. Multi-P450 inhibitors were identified using the Metabolism and Transport Drug Interaction Database. A total of 38 multi-P450 inhibitors, defined as inhibitors that increased the AUC or decreased the clearance of probes of two or more P450s, were identified. Seventeen (45%) multi-P450 inhibitors were strong inhibitors of at least one P450, and an additional 12 (32%) were moderate inhibitors of one or more P450s. Only one inhibitor (fluvoxamine) was a strong inhibitor of more than one enzyme. Fifteen of the multi-P450 inhibitors also inhibit drug transporters in vivo, but such data are lacking on many of the inhibitors. Inhibition of multiple P450 enzymes by a single inhibitor resulted in significant (>2-fold) clinical DDIs with drugs that are cleared by multiple pathways such as imipramine and diazepam, while strong P450 inhibitors resulted in only weak DDIs with these object drugs. The magnitude of the DDIs between multi-P450 inhibitors and diazepam, imipramine, and omeprazole could be predicted using in vitro data with similar accuracy as probe substrate studies with the same inhibitors. The results of this study suggest that inhibition of multiple clearance pathways in vivo is clinically relevant, and the risk of DDIs with object drugs may be best evaluated in studies using multi-P450 inhibitors.