Drug Metab Dispos. 2019 Feb; 47(2); 135-144
Pharmacokinetic-based drug-drug interaction (DDI) data for drugs approved by the U.S. Food and Drug Administration in 2017 (N = 34) were analyzed using the University of Washington Drug Interaction Database. The mechanisms and clinical relevance of these interactions were characterized based on information from new drug application reviews. CYP3A inhibition and induction explained most of the observed drug interactions (new drugs as victims or as perpetrators), and transporters mediated about half of all DDIs, alone or with enzymes. Organic anion transporting polypeptide (OATP)1B1/1B3 played a significant role, mediating more than half of the drug interactions with area under the time-plasma curve (AUC) changes ≥5-fold. As victims, five new drugs were identified as sensitive substrates: abemeciclib, midostaurin, and neratinib for CYP3A and glecaprevir and voxilaprevir for OATP1B1/1B3. As perpetrators, three drugs were considered strong inhibitors: ribociclib for CYP3A, glecaprevir/pibrentasvir for OATP1B1/1B3, and sofosbuvir/velpatasvir/voxilaprevir for OATP1B1/1B3 and breast cancer resistance protein. No strong inducer of enzymes or transporters was identified. DDIs with AUC changes ≥5-fold and almost all DDIs with AUC changes 2- to 5-fold had dose recommendations in their respective drug labels. A small fraction of DDIs with exposure changes <2-fold had a labeling impact, mostly related to drugs with narrow therapeutic indices. As with drugs approved in recent years, all drugs found to be sensitive substrates or strong inhibitors of enzymes or transporters were among oncology or antiviral treatments, suggesting a serious risk of DDIs in these patient populations for whom effective therapy is already complex because of polytherapy.
AMIA Annu Symp Proc. 2018 Dec 5; 2018; 279-287
Pharmacokinetic interactions between natural products and conventional drugs can adversely impact patient outcomes. These complex interactions present unique challenges that require clear communication to researchers. We are creating a public information portal to facilitate researchers’ access to credible evidence about these interactions. As part of a user-centered design process, three types of intended researchers were surveyed: drug-drug interaction scientists, clinical pharmacists, and drug compendium editors. Of the 23 invited researchers, 17 completed the survey. The researchers suggested a number of specific requirements for a natural product-drug interaction information resource, including specific information about a given interaction, the potential to cause adverse effects, and the clinical importance. Results were used to develop user personas that provided the development team with a concise and memorable way to represent information needs of the three main researcher types and a common basis for communicating the design’s rationale.
J Biomed Semantics. 2018 May 9; 9(1): 15
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.
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.
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.
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.
Presented at Asia Pacific ISSX conference, May 2018, Hangzhou City, China
2018 Asia Pacific ISSX Poster Presentation – Transporter-mediated DDIs
Jingjing Yu and Isabelle Ragueneau-Majlessi
The present work aimed to systematically review transporter-based in vitro and clinical inhibition evaluations of drugs approved by the U.S. Food and Drug Administration (FDA) from 2013 to 2016. In vitro inhibition parameters, pharmacokinetics, and clinical drug-drug interaction (DDI) studies available in the New Drug Application (NDA) reviews were analyzed using the University of Washington Drug Interaction Database. Following recommendations from the 2012 FDA DDI guidance, in vitro to in vivo prediction estimates were calculated for the transporters the most often studied.
Drug Metab Dispos. 2018 Jun; 46(6): 835-845.
Published online 2018 Mar 23
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.
Presented at ISSX conference, September 2017, Providence, RI, USA
2017 ISSX Poster Presentation – 2013-2016 NDA Review
Jingjing Yu and Isabelle Ragueneau-Majlessi
The aim of the present work was to systematically review pharmacokinetic-based drug-drug interaction (DDI) data available in the most recent (2013-2016) New Drug Applications (NDAs) and highlight significant findings. The University of Washington Metabolism and Transport Drug Interaction Database was used to extract the results of metabolism, transport, and clinical DDI studies. All the DDI studies (new molecular entity (NME) as victim or perpetrator) with AUC changes ≥ 2-fold or < 2-fold but triggering dose recommendations were included in the analysis.
Presented at ISSX conference, September 2017, Providence, RI, USA
2017 ISSX Poster Presentation – Evaluation of Clinical Substrates of OATP1B1/3
Savannah J. McFeely, Yu, Tasha K. Ritchie, Jingjing Yu, Eva Gil Berglund, Anna Nordmark, and Isabelle Ragueneau-Majlessi
The aim of this work was twofold: i) Provide a thorough analysis of the available in vitro and in vivo data regarding OATP1B1/1B3 substrates, ii)Propose the most sensitive and selective probe markers of OATP1B1/1B3 activity.
J Pharm Sci. 2017 Sep; 106(9); 2312-2325
Published online 2017 Apr 13
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.
Presented at ASCPT conference, March 2017, Washington, DC, USA
2017 ASCPT Poster Presentation – 2015 NDA Review
Jingjing Yu, Zhu Zhou, Katie Owens, Tasha K. Ritchie, and Isabelle Ragueneau-Majlessi
The aim of the present work was to perform a systematic analysis of metabolism, transport, and drug interaction data available in New Drug Applications (NDAs) and Biologic License Applications (BLAs) of drugs approved in 2015, and highlight significant findings.
Drug Metab Dispos. 2017 Jan; 45(1); 86-108.
Published online 2016 Nov 7
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.