News

Identification and Evaluation of Clinical Substrates of Organic Anion Transporting Polypeptides 1B1 and 1B3

Clin Transl Sci. 2019 Jul; 12(4): 379-387
Published online 2019 Feb 01

Abstract

Organic anion transporting polypeptides (OATPs) 1B1 and 1B3 facilitate the uptake of drugs and endogenous compounds into the liver. In recent years, the impact of these transporters on drug-drug interactions (DDIs) has become a focus of research, and the evaluation of their role in drug disposition is recommended by regulatory agencies worldwide.1-3 Although sensitive substrates of OATP1B1/1B3 have been identified in the literature and probe drugs have been proposed by regulatory agencies, there is no general consensus on the ideal in vivo substrate for clinical DDI studies as analysis may be confounded by contribution from other metabolic and/or transport pathways.1-3 A thorough analysis of the available in vitro and in vivo data regarding OATP1B1/1B3 substrates was performed using the in vitro, clinical, and pharmacogenetic modules in the University of Washington Drug Interaction Database. A total of 34 compounds were identified and further investigated as possible clinical substrates using a novel indexing system. By analyzing the compounds for in vivo characteristics, including sensitivity to inhibition by known OATP1B1/1B3 inhibitors, selectivity for OATP1B1/1B3 compared with other transport and metabolic pathways, and safety profiles, a total of six compounds were identified as potential clinical markers of OATP1B1/1B3 activity.

Developing User Personas to Aid in the Design of a User-Centered Natural Product-Drug Interaction Information Resource for Researchers

Abstract

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.

New features have been implemented!

The following new features have been implemented:

  • New DRUG query where you can find all studies in DIDB for a given compound, including in vitro transporter data
  • Unified in vivo measurement types across all study types
  • Unified citation tree view of all in vivo studies
  • Measurement types now displayed in their proper subscript formats
  • Tree view now more easily viewable on phones
  • New “In Vivo Other Mechanism” sub-type of “PD interaction”

Do not hesitate to contact us if you have any questions or suggestions!

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.

Analysis of in vitro- to-in vivo predictions of transporter-mediated inhibition drug interactions for drugs approved by the USA Food and Drug Administration between 2013 and 2016

Presented at Asia Pacific ISSX conference, May 2018, Hangzhou City, China
Jingjing Yu and Isabelle Ragueneau-Majlessi

2018 Asia Pacific ISSX Poster Presentation – Transporter-mediated DDIs

Abstract

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.

Dr. Jingjing Yu to present new NDA data at the upcoming 6th Asia Pacific ISSX Meeting

Dr. Jingjing Yu will be presenting a poster entitled “ANALYSIS OF IN VITRO TO IN VIVO PREDICTIONS OF TRANSPORTER-MEDIATED INHIBITION DRUG INTERACTIONS FOR DRUGS APPROVED BY THE US FOOD AND DRUG ADMINISTRATION BTEWEEN 2013 AND 2016” at the upcoming 6th Asia Pacific ISSX Meeting in Hangzhou, China, May 11 – 14, 2018.

The poster will be on display throughout the meeting and poster presentation sessions will be held on Saturday, May 12th and Sunday, May 13th.

New Manuscript in Drug Metabolism and Disposition

Our most recent publication entitled “Risk of Clinically Relevant Pharmacokinetic-based Drug-drug Interactions with Drugs Approved by the U.S. Food and Drug Administration Between 2013 and 2016” by Yu et al. is now available on Drug Metabolism and Disposition online FastForward site (https://dmd.aspetjournals.org). This is an extensive review of the NDA data we analyzed for the DIDB platform, with useful supplemental tables summarizing the main clinical findings.

Do not hesitate to contact us if you have any questions.

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.