Inhibitory Metabolic Drug Interactions with Newer Psychotropic Drugs: Inclusion in Package Inserts and Influences of Concurrence in Drug Interaction Screening Software

Boyce, Richard D.; Collins, Carol; Clayton, Marc; Kloke, John; Horn, John R.

doi:10.1345/aph.1r150

Cited by 12 publications

(11 citation statements)

References 74 publications

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“…Our finding of low agreement across public sources providing PDDI information is concordant with other studies, including the two mentioned in the introduction [7], [8]. Most relevant to the current study, Peters, Bodenreider, and Bahr mapped drugs in the VA NDF-RT, DrugBank, and ONC High-priority list to RxNorm and then examined PDDI overlap [37].…”

Section: Discussionsupporting

confidence: 87%

“…One recent study found that only one quarter of 59 contraindicated drug pairs were listed in three proprietary PDDI information sources [7]. Another recent study comparing drug product labeling to the published literature for information on pharmacokinetic DDIs found that 40% of the 44 pharmacokinetic drug-drug interactions affecting 25 psychotropic drugs were located exclusively in product labeling [8]. These findings suggest that there is a pressing need for informatics research on how to best organize both existing and emerging PDDI information for search and retrieval.…”

Section: Introductionmentioning

confidence: 99%

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Toward a complete dataset of drug–drug interaction information from publicly available sources

Ayvaz

Horn

Hassanzadeh

et al. 2015

Journal of Biomedical Informatics

105

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Although potential drug-drug interactions (PDDIs) are a significant source of preventable drug-related harm, there is currently no single complete source of PDDI information. In the current study, all publically available sources of PDDI information that could be identified using a comprehensive and broad search were combined into a single dataset. The combined dataset merged fourteen different sources including 5 clinically-oriented information sources, 4 Natural Language Processing (NLP) Corpora, and 5 Bioinformatics/Pharmacovigilance information sources. As a comprehensive PDDI source, the merged dataset might benefit the pharmacovigilance text mining community by making it possible to compare the representativeness of NLP corpora for PDDI text extraction tasks, and specifying elements that can be useful for future PDDI extraction purposes. An analysis of the overlap between and across the data sources showed that there was little overlap. Even comprehensive PDDI lists such as DrugBank, KEGG, and the NDF-RT had less than 50% overlap with each other. Moreover, all of the comprehensive lists had incomplete coverage of two data sources that focus on PDDIs of interest in most clinical settings. Based on this information, we think that systems that provide access to the comprehensive lists, such as APIs into RxNorm, should be careful to inform users that the lists may be incomplete with respect to PDDIs that drug experts suggest clinicians be aware of. In spite of the low degree of overlap, several dozen cases were identified where PDDI information provided in drug product labeling might be augmented by the merged dataset. Moreover, the combined dataset was also shown to improve the performance of an existing PDDI NLP pipeline and a recently published PDDI pharmacovigilance protocol. Future work will focus on improvement of the methods for mapping between PDDI information sources, identifying methods to improve the use of the merged dataset in PDDI NLP algorithms, integrating high-quality PDDI information from the merged dataset into Wikidata, and making the combined dataset accessible as Semantic Web Linked Data.

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Section: Discussionsupporting

confidence: 87%

Section: Introductionmentioning

confidence: 99%

Toward a complete dataset of drug–drug interaction information from publicly available sources

Ayvaz

Horn

Hassanzadeh

et al. 2015

Journal of Biomedical Informatics

105

View full text Add to dashboard Cite

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“…19,20,30-34 These variations have led some researchers to suggest that clinicians use multiple references to overcome the deficiencies of any single product. 33,35 Further examination of these usage patterns might inform improvements that would reduce burdens associated with managing multiple devices and software tools.…”

Section: Discussionmentioning

confidence: 99%

Use and Perceived Benefits of Mobile Devices by Physicians in Preventing Adverse Drug Events in the Nursing Home

Handler

Boyce

Ligons

et al. 2013

Journal of the American Medical Directors Association

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Objective Although mobile devices equipped with drug reference software may help prevent adverse drug events (ADEs) in the nursing home (NH) by providing medication information at the point-of-care, little is known about their use and perceived benefits. The goal of this study was to conduct a survey of a nationally representative sample of NH physicians to quantify the use and perceived benefits of mobile devices in preventing ADEs in the NH setting. Design/Setting/Participants We surveyed physicians who attended the 2010 the AMDA Annual Symposium about their use of mobile devices and beliefs about the effectiveness of drug reference software in preventing ADEs. Results The overall net valid response rate was 70% (558/800) with 42% (236/558) using mobile devices to assist with prescribing in the NH. Physicians with ≤15 years clinical experience were 67% more likely to be mobile device users, compared to those with >15 years of clinical experience (odds ratio=1.68; 95% confidence interval=1.17-2.41; p=0.005). For those who used a mobile device to assist with prescribing, almost all (98%) reported performing an average of one or more drug look-ups per day, performed an average of 1-2 lookups per day for potential drug-drug interactions (DDIs), and most (88%) believed that drug reference software had helped to prevent at least one potential ADE in the preceding four-week period. Conclusions The proportion of NH physicians who use mobile devices with drug reference software, while significant, is lower than in other clinical environments. Our results suggest that NH physicians who use mobile devices equipped with drug reference software believe they are helpful for reducing ADEs. Further research is needed to better characterize the facilitators and barriers to adoption of the technology in the NH and its precise impact on NH ADEs.

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“…a These drugs were chosen because they are very widely prescribed and a number of these “newer” psychotropic drugs are involved in drug-drug interactions [14]. Figure 2 shows the architecture of the proof-of-concept system that we developed for these drugs.…”

Section: Resultsmentioning

confidence: 99%

“…Another concern raised at the conference was that there is currently no standard criteria for evaluating the evidence for interactions. This leads to considerable variation in the drug-drug interactions listed across drug information sources [14]. In future work we plan to develop methods that construct more complete claim-evidence networks for drug-drug interactions that go beyond establishing the potential for the interaction [27], to also provide evidence of the potential risk of harm in patients with specific characteristics.…”

Section: Discussionmentioning

confidence: 99%

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness

et al. 2013

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Out-of-date or incomplete drug product labeling information may increase the risk of otherwise preventable adverse drug events. In recognition of these concerns, the United States Federal Drug Administration (FDA) requires drug product labels to include specific information. Unfortunately, several studies have found that drug product labeling fails to keep current with the scientific literature. We present a novel approach to addressing this issue. The primary goal of this novel approach is to better meet the information needs of persons who consult the drug product label for information on a drug’s efficacy, effectiveness, and safety. Using FDA product label regulations as a guide, the approach links drug claims present in drug information sources available on the Semantic Web with specific product label sections. Here we report on pilot work that establishes the baseline performance characteristics of a proof-of-concept system implementing the novel approach. Claims from three drug information sources were linked to the Clinical Studies, Drug Interactions, and Clinical Pharmacology sections of the labels for drug products that contain one of 29 psychotropic drugs. The resulting Linked Data set maps 409 efficacy/effectiveness study results, 784 drug-drug interactions, and 112 metabolic pathway assertions derived from three clinically-oriented drug information sources (ClinicalTrials.gov, the National Drug File – Reference Terminology, and the Drug Interaction Knowledge Base) to the sections of 1,102 product labels. Proof-of-concept web pages were created for all 1,102 drug product labels that demonstrate one possible approach to presenting information that dynamically enhances drug product labeling. We found that approximately one in five efficacy/effectiveness claims were relevant to the Clinical Studies section of a psychotropic drug product, with most relevant claims providing new information. We also identified several cases where all of the drug-drug interaction claims linked to the Drug Interactions section for a drug were potentially novel. The baseline performance characteristics of the proof-of-concept will enable further technical and user-centered research on robust methods for scaling the approach to the many thousands of product labels currently on the market.

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Inhibitory Metabolic Drug Interactions with Newer Psychotropic Drugs: Inclusion in Package Inserts and Influences of Concurrence in Drug Interaction Screening Software

Abstract: The presence in PIs of DDI information for newer psychotropics appears to have a strong influence on agreement among DDI screening tools. Users of DDI screening software should consult more than 1 source when considering interactions involving generic psychotropics.

Cited by 12 publications

References 74 publications

Toward a complete dataset of drug–drug interaction information from publicly available sources

Toward a complete dataset of drug–drug interaction information from publicly available sources

Use and Perceived Benefits of Mobile Devices by Physicians in Preventing Adverse Drug Events in the Nursing Home

Dynamic enhancement of drug product labels to support drug safety, efficacy, and effectiveness

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