Effect of Dextromethorphan-Quinidine on Agitation in Patients With Alzheimer Disease Dementia

Cummings, Jeffrey L.; Lyketsos, Constantine G.; Peskind, Elaine R.; Porsteinsson, Anton P.; Mintzer, Jacobo; Scharre, Douglas W.; Gándara, José E. De La; Agronin, Marc E.; Davis, Charles S.; Nguyen, Uyen; Shin, Paul; Tariot, Pierre N.; Siffert, João

doi:10.1001/jama.2015.10214

Cited by 162 publications

(90 citation statements)

References 33 publications

(22 reference statements)

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“…Quinidine may be effective for treating agitation in Alzheimer's patients [44], and it is possible that existing use of that medication in already diagnosed patients may be contributing to the protective effects found in this study. We did not find any evidence that the antiemetic palonosetron is being targeted specifically for use in patients with dementia.…”

Section: Discussionmentioning

confidence: 89%

Aiding the discovery of new treatments for dementia by uncovering unknown benefits of existing medications

Kern

Cepeda

Lovestone

et al. 2019

A&D Transl Res & Clin Interv

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IntroductionThere is a significant need for disease-modifying therapies to treat and prevent dementia, including Alzheimer's disease. Availability of real-world observational information and new analytic techniques to analyze large volumes of data can provide a path to aid drug discovery.MethodsUsing a self-controlled study design, we examined the association between 2181 medications and incidence of dementia across four US insurance claims databases. Medications associated with ≥50% reduction in risk of dementia in ≥2 databases were examined.ResultsA total of 117,015,066 individuals were included in the analysis. Seventeen medications met our threshold criteria for a potential protective effect on dementia and fell into five classes: catecholamine modulators, anticonvulsants, antibiotics/antivirals, anticoagulants, and a miscellaneous group.DiscussionThe biological pathways of the medications identified in this analysis may be targets for further research and may aid in discovering novel therapeutic approaches to treat dementia. These data show association not causality.

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Section: Discussionmentioning

confidence: 89%

Aiding the discovery of new treatments for dementia by uncovering unknown benefits of existing medications

Kern

Cepeda

Lovestone

et al. 2019

A&D Transl Res & Clin Interv

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“…Additionally, because DXM is rapidly metabolized by cytochrome P450 2D6 (CYP2D6), low-doses (~10 mg) of the CYP2D6 inhibitor quinidine have been added to novel drug formulations with DXM in order to alter the drug’s pharmacokinetic and pharmacodynamic profile, allowing for more prolonged exposure to DXM in the central nervous system (Doody et al, 2015). This DXM / quinidine combination has shown promise as a treatment for agitation in Alzheimer’s patients (Cummings et al, 2015), and pseudobulbar affect in dementia patients (Doody et al, 2015). …”

Section: Introductionmentioning

confidence: 99%

Clinical applications of hallucinogens: A review.

Garcia-Romeu

Kersgaard

Addy³

2016

Experimental and Clinical Psychopharmacology

148

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Hallucinogens fall into several different classes, as broadly defined by pharmacological mechanism of action, and chemical structure. These include psychedelics, entactogens, dissociatives, and other atypical hallucinogens. Although these classes do not share a common primary mechanism of action, they do exhibit important similarities in their ability to occasion temporary but profound alterations of consciousness, involving acute changes in somatic, perceptual, cognitive, and affective processes. Such effects likely contribute to their recreational use. However, a growing body of evidence indicates that these drugs may have therapeutic applications beyond their potential for abuse. This review will present data on several classes of hallucinogens with a particular focus on psychedelics, entactogens, and dissociatives, for which clinical utility has been most extensively documented. Information on each class is presented in turn, tracing relevant historical insights, highlighting similarities and differences between the classes from the molecular to the behavioral level, and presenting the most up-to-date information on clinically oriented research with these substances, with important ramifications for their potential therapeutic value.

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“…In 2015, a study was published showing dextromethorphan hydrobromide–quinidine sulfate was well tolerated in patients with Alzheimer’s disease and had clinically relevant efficacy in treating patients, as measured via agitation. 76 These examples indicate new putative drug candidate generation by the CANDO platform with these integrated pipelines is likely to work as well, if not better, relative to the prospective validation studies previously done using v1 or its components. 8,50,77–80 The full list of drug candidates for the above indications based on the concurrence score using the newer pipelines are given in the Supporting Information and available at http://protinfo.org/cando/results/fingerprinting_cando.…”

Section: Resultsmentioning

confidence: 99%

Fingerprinting CANDO: Increased Accuracy with Structure and Ligand Based Shotgun Drug Repurposing

Schuler

Samudrala

2019

Preprint

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1We have upgraded our Computational Analysis of Novel Drug Opportunities (CANDO) 2 platform for shotgun drug repurposing to include ligand-based, data fusion, and decision tree 3 pipelines. The first version of CANDO implemented a structure-based pipeline that mod-4 eled interactions between compounds and proteins on a large scale, generating compound-5 proteome interaction signatures used to infer similarity of drug behavior; the new pipelines 6 accomplish this by incorporating molecular fingerprints and the Tanimoto coefficient. We 7 obtain improved benchmarking performance with the new pipelines across all three evalua-8 tion metrics used: average indication accuracy, pairwise accuracy, and coverage. The best 9 performing pipeline achieves an average indication accuracy of 19.0% at the top10 cutoff, 10 compared to 11.7% for v1, and 2.2% for a random control. Our results demonstrate that the 11 CANDO drug recovery accuracy is substantially improved by integrating multiple pipelines, 12 thereby enhancing our ability to generate putative therapeutic repurposing candidates, and 13 increasing drug discovery efficiency. 14 Introduction 15 Drug repurposing 16 Bringing a new drug to the market may costs hundreds of millions of dollars and takes years 17 of work. 1 Drug repurposing is the process of discovering a new use for an existing drug. 2,3 18This process may take advantage of existing data on safety and pharmacokinetic properties 19 from previous trials and clinical use to reduce costs and time associated with traditional drug 20 discovery. Classic examples of drug repurposing include sildenafil (Viagra) and thalidomide, 21 which initially were developed to treat chest pain and morning sickness, but were repurposed 22 to treat erectile dysfunction and erythema nodosum leprosum respectively. 2,4,5 Drugs which 23 have already been repurposed once are being researched for even more novel uses. For exam-24 ple, raloxifene was originally indicated for prevention of osteoporosis and was subsequently 25 approved for risk reduction in the development of breast cancer. 6 More recently, raloxifene 26 has been suggested as a possible treatment for Ebola virus disease 7-9 '. These examples of 27 putative and/or successful drug repurposing underlies the diverse mechanisms through which 28 a single compound may treat a variety of disease types. 10,11 High throughput, target-based, 29 and phenotypic screening of compounds can be used to generate putative candidates for re-30 purposing. 12 For example, potential treatments for Zika virus infection were identified using 31 a phenotypic screen. 13 32 Computational drug discovery and repurposing 33 Finding new drugs or new uses for existing drugs computationally takes advantage of the 34 growing amount of data generated from wet lab experiments accessible on the Internet, 35 increased computational power, and higher fidelity of computational models to reality. Ap-36 proaches to computational drug discovery and repurposing have been classified as structure-37 b...

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Effect of Dextromethorphan-Quinidine on Agitation in Patients With Alzheimer Disease Dementia

Abstract: clinicaltrials.gov Identifier: NCT01584440.

Cited by 162 publications

References 33 publications

Aiding the discovery of new treatments for dementia by uncovering unknown benefits of existing medications

Aiding the discovery of new treatments for dementia by uncovering unknown benefits of existing medications

Clinical applications of hallucinogens: A review.

Fingerprinting CANDO: Increased Accuracy with Structure and Ligand Based Shotgun Drug Repurposing

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