Limits...
Concept Modeling-based Drug Repositioning.

Patchala J, Jegga AG - AMIA Jt Summits Transl Sci Proc (2015)

Bottom Line: To test this, we constructed a probabilistic topic model based on the Unified Medical Language System (UMLS) concepts that appear in the disease and drug related abstracts in MEDLINE.The resulting probabilistic topic associations were used to measure the similarity between disease and drugs.The success of the proposed model is evaluated using a set of repositioned drugs, and comparing a drug's ranking based on its similarity to the original and new indication.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, USA.

ABSTRACT
Our hypothesis is that drugs and diseases sharing similar biomedical and genomic concepts are likely to be related, and thus repositioning opportunities can be identified by ranking drugs based on the incidence of shared similar concepts with diseases and vice versa. To test this, we constructed a probabilistic topic model based on the Unified Medical Language System (UMLS) concepts that appear in the disease and drug related abstracts in MEDLINE. The resulting probabilistic topic associations were used to measure the similarity between disease and drugs. The success of the proposed model is evaluated using a set of repositioned drugs, and comparing a drug's ranking based on its similarity to the original and new indication. We then applied the model to rare disorders and compared them to all approved drugs to facilitate "systematically serendipitous" discovery of relationships between rare diseases and existing drugs, some of which could be potential repositioning candidates.

No MeSH data available.


Related in: MedlinePlus

Stacked bar chart showing the top five topic proportions found in modafinil (drug) and its two indications (bipolar disorder and narcolepsy) and ten random disease sets.
© Copyright Policy
Related In: Results  -  Collection


getmorefigures.php?uid=PMC4525261&req=5

f2-2089413: Stacked bar chart showing the top five topic proportions found in modafinil (drug) and its two indications (bipolar disorder and narcolepsy) and ten random disease sets.

Mentions: Topic (Topic 4 – Fig. 2) shared between modafinil and biopolar disorder showed words/concepts related to neuropsychiatric or behavioral conditions (e.g., mental Depression, major depressive disorder, attention deficit hyperactivity disorder, antidepressive agents, mental association, methylphenidate, attention, lithium, sleep, etc.) while topic 0 shared between modafinil and narcolepsy was predominantly sleep-related (sleep disorders, cataplexy, narcolepsy-cataplexy syndrome, sleep, REM, obstructive sleep apnea, drowsiness, hypersomnia, wakefulness, REM sleep behavior disorder, etc.).


Concept Modeling-based Drug Repositioning.

Patchala J, Jegga AG - AMIA Jt Summits Transl Sci Proc (2015)

Stacked bar chart showing the top five topic proportions found in modafinil (drug) and its two indications (bipolar disorder and narcolepsy) and ten random disease sets.
© Copyright Policy
Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC4525261&req=5

f2-2089413: Stacked bar chart showing the top five topic proportions found in modafinil (drug) and its two indications (bipolar disorder and narcolepsy) and ten random disease sets.
Mentions: Topic (Topic 4 – Fig. 2) shared between modafinil and biopolar disorder showed words/concepts related to neuropsychiatric or behavioral conditions (e.g., mental Depression, major depressive disorder, attention deficit hyperactivity disorder, antidepressive agents, mental association, methylphenidate, attention, lithium, sleep, etc.) while topic 0 shared between modafinil and narcolepsy was predominantly sleep-related (sleep disorders, cataplexy, narcolepsy-cataplexy syndrome, sleep, REM, obstructive sleep apnea, drowsiness, hypersomnia, wakefulness, REM sleep behavior disorder, etc.).

Bottom Line: To test this, we constructed a probabilistic topic model based on the Unified Medical Language System (UMLS) concepts that appear in the disease and drug related abstracts in MEDLINE.The resulting probabilistic topic associations were used to measure the similarity between disease and drugs.The success of the proposed model is evaluated using a set of repositioned drugs, and comparing a drug's ranking based on its similarity to the original and new indication.

View Article: PubMed Central - PubMed

Affiliation: Department of Computer Science, University of Cincinnati, Cincinnati, Ohio, USA.

ABSTRACT
Our hypothesis is that drugs and diseases sharing similar biomedical and genomic concepts are likely to be related, and thus repositioning opportunities can be identified by ranking drugs based on the incidence of shared similar concepts with diseases and vice versa. To test this, we constructed a probabilistic topic model based on the Unified Medical Language System (UMLS) concepts that appear in the disease and drug related abstracts in MEDLINE. The resulting probabilistic topic associations were used to measure the similarity between disease and drugs. The success of the proposed model is evaluated using a set of repositioned drugs, and comparing a drug's ranking based on its similarity to the original and new indication. We then applied the model to rare disorders and compared them to all approved drugs to facilitate "systematically serendipitous" discovery of relationships between rare diseases and existing drugs, some of which could be potential repositioning candidates.

No MeSH data available.


Related in: MedlinePlus