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Business Cases

Patient Use Case

A patient who is diagnosed with the Alzheimer's Disease (AD) wants to look for alternative medicines.

  1. The patient starts with looking for alternative medicines targetted at AD. The patient also wants to know (putative) therapeutic and side effects reported about these alternative medicines.
    • The TCM dataset can be used to search for herbs possibly targetting at AD and to search for putative effects information about these herbs
    • The SIDER and DailyMed datasets together can be used to search for side-effects information about the ingredients contained in an alternative medicine. Thus, the TCM and SIDER together provide complementary information about the effects of an alternative medicine. Example side-effection information from sider include:
      • For ingredient adenosine, there are side effects like hypertension, back pain, numbness, nervousness, cardias arrest etc
      • For ingredient testosterone, there are side effects like hypertension, Confusion, ABDOMINAL PAIN, Dizziness, etc
      • For ingredient Acetic_Acid, there are side effects like pain, infection, Acidosis etc.
  2. The patient then wants to have some clinical trials information about these herbal medicines.
    • The LinkedCT dataset and the DailyMed might provide some information about these herbs.
      • Example of a LinkedCT dataset on a (negative) trial of Ginkgo for Alzheimer's dementia: http://data.linkedct.org/resource/trials/NCT00010803
      • This trial is also mentioned in a PubMed abstract: http://www.ncbi.nlm.nih.gov/pubmed/19017911 -- is this reflected in the LinkedCT dataset? (Notes from Jun: There are indeed reference information in LinkedCT. But for this trial record, that pubmed article 19017911 is not present in the LinkedCT database. Article 19017911 is published in Nov 2008. Is LinkedCT slightly behind? Is this where aTags can add value? How did you find the article in the first place?)
  3. Nowadays, more patients have advanced medical knowledge. This patient also wants to find out the genes reported being associated with "Ginkgo biloba" for AD, to see whether these genes (aka Ginkgo genes) are also reported in AD medical research community. If these genes not reported as being the top genes associated with AD, the patient wants to know whether these genes have been reported being associated with AD at all and what other diseases these genes have been reported being associated with.
    • The TCM dataset can be used to search for the genes associated with "Ginkgo biloba" for the disease of AD. These genes include MAPT, AGPS, APP, CASP3, CREB1, ADAMTS2, TTR, APLP2, ACHE, APOE, MAPK1
    • The Diseasesome dataset (http://www4.wiwiss.fu-berlin.de/diseasome/sparql) can be used to find out whether the "Ginkgo genes" have been reported being associated with AD at all. Results of a SPARQL search show that there are mapping genes APP, TTR, and ACHE, and APOE in Diseasome, and APP and APOE are also reported in Diseasome dataset as being associated with AD.
    • The Diseasesome dataset can also be used to search for other diseases associated with the "Ginkgo genes".
  4. Safety is an important concern for patients. While the patient believes that Ginkgo biloba could be a potential alternative drug for neurological diseases such as AD, it is important to know the ingredients of Ginkgo biloba, in order to find out i) whether he/she is not allergic to any of the ingredients, ii) what contraindications the ingredients may bring, and iii) adverse interactions with other drugs/herbs.
    • The TCM dataset can be used to find out the ingredients of "Ginkgo biloba".

Scientific Use Case

  1. Use [stitch.embl.de/ STITCH] to find the target proteins of a herb. STITCH contains chemical-protein interactions. It can potentially help provide more molecular information to the herb-gene-disease associations by adding information about what proteins interact with what herb ingredients. If we know what proteins interact with some of the ingredients of ginkgo biloba, for example. We may understand better the molecular mechanism underlying the effect of ginkgo biloba on memory.
    • The TCM data provider provides links for the ingredients/genes of TCM to STITCH by their names/symbols. There are STICH ids in the drugbank dataset.
    • We can use DailyMed and Drugbank together to find STITICH ids for TCM herb ingredients; or use the mapping gene names between TCM and Drugbank to find STITICH ids from Drugbank.
Possible help we can get from aTags
  1. For step 1, we need to process the TCM dataset to articulate that: some of the herbs target at *curing* AD, while others actually *cause* AD.
  2. Also for step 1, we need to process the TCM dataset to articulate whether some effects are negative for patients while others are positive effects [The SIDER dataset might also provide useful information about this??]
  3. For step 2, we need to annotate clinical trials of the herbal medicines reported in publications and other web pages to exact knowledge that is not present in any of the drug / clinical trial databases, which mainly target at western drugs.
  4. Use aTags to curate from scientific literature, other herbs reported being associated with AD, and their side effects, therapeutic effects, and target moleculars (e.g., NMDA receptors, acetylcholinesterase inhibitor). An example literature is doi:10.1016/S0091-3057(03)00128-X, and aTags examples for this article can be found at: http://hcls.deri.org/atag/data/tcm_atags.html, which maily focus on describing potential therapeutic effects of TCM herbs.