Re: Minutes from Clinical Decision Support teleconference

> > It might also be interesting to link to the evidence that motivated 
> that decision for which one would have to go to a different source 
> e.g., <http://www.ncbi.nlm.nih.gov/pubmed/19228618>or 
> <http://www.ncbi.nlm.nih.gov/pubmed/17906972>
> I don't understand -- could you elaborate?
Sure. The issue is that DailyMed currently has 73 product labels with 
warfarin as the active ingredient and the current DS rules cites only 
one of them. While it is understood in the warfarin case that all of the 
oral formulations should have the dosing recommendations, there is no 
guarantee that the FDA's suggestion will be implemented in all labels. 
This is because, in the US, the product labels are written by industry 
and there are different rules and liability issues for the makers of 
generic vs branded drugs. So, I think that it would be more robust to 
use a document that reports the FDA's decision on pharmacogenetic dosing 
with warfarin rather than a single product label. This could be done by 
citing...

1) A published summary of the decision 
<www.ncbi.nlm.nih.gov/pubmed?term=17906972> and attached

2)  The minutes of meeting at which the FDA decided to make the decision 
<http://www.fda.gov/ohrms/dockets/ac/05/minutes/2005-4194M1.pdf>

3) The actual clinical trials that were used as justification for the 
decision

I think that (1) is probably preferred since the paper is co-authored by 
an FDA person and seems to provide all of the information that you 
pulled from the individual product label.

(btw, since many active ingredients can appear in multiple formulations 
and your current example refers to the tablet form warfarin, it might be 
good to add formulation to your decision rules)

> *TODO:* Would you (or someone else) be interested in looking into 
> these classification schemes to see what would fit best? Are some of 
> these schemes available as ontologies, e.g. via BioPortal? However, I 
> guess we should at least retain some compatibility with PharmGKB, CPIC 
> and other such initiatives!
I would be glad to look into the schemes you list and will get back to 
you before the next meeting (5/10). From a standards perspective though, 
my concern is that there are bound to be different ratings that are 
considered reasonable by different groups of users. I think that it 
would be best to develop the rules so that, in the case that there are 
multiple ratings for level of evidence or clinical relevance, CDS system 
maintainers can choose the ratings their organization thinks is best.

cheers,
-Rich
> Cheers,
> Matthias
> [1] 
> https://docs.google.com/spreadsheet/pub?hl=en_US&hl=en_US&key=0AiGT-vnkGcoLdFFVMEdqcFdYaDFqS0xHTnlUT0N3cEE&single=true&gid=3&output=html 
> <https://docs.google.com/spreadsheet/pub?hl=en_US&hl=en_US&key=0AiGT-vnkGcoLdFFVMEdqcFdYaDFqS0xHTnlUT0N3cEE&single=true&gid=3&output=html>
>
> *From:* Richard Boyce <mailto:rdb20@pitt.edu>
> *Sent:* Thursday, April 26, 2012 8:26 PM
> *To:* public-semweb-lifesci@w3.org <mailto:public-semweb-lifesci@w3.org>
> *Subject:* Re: Minutes from Clinical Decision Support teleconference
>
> I wanted to first thank Matthias and the CDS group for doing a very 
> nice job on some initial OWL and SPARQL rules for pharmacogenomic 
> clinical decision support [1]. I had a few comments and questions 
> regarding the rules...
>
> Questions:
>
> - Were the entries blank in "Germ-line genetic marker (curated SNPs)" 
> because the 2C9 variants were not present in a curated resource?
>
> - What is the meaning of the evidence column? I could imagine 
> assigning and evidence type, an OBI description of the study from 
> which the evidence was derived, or a citation. Thinking about the big 
> picture, it would be neat if the evidence was a URI or SPARQL query to 
> an annotation of the text (human or computer) complete with metadata 
> on when the annotation was created and the expertise of the group 
> providing the annotation. Perhaps there should be both an entry for 
> the annotation and metadata about the scientific provenance of the 
> data from which the rule was derived. In this case, the scientific 
> provenance would be that the statement came from a decision made by an 
> authoritative source (the FDA). It might also be interesting to link 
> to the evidence that motivated that decision for which one would have 
> to go to a different source e.g., 
> <http://www.ncbi.nlm.nih.gov/pubmed/19228618> or 
> <http://www.ncbi.nlm.nih.gov/pubmed/17906972>
>
> Comments:
>
> - It might help communicate the rules more clearly if you provide a 
> label for VKORC1 variants in the column "Germ-line genetic marker (as 
> appearing in source)"
>
> - I think that the key to really making this example strong will be to 
> include rules that factor in both clinical and genetic factors. 
> Genetic variability is important but it is only part of the picture. 
> Perhaps some rules could be derived from clinical dosing algorithms 
> that factor in clinical and genetic factors such as described in 
> <http://www.ncbi.nlm.nih.gov/pubmed/19228618>
>
> - You might find it interesting that one can get a SPARQL query to the 
> actual text and table from which you grabbed this variant information 
> using the linkedSPLs endpoint: 
> http://dbmi-icode-01.dbmi.pitt.edu/linkedSPLs/sparql:
> PREFIX dailymed:<http://dbmi-icode-01.dbmi.pitt.edu/linkedSPLs/vocab/resource/>
> SELECT ?dosage WHERE {
>   ?s dailymed:setId "d91934a0-902e-c26c-23ca-d5accc4151b6".
>   ?s dailymed:dosage ?dosage.
> }
>
>
> - The "level of evidence" and "clinical significance" columns are very 
> challenging things to assign. The level of evidence could be some 
> evidence-based ranking 
> (e.g.,<http://www.fda.gov/ohrms/dockets/dailys/03/Aug03/080103/03n-0069-rpt0001-04-Attachment-b-vol4.pdf> 
> ) or a consensus-based scale (e.g., SORT, 
> <http://www.aafp.org/afp/2004/0201/p548.html>). I think that there is 
> no standard rating scale but that most will agree some kind of rating 
> is important. So, it might make sense to include a triple that has the 
> rating and metadata describing the scale used and who did the rating.
>
> Clinical significance is even more challenging because no one can 
> agree on what this means. In drug-drug interactions, all of the major 
> drug compendia have very poor agreement on the clinical severity of an 
> interaction and local sites will customize the severity rankings to 
> fit the populations they work with. Some groups avoid classifying 
> severity and go for an operational classification such as "avoid", 
> "minimize risk", or "no special precaution" 
> (<www.ncbi.nlm.nih.gov/pubmed/11297327>. Here again, it might make 
> sense to include a triple that has the clinical significance (or 
> operational) rating and metadata describing the scale used and who did 
> the rating.
>
> thanks,
> -Rich
>
>
> [1] 
> <https://docs.google.com/spreadsheet/pub?hl=en_US&hl=en_US&key=0AiGT-vnkGcoLdFFVMEdqcFdYaDFqS0xHTnlUT0N3cEE&single=true&gid=3&output=html> 
>
>
> On 04/26/2012 12:19 PM, M. Scott Marshall wrote:
>> You will find the minutes for today's Clinical Decision Support
>> teleconference here:
>> http://www.w3.org/2012/04/26-HCLS-minutes.html
>>
>> Matthias showed us an interested demonstration of his SPARQL rule
>> approach to pharmacogenomic data (example: matching on certain SNPs to
>> produce personalized drug advice). Very nice! Many participants are
>> hoping to look deeper into this in a followup call.
>>
>> Cheers,
>> Scott
>>
>
>
> -- 
> Richard Boyce, PhD
> Assistant Professor of Biomedical Informatics
> Scholar, Comparative Effectiveness Research Program
> University of Pittsburgh
> rdb20@pitt.edu
> 412-648-6768


-- 
Richard Boyce, PhD
Assistant Professor of Biomedical Informatics
Scholar, Comparative Effectiveness Research Program
University of Pittsburgh
rdb20@pitt.edu
412-648-6768