Talk at SUMMER SCHOOL: GENOMIC MEDICINE – Bridging research and the clinic, May 7 2016, Portoroz, Slovenia

1. Clinical decision support systems for personalized medicine
Asst.-Prof. Mag. Dr. Matthias Samwald
CeMSIIS, Medical University of Vienna
SUMMER SCHOOL: GENOMIC MEDICINE – Bridging research and the clinic, May 7 2016,
Portoroz, Slovenia
Bridging theory and practice
Funded by Austrian Science Fund (FWF): [P 25608-N15]
This project has received funding from the European Union’s Horizon
2020 research and Innovation programme under grant agreement
No 668353 (KB and MS).

2. Drug safety and effectiveness vary drastically
between patients

3. Part of this variability can be explained by
genetic variation influencing individual
pharmacokinetics and –dynamics
The frequencies of actionable pharmacogenes. Over 95% of the population carries at least one
actionable genotype for one of the genes covered by the DPWG guidelines (Dunnenberger, 2015)

4. However, several barriers to widespread
implementation of pharmacogenomics remain
×Lack of selection of a panel of clinically relevant PGx
markers
×Lack of information on cost-effectiveness and cost-
consequences of PGx testing
×Lack of knowledge when test needs to be conducted;
organizational overheads discourage testing
×Lack of appropriate information technologies for
interpretation and incorporation in the workflow of
physicians and pharmacists

5. We are aiming for pre-emptive pharmacogenomic testing,
where data on all essential pharmacogenes are tested in one
go and are made available for immediate use in the future
Gene Substances associated with gene in pharmacogenomic guidelines
Core list
CYP2C19 amitriptylinea,b, clomipraminea,b, clopidogrela,b, desipraminea, doxepinb, imipraminea,b, nortriptylinea,b,
trimipraminea, citalopramb, escitalopramb, esomeprazoleb, lansoprazoleb, moclobemideb, omeprazoleb,
pantoprazoleb, rabeprazoleb, sertralineb, voriconazoleb
CYP2C9 warfarina, acenocoumarolb, glibenclamideb, gliclazideb, glimepirideb, phenprocoumonb, phenytoinb,
tolbutamideb
CYP2D6 amitriptylinea,b, clomipraminea,b, codeinea,b, desipraminea, doxepina,b, imipraminea,b, nortriptylinea,b,
trimipraminea, aripiprazoleb, atomoxetine b, carvedilol b, clozapineb, codeinea,b, Duloxetineb, flecainideb,
flupenthixolb, haloperidolb, metoprololb, mirtazapineb, olanzapineb, oxycodoneb, paroxetineb, propafenoneb,
risperidoneb, tamoxifenb, tramadolb, venlafaxineb, zuclopenthixolb
CYP3A5 tacrolimusb
DPYD capecitabinea,b, fluorouracila,b, tegafura,b
TPMT azathioprinea,b, mercaptopurinea,b, thioguaninea,b
UGT1A1 irinotecanb
SLCO1B1 simvastatina
VKORC1 warfarina, phenprocoumonb
Others
F5 estrogen-containing oral contraceptivesb
HLA-B abacavira,b, allopurinola, carbamazepinea, ribavirina,b
IFNL3 peginterferon alfa-2aa, peginterferon alfa-2ba, ribavirina,b
a: substance covered by CPIC guidelines, b: substance covered by DPWG guidelines. Data as of
mid-2014.

6. But how to make use of these data when they are
finally available?
 Clinical decision support systems!

7. Is there evidence for the effectiveness of clinical
decision support systems (CDSS)?
• A 2005 systematic review by Garg et al. of 100 studies
concluded that
o CDSS improved practitioner performance in 64% of
the studies
o CDSS improved patient outcomes in 13% of the
studies (detecting patient outcomes often difficult)
• CDSS could also help improve translation of findings from
clinical research into practice
o Currently this often takes 10+ years

8. Have clinical decision support systems been widely
adopted in the last decades?
• Initial discussions already in the 1960s,
prototypes in the 1970s
• However, mostly research prototypes
that were never widely deployed
o Even though several were shown to
perform better than humans
• Several reasons for lacking adoption
o Lack of integration into existing
workflows, bad user interfaces (!!)
o Lack of trust
o Lack of incentive
o Knowledge bases not kept up-to-date

9. Which features of clinical decision support system
have an impact on their success?
CDSS is integrated into the clinical workflow
CDSS provides decision support at the time and location of
decision making
Integration with charting or order entry system
CDSS actively provides recommendations / alternatives for
care, not just assessments
Avoiding over-alerting / ‚altert fatigue‘
Justification of decision support via research evidence
Provision of decision support results to patients as well as
providers

11. This is idealThis is what is possible in
most places 

12. Current status among U-PGx implementation sites

15. We conducted a mixed-method study on system
design
1. Interviews with clinical pharmacologists (n = 8)
2. Survey A: PGx professionals (n = 63)
3. Survey B: Physicians and pharmacists (n = 43)

16. Practical question:
Which drugs might cause
trouble for this patient?
Not:
Which genotype/phenotype
does the patient have?
Filtered for actual
clinical significance

17. Anonymous! No central database!
Open-source codebase!

18. The MSC system was evaluated positively

19. We also asked participants to use the system for
solving two cases

20. See http://safety-code.org/

21. Take-home messages
• Computer-based decision support is essential…
• …but tricky to implement effectively
• Busy practitioners want a tweet, not an essay
• In passive CDS, show most important information first
(medications with added risk!)
• Let us know if you want to adopt the MSC system!

22. Local team (Medical University of Vienna)
Asst.-Prof. Mag. Dr. Matthias Samwald
Dr. Kathrin Blagec
Mag. Sebastian Hofer
Hong Xu
Web
http://samwald.info/
http://safety-code.org/
http://upgx.eu
Questions?