Clinical decision support systems for personalized medicine

Asst.-Prof. Mag. Dr. Matthias SamwaldCeMSIIS, 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).

Drug safety and effectiveness vary drastically between patients

Part of this variability can be explained bygenetic variation influencing individual pharmacokinetics and –dynamics

The frequencies of actionable pharmacogenes. Over 95% of the population carries at least oneactionable genotype for one of the genes covered by the DPWG guidelines (Dunnenberger, 2015)

However, several barriers to widespreadimplementation 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

We are aiming for pre-emptive pharmacogenomic testing, where data on all essential pharmacogenes are tested in onego 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 ofmid-2014.

But how to make use of these data when they arefinally available?

Clinical decision support systems!

Is there evidence for the effectiveness of clinicaldecision 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 fromclinical research into practice

o Currently this often takes 10+ years

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 toperform better than humans

• Several reasons for lacking adoption

o Lack of integration into existingworkflows, bad user interfaces (!!)

o Lack of trust

o Lack of incentive

o Knowledge bases not kept up-to-date

Which features of clinical decision support systemhave 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

This is idealThis is what is possible in most places

Current status among U-PGx implementation sites

We conducted a mixed-method study on systemdesign

1. Interviews with clinical pharmacologists (n = 8)

2. Survey A: PGx professionals (n = 63)

3. Survey B: Physicians and pharmacists (n = 43)

Practical question:Which drugs might causetrouble for this patient?

Not:Which genotype/phenotypedoes the patient have?

Filtered for actualclinical significance

Anonymous! No central database!

Open-source codebase!

The MSC system was evaluated positively

We also asked participants to use the system forsolving two cases

See http://safety-code.org/

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!

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?