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ECO 11: Medicines Optimisation Through Precision - Sir Munir Pirmohamed

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Munir Pirmohamed discusses the potential impact of medicines optimisation in terms of ensuring the right patients get the right choice if medicine at the right time. He presents a case history of over prescription and introduces three examples of medicines optimisation through use of genetics, big data, and pharmacogenetics profiling.

Published in: Health & Medicine
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ECO 11: Medicines Optimisation Through Precision - Sir Munir Pirmohamed

  1. 1. Medicines Optimisation Through Precision Munir Pirmohamed David Weatherall Chair of Medicine Department of Molecular and Clinical Pharmacology Institute of Translational Medicine University of Liverpool
  2. 2.  ensuring that the right patients get the right choice of medicine, at the right time.  the goal is to help patients to:  improve their outcomes;  take their medicines correctly;  avoid taking unnecessary medicines;  reduce wastage of medicines; and  improve medicines safety. Medicines optimisation
  3. 3. Current Paradigm Efficacy • One drug fits all Safety • One dose fits all
  4. 4. Case History  70 year old man  Attended for hypertension – was on 7 antihypertensives  In total was on 17 drugs  Assured me he was fully adherent  Was on beta-blocker but HR 92/min  Assured me he was fully adherent Urinary drug Screen by LCMS CAFFEINE
  5. 5. GWAS Warfarin Mean Weekly Dose (UK Prospective Cohort; n=714) CYP2C9 VKORC1 Total = 57.9% Age: 11.2% Height 3.56% Weight: 5.98% Interacting meds: 0.98% Sum of interacting meds: 2.2% VKORC1: 25.61% CYP2C9: 16.65% CYP4F2: 0.49%
  6. 6. Time in Therapeutic Range 7%
  7. 7. VK *3 *2 ParaDNA: Point of Care Device 1. Take sample 2. Use device to transfer and seal sample into four wells pre-loaded with single or multiplex test chemicals 3. Four separate independent analyses possible 4. Analysis is complete in 45 minutes. 8 Courtesy of LGC, Commercial in Confidence Sample Dispense Three genotyping tests (VKORC1, CYP2C9*2, *3)
  8. 8. Paul Downie, 56, of Grappenhall in Warrington was referred to the anticoagulation clinic following treatment for an irregular heart rate. He said: “The old way of prescribing warfarin is more hit and miss; this is bespoke medication, calculated on my gene type. “My mum went on warfarin eight months ago and she was back and forward to the clinic at least four times on a weekly basis before they got the dose right. I went back once, which meant I could go back to work quicker, feeling well enough to go back to normal life. I think this a win-win, for me and for the health service.” NIHR Collaboration for Leadership in Applied Health Research and Care North West Coast University of Liverpool Clinics in Chester, Warrington and Liverpool
  9. 9.  6.5% of all admissions to hospital are due to ADRs  2nd commonest cause was due to diuretic-induced acute renal impairment  No clear guidance for renal function monitoring in the literature  NICE guidance suggests once every 6 months – but not based on robust data  Practice likely to vary throughout UK BMJ, 2004
  10. 10. Big Data Approach to Personalised Renal Function Monitoring: Phase I Big Data Anonymised electronic health records Cardiac failure Diuretic doses Machine learning Development of robust algorithms Patient acceptability GP acceptability Aims Personalised renal function monitoring guidance Assess clinical effectiveness and cost effectiveness
  11. 11.  Point of care renal function monitoring  Use of sensor for non-invasive monitoring  Results sent via mobile phone technology to secure cloud based server  Personalised renal function monitoring algorithm – to be continually refined Personalised messaging to GP about review of patient to assess diuretic dosage  Personalised renal function monitoring would optimise diuretic dosing, prevent renal impairment, and prevent hospital admission in keeping with 5-year forward view  Cost effectiveness would need to be assessed Big Data Approach to Personalised Renal Function Monitoring: Phase II
  12. 12. Changing Demographics • Multiple diseases • Multiple organ systems affected • Deterioration in: • Renal function • Liver function • Respiratory function • Cognitive function • Mobility • Polypharmacy
  13. 13. • Over 50 years • Polypharmacy patients • Small trial n=57 vs 53 • Pharmacogenetic profiling • Clinical outcome measures • We already have kidney and liver tests before we prescribe. • What if we also had genetic profiling?
  14. 14. • €15 million, H2020, 10 EU countries • Implement pre-emptive PGx testing in a real world clinical setting across 7 EU sites • Evaluate patient outcome and cost effectiveness using solid scientific methodology • Start 1-1-2016, 5 years • Consortium members: • H-J Guchelaar (Coordinator), • JJ Swen, M Kriek, LUMC • M Pirmohamed, R Turner, UOL • J Stingl, FDMD • M Ingelman-Sundberg, KI • M Karlsson, S Jönsson, PBUU • M Schwab, E Schaeffeler, IKP • VHM Deneer STZHM • M Samwald, G Sunder-Plassmann, MUWV • M van Rhenen, KC Cheung, KNMP • C Mitropoulou, GHXF • D Steinberger, BIOL • CL Davila Fajardo, SAS • G Patrinos, UPAT • V Dolžan, ULMF • A Cambon-Thomsen, UPS • G Toffoli, E Cecchin, CROA
  15. 15. N=8,000 Project Outline
  16. 16. The Only Thing That Is Constant Is Change Heraclitus (535BC - 475BC)

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