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Approaches to incorporating pharmacoeconomic data into early drug discovery

Approaches to incorporating pharmacoeconomic data into early drug discovery. Kevin Sheehy Acting CEO Medicines New Zealand. About Us.

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Approaches to incorporating pharmacoeconomic data into early drug discovery

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  1. Approaches to incorporating pharmacoeconomic data into early drug discovery Kevin Sheehy Acting CEO Medicines New Zealand

  2. About Us Medicines New Zealand is the industry association representing companies engaged in the research, development, manufacture and marketing of prescription medicines. Our Vision To improve health outcomes for New Zealanders through equitable access to quality medicines. Our Mission To advocate for patients’ needs by influencing public policy to achieve equitable access to quality medicines.

  3. In Brief • For a better understanding of your product’s potential • Tools available • Resources in NZ

  4. Dose selection • intuition, experience (tradition), empirical • Identifying optimal target population • pandemic & cervical cancer vaccines • new diabetic agents • Pandemic modelling • astoundingly accurate - IF appropriate parameters used

  5. Principle • Pharmacoeconomics • understanding what your product does and its effects in the population • Impacted by • development costs • product attributes • target population

  6. Pharmacoeconomics 101 • Disease and treatment models • disease progression in the population • treatment effects modifying disease progression • Cost structures • imposed onto simulations

  7. Biomarkers • ensure appropriate choice and widely recognised • Simulations • available or achievable for most diseases • Clinical Trial Simulation (and Pharmacometrics) • resource available in NZ • Cost structures • available, but vary geographically and in time

  8. Applications • Clinical Trial Simulation • mechanistic • disease progression + molecule effect = accurate predictive value • relatively new but well respected • FDA encourages its use – NICE supports use • low cost high value • enables adaptive clinical trial design • may reduce unnecessary trials being done • time intensive – so plan early • resource available in NZ

  9. Clinical Trial Simulation – Track record • Docetaxelfor non small-cell lung cancer • Simulation demonstrated low power to detect difference in dose intensification and eliminated the need to proceed with phase III trial • Ivabradine in angina pectoris • The best regimen and size required for validation for future phase III clinical trial found using CTS • Pregabalin for chronic neuropathic pain • CTS used to investigate how precisely the dose of pregabalin that causes a reduction in pain score can be estimated • Etanercept in pediatric patients with juvenile rheumatoid arthritis • Comparison of simulated 0.8 mg/kg with actual 0.4 mg/kg twice-daily regimen • CTS confirmed and subsequently FDA approved • Holford N, Ma SC and Ploeger BA, Clinical pharmacology & Therapeutics - State of the Art, Clinical Trial Simulation: A Review

  10. Clinical Trial Simulation – Track record • NZ contribution to CTS in Alzheimer’s disease • Phase 1 PK / PD data • disease progression • placebo • residual error • within subject variability • Showed that 4x4 crossover design capable of identifying a meaningful effect • Avoided need for 12 week parallel group • Retrospectively confirmed most appropriate trial was 4x4 • Subsequently decided to discontinue further development • Savings of $3 mil and 17 months • Lockwood P, Ewy Y, Hermann D, Holford N, Application of clinical trial simulation to compare proof of concept study designs for drugs with a slow onset of action; an example in Alzheimer’s disease. Pharm. Res. 23, 2050 – 2059 (2006)

  11. Cost component • Costs vary • with time • as standard treatment approaches change • early assessment will be imprecise, but can give and idea of the value compared to other products being developed. • Dependent on • Most efficient development pathway

  12. Opportunities • Identify • optimal evidence development needs • optimal target population • size of benefit and adverse effects • Minimise development costs • directly by reducing unhelpful trials • streamline development critical path (decision points) • Project • relative cost – benefit relationship

  13. Resources • FDA –Critical Path Initiative http://www.fda.gov/downloads/Drugs/GuidanceComplianceRegulatoryInformation/Guidances/UCM201790.pdf • NICE - Scientific Advice Consultancy Service http://www.nice.org.uk/aboutnice/scientificadvice/AboutScientificAdvice.jsp • University of Auckland • Shu Chin Ma, Ph.D • Research Fellow in Pharmacometrics • Dept Pharmacology & Clinical Pharmacology • Coming soon • NZ chapter of ISPOR

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