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- 1. CT-FAST Simulation support to leansupplychainmanagement Cédric Druck cedric.druck@n-side.com +32 497 31 84 69 www.ct-fast.com
- 2. Outline Introduction to clinical trials The Challenge Simulation & optimization
- 3. Outline Introduction to clinical trials The Challenge Simulation & optimization
- 4. Drug Development Drug Discovery (5,000-10,000) Lab, animal testing PreClinical Development (250) First Human Dose Clinical Research (5) $550M NDA $350M To market (1) : 10 years
- 5. Clinical Trial Design GLOBAL ENROLLMENT Target number of Patients Investigation Sites Countries Label Groups STRATIFICATION Differentclasses of patients BLINDING Treatmentassignmentisundisclosed RANDOMIZATION Randomtreatmentassignment e.g. Active/Placebo/Comparator A A B A A ? ? ? ? ? B ? B B ? ?
- 6. Visits and Treatment VISIT SCHEDULE Patient returnsat a defined (flexible) schedule TITRATIONS Dosage may change based on events / doctor opinion / …
- 7. Supply Chain WHAT? Specific (expensive) Kit Types Limited shelf life(potential extension) Limited availability Different Labels / booklets HOW? Shipping strictlydownstream, long lead times, sometimes cold-chain
- 8. Outline Introduction to clinical trials The Challenge Simulation & optimization
- 9. Do it Right7! Don’t let us down! DRASTIC SERVICE LEVELS DEMANDED Patients healthatstake!
- 10. The rest of the trouble makers…
- 12. reduce the costs of the othertwo
- 13. maintain a high service levelProduction / safety stocks Potentiallyexpensive Just-in-time: frequentsmallshipments Potentiallyexpensive
- 14. Do itJUST right7! LEAN Balance riskand the differentcosts to effectivelyachieve a high service level
- 15. Outline Introduction to clinical trials The Challenge Simulation & optimization
- 16. Benefits
- 17. Simulation Principles INTEGRATED MONTE-CARLO Enroll & treat patients – learning set Computeinventory managementstrategies Distribute kits & match thedemand – validation set Estimate performanceindicators WHAT-IF ANALYSIS Compare differentstudy designs Verifyrobustnesswith regards to assumptions REAL-LIFE DATA TO Initializethe simulations Balance the user assumptions
- 21. CT-FAST Process
- 22. Cost vs. Risk: Case study Processimprovement suggestions Supplystrategyoptimization
- 23. Deliverables What-if analysis Cost vs. Riskanalysis & optimal strategyselection Detailed optimal strategy Assumptions Demandforecasts Shortageriskdetails Production schedule Shipping forecast IRT resupplyparameters
- 24. Future challenges Business Drug pooling Adaptive designs Parametersoptimization Detailedresults DB … Technology Web based client Cloud computing Open-end scripting …
- 25. Conclusion Our Simulation toolenables Increasing the cost-efficiency of the supplychain Better control on the service levels Communication and processimprovement How can simulation help you ? Betterunderstand/control complexsystems Forecastwithouthistorical data …
- 26. THANK YOU! Questions? Cédric Druck cedric.druck@n-side.com +32 497 31 84 69 www.ct-fast.com
Notas do Editor
- 4. Simulationprinciples – integrated, demand/supply/network. Based on assumptions, distributions and randomevents, real-life dataWhen to use it and howEarlyInitialAfterstudystartReacting to change
- 4. Simulationprinciples – integrated, demand/supply/network. Based on assumptions, distributions and randomevents, real-life dataWhen to use it and howEarlyInitialAfterstudystartReacting to change
- New Drug Application (NDA)EMA = EuropeanMedicinesAgency
- 4. Simulationprinciples – integrated, demand/supply/network. Based on assumptions, distributions and randomevents, real-life dataWhen to use it and howEarlyInitialAfterstudystartReacting to change
- 4. Simulationprinciples – integrated, demand/supply/network. Based on assumptions, distributions and randomevents, real-life dataWhen to use it and howEarlyInitialAfterstudystartReacting to change