Alan Maloney
  • Drug Development for Patients
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  1. 21  Technical Sections To Write
  • Welcome
  • 1  Introduction
  • 2  My Motivation For This Book
  • 3  Why Patients Outcomes Must Come First
  • 4  A Brief History Of Drug Development; The Good, The Bad And The Ugly
  • 5  Dose-Response Trials; A Brief History And Overview Of Current Practices
  • 6  The Science; Why We Must Care About Dose, Pharmacokinetics, Pharmacodynamics And Utility
  • 7  Introduction To IIV In PK And Its Consequences To D-E-R Trial Design
  • 8  Introduction To IIV In PD And D-E-R Analysis As Evidence For Regulators
  • 9  Personalised Dosing; Patients Are Different
  • 10  Where Does Precision Medicine And Personalised Medicine Fit In?
  • 11  Dose-Response Modelling; Why We Need Integrated Analyses Across All Doses/Trials
  • 12  Introducing The Most Important Dose-Response Model
  • 13  Population and Individual Dose-Exposure-Responses, Therapeutic Windows and Maximum Tolerated Doses
  • 14  What Should Be The Role For Regulators?
  • 15  The Two Regulatory Approval Pathways; “Approval P” and “Approval I”
  • 16  The Two Development Strategies; “Strategy P” and “Strategy I”
  • 17  Changing How We Pay For Drugs; Value/Outcome-Based Pricing And Subscription-Based Pricing
  • 18  What Product Should Drug Companies Sell? (can be skipped)
  • 19  Adaptive Randomisation In Population D-E-R Trials; Why We Should Learn As We Go
  • 20  The Half-Time Summary; What Have We Learnt, And What Solutions Are Outstanding?
  • 21  Technical Sections To Write
  • 22  Conclusions
  • 23  Acknowledgements
  • Glossary
  • Contact

21  Technical Sections To Write

to do!

  • Explain basic Clinical Trial Simulation (Simulation/Estimation * 1000)

  • Explain key concepts around how we define/assess precision of DR

  • Explain key concepts around how we define/assess bias of DR

  • More advanced topics for optimal designs of DR, like D-optimality and V-optimality

  • Compare optimal(adaptive) designs of D-E-R versus DR

  • Introduce Planned Titration trials (a much better name for “forced” titration!)

  • Explain the value of ER models for prediction (extrapolation to new regimens, pediatrics etc.)

  • Explain the benefit of dose titration with respect to tolerance

  • Have sections entitled:

    • Design and Analysis of Population D-E-R Trials

    • Design and Analysis of Individual D-E-R Trials

  • Introduce technical code to fit D-E-R models? e.g. Bayesian analysis using HMC in STAN? Mention diffuse priors (better in Appendix?)

  • Show case examples where drugs are individualised (to remove the mystery!)

20  The Half-Time Summary; What Have We Learnt, And What Solutions Are Outstanding?
22  Conclusions
Copyright Alan Maloney, May 2023
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