4.4 Article

Use of Monte Carlo simulation and considerations for PK-PD targets to support antibacterial dose selection

期刊

CURRENT OPINION IN PHARMACOLOGY
卷 36, 期 -, 页码 107-113

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ELSEVIER SCI LTD
DOI: 10.1016/j.coph.2017.09.009

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资金

  1. Achaogen Inc.
  2. AiCuris GmbH
  3. Arsanis Inc.
  4. Cellceutix Corporation
  5. Cempra Pharmaceuticals
  6. Cidara Therapeutics Inc.
  7. Contrafect Corporation
  8. Debiopharm International SA
  9. Entasis Therapeutics
  10. Geom Therapeutics, Inc.
  11. GlaxoSmithKline
  12. Horizon
  13. Insmed Inc.
  14. Kalyra Pharmaceuticals
  15. Medicines Company
  16. Meiji Seika Pharma Co., Ltd.
  17. Melinta Therapeutics
  18. Merck Sharpe Dohme.
  19. Nabriva Therapeutics
  20. Naeja RGM Pharmaceuticals Inc.
  21. NuCana Biomed
  22. Paratek Pharmaceuticals
  23. Pernix Therapeutics
  24. Polyphor Ltd.
  25. Roche Bioscience
  26. Shionogi, Inc.
  27. Sofinnova Ventures, Inc.
  28. Spero Therapeutics
  29. Theravance Biopharma Pharmaceutica
  30. Tetraphase Pharmaceuticals
  31. VenatoRx
  32. Wockhardt Ltd.
  33. Zavante Therapeutics

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Monte Carlo simulation is used to generate data for pharmacokinetic pharmacodynamic (PK-PD) target attainment analyses to assess antibacterial dosing regimens in early and late stage drug development. Careful consideration of the quality of data for pharmacokinetics, non-clinical PK-PD targets for efficacy, the choice of the bacterial reduction endpoint upon which the PK-PD target is based, variability in the PK-PD target, and effect site exposures ensures optimal dose selection. Relationships between drug exposure and efficacy and/or safety endpoints based on clinical data can also be applied to simulated data to support dose selection. These in silico analyses, conducted throughout drug development, provide the greatest opportunity to de-risk the development of antibacterial agents.

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