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Pharmacokinetics (II) 藥物動力學

Pharmacokinetics (II) 藥物動力學. 鮑力恒 國防醫學院藥學系. Early and Late PhaseⅠStudies. Phase 2 Clinical Studies Involving Pharmacokinetics. Phase 3 Clinical Studies Involving Pharmacokinetics. 生體可用率與生體相等性 學名藥與原開發廠 國產藥品與國外進口藥品. 體外品管之指標. 藥品含量 藥品主成份含量均一度 藥品之安定性 藥品之溶離試驗等 符合藥典之規定. ?. A 廠 = B 廠.

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Pharmacokinetics (II) 藥物動力學

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  1. Pharmacokinetics (II)藥物動力學 鮑力恒 國防醫學院藥學系

  2. Early and Late PhaseⅠStudies

  3. Phase 2 Clinical Studies Involving Pharmacokinetics

  4. Phase 3 Clinical Studies Involving Pharmacokinetics

  5. 生體可用率與生體相等性 學名藥與原開發廠 國產藥品與國外進口藥品

  6. 體外品管之指標 • 藥品含量 • 藥品主成份含量均一度 • 藥品之安定性 • 藥品之溶離試驗等 符合藥典之規定

  7. ? A廠 = B廠 A廠藥效 = B廠藥效

  8. 體內品管之指標 –生體可用率 • 藥品有效成份由製劑中吸收進入全身血液循環或作用部位之量與速率之指標。

  9. 體內品管之指標 –生體可用率 (BA) 最高濃度：吸收之速率 血漿中藥物濃度 曲線下之面積：吸收進入體內之量 時間

  10. 生體相等性 (BE) • 以相同條件給予同一組人： • 隨機交叉試驗方式，以減少個體間之差異

  11. 生體相等性 (BE) - 原製造廠 - 非原製造廠 血漿中藥物濃度 時間

  12. 生體相等性 (BE) 之判斷 血漿中藥物濃度 血漿中藥物濃度 時間 時間 血漿中藥物濃度 時間

  13. 新劑型的研發

  14. 控釋劑型之設計 • 藥物自控釋劑型中釋出之量： • 藥物之藥動性質 • 治療濃度 • 用藥頻率

  15. 控釋劑型之設計 – 劑量之計算 • Dtot = Di + Dm • Di :初始劑量 • Dm : 維持劑量- 以zero-order(k0)釋出維持td時間 • Dtot = Di + k0 td • Dtot = Di - k0tp+ k0 td td : 到達最高濃度所需之時間

  16. 控釋劑型之設計 – 釋出之速率 • 到達穩定狀態 • Rate in = Rate out • 藥物自體內清除之速率 ：ClT (ml/min) • ClT (ml/min) x Cp (μg/ml) = μg/min • K0 = ClT Cp

  17. Dtot = ClT Cp τ

  18. Transdermal dosage form穿皮製劑 如何判斷是否該出方之實用性？ 穿皮速率是否足夠？

  19. 體外實驗之結果 • 體外穿皮試驗 • 流量 (Flux)：單位時間內穿擴單位面積之藥量 此可視為單位面積藥物之給藥速率

  20. 治療濃度：Cp藥物之清除率：Cl • 藥物自體內之清除速率：R • R = Cl*Cp • 製劑面積大小 = Cl*Cp / J • 可知是否要製成背心穿在身上才會有效

  21. 臨床藥物治療監測 Therapeutic Drug MonitoringTDM - Applied Pharmacokinetics

  22. Steady-state Rate in = F . Dose / t Unit : mg/hr Rate out = Css. CL Unit : mg/L . L/hr = mg/hr

  23. 例題： • 一男性Asthma病患：40歲，體重：70 Kg，如給予Aminophylline IV infusion(點滴)，則其Loading dose (初始劑量)是多少? • 兩天以後，病患出院，改以口服之劑型，病患之服藥劑量應是多少？要多久服用一次？

  24. Population Pharmacokinetics

  25. Source of variability The drug. Body acts on the drug, ADME, Pharmacokinetics Drug is distributed in the body Modern Drug Delivery Clinical endpoint Drug acts on the body Pharmacodynamics Efficacy and Toxicity

  26. Extensive PK Sparse PK Mixed Effects Modeling 0.20 0.15 Drug Concentration 0.10 0.05 Safety Efficacy 0.0 0 1 2 3 4 5 6 Time (h) Exposure Exposure Clinical data are sparse and observational. Population mixed- effect modeling method is a fundamental tool for characterizing the multi –dimensional relationships with sparse data Choice of Dosage Regimen

  27. Populationapproach • To utilize sparse data in data analysis • To handle mixed data sets • To screen covariates that impact drug’s kinetic and dynamic properties • To model random inter-subject, intra-subject, as well as inter-occasion variabilities • To estimate individual kinetic and/or dynamic parameters via post hoc • To simultaneously model kinetic, dynamic, and safety data

  28. Software • Software used for modeling: • S-PLUS • WinNonMix • Ppharm • SAAM II Pop • NONMEM • Other • Software used for model automation: • Expose • WinBugs • WAM • Other • Software validation • Software modification • Custom software

  29. Examples: Pediatric PK • Number of subject are limited • Measurements are sparse, unbalanced, and very limited. • PK characteristics may differ from those of Adults or unknown • CL may be a function of Age, or BSA • Vd may be a function of WT • Poor protocol compliance • Product development time line • Cost in increasing N vs. increasing n • Competitors market • Age or WT data treated as groups vs. as continuous variables.

  30. Sampling time options

  31. Sampling Options

  32. Pediatric PK study

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