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| 題名: | 建構非固醇類抗發炎藥穿皮吸收之結構與滲透定量關係式與使用高效液相層析串聯質譜儀分析神經醯胺與甘油磷脂及鞘脂質 |
| 作者: | 劉怡伯 |
| 貢獻者: | 藥學系(博士班) |
| 關鍵詞: | 穿皮滲透 結構與滲透定量關係式 非固醇類抗發炎藥 溶解因子 生理參數 正相液相層析串聯大氣壓化學電離質譜儀 神經醯胺 裸鼠皮膚 逆相液相層析串聯電灑游離質譜儀 甘油磷脂 鞘脂質 |
| 日期: | 2010 |
| 上傳時間: | 2010-10-21 10:24:35 (UTC+8) |
| 摘要: | 本研究將建立一非類固醇抗發炎藥物(non-steroidal anti-inflammatory drugs, NSAIDs)經皮傳遞之結構與滲透量化關係(quantitative structure permeability relationship, QSPR)的實驗模式來預測滲透係數(permeability coefficients, kp)。選取十三種不同非類固醇抗發炎藥物來進行裸鼠全皮穿皮體外試驗。而其相關的裸鼠皮生理參數經皮水分散失(transepidermal water loss, TEWL)、皮膚水分含量(hydration content, HD)、皮膚油脂含量(lipid content, SB)、皮膚纖維彈性及方向性 (elasticity and direction of the fibers, RVM)及皮膚彈性係數(elasticity, EL)也被測量。將全部藥物根據不同軟體系統所得到的藥物極性度分成三個資料庫且將這三個資料庫中的藥物再依極性度(clogP 或 logKo/w)分為大於2及小於2兩組。而後根據模式藥物有關的物理特性分子量及極性度或溶解因子(solubility parameter)在有或無考慮皮膚的生理參數下進行迴歸。結果顯示，不管有沒有考慮裸鼠皮的生理參數，clogP 或 logKo/w值小於2的藥物組，當加入溶解因子進行迴歸後其所得到的相關係數(adjusted R2)大於0.90以上，相較於只有使用clogP 或 logKo/w所得到的相關係數有顯著提升。這個結果說明藥物的溶解因子可能是一個較適合用來評估預測NSAIDs藥物穿皮吸收的影響因子。將觀察所得的滲透係數對經由QSPR預測的滲透係數作圖，其結果證明此關係式具有預測經皮傳遞滲透係數的能力。結論得知，將clogP 或 logKo/w值小於2的模式藥物加上溶解因子及裸鼠皮的生理參數下所得到的預測QSPR關係式可以得到最理想的預測結果。另一方面，一個快速、敏感度高且準確性佳的高效液相層析串聯質譜儀分析方法(LC-MS)將用來分析脂質包括裸鼠皮皮膚中重要且複雜的神經醯胺物質，及大腦內主要脂質甘油磷脂族群及鞘脂質成份。使用正相的二氧化矽層析管柱來分析裸鼠皮中的神經醯胺物質，流動相由100%庚烷至100%丙酮/丁醇(90:10 v/v)，以每分鐘2%進行梯度沖堤，所有溶劑皆含有體積百分比0.1%的三乙醇胺及0.1%的甲酸，流速為每分鐘0.8毫升。正相的LC-APCI-MS可以很理想的分離裸鼠皮角質層中神經醯胺的九個族群。而藉由分析神經醯胺Ceramide [NS]標準品，並確效建立一檢量線來量化所有類型的神經醯胺。而甘油磷脂族群及鞘脂質成份則使用逆相的層析管柱Inertsil 6 ODS-3 (4.6 × 150mm) 來分析，流速設定為1.0 mL/min，移動相組成以acetonitrile/methanol/triethylamine =550/1000/25 (w/w/w) ，所有溶劑皆含有體積百分比0.1%的三乙醇胺。逆相的LC-ESI-MS可以很理想的分析甘油磷脂族群及鞘脂質成份。未來可將分析神經醯胺及甘油磷脂及鞘脂質的方法應用於了解人類身體的變化，以期在預防醫學，治療醫學或新藥開發領域上有新的進展。
In this study, an empirical model of the quantitative structure permeability relationship (QSPR) of the transdermal delivery of non-steroidal anti-inflammatory drugs (NSAIDs) was constructed in an attempt to predict the permeability coefficients (kP). Thirteen model NSAIDs were selected, and their in vitro permeation through the full skin of nude mice was examined. The biological parameters of transepidermal water loss (TEWL), hydration content (HD), lipid content (SB), elasticity and direction of the fibers (RVM), and elasticity (EL) were measured. The permeability coefficients were obtained by using three kinds of datasets of clogP or logKo/w and all model drugs were grouped into two group that were clogP or logKo/w values > 2 and < 2; these datasets were regressed with respect to the physical characters of molecular weight (MW) and polarity factor (clogP or logKo/w) or the solubility parameter (δ) of the model drugs rationally chosen to replace the polarity factor with or without taking into consideration the biological parameters of the skin. Results demonstrated that δ could be greatly improved compared to clogP and logKo/w in the regression with an adjusted R2 of > 0.90 using the dataset of those drugs with clogP or logKo/w values of < 2, regardless of whether or not biological parameters were taken into consideration. This indicates that δ might rationally be a more-appropriate drug parameter for predicting the skin permeability of NSAIDs for transdermal delivery. A plot of observed kP versus predicted kP values by this simple empirical model of QSPR was validated to demonstrate the predictive capability of kP for transdermal delivery. In conclusion, an empirical model of QSPR to predict kp based on the hydrophilicity of the model drugs was statistically improved with δ and by taking the biological parameters of the skin into consideration. A sensitive and accurate liquid chromatography and mass spectrometry (LC- MS) for determining the standard ceramide [NS], glycerophospholipid and sphingolipid were developed. A normal-phase silica column was utilized with the gradient elution from 100% heptane to 100% acetone/butanol 90:10 v/v in 2%/min at 0.8 mL/min (all solvents contained 0.1% triethylamine and 0.1%formic acid v/v). Normal-phase LC-APCI-MS was optimized to separate the nine classes of ceramide presented in the stratum corneum (SC) of nude mouse skin. Then analysis of ceramide [NS] was validated and employed as the standard for constructing a calibration curve for quantitation of all classes of ceramides. Application of this method to profile the class and content of ceramides in the SC of nude mouse skin was conducted and proved to be workable. Reverse-phase LC-ESI-MS was optimized to analyze glycerophospholipid and sphingolipid, and Inertsil 6 ODS-3 (4.6 × 150mm) column was utilized with mobile phase : acetonitrile / methanol / triethylamine = 550 / 1000 / 25 (w/w/w) contained 0.1% triethylamine v/v。Flow rate was 1.0 mL/min. It was concluded that this improved method could be used to detect ceramide and glycerophospholipid and sphingolipid directly. Furthermore, the analysis method of ceramide and glycerophospholipid and sphingolipid could be applied to detect the physiology change of human in order to discover the preventive medicine, treatment medicine, or new drugs development field. |
| 關聯: | 126頁 |
| 描述: | (一)論文目次
目錄
附表目錄 IV
附圖目錄 VI
中文摘要 IX
ABSTRACT XI
壹、緒論 1
第一節 研究背景介紹 1
一、藥物穿皮試驗及結構與滲透定量關係式(QSPR)之原理與應用 1
二、非固醇類抗發炎藥物(NSAIDs)之概述 5
三、皮膚組成及生理參數之概述與實驗理論 7
四、皮膚內容物神經醯胺之概述及其分析研究 9
五、甘油磷脂(Glycerophospholipids) 及鞘脂質(Sphingolipid)之研究概述 15
六、LC/MS儀器原理 20
第二節 研究動機 24
貳、實驗材料與方法 25
第一節 實驗材料 25
第二節 儀器設備 26
第三節 實驗方法 30
一、利用高壓液相層析法(HPLC)進行十三個模式藥物分析 30
二、藥物極性(polarity)及溶解因子(solubility parameters, δ)的分析 31
三、裸鼠皮膚特性評估試驗 33
四、體外穿皮吸收試驗 33
五、QSPR預測模式之數據處理分析 36
六、裸鼠皮膚神經醯胺之分析 37
七、甘油磷脂(Glycerophospholipids) 及鞘脂質(Sphingolipid)之方析方法 41
參、結果與討論 42
第一節、NSAIDs模式藥物分析確效 42
第二節、藥物極性(polarity)及溶解因子(solubility parameter, δ)分析 55
第三節、裸鼠皮膚特性評估 60
第四節、體外穿皮吸收試驗 65
第五節、探討QSPR預測關係式之建立 68
第六節、裸鼠皮膚中神經醯胺之分析 79
第七節、甘油磷脂(Glycerophospholipids)及鞘脂質(Sphingolipid)之分析 93
肆、結論 116
伍、參考文獻 118
陸、著作選集 127
附表目錄
Table 1. Molecular weight of the model drugs 6
Table 2. List of analytical method of ceramides 14
Table 3. List of analytical method of glycerophospholipids and sphingolipid 19
Table 4. Analytical condition of the model drugs 31
Table 5. Gradient used to analyse and validate ceramide standard by normal phase HPLC prior to mass spectrometry 38
Table 6. Intraday accuracy and precision of aspirin（n=6） 43
Table 7. Interday accuracy and precision of aspirin（n=6） 43
Table 8. Intraday accuracy and precision of diclofenac（n=6） 44
Table 9. Interday accuracy and precision of diclofenac（n=6） 44
Table 10. Intraday accuracy and precision of diclofenac sodium（n=6） 45
Table 11.Interday accuracy and precision of diclofenac sodium（n=6） 45
Table 12. Intraday accuracy and precision of diflunisal（n=6） 46
Table 13. Interday accuracy and precision of diflunisal（n=6） 46
Table 14. Intraday accuracy and precision of flufenamic acid（n=6） 47
Table 15. Interday accuracy and precision of flufenamic acid（n=6） 47
Table 16. Intraday accuracy and precision of ibuprofen（n=6） 48
Table 17. Interday accuracy and precision of ibuprofen（n=6） 48
Table 18. Intraday accuracy and precision of ibuprofen sodium（n=6） 49
Table 19. Interday accuracy and precision of ibuprofen sodium（n=6） 49
Table 20. Intraday accuracy and precision of ketoprofen（n=6） 50
Table 21. Interday accuracy and precision of ketoprofen（n=6） 50
Table 22. Intraday accuracy and precision of nabumetone（n=6） 51
Table 23. Interday accuracy and precision of nabumetone（n=6） 51
Table 24. Intraday accuracy and precision of naproxen（n=6） 52
Table 25. Interday accuracy and precision of naproxen（n=6） 52
Table 26. Intraday accuracy and precision of piroxicam（n=6） 53
Table 27. Interday accuracy and precision of piroxicam（n=6） 53
Table 28. Intraday accuracy and precision of tenoxicam（n=6） 54
Table 29. Interday accuracy and precision of tenoxicam（n=6） 54
Table 30. Intraday accuracy and precision of indomethacin（n=6） 55
Table 31. Interday accuracy and precision of indomethacin（n=6） 55
Table 32. Molecular properties of the model drugs 56
Table 33. Calculation of solubility parameter by the structure of the model drugs 57
Table 34. Solubility parameter of the model drugs 59
Table 35. The skin parameters study of nude mice 61
Table 36. The correlation of skin parameters of nude mice 64
Table 37. The skin parameters and permeability coefficient (kp) of model drugs. 66
Table 38. List of mathematical equations and adjusted R2 for predicting skin permeability from drug parameters 72
Table 39. List of mathematical equations and adjusted R2 values for predicting the skin permeability from drug parameters and skin parameters 78
Table 40. Intraday and interday (n = 6) analytical precisions for ceramide[NS] by normal phase (NP) LC-APCI-MS 84
Table 41. The molecules and chain length of ceramides Cer[EOS], Cer[EOH], Cer[EOP], Cer[NS], Cer[NP], Cer[AS], Cer[NH], Cer[AP], Cer[AH] identified in the SC of nude mice skin by normal-phase LC-APCI-MS 88
Table 42. The percentage (%) and content (ng/cm2) of ceramide profile in six different parts of nude mice skin by LC-APCI-MS 90
Table 43. Intraday accuracy and precision of phosphatidylcholine (PC)（n=5）. 97
Table 44. Interday accuracy and precision of phosphatidylcholine (PC)（n=5）. 97
Table 45. Intraday accuracy and precision of phosphatidylethanolamine (PE)（n=5）. 101
Table 46. Interday accuracy and precision of phosphatidylethanolamine (PE)（n=5）. 101
Table 47. Intraday accuracy and precision of phosphatidylinositol (PI)（n=5） 105
Table 48. Interday accuracy and precision of phosphatidylinositol (PI) （n=5） 105
Table 49. Intraday accuracy and precision of phosphatidylserine (PS)（n=5） 109
Table 50. Interday accuracy and precision of phosphatidylserine (PS) （n=5） 109
Table 51. Intraday accuracy and precision of sphingomyelin (SM) （n=5） 113
Table 52. Interday accuracy and precision of sphingomyelin (SM) （n=5） 113
附圖目錄
Figure 1. The structure of human skin. 7
Figure 2. The distribution of components in human skin. 10
Figure 3. The common structure of ceramide. R is fatty acid and R' is sphingoid base. 12
Figure 4. The structures of ceramide classes in stratum corneum. 12
Figure 5. Evolution of genomics to lipidomics through proteomics and metabolomics. 16
Figure 6. Major classes of brain glycerophospholipids and sphingolipids. 19
Figure 7. The profile of LC-MS. 21
Figure 8. The profile of (A)electrospray ionization (ESI) and (B) atmospheric pressure chemical ionization (APCI). 23
Figure 9. High-performance liquid chromatography and mass spectrometeter (LC-MS). 27
Figure 10. The instrument of MPA 580. 29
Figure 11. Franz diffusion cell used in vitro penetration test. 35
Figure 12. Skin from the abdomen and back was taken off the nude mice divided into six pieces. 40
Figure 13. The normal distribution curve of skin parameters in nude mice (n=78). (A)TEWL; (B)hydration; (C)sebum; (D)RVM; (E)elasticity. 63
Figure 14. Cumulative amount of 13 model drugs permeated (µg/cm2) across nude mice skin: (A) aspirin, (B) diclofenac, (C) diclofenac sodium, (D) diflunisal, (E) flufenamic acid, (F) ibuprofen, (G) ibuprofen sodium, (H) ketoprofen, (I) nabumetone, (J) naproxen, (K) piroxicam, (L) tenoxicam, and (M) indomethacin. 67
Figure 15. A comparison of experimental data with predicted data by the constructed empirical model of QSPR. Skin permeability regressed versus drug parameters without (A) or with (B) solubility parameter; skin permeability regressed versus drug parameters and skin parameters without (C) or with (D) solubility parameter. 72
Figure 16. Possible routes of solute transport through the epidermis. 73
Figure 17. Simulated permeability coefficients with respective to the molecular weight (MW) and the solubility parameter (δ) of drugs based on the QSPR model (=0.00717 MW - 0.02129??- 7.34074). 74
Figure 18. Chromatogram of the separated standard Cer[NS] by normal-phase HPLC-APCI-MS in positive mode. 82
Figure 19. Mass spectra [M+H]+ of standard Cer[NS]. 82
Figure 20. Calibration curve of Cer[NS] at working concentrations of 0.1-10 ng/mL. 83
Figure 21. Calibration curve of Cer[NS] at working concentrations of 1.0-100 ng/mL. 83
Figure 22. Optimization of extraction solvent ratio. Chloroform: methanol =(A) 2:1; (B) 1:1; (C) 1:2. 86
Figure 23. Chromatograms of stratum corneum ceramides by normal - phase LC-APCI-MS in positive mode, (A) whole spectrum, (B) exclusion of first 10 min). (1): Cer[EOS], (2): Cer[NS], (3): Cer[EOH], (4): Cer[EOP], (5): Cer[NP], (6): Cer[AS]/[NH], (7): Cer[AP], (8): Cer[AH]. 87
Figure 24. The percentage of ceramide subclasses(relative abundance % ±SD) in different parts of nude mice skin by LC-APCI-MS analysis. 91
Figure 25. The content of ceramide subclasses in different parts of nude mice skin by LC-APCI-MS analysis. 92
Figure 26. LC-ESI-MS single ion chromatograms of phosphatidylcholine (PC) standard. 95
Figure 27. Mass spectra [M+H]+ of molecular ions in phosphatidylcholine (PC) with RP-HPLC in combination with positive ESI MS. 95
Figure 28. In positive ESI the most abundant peaks were found to be the [M+H]+ ions of phosphatidylcholine (PC). (A) 16:0/18:2 (m/z 758); (B) 18:0/18:2 (m/z 786); (C) 18:0/18:1 (m/z 788). 96
Figure 29. Calibration curve of phosphatidylcholine (PC). . 96
Figure 30. LC-ESI-MS single ion chromatograms of phosphatidylethanolamine (PE) standard. 99
Figure 31. Mass spectra [M+H]+ of molecular ions in phosphatidylethanolamine (PE) with RP-HPLC in combination with positive ESI MS. 99
Figure 32.In positive ESI the most abundant peaks were found to be the [M+H]+ ions of phosphatidylethanolamine (PE). (A) 18:2/18:2 (m/z 740); (B) 16:1/22:6 (m/z 761); (C) 20:4/20:4 (m/z 788). 100
Figure 33. Calibration curve of phosphatidylethanolamine (PE).. 100
Figure 34. LC-ESI-MS single ion chromatograms of phosphatidylinositol (PI) standard. 103
Figure 35. Mass spectra [M+H]+ of molecular ions in phosphatidylinositol (PI) with RP-HPLC in combination with positive ESI MS. 103
Figure 36. In positive ESI the most abundant peaks were found to be the [M+H]+ ions of phosphatidylinositol (PI). (A) 16:0/20:4 (m/z 858); (B) 18:1/18:1 (m/z 862); (C) 17:0/20:4 (m/z 871). 104
Figure 37. Calibration curve of phosphatidylinositol (PI).. 104
Figure 38. LC-ESI-MS single ion chromatograms of phosphatidylserine (PS) standard. 107
Figure 39. Mass spectra [M+H]+ of molecular ions in phosphatidylserine (PS) with RP-HPLC in combination with positive ESI MS. 107
Figure 40. In positive ESI the most abundant peaks were found to be the [M+H]+ ions of phosphatidylserine (PS). (A) 18:0/20:1 (m/z 816); (B) 18:0/22:5 (m/z 837). 108
Figure 41. Calibration curve of phosphatidylserine (PS). 108
Figure 42. LC-ESI-MS single ion chromatograms of sphingomyelin (SM) standard. 111
Figure 43. Mass spectra [M+H]+ of molecular ions in sphingomyelin (SM) with RP-HPLC in combination with positive ESI MS. 111
Figure 44. In positive ESI the most abundant peaks were found to be the [M+H]+ ions of sphingomyelin (SM). (A) 18:1/16:0 (m/z 703); (B) 18:1/22:0 (m/z 788); (C) 18:1/24:0 (m/z 815). 112
Figure 45. Calibration curve of sphingomyelin (SM). 112
Figure 46. LC-ESI-MS chromatograms of major classes of brain glycerophospholipids standards (PC, PS, PI, PE) and sphingolipid (SM) standard. 115
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