Coupling Chemical Analysis to High Resolution Microscopy for Enhanced Physicochemical Characterization of Drug Products Containing Nanomaterials and Other Complex Formulations
Sheetal D’Mello, Mamta Kapoor, Katherine Tyner, Sau (Larry) Lee
Office of Pharmaceutical Quality, Center for Drug Evaluation and Research,
Food and Drug Administration, Silver Spring, MD 20993
在提交給FDA的申請中,含有納米材料的藥物產(chǎn)品越來越引人注目。這些新藥中有許多是單相或多相體系中含有顆粒的復(fù)合劑型。通常,產(chǎn)品的實際微觀結(jié)構(gòu)是未知的。隨著產(chǎn)品數(shù)量的增加,如何恰當(dāng)?shù)囟x和描述這些配方的關(guān)鍵質(zhì)量屬性也是一個問題。通過光散射或成像分析藥物的粒度分布(這類產(chǎn)品的常見特征)很少能夠提供有關(guān)藥物的化學(xué)微觀結(jié)構(gòu)的信息(例如,活性藥物成分(API)的位置)。從質(zhì)量控制的角度來看,隨著配方復(fù)雜性的增加,這些信息變得更加重要。因此,我們的工作重點是利用納米高光譜顯微鏡定量評價復(fù)雜藥物制劑中的顆粒大小分布,獲得藥物產(chǎn)品的整體微觀結(jié)構(gòu)信息。
納米高光譜顯微成像系統(tǒng)可以觀察復(fù)雜配方中納米尺度域的多分散性,為DLS的測量結(jié)果提供了補(bǔ)充。
運(yùn)用CytoViva®顯微鏡綜合配方,不同大小的數(shù)量被確定(類似于DLS直方圖),但圖像分析進(jìn)一步能夠區(qū)分聚集,這在其他技術(shù)中是不可能實現(xiàn)的。
該方法通過建立參比材料的光譜庫,實現(xiàn)了水包油乳液中納米尺度結(jié)構(gòu)域的識別和映射。
我們能夠?qū)Χ嘞嘀苿┲械囊后w微環(huán)境進(jìn)行區(qū)分和鑒別,并識別藥物產(chǎn)品中原料藥的分布。
我們還能夠光學(xué)和光譜分析其他復(fù)雜的環(huán)境,如奶油。
本報告演示了使用這種成像技術(shù)在復(fù)雜微觀結(jié)構(gòu)中建立API位置的概念驗證數(shù)據(jù)。
進(jìn)一步的工作包括方法驗證和技術(shù)魯棒性評價。
通過將化學(xué)信息與高分辨率成像技術(shù)產(chǎn)生的形態(tài)學(xué)信息耦合起來,我們可以通過獲取制劑微觀結(jié)構(gòu)的關(guān)鍵信息,重新定義成像方法在復(fù)雜藥物產(chǎn)品表征中的作用,否則無法獲得這些信息。
確定用于質(zhì)量控制和理化表征的成像參數(shù)將支持納米技術(shù)研究和復(fù)雜藥物產(chǎn)品開發(fā)。
此外,該項目將為驗證復(fù)雜產(chǎn)品的成像方法時的穩(wěn)健性研究提供一個框架。
最后,將討論有關(guān)感興趣的復(fù)雜配方的形態(tài)學(xué)的具體問題,并將代表我們理解復(fù)雜微觀結(jié)構(gòu)能力的提高
該技術(shù)發(fā)展成為一個FDA批準(zhǔn)APIs(活性藥物成分)的有效工具,用于表征納米或微米級的載體靶向給藥、藥物毒性等。同時該技術(shù)它也廣泛地應(yīng)用到成像和表征用于光熱治療及相關(guān)診療的研究中,比如納米毒理學(xué)和其他通用型納米材料的合成開發(fā)。目前美國FDA擁有五臺CytoViva系統(tǒng),2019年又將有一臺新系統(tǒng)投入使用。
原文:
Outlined below are some example hyperspectral images and associated data from a RESTASIS® sample. This data was captured separately from the FDA work but is illustrative of the ability to capture hyperspectral images and conduct image analysis as well as identify and spectrally map the API within the emulsion vector.
Outlined below are some example hyperspectral images and associated data from a RESTASIS® sample. This data was captured separately from the FDA work but is illustrative of the ability to capture hyperspectral images and conduct image analysis as well as identify and spectrally map the API within the emulsion vector.
Figure 7: Spectral Mapping of the API Spectra Throughout the Entire Image. Note That Most Mapping of the API Occurs Inside of the Emulsion.
In Figure 6 above, example spectrum from pixel areas of the emulsion chemistry and API are illustrated. There is a distinct red-shift of the API spectrum, which is ~100 nm difference at the peak wavelength versus that of the emulsion edge spectrum. Based on this difference, a spectral library of the API spectrum is created and tested against a negative control and is then used to conduct spectral mapping of all pixels matching the spectrum of the API in the image shown in Figure 7.
CytoViva是由美國Auburn大學(xué)與Aetos技術(shù)有限公司合作成立,具有高校和軍事公司背景,CytoViva納米高光譜成像技術(shù)最初是由美國國防部和美國宇航局空間衛(wèi)星航空成像開發(fā)的技術(shù)發(fā)展而來,該公司創(chuàng)造性的將該技術(shù)與增強(qiáng)型暗場技術(shù)結(jié)合并應(yīng)用于微觀層面,使其成為一個專有、集成的系統(tǒng),能夠在納米尺度上對材料、藥物、生命單元、活性大分子、環(huán)境污染物等進(jìn)行高光譜成像及定性定量分析。
CytoViva納米高光譜成像技術(shù)2005年一經(jīng)面市,就在2006年和2007年連續(xù)兩屆獲得著名的R&D100大獎,07年同年獲得Nano50TM獎,在09年獲得了兩項美國專利,專利號7542203和7564623,并迅速得到全球各個國家重點實驗室、科研機(jī)構(gòu)及大型制藥企業(yè)的認(rèn)可,包括FDA, NASA, NIST, NIH, EPA, USDA, NIOSH, Lawrence Berkeley Labs, Dow Chemical,Merck, Johnson& Johnson, Stanford, Duke, Harvard等等。
The application above is just one of many successful examples of drug delivery vector analysis that has been conducted utilizing CytoViva’s enhanced darkfield hyperspectral microscopy system to provide visual spatial and spectral context concerning the interaction between an API and its delivery vector.
Finally, CytoViva’s enhanced nano-scale hyperspectral imaging has recently been integrated with full-featured Raman imaging on the same microscope platform. This enables cross-correlation between the two techniques of an identical area of a sample. More information regarding this integration of fully featured Raman and broadband hyperspectral microscopy will be outlined in a separate white paper.