School of Chemistry and Biochemistry, Georgia Institute of Technology, Atlanta, Georgia, United States of America.
Lao-Oxford-Mahosot Hospital-Wellcome Trust-Research Unit, Microbiology Laboratory, Mahosot Hospital, Vientiane, Lao PDR.
PLoS Negl Trop Dis. 2021 Sep 30;15(9):e0009360. doi: 10.1371/journal.pntd.0009360. eCollection 2021 Sep.
Post-market surveillance is a key regulatory function to prevent substandard and falsified (SF) medicines from being consumed by patients. Field deployable technologies offer the potential for rapid objective screening for SF medicines.
We evaluated twelve devices: three near infrared spectrometers (MicroPHAZIR RX, NIR-S-G1, Neospectra 2.5), two Raman spectrometers (Progeny, TruScan RM), one mid-infrared spectrometer (4500a), one disposable colorimetric assay (Paper Analytical Devices, PAD), one disposable immunoassay (Rapid Diagnostic Test, RDT), one portable liquid chromatograph (C-Vue), one microfluidic system (PharmaChk), one mass spectrometer (QDa), and one thin layer chromatography kit (GPHF-Minilab). Each device was tested with a series of field collected medicines (FCM) along with simulated medicines (SIM) formulated in a laboratory. The FCM and SIM ranged from samples with good quality active pharmaceutical ingredient (API) concentrations, reduced concentrations of API (80% and 50% of the API), no API, and the wrong API. All the devices had high sensitivities (91.5 to 100.0%) detecting medicines with no API or the wrong API. However, the sensitivities of each device towards samples with 50% and 80% API varied greatly, from 0% to 100%. The infrared and Raman spectrometers had variable sensitivities for detecting samples with 50% and 80% API (from 5.6% to 50.0%). The devices with the ability to quantitate API (C-Vue, PharmaChk, QDa) had sensitivities ranging from 91.7% to 100% to detect all poor quality samples. The specificity was lower for the quantitative C-Vue, PharmaChk, & QDa (50.0% to 91.7%) than for all the other devices in this study (95.5% to 100%).
The twelve devices evaluated could detect medicines with the wrong or none of the APIs, consistent with falsified medicines, with high accuracy. However, API quantitation to detect formulations similar to those commonly found in substandards proved more difficult, requiring further technological innovation.
上市后监测是防止劣药和假药(SF)被患者使用的关键监管功能。现场可部署技术为快速客观筛查 SF 药品提供了潜力。
我们评估了十二种设备:三种近红外光谱仪(MicroPHAZIR RX、NIR-S-G1、Neospectra 2.5)、两种拉曼光谱仪(Progeny、TruScan RM)、一种中红外光谱仪(4500a)、一种一次性比色测定法(纸分析设备,PAD)、一种一次性免疫测定法(快速诊断测试,RDT)、一种便携式液相色谱仪(C-Vue)、一种微流系统(PharmaChk)、一种质谱仪(QDa)和一种薄层色谱试剂盒(GPHF-Minilab)。每种设备都用一系列现场采集的药物(FCM)和实验室中配制的模拟药物(SIM)进行了测试。FCM 和 SIM 的范围从具有良好质量活性药物成分(API)浓度的样品、API 浓度降低(API 的 80%和 50%)、无 API 和错误 API 的样品。所有设备对无 API 或错误 API 的药物的检测均具有很高的灵敏度(91.5%至 100.0%)。然而,每种设备对 API 为 50%和 80%的样品的灵敏度差异很大,从 0%到 100%不等。红外和拉曼光谱仪对检测 API 为 50%和 80%的样品的灵敏度各不相同(5.6%至 50.0%)。具有定量 API 能力的设备(C-Vue、PharmaChk、QDa)对所有劣质样品的检测灵敏度均在 91.7%至 100%之间。定量 C-Vue、PharmaChk 和 QDa 的特异性(50.0%至 91.7%)低于本研究中其他所有设备(95.5%至 100%)。
评估的十二种设备可以检测到 API 错误或不存在的药物,与假药一致,具有很高的准确性。然而,要检测到与劣质品中常见的制剂相似的制剂,API 定量就更具挑战性,需要进一步的技术创新。