Quantitative thin layer chromatography for the determination of medroxyprogesterone acetate using a smartphone and open-source image analysis.

Intramuscular medroxyprogesterone acetate (MPA) products are commonly used to treat endometriosis and are the most widely used injectable contraceptives worldwide. Therefore, dependable quality screening of MPA injectables is a crucial measure necessary for ensuring that consumers are provided with safe and effective medications. Here, a thin-layer chromatography (TLC) method for MPA identification is combined with image analysis using a smartphone, 3D-printed light box, and open-source ImageJ software. The method's validation included two brands of MPA injectables, both at 150 mg mL-1 dosage. The TLC procedure used was based on the identity test found in The International Pharmacopoeia's Medroxyprogesterone injection monograph. Spots produced on the TLC plates were then photographed using a smartphone camera and quantified using ImageJ's image analysis software. The pixel data collected from each plate's standard spots were compared to the data generated from its sample spots. Data sets collected across multiple TLC plates and numerous days of method performance were evaluated to assess linearity, accuracy, precision, specificity, and robustness. Across the range of 75-125% of the target concentration, the method was found to have linearity of standard spots (with R2 generally greater than 0.99), overall accuracy of 101.0% (4.1% RSD), repeatability pooled standard deviation of 2.44%, intermediate precision pooled standard deviation of 3.68%, and observed demonstration of specificity and robustness. In low and middle-income countries (LMICs), quality screening of pharmaceutical products like MPA injectables can be challenging when testing resources are expensive, difficult to procure, or complex to utilize. The results of the TLC/ImageJ method validation suggest that this simple procedure that requires minimal resources may serve as a viable option for reliable quality screening of MPA levels in injectable suspensions.

A low-cost and portable near-infrared spectrometer using open-source multivariate data analysis software for rapid discriminatory quality assessment of medroxyprogesterone acetate injectables.

Medroxyprogesterone acetate (MPA) injectable suspensions are used by millions of women for family planning and hormonal therapy. Falsified or substandard medications may result in a health risk for consumers. Near-infrared spectroscopy (NIR) has previously been applied as a means of non-destructive and rapid screening of product quality compliance. These methods offer advantages but can be logistically and cost prohibitive for field use in resource limited areas. Here, a handheld spectrometer (900-1700 nm) with open-sourced software is used to evaluate vials of MPA from three suppliers (N = 227 vials) and verified by a benchtop UV-VIS-NIR (350-2500 nm) with licensed software. Multivariate data analysis assesses the spectral signatures of samples and builds a discriminant classification method based on Mahalanobis distances calculated from a principal component analysis scores. The handheld device paired with open-source software resulted in a product discrimination accuracy of 100% (verified by benchtop UV-VIS-NIR and chemical testing data) as well indicating that the low-cost field portable device is suitable for rapidly assessing samples in resource limited areas for consistency of manufacturing and sourcing.