In quality control with HPTLC, a specific method using optimized developing solvents is generally used for each kind of sample. In order to simplify routine analysis, the lab team at CAMAG has developed the complementary developing solvents (CDS) concept based on one solvent of low polarity (LPDS), one of medium polarity (MPDS), and one of high polarity (HPDS). With these three developing solvents (DS), each on a separate plate and targeting compounds of different polarity, the same complex sample could be spread over up to three times the separation distance on a single plate, making available more information about the sample’s composition. Single substances can be characterized with three R_F values instead of one. Even though this approach triples the analytical workload (3 analyses instead of one), it may be considered, that routine work with multiple and diverse samples can be simplified and maintenance of methods, plates, solvents and standards can be kept to a minimum, particularly if the process is automated. Identification of individual compounds will be more certain. A further advantage of the concept is that all samples can be compared with any other sample that has been previously analyzed with the same CDS and data could be compiled in a database for treatment with advanced algorithms.

In their paper [1] the researchers at CAMAG describe the development, validation and application of a CDS, applicable to a large number of very diverse samples including individual compounds and complex herbal materials. In combination with thorough standardization, the concept could help positioning HPTLC as a very powerful, general, and medium to high throughput technique for routine analysis and sophisticated research.

Visualization of the CDS and its fingerprints

The Universal HPTLC mix (UHM) was prepared in house according to [2]. With the UHM, HPTLC laboratories have a single solution, applicable as system suitability test to a wide range of chromatographic systems.

Powdered herbal drugs and finished products were prepared in methanol using 10 min sonication followed by 5 min centrifugation. Ginkgo biloba, Camellia sinensis, Styphnolobium japonica and Piper nigrum were prepared at 100 mg/mL, Curcuma longa at 66.7 mg/mL, Angelica samples at 200 mg/mL, and the poly-herbal formulation at 50 mg/mL.

HPTLC plates silica gel 60 F₂₅₄ (Merck), 20 x 10 cm are used.

Samples are applied as bands with the Automatic TLC Sampler (ATS 4), 15 tracks, band length 8.0 mm, distance from left edge 20.0 mm, distance from lower edge 8.0 mm.

Plates were developed with the three developing solvents in the ADC 2 with activation of the plate at 33% relative humidity for 10 min using a saturated solution of magnesium chloride. LPDS was used without saturation, whereas MPDS and HPDS were used with 20 min chamber saturation (with filter paper). The developing distance for all three methods was 70 mm (from the lower edge). Plates were dried for 5 min.

Natural product (NP) reagent (1.0 g of 2-aminoethyl diphenylborinate in 100.0 mL of methanol) is used as derivatization reagent for the identification of Camelia sinensis, Styphnolobium japonicum and Ginkgo biloba. For Ginkgo biloba, the derivatization with NP is followed by anisaldehyde sulfuric acid (AS) reagent [slowly and carefully 170.0 mL of ice-cooled methanol are mixed with 20.0 mL of acetic acid and 10.0 mL of sulfuric acid; mixture is allowed to cool to room temperature, then 1.0 mL of anisaldehyde (p-methoxybenzaldehyde) is added]. Only AS reagent is used for the identification of Curcuma longa and Piper nigrum.

Images are captured with the TLC Visualizer 2 in UV 254 nm, UV 366 nm, and white light prior to derivatization, and UV 366 nm, and white light after derivatization (when needed).

For the system suitability test using the UHM, TLC Scanner 4 and visionCATS are used in absorbance mode at 254 nm and in fluorescence mode at 366>/400 nm, with slit dimension 5.00 x 0.20 mm and scanning speed of 50 mm/s.

The solvents selected for the CDS had to meet the following criteria: be of minimal hazard, stable, and easily available, to cover all selectivity groups according to Snyder, and include a broad range of polarity. The composition and properties of the CDS are shown in the table.

Composition and properties of the CDSs

The power of the CDS concept is illustrated with HPTLC fingerprints for identification of herbal drugs, herbal products, and poly-herbal formulations. Green tea leaves, for example, produce a different fingerprint with each of the DS zooming into specific polarities of the sample composition. The composite fingerprint gives complementary information emulating an extended developing distance.

HPTLC fingerprints of green tea leaves obtained with the CDS

HPTLC can easily detect adulteration of one herbal drug with another, using optimized developing solvents. For example, a method from the HPTLC Association [3] detects adulteration of Ginkgo biloba leaves with fruits of Styphnolobium japonicum. The CDS achieves the same goal, but offers even more certainty based on the data obtained with MPDS and HPDS.

Detection of 20% Styphnolobium japonicum fruit in Ginkgo biloba leaves with method [3] and CDS

Poly-herbal formulations such as products containing Curcuma longa and Piper nigrum are generally identified based on specific markers. The CDS can identify with certainty the presence of curcuminoids for turmeric and piperine for black pepper.

Fingerprints of Curcuma longa and Piper nigrum in comparison to those of two poly-herbal products

The CDS has been qualified using the universal HPTLC mix (UHM). A maximum margin of error of 0.014 was determined for the relevant zones.

Separation of the UHM components with the CDS

The examples above illustrate the potential of the CDS for replacing the established methods for identification of herbal materials. Additional information concerning the chromatographic behavior of representative substances from different chemical classes is presented in the original paper [1]. When combined with fully automated chromatography, the CDS concept may become the basis for new applications of HPTLC in routine analysis and sophisticated research.

[1] T.K.T. Do et al. (2022) JPC, https://doi.org/10.1007/s00764-022-00185-1.
[2] T.K.T. Do et al. (2021) J. Chromatogr. A. 1638, https://doi.org/10.1016/j.chroma.2020.461830.
[3] HPTLC Association, Identification method of Ginkgo biloba, Leaf and leaf extract (flavonoids), (n.d.). https://www.hptlc-association.org/methods/methods_ for_identification_of_herbals.cfm.

Contact: Dr. Tiên Do, CAMAG, Sonnenmattstrasse 11, 4132 Muttenz, Switzerland, tien.do@camag.com

The Jean-Pierre Bourgin Institute (IJPB) is the largest center for plant biology at the National Research Institute for Agriculture, Food and Environment (INRAE). It combines resources and multidisciplinary skills in the areas of biology, chemistry, and mathematics. Located in Versailles, it is a Joint Research Unit between INRAE and AgroParisTech. The DYSCOL (Dynamics and structure of Lipid Droplets) team studies various aspects of lipid accumulation in seeds from oil crops and model plants. The Kennedy pathway allows storage of fatty acids in eukaryotes in the form of triacylglycerols (TAG), through successive acylation of a glycerol backbone by acyltransferases. Hundreds of different fatty acids are found in plants. The different fatty acids incorporated into vegetable oils confer them specific physical, chemical and nutritional properties. DGATs (diacylglycerol acyltransferases) incorporate the final fatty acid in position sn-3 of the glycerol skeleton. They catalyze the rate-limiting step of the whole pathway. Due to their impact on oil yield and quality, DGATs are targets of interest for oil engineering. We aimed to identify candidate proteins as DGATs and to understand their substrate specificity. We used various approaches based on recombinant protein expression in different hosts, and analysis of the products of the reaction by complementary approaches, GC and HPTLC.

Historically, demonstration of DGAT activity used radioactive precursors of substrates [1] followed by tedious extraction of the products (TAGs) [2] and quantification by liquid scintillation counting. Trans-methylation of TAGs produces fatty acid methyl esters, subsequently extracted, then separated and analyzed by GC. Alternatively, extraction of TAGs by improved methods and their separation from other cellular constituents by TLC is a convenient method avoiding radioactivity. Derivatization permits direct identification and quantification of the TAGs by comparison with standards.

HPTLC represents a valuable improvement of TLC. 12–15 samples are routinely separated at the same time on one plate. The method exhibits high sensitivity and reproducibility, and uses low amounts of organic solvents (< 50 mL for one run). Herein, we describe two methods to evidence DGAT activity and specificity using HPTLC.

Method (1) allows the analysis of extracted lipids by derivatization with phosphomolybdic acid reagent. Method (2) is used to study the activity and specificity of a purified DGAT.

1. Solutions of cholesteryl oleate, oleic acid methyl ester, trioleine, oleic acid, cholesterol at 2.7 μg/μL each in CHCl₃ are prepared.
2. NBD-DOG (1-{N-[(7-nitro-2-1,3-benzoxadiazol- 4-yl)-methyl] amino-decanoyl-2-decanoyl-sn-glycerol) stock solution in chloroform – methanol 2:1 (V/V) at 67.5 ng/μL (between 5.5 ng to 2.7 μg are applied to generate a calibration curve).

1. Lipids are extracted from yeast biomass according to Folch [2], dried under nitrogen, and resuspended in 200 μL of chloroform – methanol 2:1 (V/V).
2. DGAT assay to investigate enzyme specificity: NBD-DOG as a fluorescent DAG acceptor and different acyl donors (lauroyl-CoA, palmitoyl-CoA, stearoyl-CoA, oleoyl-CoA, and linoleoyl-CoA. The reaction is carried out at 31°C for one hour under shaking, then stopped by the addition of chloroform – methanol 2:1 (V/V).

HPTLC plates silica gel 60 (Merck), pre-washed with isopropanol, are used.

Between 3.0–6.0 μL for standard solutions and 50.0 μL for sample solutions (corresponding to 400 μg cells, dry weight) are applied as bands with the Automatic TLC Sampler (ATS 3), 15 tracks, band length 5.0 mm, distance from left edge 15.0 mm, distance from lower edge 8.0 mm.

Plates are developed in the Automatic Developing Chamber (ADC 2) with chamber saturation (with filter paper) for 20 min, (1) development with diethyl ether – hexane –methanol – acetic acid 60:40:5:1 (V/V) to the migration distance of 80 mm (from the lower edge), drying for 20 min, (2) development with hexane – diethyl ether – acetic acid 80:20:2 (V/V) to the migration distance of 80 mm (from the lower edge), drying for 20 min.

The plates are immersed in 5% phosphomolybdic acid in ethanol, then incubated for 30 min at 100 °C using an oven.

Images of the plates are captured in white light.

Fluorescence measurement is performed with the TLC Scanner 3 (excitation at 473 nm and emission > 510nm). DGAT activity is expressed as picomoles of TAG formed per minute and per milligram of purified protein, using a calibration curve based on the fluorescent signal of NBD-DOG.

The following figure shows the results of the separation of lipids extracted from three yeast strains (method 1). The control yeast strain was transformed with an empty vector; a second strain was transformed with the AtDGAT1 sequence encoding for Arabidopsis thaliana DGAT1, and the last strain was transformed with the EgDGAT1 sequence encoding for Elaeis guineensis DGAT1-1, a putative DGAT [3]. Both cassettes encoding for plant DGAT1 restored TAG accumulation in the Yarrowia lipolytica mutant strain [4]. Thus, we conclude that EgDGAT1 sequence was encoding for an active E. guineensis DGAT1-1.

Separation of lipids extracted from yeasts strains expressing plant type 1 DGATs (1: standards, 2: empty cassette, 3: AtDGAT1, 4: EgDGAT1-1).

To generate a calibration curve (method 2), the fluorescence of the NBD-DOG standard applied in different amounts is measured. The standard curve is depicting the dependence of the intensity of the fluorescence of NBD-DOG (minus blank value).

Calibration curve of NBD-DOG (scanned at 473 nm in fluorescence mode) depicting the dependence of the intensity of the fluorescence of NBD-DOG (top) as function of the amount separated on HPTLC plate (bottom)

In another experiment, purified recombinant DGA1, a type 2 DGAT from the yeast Yarrowia lipolytica was incubated with NBD-DOG and acyl-CoA with various acyl chain lengths (C12:0, C16:0; C18:0).

Separation of TAG synthetized by purified recombinant yeast type 2 DGAT (DGA1) using acyl-CoA with different chain lengths.

In the absence of an acyl donor, no NBD-TAG was formed (blank track). In the presence of acyl donors (C12:0, C16:0; C18:0–CoA), NBD-TAGs were formed. Noticeably, the migration of the reaction product depended on the length of the acyl chain incorporated. NBD-TAG with C18:0 migrate over a longer distance by comparison to NBD-TAG with C16:0 or C12:0.

HPTLC is a fast (within two hours), reproducible, and robust method to evidence acyltransferases activities. In vivo (1), complementation of microbial strains affected in neutral lipid metabolism by sequences coding for DGAT led to accumulation of TAGs. The products were extracted, separated by HPTLC and identified directly by comparison with standard molecules. In vitro (2), DGATs transferred various acyls to fluorescent DAG acceptors. Fluorescent products of the reaction (TAGs) were quantified using a substrate calibration curve. The method was sensitive enough to distinguish TAGs differing by only two carbons [5]. Both approaches avoided the use of radioactive labeled products.

[1] Erickson, S.K. and Fielfing, P.E. J Lipid Res 27 (1986) 875–883
[2] Folch, J. et al. J Biol Chem 226 (1957) 497–509
[3] Aymé, L., et al. PLoS One (2015) 10: e0143113
[4] Beopoulos, A., et al. (2012) Appl Microbiol Biotechnol 93: 1523–1537
[5] Haili N., et al. (2016) J Biol Chem 277: 6478–6482

Contact: Dr. Laure Aymé and Dr. Thierry Chardot, Institut Jean-Pierre Bourgin, INRAE, AgroParisTech, Université Paris- Saclay, 78000, Versailles, France, laure.ayme[at]recherche.gouv.fr, thierry.chardot@inrae.fr

Didier Rigollet, Amélie Havard and Daniel Dron are working at the R&D department Analytical Innovative Technologies of the Industrial Research Centre at Oril Industrie, in Bolbec, France (Servier group). The use of HPTLC in Oril started even earlier than the foundation of Chromacim, including trainings at CAMAG organised by Pierre Bernard-Savary, where Daniel Dron participated already more than 20 years ago. The R&D team is specialized in purification processes of intermediates and active pharmaceutical ingredients (APIs) for toxicological, galenical or clinical studies. Part of their work is devoted to the isolation of impurities and production of APIs or impurity reference batches. In 2018, the team launched their preparative chromatography service InnoPrepTM, dedicated to small and large-scale purifications. Intermediates, APIs and impurities are characterized by MS and NMR. Quantitative analysis by NMR is also performed on these molecules.

Servier, an independent international pharmaceutical group, is committed to therapeutic progress for the benefit of patients.

Their goal is to speed up the development of new molecules in order to bring a new molecular entity to market every 3 years, particularly in the field of oncology. Preparative chromatography is, therefore, a method of choice in R&D to provide pure products for the first pharmacological, toxicological and clinical studies in a very short time. This technique also makes it possible to isolate impurities present at low levels in active ingredients whose complex structure does not allow rapid synthesis and to provide a batch within the time limits set for toxicological studies.

About 75% of the purifications at Oril Industrie are done with silica gel. The necessary conditions for an efficient purification are determined using TLC. Then, the purification progress by preparative column chromatography is checked by HPTLC. Twenty fractions can be analyzed within one hour. TLC/HPTLC is the method of choice due to its simplicity, rapidness and the successful scale up from TLC to preparative separations. The HPTLC-MS carried out beforehand allows targeting the molecule sought in often very complex mixtures.

Crude product (0.05 g) is dissolved in 5.0 mL of ethyl acetate.

For method development (optimization of purification conditions) TLC plates silica gel 60 F₂₅₄ (Merck), 20 x 5 cm are used, while quantification and coupling to mass spectrometry is done on HPTLC plates silica gel 60 F₂₅₄ s (Merck), 20 x 10 cm.

Samples are applied as bands with the Automatic TLC Sampler (ATS 4), two tracks for TLC and up to 20 tracks for HPTLC, band length 8.0 mm, sample volumes of 1.0 –15.0 μL.

Plates are developed in the Twin Trough Chamber 20 x 20 cm (TLC) or 20 x 10 cm (HPTLC) with chamber saturation (with filter paper) for 20 min with different developing solvents to the separation distance of 100 mm (from the lower edge) for TLC and 50 mm for HPTLC, followed by drying in a stream of cold air for 5 min.

Images of the plates are captured with the TLC Visualizer in UV 254 nm and white light.

Zones are eluted with the TLC-MS Interface (oval elution head) at a flow rate of 0.2 mL/min with methanol – water 1:1 (V/V) into a Q-TOF-MS (Xevo® G2-S QTof, Waters), operating in positive ionization mode (m/z 50 –1200).

The objective of this study was to isolate a sufficient quantity of an impurity present at a content of 0.35% in a batch of an intermediate in a product under development. The aim was to confirm its structure and to carry out toxicological tests. The nature of this impurity was determined beforehand by LC-MS. Its structure being complex, a synthesis would be too time-consuming. The conditions used in RP-HPLC are too complex for direct transfer to preparative chromatography (expensive stationary phase). The mobile phase used was water + 0.1% methane sulfonic acid and acetonitrile +0.1% methane sulfonic acid is too complexed for the isolation after preparative chromatography.

RP-LC-UV Chromatogram of the crude product

TLC was selected for method development to separate the major impurity from the other compounds with a reasonable R_F value allowing an efficient purification.

TLC chromatograms of the crude product in UV 254 nm obtained with different developing solvents

Mass spectra were recorded to characterize the different compounds (main substance at R_F 0.25 and impurity at R_F 0.38).

Instruments used for TLC-MS (left); TLC chromatogram of the main substance and the impurity in white light (middle); mass spectra of the selected zones (a: impurity, b: main substance) measured in positive ionization mode (right)

The purification of the crude product (two injections of 90g dissolved in toluene) on a 20-cm column (packed at 40 bars with 6 kg silica gel 60, 15–40 μm, Merck) at a flow rate of 2.0 L/min with toluene – ethyl acetate 95:5 (V/V), was monitored online with UV 290 nm detection and in parallel offline by HPTLC.

Online monitoring of the purification process by LC-UV (290 nm, left) versus offline by HPTLC-UV (HPTLC chromatogram of the individual fractions at 254 nm, right; C2-C9 are fractions collected during purification and C5 corresponds to the impurity)

The different fractions of the target impurity were collected, and the combined fractions were analyzed by NMR. 670 mg of impurity was obtained (yield: 0.35%) purity > 99%. The quantity obtained after purification on column was also consistent with the estimated content in analytical HPLC. For Oril, the use of HPTLC has a big positive impact on the production costs, with a benefit of thousands of Euros per year. This is due to the use of HPTLC for various optimizations of the manufacturing process and of raw materials external supply.

Contact: Amélie Havard, Daniel Dron, Oril Industrie (Servier), Industrial Research Centre, Department of Analytical Innovative Technologies R&D, 13 rue Auguste Desgenétais, CS 60125, 76210 Bolbec, France, amelie.havard@servier.com, daniel.dron@servier.com

Honey is one of the most frequently tested natural food products. In recent years, Manuka honey has gained popularity because of its high antibacterial activity [1]. Methylglyoxal (MGO) was identified as one of the major contributors to its antibacterial property. MGO is present in high concentrations in manuka honey and is directly responsible for its potency. This makes the Manuka honey exclusive and high-priced as compared to the other traditional kinds of honey. Manuka honey from New Zealand usually contains 40 to 800 mg/kg of MGO but can even contain up to 1900 mg/kg [2]. To avoid adulteration of Manuka honey products, a strict quality regulation regarding its origin, purity, and quality needs to be fulfilled and is a prerequisite for the UMF™ (Unique Manuka Factor) grading [2]. It mostly reflects the MGO amount in the honey but also considers other authenticity markers.

In the following application, we focus on the MGO quantification using HPTLC with subsequent substance confirmation by MS measurement. The high viscosity and high sugar content of honey make it a very complex and matrix-rich sample to analyze. HPTLC is a convenient, fast, and efficient separation technique that enables the development of analytical methods without the need for complicated sample preparations or high investments [3]. Low cost and short analysis time per sample are given by the parallel analysis of many samples on one plate. Furthermore, the high matrix tolerance of HPTLC offers additional opportunities to existing routine methods.

Six different commercially available Manuka honey samples were analyzed. MGO shows a mesomeric effect and reacts immediately with water to form either methylglyoxal monohydrate or methylglyoxal dihydrate [4]. Only a small amount of around 1% MGO remains unreacted. Direct detection of MGO in Manuka honey is difficult with conventional methods. In this application, MGO is converted to the stable 2-methylquinoxaline by derivatization with 1,2-phenylenediamine [5]. The stable form is then used as the reference. For confirmation of the method and determination of the recovery rate, regular honey samples were spiked with MGO and 1,2-phenylenediamine. Other derivatization options were tested but the reaction with 1,2-phenylenediamine performed best. Water and honey matrix were tested, to confirm that the optimized reaction conditions provide reproducible results for both matrices.

The standards are prepared by dissolving 100 μL of Sigma-Aldrich ~40% aqueous MGO solution (exact content known from batch specification) in 20.0 mL of water. 800 μL of the stock solution is further diluted with water to 10.0 mL and 0.2% (2 mg/mL) of the reactant Supelco 1,2-phenylenediamine powder is added. All standard solutions are stored at 8°C for two days before use to achieve reproducible reaction of MGO with 1,2-phenylendiamine. Longer storage time (>3 days) leads to partial degradation of 2-methylquinoxaline.

Honey samples are prepared at 100–150 mg/mL (in the shown examples: honey sample solutions of 100 mg/mL in case of sample numbers 1, 3, 5, and 150 mg/mL in case of honey samples 2, 4 and 6 were applied in a higher volume due to the expected lower amount of MGO). To each sample 0.2% of 1,2-phenylenediamine is added, e.g., sample 1, 4.0 g honey diluted in 40 mL solution of water /ethanol in 3:2. To the solution, 0.2% (2 mg/mL) of the reactant 1,2-phenylenediamine is added. Before using the samples, they need to be stored at 8°C for two days to complete the reaction.

Contact: Dr. Monika Bäumle, Global Product Manager TLC, Merck, monika.baeumle[at]merckgroup.com.

The life science business of Merck KGaA, Darmstadt, Germany operates as MilliporeSigma in the U.S. and Canada.

The subject of this article was investigated by Prof. Dr. Martin Brandl, Anette Engels, Dr. Matthias Vogel, Dr. Thomas Zapf and Sarah Leitzen [1]. Prof. Dr. Martin Brandl is a pharmacist and professor at the Department of Physics, Chemistry and Pharmacy at the University of Southern Denmark (SDU), Odense, Denmark and supervisor of Sarah Leitzen’s doctoral thesis. Anette Engels, Dr. Matthias Vogel and Dr. Thomas Zapf work at the Federal Institute for Drugs and Medical Devices (BfArM) in Bonn. Sarah Leitzen is a pharmacist and PhD student working at both BfArM and SDU.

Sterile glucose solutions are commonly used as reconstitution solvents or diluents for injectable drugs and also for peritoneal dialysis solutions. In Germany, regulatory requirements for the different strengths of glucose solutions used for parenteral administration are regulated and published as standard marketing authorizations. During heat sterilization of glucose solutions for parenteral use, a variety of glucose degradation products (GDPs) may be formed. GDPs can cause cytotoxic effects after parenteral administration of these solutions. Therefore, the aim of the current study was to develop a simple and quick HPTLC method by which the major GDPs can be identified and (summarily) quantified in glucose solutions for parenteral administration. All GDPs were derivatized with o-phenylenediamine (OPD). The identity of the resulting GDP derivatives (quinoxalines) during method validation was confirmed via mass spectrometry

Plates are developed in the Twin Trough Chamber (TTC 20 x 20 cm) with chamber saturation (with filter paper) for 20 min, development with 25 mL of 1,4-dioxane – toluene – glacial acetic acid 49:49:2 (V/V) (each trough) to the migration distance of 160 mm (from the lower edge), followed by drying for 10 min.

Editor’s Note: in this special case, a migration distance of 160 mm leads to a significantly improved separation on HPTLC with the selected solvent system. Usually, a migration exceeding 80 mm on HPTLC plates does not improve resolution due to increasing diffusion

The plates are sprayed with the Derivatizer (yellow nozzle, level 4, 2 mL) with thymolsulfuric acid reagent (2 mL of a solution of 0.5 g of thymol in a mixture of 5 mL of sulfuric acid and 95 mL of ethanol 96%) and heated at 130˚C for 10 minutes on the TLC Plate Heater.

Authors’ Note: While establishing the method, two identical plates were run simultaneously (in separate twin trough chambers with chamber saturation), where one of the two plates was not treated with thymol-sulfuric acid reagent for substance confirmation by mass spectrometry.

Contact: Sarah Leitzen, Federal Institute for Drugs and Medical Devices, Bonn, Germany, sarah.leitzen[at]bfarm.de

Mrs. Carole Vrignaud and her colleagues at the Anti-counterfeiting Laboratory (LCAC) at Sanofi Tours, France, employ chromatographic separation techniques, especially HPTLC, to develop new qualitative analytical methods for detection of falsified drugs, in a variety of sample matrices. The world drug market is about 1000 billion € (2019). The World Health Organization (WHO) considers that half of the drugs sold through the internet are fakes. This is why Sanofi group in 2008 created this unique laboratory to fight against drug falsification using various analytical methods, including HPTLC. The main objective is to confirm the presence of active ingredients (API) or excipients (preservatives, flavoring…) in each Sanofi formulation. HPTLC is also often used to detect degradation of products stored under inappropriate conditions, as well as unexpected compounds, allowing characterization of the falsified products. To detect falsification of drugs, a generic HPTLC method was developed.

HPTLC is well suited for a rapid parallel screening of many samples. Up to 10 samples can be analyzed in less than one hour. The developed method is simple and can be perform ed with little consumption of solvents and reagents.

A representative plate with real samples is shown. During method development simulated and spiked samples gave the same R_F values as the standards and were well separated from matrix components. Any positive identification of API no. 2 and no. 3 can be confirmed by spectral comparison of samples and standards as well as the expected presence of impurity of API no. 2. Detection of API no. 1 (cases no. 1–7) is achieved after derivatization in white light. Results are shown for selected drug products as well as the identification of three active ingredients expected in different oral formulations. HPTLC is also used to estimate each quantity. API no. 3 is not present in the composition of the original tablets (cases no. 8–9). However, some previous cases were identified as counterfeit tablets containing API no. 3 instead of API no. 2.

In the shown real cases no falsification was detected. Nevertheless, the approach has proved suitable by several positive cases. HPTLC is therefore used at Sanofi as high throughput screening technique.

Contact: Carole Vrignaud, 30-36 avenue Gustave Eiffel, 37100 Tours, France, carole.vrignaud[at]sanofi.com