"NOTA-PRGD2 and NODAGA-PRGD2 : Bioconjugation, characterization, radiolabelling, and design space".

This work reports on the development of amide bond bioconjugation for the production of -NOTA and -NODAGA PRGD2 using batch strategy and microfluidic reactor technology. The final radiolabelling step was fully optimized using Design of Experiments and Design Space approaches, hence targeting robust labelling yields in routine. Optimal labelling conditions were defined in sodium acetate buffer as 168 µg/mL peptide concentration, 4.9 pH, 47.5°C temperature, and 12.5-minute reaction time. Upon optimization, the Gallium-68 radiolabelling was fully automated. All the work was designed to be compliant to the GMP environment and to support the pharmaceutical scale-up.

Development and validation of an integrated microfluidic device with an in-line Surface Enhanced Raman Spectroscopy (SERS) detection of glyphosate in drinking water.

Glyphosate, also known as N-(phosphonomethyl)glycine, is one of the most widely used herbicides in the world. However, the controversy surrounding the toxicity of glyphosate and its main breakdown product, aminomethylphosphonic acid (AMPA), remains a serious public concern. Therefore, there is a clear need to develop a rapid, sensitive and automated alternative method for the quantification of glyphosate and AMPA. In this context, surface enhanced Raman spectroscopy (SERS) coupled with a microfluidic system for the determination of glyphosate in tap water was developed, optimized and validated. The design of the microfluidic configuration for this application was built constructed to integrate the synthesis of the SERS substrate through to the detection of the analyte. To optimize the microfluidic setup, a design of experiments approach was used to maximize the SERS signal of glyphosate. Subsequently, an approach based on the European guideline document SANTE/11312/2021 was used to validate the method in the range of 78-480 µg/L using the normalized band intensities. The limit of detection and quantification obtained for glyphosate were 40 and 78 µg/L, respectively. Recoveries were in the range 76-117%, while repeatability and intra-day reproducibility were ≤17%. Finally, the method was also tested for the determination of AMPA in tap water matrix and for the simultaneous detection of AMPA and glyphosate.

Optimization of a robust and reliable FITC labeling process for CE-LIF analysis of pharmaceutical compounds using design of experiments strategy.

Fluorescence, especially laser induced fluorescence (LIF), is a powerful detection technique thanks to its specificity and high sensitivity. The use of fluorescence detection hyphenated to separation technique often requires the labeling of analytes with suitable fluorescent dye, such as FITC for the labeling of molecules presenting amino groups. Nevertheless, the labeling of analytes could be a tedious, time consuming and a non-robust step of the analytical workflow. In this context, the objective of the present work was to propose a robust and reliable FITC labeling process. Primary and secondary amino compounds (i.e. synthetic cathinones) were selected as model compounds because they are representative of a large proportion of pharmaceutical small molecules. Based on prior knowledge, DoE combined with multivariate statistical modeling was performed to optimize the process. Reaction time and pH of reaction buffer were highlighted as the most critical parameters to control the process. The study showed also the benefit of short reaction time to maximize the labeling efficiency. Indeed, optimal condition was defined as reaction time of 32 min with ratio between FITC and analytes of 40.4 and the buffer reaction pH of 9.7. In addition, variance component analysis was integrated to the DoE to estimate the variability of process and to evaluate its applicability for quantitative purpose. These chemometric approaches helped to develop an efficient labeling process able to reach high sensitivity for CE-LIF analysis (i.e. 10 nM) with good precision (i.e. intermediate precision values lower or close to 5 %).

Design of experiments and design space approaches in the pharmaceutical bioprocess optimization.

The optimization of pharmaceutical bioprocesses suffers from several challenges like complexity, upscaling costs, regulatory approval, leading to the risk of delivering substandard drugs to patients. Bioprocess is very complex and requires the evaluation of multiple components that need to be monitored and controlled in order to attain the desired state when the process ends. Statistical design of experiments (DoE) is a powerful tool for optimizing bioprocesses because it plays a critical role in the quality by design strategy as it is useful in exploring the experimental domain and providing statistics of interest that enable scientists to understand the impact of critical process parameters on the critical quality attributes. This review summarizes selected publications in which DoE methodology was used to optimize bioprocess. The main objective of the critical review was to clearly demonstrate potential benefits of using the DoE and design space methodologies in bioprocess optimization.

A spatial database of lowland cropping systems in Benin, Mali and Sierra Leone.

This paper presents data collected in 2013, 2014 and 2015 on the cultural practices and agronomic performance of cropping systems in 500 lowland rice fields located in five regions of three West African countries, Benin, Mali and Sierra Leone. Data were collected in two stages. In the first stage, the main regions containing inland valleys were identified in each of the three countries and the most cultivated inland valley in each region was selected. Weather data were obtained from weather stations located close to the selected inland valleys. In regions with no weather stations, Tinytag data loggers were installed in the inland valleys to collect data on temperature, rainfall and relative humidity. In the second stage, the location and size of all the farmers' fields in each inland valley were determined using GPS devices. In 2013, soil samples were collected in each farmer's field and the soil physical-chemical properties were determined. Agronomic and socio-economic surveys were conducted to collect data on cultivated crops, crop sequences and management techniques using questionnaires and informal interviews. Crop yields were determined in each farmer's field in the growing season. The database contains a total of 131 variables divided into 9 themes: field characteristics, land preparation, field maintenance, irrigation, residue management, soil data, weather data, crop productions in the dry season and crop production in the rainy season.

Analytical quality by design: Development and control strategy for a LC method to evaluate the cannabinoids content in cannabis olive oil extracts.

Cannabidiol (CBD) and Δ9-tetrahydrocannabinol (Δ9-THC) are considered as the most interesting cannabinoids in Cannabis sativa L. for the clinical practice. Since 2013, the Italian law allows pharmacists to prepare and dispense cannabis extracts to patients under medical prescription, and requires the evaluation of CBD and Δ9-THC content in cannabis extracts before sale. Cannabis olive oil extracts are prepared from dried female cannabis inflorescences, but a standard protocol is still missing. In this study, a fast RP-HPLC/UV method has been developed to quantify CBD and Δ9-THC in cannabis olive oil extracts. The analytical quality by design strategy has been applied to the method development, setting critical resolution and total analysis time as critical method attributes (CMAs), and selecting column temperature, buffer pH and flow rate as critical method parameters. Information from Doehlert Design in response surface methodology combined to Monte-Carlo simulations led to draw the risk of failure maps and to identify the method operable design region. The method was validated according to the International Council for Harmonisation of Technical Requirements for Pharmaceuticals for Human Use (ICH) guidelines and then implemented in routine analysis. A control strategy based on system control charts was planned to monitor the developed method performances. Evaluation data were recorded over a period of one year of routine use, and both the CMAs showed values within the specifications in every analysis performed. Hence, a new risk evaluation for the future performances of the method was achieved by using a Bayesian approach based on the routine use data, computing the future distribution of the two CMAs. Finally, a study focusing on the monitoring of CBD and Δ9-THC concentrations in cannabis olive oil extracts was carried out. The developed method was applied to 459 extracts. The statistical analysis of the obtained results highlighted a wide variability in terms of concentrations among different samples from the same starting typology of cannabis, underlining the compelling need of a standardised procedure to harmonise the preparation of the extracts.

Implementation of a generic SFC-MS method for the quality control of potentially counterfeited medicinal cannabis with synthetic cannabinoids.

In this study, we describe the development of a SFC-MS method for the quality control of cannabis plants that could be potentially adulterated with synthetic cannabinoids. Considering the high number of already available synthetic cannabinoids and the high rate of development of novel structures, we aimed to develop a generic method suitable for the analysis of a large panel of substances using seventeen synthetic cannabinoids from multiple classes as model compounds. Firstly, a suitable column was chosen after a screening phase. Secondly, optimal operating conditions were obtained following a robust optimization strategy based on a design of experiments and design space methodology (DoE-DS). Finally, the quantitative performances of the method were assessed with a validation according to the total error approach. The developed method has a run time of 9.4 min. It uses a simple modifier composition of methanol with 2% H2O and requires minimal sample preparation. It can chromatographically separate natural cannabinoids (except THC-A and CBD-A) from the synthetics assessed. Also, the use of mass spectrometry provides sensitivity and specificity. Moreover, this quality by design (QbD) approach permits the tuning of the method (within the DS) during routine analysis to achieve a desirable separation since the future compounds that should be analyzed could be unknown. The method was validated for the quantitation of a selected synthetic cannabinoid in fiber-type cannabis matrix over the range of 2.5% - 7.5% (w/w) with LOD value as low as 14.4 ng/mL. This generic method should be easy to implement in customs or QC laboratories in the context of counterfeit drugs tracking.