Optimization of silver nanoparticles synthesis by chemical reduction to enhance SERS quantitative performances: Early characterization using the quality by design approach.

Surface-enhanced Raman scattering (SERS) is a vibrational widely used technique thanks to its multiple advantages such as its high specificity and sensitivity. The Raman signal exaltation comes from the use of metallic nanoparticles (Nps) acting as antennas by amplifying the Raman scattering. Controlling the Nps synthesis is a major point for the implementation of SERS in routine analysis and especially in quantitative applications. Effectively, nature, size and shape of these Nps considerably influence the SERS response intensity and repeatability. The Lee-Meisel protocol is the most common synthesis route used by the SERS community due to the low cost, rapidity and ease of manufacturing. However, this process leads to a significant heterogeneity in terms of particle size and shape. In this context, this study aimed to synthesize repeatable and homogeneous silver nanoparticles (AgNps) by chemical reduction. The Quality by Design strategy from quality target product profile to early characterization design was considered to optimize this reaction. The first step of this strategy aimed to highlight critical parameters by the means of an early characterization design. Based on an Ishikawa diagram, five process parameters were studied: the reaction volume as categorical variable and the temperature, the time of reaction, the trisodium citrate concentration and pH as continuous variables. A D-Optimal design of 35 conditions was performed. Three critical quality attributes were selected to maximize the SERS intensity, minimize the variation coefficient on SERS intensities and the polydispersity index of the AgNps. Considering these factors, it appeared that concentration, pH and time of reaction were identified as having a critical impact on the Nps formation and can then be considered for the further optimization step.

Application of design space and quality by design methodologies combined with ultra high-performance liquid chromatography for the optimization of the sample preparation of complex pharmaceutical dosage forms.

Accurate and precise analytical measurements play a significant role in assessments and decisions that are made throughout the drug development process. Developing a robust and reliable sample preparation is essential for drug product formulations to generate consistent results guaranteeing the product quality. However, due to the complex nature of the different pharmaceutical formulations with diverse excipients, developing robust sample preparation methods can be challenging and time consuming. Ensuring sample extraction robustness of pharmaceutical dosage forms becomes increasingly important with the potential impact to patient safety, product efficacy, and business efficiency. In this work we demonstrate and evaluate potential application of Quality by Design (QbD) principles to develop and optimize a robust sample preparation method in combination with the chromatographic analytical technique for a solid pharmaceutical dosage form. Practicability and utility of a QbD approach in optimization of sample preparation of this drug product are demonstrated as the active pharmaceutical ingredient (API) used in the drug product is proven to be highly sensitive for hydrolysis during analysis. Finally, the ultra-high-performance liquid chromatography method with UV detection that was applied during the design of experiments (DoE) was validated as per regulatory requirements. This systematic approach in analytics could provide guidance for the pharmaceutical industry in the development of robust sample preparation methods for different pharmaceutical dosage forms thus significantly reduce risks associated with the method transfers at clinical and commercial manufacturing sites.

Optimizing the soft independent modeling of class analogy (SIMCA) using statistical prediction regions.

The ultimate goal of a one-class classifier like the "rigorous" soft independent modeling of class analogy (SIMCA) is to predict with a certain confidence probability, the conformity of future objects with a given reference class. However, the SIMCA model, as currently implemented often suffers from an undercoverage problem, meaning that its observed sensitivity often falls far below the desired theoretical confidence probability, hence undermining its intended use as a predictive tool. To overcome the issue, the most reported strategy in the literature, involves incrementing the nominal confidence probability until the desired sensitivity is obtained in cross-validation. This article proposes a statistical prediction interval-based strategy as an alternative strategy to properly overcome this undercoverage issue. The strategy uses the concept of predictive distributions sensu stricto to construct statistical prediction regions for the metrics. Firstly, a procedure based on goodness-of-fit criteria is used to select the best-fitting family of probability models for each metric or its monotonic transformation, among several plausible candidate families of right-skewed probability distributions for positive random variables, including the gamma and the lognormal families. Secondly, assuming the best-fitting distribution, a generalized linear model is fitted to each metric data using the Bayesian method. This method enables to conveniently estimate uncertainties about the parameters of the selected distribution. Propagating these uncertainties to the best-fitting probability model of the metric enables to derive its so-called posterior predictive distribution, which is then used to set its critical limit. Overall, the evaluation of the proposed approach on a diversity of real datasets shows that it yields unbiased and more accurate sensitivities than existing methods which are not based on predictive densities. It can even yield better specificities than the strategy that attempts to improve sensitivities of existing methods by "optimizing" the type 1 error, especially in low sample sizes' contexts.

Potato Production in Northwestern Europe (Germany, France, the Netherlands, United Kingdom, Belgium): Characteristics, Issues, Challenges and Opportunities.

In Northwestern Europe, Germany, France, the Netherlands, the UK and Belgium constitute the biggest five potato producers, with total potato crop production around 60% of EU-28 production before Brexit. Soil and climate conditions are highly favourable for potato growth in this region. Production is under driving forces of (i) the potato processing industry, particularly in Belgium; (ii) the innovation for fresh potato in the UK, France and Germany; (iii) the leadership of Germany and the Netherlands for starch potato; and (iv) the dominance of the Netherlands for seed production. Based on an industrial agri-food production system, the region has the highest potato yield levels worldwide and developed relevant trade networks for export of seed, fresh and processed potato products in and outside Europe. Conventional and intensive potato production is widespread over the region, whilst organic production started to develop in Germany and France. Whether the coming decades will be as successful as the last ones for sustainable potato production will depend on how the sector and stakeholders of the whole potato value-chain will overcome new issues and challenges. These are mainly soil quality and health conservation, consequences of climate change, increasing bans on the use of plant protection products, tightening environmental standards, food waste reduction and increasing trade tensions hampering the flow of potatoes around the world. After a detailed description of the potato production in the region, this paper contains a SWOT analysis aiming to identify potential solutions to overcome environmental, technical, economic, political and societal issues in the region for sustainable potato production in the coming years and decades.

Controlling the Reproducibility of AC50 Estimation during Compound Profiling through Bayesian ß-Expectation Tolerance Intervals.

During drug discovery, compounds/biologics are screened against biological targets of interest to find drug candidates with the most desirable activity profile. The compounds are tested at multiple concentrations to understand the dose-response relationship, often summarized as AC50 values and used directly in ranking compounds. Differences between compound repeats are inevitable because of experimental noise and/or systematic error; however, it is often desired to detect the latter when it occurs. To address this, the ß-expectation tolerance interval is proposed in this article. Besides the classical acceptance criteria on assay performance, based on control compounds (e.g., quality control samples), this metric permits us to compare new estimates against historical estimates of the same study compound. It provides a measure that detects whether observed differences are likely due to systematic error. The challenge here is that limited information is available to build such compound-specific acceptance limits. To this end, we propose the use of Bayesian ß-expectation tolerance intervals to validate agreement between replicate potency estimates for individual study compounds. This approach allows the variability of the compound-testing process to be estimated from reference compounds within the assay and used as prior knowledge in the computation of compound-specific intervals as from the first repeat of the compound and then continuously updated as more information is acquired with subsequent repeats. A repeat is then flagged when it is not within limits. Unlike a fixed threshold such as 0.5log, which is often used in practice, this approach identifies unexpected deviations on each compound repeat given the observed variability of the assay.

Interaction between the scaffold proteins CBP by IQGAP1 provides an interface between gene expression and cytoskeletal activity.

Crosstalk between cellular pathways is often mediated through scaffold proteins that function as platforms for the assembly of signaling complexes. Based on yeast two-hybrid analysis, we report here the interaction between two complex scaffold proteins, CREB-binding protein (CBP) and the Ras GTPase-activating-like protein 1 (IQGAP1). Dissection of the interaction between the two proteins reveals that the central, thus far uncharacterized, region of IQGAP1 interacts with the HAT domain and the C-terminal intrinsically disordered region of CBP (termed ID5). Structural analysis of ID5 by solution NMR spectroscopy and SAXS reveals the presence of two regions with pronounced helical propensity. The ID5 region(s) involved in the interaction of nanomolar affinity were delineated by solution NMR titrations and pull-down assays. Moreover, we found that IQGAP1 acts as an inhibitor of the histone acetyltransferase (HAT) activity of CBP. In in vitro assays, the CBP-binding region of IQGAP1 positively and negatively regulates the function of HAT proteins of different families including CBP, KAT5 and PCAF. As many signaling pathways converge on CBP and IQGAP1, their interaction provides an interface between transcription regulation and the coordination of cytoskeleton. Disruption or alteration of the interaction between these scaffold proteins may lead to cancer development or metastatic processes, highlighting the importance of this interaction.

Quantification of Intrinsically Disordered Proteins: A Problem Not Fully Appreciated.

Protein quantification is essential in a great variety of biochemical assays, yet the inherent systematic errors associated with the concentration determination of intrinsically disordered proteins (IDPs) using classical methods are hardly appreciated. Routinely used assays for protein quantification, such as the Bradford assay or ultraviolet absorbance at 280 nm, usually seriously misestimate the concentrations of IDPs due to their distinct and variable amino acid composition. Therefore, dependable method(s) have to be worked out/adopted for this task. By comparison to elemental analysis as the gold standard, we show through the example of four globular proteins and nine IDPs that the ninhydrin assay and the commercial QubitTM Protein Assay provide reliable data on IDP quantity. However, as IDPs can show extreme variation in amino acid composition and physical features not necessarily covered by our examples, even these techniques should only be used for IDPs following standardization. The far-reaching implications of these simple observations are demonstrated through two examples: (i) circular dichroism spectrum deconvolution, and (ii) receptor-ligand affinity determination. These actual comparative examples illustrate the potential errors that can be incorporated into the biophysical parameters of IDPs, due to systematic misestimation of their concentration. This leads to inaccurate description of IDP functions.

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.

"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.

Linking functions: an additional role for an intrinsically disordered linker domain in the transcriptional coactivator CBP.

The multi-domain transcriptional coactivators CBP/p300 integrate a multitude of signaling inputs, interacting with more than 400 proteins via one or more of their globular domains. While CBP/p300 function is typically considered in terms of these structured domains, about half of the protein consists of intrinsically disordered regions (IDRs) of varying length. However, these IDRs have only been thought of as linkers that allow flexible spatial arrangement of the structured domains, but recent studies have shown that similar IDRs mediate specific and critical interactions in other proteins. To examine the roles of IDRs in CBP, we performed yeast-two-hybrid screenings of placenta and lung cancer cDNA libraries, which demonstrated that the long IDR linking the KIX domain and bromodomain of CBP (termed ID3) can potentially bind to several proteins. The RNA-binding Zinc-finger protein 106 (ZFP106) detected in both libraries was identified as a novel substrate for CBP-mediated acetylation. Nuclear magnetic resonance (NMR) spectroscopy combined with cross-linking experiments and competition-binding assays showed that the fully disordered isolated ID3 transiently interacts with an IDR of ZFP106 in a fashion that disorder of both regions is maintained. These findings demonstrate that beside the linking function, ID3 can also interact with acetylation substrates of CBP.

To be disordered or not to be disordered: is that still a question for proteins in the cell?

There is ample evidence that many proteins or regions of proteins lack a well-defined folded structure under native-like conditions. These are called intrinsically disordered proteins (IDPs) or intrinsically disordered regions (IDRs). Whether this intrinsic disorder is also their main structural characteristic in living cells has been a matter of intense debate. The structural analysis of IDPs became an important challenge also because of their involvement in a plethora of human diseases, which made IDPs attractive targets for therapeutic development. Therefore, biophysical approaches are increasingly being employed to probe the structural and dynamical state of proteins, not only in isolation in a test tube, but also in a complex biological environment and even within intact cells. Here, we survey direct and indirect evidence that structural disorder is in fact the physiological state of many proteins in the proteome. The paradigmatic case of α-synuclein is used to illustrate the controversial nature of this topic.

Application of design space optimization strategy to the development of LC methods for simultaneous analysis of 18 antiretroviral medicines and 4 major excipients used in various pharmaceutical formulations.

As one of the world's most significant public health challenges in low- and middle-income countries, HIV/AIDS deserves to be treated with appropriate medicines, however which are not spared from counterfeiting. For that, we developed screening and specific HPLC methods that can analyze 18 antiretroviral medicines (ARV) and 4 major excipients. Design of experiments and design space methodology were initially applied for 15 ARV and the 4 excipients with prediction thanks to Monte Carlo simulations and focusing on rapidity and affordability thus using short column and low cost organic solvent (methanol) in gradient mode with 10mM buffer solutions of ammonium hydrogen carbonate. Two other specific methods dedicated to ARV in liquid and in solid dosage formulations were also predicted and optimized. We checked the ability of one method for the analysis of a fixed-dose combination composed by emtricitabine/tenofovir/efavirenz in tablet formulations. Satisfying validation results were obtained by applying the total error approach taking into account the accuracy profile as decision tool. Then, the validated method was applied to test two samples coded A and B, and claimed to contain the tested ARV. Assay results were satisfying only for sample B.

Quantitative determination of salbutamol sulfate impurities using achiral supercritical fluid chromatography.

In the last years, supercritical fluid chromatography has largely been acknowledged as a singular and performing technique in the field of separation sciences. Recent studies highlighted the interest of SFC for the quality control of pharmaceuticals, especially in the case of the determination of the active pharmaceutical ingredient (API). Nevertheless, quality control requires also the determination of impurities. The objectives of the present work were to (i) demonstrate the interest of SFC as a reference technique for the determination of impurities in salbutamol sulfate API and (ii) to propose an alternative to a reference HPLC method from the European Pharmacopeia (EP) involving ion-pairing reagent. Firstly, a screening was carried out to select the most adequate and selective stationary phase. Secondly, in the context of robust optimization strategy, the method was developed using design space methodology. The separation of salbutamol sulfate and related impurities was achieved in 7min, which is seven times faster than the LC-UV method proposed by European Pharmacopeia (total run time of 50min). Finally, full validation using accuracy profile approach was successfully achieved for the determination of impurities B, D, F and G in salbutamol sulfate raw material. The validated dosing range covered 50 to 150% of the targeted concentration (corresponding to 0.3% concentration level), LODs close to 0.5µg/mL were estimated. The SFC method proposed in this study could be presented as a suitable fast alternative to EP LC method for the quantitative determination of salbutamol impurities.

Continuous production of itraconazole-based solid dispersions by hot melt extrusion: Preformulation, optimization and design space determination.

The purpose of this work was to increase the solubility and the dissolution rate of itraconazole, which was chosen as the model drug, by obtaining an amorphous solid dispersion by hot melt extrusion. Therefore, an initial preformulation study was conducted using differential scanning calorimetry, thermogravimetric analysis and Hansen's solubility parameters in order to find polymers which would have the ability to form amorphous solid dispersions with itraconazole. Afterwards, the four polymers namely Kollidon® VA64, Kollidon® 12PF, Affinisol® HPMC and Soluplus®, that met the set criteria were used in hot melt extrusion along with 25wt.% of itraconazole. Differential scanning confirmed that all four polymers were able to amorphize itraconazole. A stability study was then conducted in order to see which polymer would keep itraconazole amorphous as long as possible. Soluplus® was chosen and, the formulation was fine-tuned by adding some excipients (AcDiSol®, sodium bicarbonate and poloxamer) during the hot melt extrusion process in order to increase the release rate of itraconazole. In parallel, the range limits of the hot melt extrusion process parameters were determined. A design of experiment was performed within the previously defined ranges in order to optimize simultaneously the formulation and the process parameters. The optimal formulation was the one containing 2.5wt.% of AcDiSol® produced at 155°C and 100rpm. When tested with a biphasic dissolution test, more than 80% of itraconazole was released in the organic phase after 8h. Moreover, this formulation showed the desired thermoformability value. From these results, the design space around the optimum was determined. It corresponds to the limits within which the process would give the optimized product. It was observed that a temperature between 155 and 170°C allowed a high flexibility on the screw speed, from about 75 to 130rpm.

Screening study of SFC critical method parameters for the determination of pharmaceutical compounds.

Nowadays, supercritical fluid chromatography is commonly presented as a promising alternative technique in the field of separation sciences. Nevertheless the selection of chromatographic conditions and sample preparation of pharmaceutical compounds remain a challenge and peak distortion was previously highlighted. The main objective of the present work was to evaluate the impact of different critical method parameters (CMPs), i.e. stationary phase, mobile phase composition and injection solvent nature. The experiments were performed considering two groups of antimalarial molecules: one group with neutral/apolar compounds and the other one with salt form of polar compounds. In this context, another objective was to propose a suitable sample solvent for quantitative analysis. The interest of new generation stationary phase to obtain good peak shape and the interest to tune the mobile phase composition were demonstrated. During this study, design of experiments and desirability function approach enabled to highlight optimal chromatographic conditions in order to maximise peak capacity and to get acceptable value of symmetry factor. Regarding sample injection solvent composition, some counterintuitive results were observed: solvents closer to the mobile phase polarity (i.e heptane or 2-propanol/heptane mixture) did not provide best results in terms of peak symmetry. In addition, acetonitrile and short aliphatic alcohols offered an interesting alternative as injection solvent: toxicity of solvents used is clearly reduced and better quantitative performances could be expected while keeping high peak capacity and symmetric sharp peaks. Finally, the quantitative performances were evaluated by the method validation for the quantitative determination of quinine sulfate in a pharmaceutical formulation. These better understandings on critical method parameters led SFC to be an even more promising technique in the field of the analysis of pharmaceutical compounds.

Optimization of a pharmaceutical tablet formulation based on a design space approach and using vibrational spectroscopy as PAT tool.

The aim of the present study was to optimize a tablet formulation using a quality by design approach. The selected methodology was based on the variation of the filler grade, taking into account the particle size distribution (PSD) of active pharmaceutical ingredient (API) in order to improve five critical quality attributes (CQAs). Thus, a mixture design of experiments (DoE) was performed at pilot scale. The blending step was monitored using near infrared (NIR) spectroscopy as process analytical technology tool enabling real-time qualitative process monitoring. Furthermore, some tablets were analyzed by Raman imaging to evaluate the API distribution within the samples. Based on the DoE results, design spaces were computed using a risk-based Bayesian predictive approach to provide for each point of the experimental domain the expected probability to get the five CQAs jointly within the specifications in the future. Finally, the optimal conditions of the identified design space were successfully validated. In conclusion, a design space approach supported by NIR and Raman spectroscopy was able to define a blend that complies with the target product profile with a quantified guarantee or risk.

Optimization of a PGSS (particles from gas saturated solutions) process for a fenofibrate lipid-based solid dispersion formulation.

The aim of this study was to develop a formulation containing fenofibrate and Gelucire(®) 50/13 (Gattefossé, France) in order to improve the oral bioavailability of the drug. Particles from gas saturated solutions (PGSS) process was chosen for investigation as a manufacturing process for producing a solid dispersion. The PGSS process was optimized according to the in vitro drug dissolution profile obtained using a biphasic dissolution test. Using a design of experiments approach, the effects of nine experimental parameters were investigated using a PGSS apparatus provided by Separex(®) (Champigneulles, France). Within the chosen experimental conditions, the screening results showed that the drug loading level, the autoclave temperature and pressure, the connection temperature and the nozzle diameter had a significant influence on the dissolution profile of fenofibrate. During the optimization step, the three most relevant parameters were optimized using a central composite design, while other factors remained fixed. In this way, we were able to identify the optimal production conditions that would deliver the highest level of fenofibrate in the organic phase at the end of the dissolution test. The closeness between the measured and the predicted optimal dissolution profiles in the organic phase demonstrated the validity of the statistical analyses.

A quality by design approach for longitudinal quality attributes.

The concept of quality by design (QbD) as published in ICH-Q8 is currently one of the most recurrent topics in the pharmaceutical literature. This guideline recommends the use of information and prior knowledge gathered during pharmaceutical development studies to provide a scientific rationale for the manufacturing process of a product and provide guarantee of future quality. This poses several challenges from a statistical standpoint and requires a shift in paradigm from traditional statistical practices. First, to provide "assurance of quality" of future lots implies the need to make predictions regarding the quality given past evidence and data. Second, the quality attributes described in the Q8 guidelines are not always a set of unique, independent measurements. In many cases, these criteria are complicated longitudinal data with successive acceptance criteria over a defined period of time. A common example is a dissolution profile for a modified or extended-release solid dosage form that must fall within acceptance limits at several time points. A Bayesian approach for longitudinal data obtained in various conditions of a design of experiment is provided to elegantly address the ICH-Q8 recommendation to provide assurance of quality and derive a scientifically sound design space.

Analytical procedure validation and the quality by design paradigm.

Since the adoption of the ICH Q8 document concerning the development of pharmaceutical processes following a quality by design (QbD) approach, there have been many discussions on the opportunity for analytical procedure developments to follow a similar approach. While development and optimization of analytical procedure following QbD principles have been largely discussed and described, the place of analytical procedure validation in this framework has not been clarified. This article aims at showing that analytical procedure validation is fully integrated into the QbD paradigm and is an essential step in developing analytical procedures that are effectively fit for purpose. Adequate statistical methodologies have also their role to play: such as design of experiments, statistical modeling, and probabilistic statements. The outcome of analytical procedure validation is also an analytical procedure design space, and from it, control strategy can be set.

Mechanistic insights in glycation-induced protein aggregation.

Protein glycation causes loss-of-function through a process that has been associated with several diabetic-related diseases. Additionally, glycation has been hypothesized as a promoter of protein aggregation, which could explain the observed link between hyperglycaemia and the development of several aggregating diseases. Despite its relevance in a range of diseases, the mechanism through which glycation induces aggregation remains unknown. Here we describe the molecular basis of how glycation is linked to aggregation by applying a variety of complementary techniques to study the nonenzymatic glycation of hen lysozyme with ribose (ribosylation) as the reducing carbohydrate. Ribosylation involves a chemical multistep conversion that induces chemical modifications on lysine side chains without altering the protein structure, but changing the protein charge and enlarging its hydrophobic surface. These features trigger lysozyme native-like aggregation by forming small oligomers that evolve into bigger insoluble particles. Moreover, lysozyme incubated with ribose reduces the viability of SH-SY5Y neuroblastoma cells. Our new insights contribute toward a better understanding of the link between glycation and aggregation.