Estimation of Nonlinear Adsorption Isotherms in Gradient Elution RP-LC of Peptides in the Presence of an Adsorbing Additive

Uncovering the intricate relationship between plant nutrients and microplastics in agroecosystems

Recent scientific and media focus has increased on the impact of microplastics (MPs) on terrestrial and soil ecosystems. However, the interactions between MPs with macronutrients and micronutrients and their potential consequences for the agroecosystem are not well understood. Wheat (Triticum aestivum) is a staple food grown globally and has special importance for nations economies. Different elements can cause dangerous outcomes for wheat quality and production yield. In this study, batch adsorption experiments were done using 1 g of polyethylene tetra phthalate MP particles (PET-MPs) in varying concentrations of thirteen elements. The adsorption data were fitted by two common adsorption models (Langmuir and Freundlich). The effect of pH on the speciation of elements in aqueous solutions was investigated. The non-invasive characterization methods indicate the importance of O- and H-containing groups as the main component of selected MPs in controlling the adsorption of the elements ions. In the current study, adsorption and potential transport of the adsorbed macronutrients (K and Na) and micronutrients (Ni, Co, Cu, Al, Ba, Se, Fe, As, B, V and Ag) which include some beneficial (Na, Se, V), and non-essential or toxic elements (Al, As, Ag, Ba) onto MPs to the simulated roots of wheat were evaluated. The maximum sorption capacities of K+> Ni+2> Na+ > Co2+> Cu2+>Al+3 >Ba+2 >Se4+>Fe2+ >As5+ >B3+ >V5+> Ag + on PET-MPs at pH 5.8 and 25 ± 1 °C were 290.6 > 0.52> 0.51 > 0.20> 0.10 > 0.051> 0.024 > 0.003> 0.003 > 0.0015> 5.05 × 10-4> 1.7 × 10-4>3.7 × 10-6 mg g-1, respectively. The results highlight the importance of PET-MPs in controlling element adsorption in the rhizosphere. Our observations provide a good start for understanding the adsorption of multiple elements from the soil rhizosphere zone by PET-MPs.

Strategies for predictive modeling of overloaded oligonucleotide elution profiles in ion-pair chromatography

Due to their potential for gene regulation, oligonucleotides have moved into focus as one of the preferred modalities modulating currently undruggable disease-associated targets. In the course of synthesis and storage of oligonucleotides a significant number of compound-related impurities can be generated. Purification protocols and analytical methods have become crucial for the therapeutic application of any oligonucleotides, be they antisense oligonucleotides (ASOs), small interfering ribonucleic acids (siRNAs) or conjugates. Ion-pair chromatography is currently the standard method for separating and analyzing therapeutic oligonucleotides. Although mathematical modeling can improve the accuracy and efficiency of ion-pair chromatography, its application remains challenging. Simple models may not be suitable to treat advanced single molecules, while complex models are still inefficient for industrial oligonucleotide optimization processes. Therefore, fundamental research to improve the accuracy and simplicity of mathematical models in ion-pair chromatography is still a necessity. In this study, we predict overloaded concentration profiles of oligonucleotides in ion-pair chromatography and compare relatively simple and more advanced predictive models. The experimental system consists of a traditional C18 column using (dibutyl)amine as the ion-pair reagent and acetonitrile as organic modifier. The models were built and tested based on three crude 16-mer oligonucleotides with varying degrees of phosphorothioation, as well as their respective n - 1 and (P = O)1 impurities. In short, the proposed models were suitable to predict the overloaded concentration profiles for different slopes of the organic modifier gradient and column load.

Experimental and theoretical investigation of high- concentration elution bands in ion-pair chromatography

The effective separation of many solutes, including pharmaceuticals, can be performed using an ion-pair reagent (IPR) in the mobile phase. However, chromatographic separation and mathematical modelling are a challenge in ionpair chromatography (IPC), especially in preparative mode, due to the complicated chromatographic process. In this study, we present a retention mechanism and a mathematical model that predict overloaded concentration profiles in IPC using a system with X-Bridge C18 as stationary phase and tetrabutylammonium bromide in the 0 - 15 mM concentration range as the IPR. Two different mobile phases were used: (i) 15/85 [v/v] acetonitrile/water, (ii) 25/75 methanol/water. The model compounds were sodium salts of organic compounds with sulfonic acid functions. The analytical and preparative elution profiles were obtained for specified conditions. The analytical data were utilized to calculate the difference in electrical potential between the surface and bulk solution using firm electrostatic theory. In the preparative mode in a certain range of IPR concentrations, complicated U-shaped overloaded profiles were observed. In the other considered cases, Langmuir overloaded elution profiles were recorded. A multilayer adsorption model was derived, which is consistent with the dynamic ion exchange models. The model assumes that lipophilic IPR adsorbs on the stationary phase, creating charged active sites that serve as exchange sites for the solutes. The molecules of the solute can adsorb on the already formed IPR layer. It was also assumed that a subsequent layer of solute can form on the formed layer of complexes due to interactions between the solute molecules. The model takes into account the electrostatic attraction and repulsion of the molecules, depending on the considered situation. The proposed model allowed prediction of the overloaded concentration profiles with very good agreement for the model solute and followed the progression from Langmuirian, through U-shaped, to again Langmuirian profiles.

Impact of changes in physicochemical parameters of the mobile phase along the column on the retention time in gradient liquid chromatography. Part A - temperature gradient

Gradient chromatography has been widely applied in analytical and preparative chromatography since it provides better peak shapes and the ability to elute analytes in a shorter time frame. Apart from changes in the composition of a mobile phase also alteration of process temperature can be applied during separation procedures to improve efficiency. However, proper mathematical modeling of the gradient chromatography and further correct prediction of solutes' retention behavior have become a serious challenge as it involves the need to develop computational procedures that accurately account for the time and spatial gradients of crucial parameters. In this work, a computational procedure including the equilibrium-dispersive two-dimensional mass transfer model, the two-dimensional (2D) heat transfer model together with Darcy's law and the continuity equation have been proposed. Additionally, the calculation procedure was simplified by replacing the 2D model with the one-dimensional (1D) mass transfer model in order to speed up the computations. Both proposed solutions were validated employing external experimental data of temperature gradient HPLC [1] as well as with predictions based on the linear elution strength (LES) model available therein. The proposed procedures made it possible to efficiently predict the concentration profiles with average relative errors of calculated retention times not exceeding 3.22%. Moreover, the effect of the axial dispersion coefficient determination method on the obtained peak shapes was examined involving the Gunn, the Wen-Fan, and the Chung-Wen correlations, indicating that the latter produces the most accurate results. Finally, the proposed mathematical procedures were tested under UHPLC conditions, and due to a significant difference in retention times found the 2D model is strongly advised.

Downstream Processing of Therapeutic Peptides by Means of Preparative Liquid Chromatography

The market of biomolecules with therapeutic scopes, including peptides, is continuously expanding. The interest towards this class of pharmaceuticals is stimulated by the broad range of bioactivities that peptides can trigger in the human body. The main production methods to obtain peptides are enzymatic hydrolysis, microbial fermentation, recombinant approach and, especially, chemical synthesis. None of these methods, however, produce exclusively the target product. Other species represent impurities that, for safety and pharmaceutical quality reasons, must be removed. The remarkable production volumes of peptide mixtures have generated a strong interest towards the purification procedures, particularly due to their relevant impact on the manufacturing costs. The purification method of choice is mainly preparative liquid chromatography, because of its flexibility, which allows one to choose case-by-case the experimental conditions that most suitably fit that particular purification problem. Different modes of chromatography that can cover almost every separation case are reviewed in this article. Additionally, an outlook to a very recent continuous chromatographic process (namely Multicolumn Countercurrent Solvent Gradient Purification, MCSGP) and future perspectives regarding purification strategies will be considered at the end of this review.

Modern trends in downstream processing of biotherapeutics through continuous chromatography: The potential of Multicolumn Countercurrent Solvent Gradient Purification

Single-column (batch) preparative chromatography is the technique of choice for purification of biotherapeutics but it is often characterized by an intrinsic limitation in terms of yield-purity trade-off, especially for separations containing a larger number of product-related impurities. This drawback can be alleviated by employing multicolumn continuous chromatography. Among the different methods working in continuous mode, in this paper we will focus in particular on Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) which has been specifically designed for challenging separations of target biomolecules from their product-related impurities. The improvements come from the automatic internal recycling of the impure fractions inside the chromatographic system, which results in an increased yield without compromising the purity of the pool. In this article, steps of the manufacturing process of biopharmaceuticals will be described, as well as the advantages of continuous chromatography over batch processes, by particularly focusing on MCSGP.

From batch to continuous chromatographic purification of a therapeutic peptide through multicolumn countercurrent solvent gradient purification

A twin-column Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) process has been developed for the purification of a therapeutic peptide, glucagon, from a crude synthetic mixture. This semi-continuous process uses two identical columns operating either in interconnected or in batch mode, thus enabling the internal recycle of the portions of the eluting stream which do not comply with purity specifications. Because of this feature, which actually results in the simulated countercurrent movement of the stationary phase with respect to the mobile one, the yield-purity trade-off typical of traditional batch preparative chromatography can be alleviated. Moreover, the purification process can be completely automatized. Aim of this work is to present a simple procedure for the development of the MCSGP process based on a single batch experiment, in the case of a therapeutic peptide of industrial relevance. This allowed to recover roughly 90% of the injected glucagon in a purified pool with a purity of about 90%. A comparison between the performance of the MCSGP process and the classical single column batch process indicates that percentage increase in the recovery of target product is +23% when transferring the method from batch conditions to MCSGP, with an unchanged purity of around 89%. This improvement comes at the expenses of a reduction of about 38% in productivity.

Modeling the nonlinear behavior of a bioactive peptide in reversed-phase gradient elution chromatography

The thermodynamic behavior of octreotide, a cyclic octapeptide with important pharmaceutical functions, has been simulated under reversed-phase gradient elution conditions. To this end, adsorption behavior was firstly investigated in isocratic conditions, under a variety of water/acetonitrile + 0.02% (v/v) trifluoroacetic acid (TFA) mixtures as mobile phase by using a Langmuir isotherm. Organic modifier was varied in the range between 23 and 28% (v/v). Adsorption isotherms were determined by means of the so-called Inverse Method (IM) with a minimum amount of peptide. The linear solvent strength (LSS) model was used to find the correlation between isotherm parameters and mobile phase composition. This study contributes to enlarge our knowledge on the chromatographic behavior under nonlinear gradient conditions of peptides. In particular, it focuses on a cyclic octapeptide.

Optimizing Column Length and Particle Size in Preparative Batch Chromatography Using Enantiomeric Separations of Omeprazole and Etiracetam as Models: Feasibility of Taguchi Empirical Optimization

The overreaching purpose of this study is to evaluate new approaches for determining the optimal operational and column conditions in chromatography laboratories, i.e., how best to select a packing material of proper particle size and how to determine the proper length of the column bed after selecting particle size. As model compounds, we chose two chiral drugs for preparative separation: omeprazole and etiracetam. In each case, two maximum allowed pressure drops were assumed: 80 and 200 bar. The processes were numerically optimized (mechanistic modeling) with a general rate model using a global optimization method. The numerical predictions were experimentally verified at both analytical and pilot scales. The lower allowed pressure drop represents the use of standard equipment, while the higher allowed drop represents more modern equipment. For both compounds, maximum productivity was achieved using short columns packed with small-particle size packing materials. Increasing the allowed backpressure in the separation leads to an increased productivity and reduced solvent consumption. As advanced numerical calculations might not be available in the laboratory, we also investigated a statistically based approach, i.e., the Taguchi method (empirical modeling), for finding the optimal decision variables and compared it with advanced mechanistic modeling. The Taguchi method predicted that shorter columns packed with smaller particles would be preferred over longer columns packed with larger particles. We conclude that the simpler optimization tool, i.e., the Taguchi method, can be used to obtain "good enough" preparative separations, though for accurate processes, optimization, and to determine optimal operational conditions, classical numerical optimization is still necessary.