Continuous countercurrent chromatographic twin-column purification of oligonucleotides: the role of the displacement effect

Hybrid Modeling of the Reversed-Phase Chromatographic Purification of an Oligonucleotide: Few-Shot Learning From Differentiable Physics Solver-in-the-Loop

Hybrid models integrate mechanistic and data-driven components, effectively addressing the challenges of limited process understanding and data availability typical of biopharmaceutical processes. In this study, we applied a hybrid modeling framework named differentiable physics solver-in-the-loop (DP-SOL) to describe the reversed-phase chromatographic purification of an oligonucleotide, overcoming the mentioned limitations of purely mechanistic and data-driven models. The framework establishes a connection between neural networks (NNs) and mechanistic models through differentiable physical operators and their gradients. We first collected a data set comprising six linear gradient elution experiments at different resin loadings and gradient slopes, split in three experiments each for training and testing, for few-shot learning. The hyperparameters were determined through a grid search, resulting in a NN with two hidden layers and 14 nodes. Compared to a calibrated mechanistic model used for initialization of NN, the DP-SOL hybrid model showed significant performance improvement on both training and testing sets, withR 2 > ${R}^{2}\,\gt $ 0.97 for the former. The good predictivity of DP-SOL is attributed to the combination of mechanistic models and NNs at the solver level. As a novel and versatile hybrid modeling paradigm, DP-SOL has the potential to significantly impact modeling approaches in the downstream processing field and the broader biopharmaceutical sector.

Integrated multidimensional chromatography on preparative scale for oligonucleotides purification

Therapeutic oligonucleotides represent a recent breakthrough in the pharmaceutical industry due to their ability to regulate gene expression with great specificity. This aspect allows treatment of a wide range of diseases. However, since oligonucleotides are used for therapeutic purposes, the Active Pharmaceutical Ingredient (API) must fulfill strict purity levels which require intensive purification steps. For oligonucleotides, and biomolecules in general, preparative liquid chromatography is the technique of choice to perform large scale purifications, typically in batch mode, i.e. using a single column. Specifically, since ONs are mainly large, hydrophilic and charged molecules, Anion Exchange chromatography (AEX) and Ion Pair Reversed Phase chromatography (IP-RP) are the preferred chromatographic modes for their downstream processing. Nevertheless, these approaches suffer from a purity-yield trade-off, and for this reason, more than one purification step is usually required. The two chromatographic modes can therefore be used consequently to remove different groups of impurities, thanks to their orthogonality. In this work, a multidimensional and orthogonal approach on a (semi)preparative scale, namely "Integrated Batch process", was applied for the purification of a single-stranded DNA oligonucleotide. This process combines two chromatographic steps without any hold step, operator intervention or sampling of the first step. The performance parameters of the Integrated Batch were compared to those obtained in the single batch runs under different experimental conditions (chromatographic mode, eluent systems), showing the potential of this integrated approach. This proof-of-concept study illustrates how this technique can considerably reduce overall production time and how it allows to increase the robustness and reproducibility of the method, since the process is highly automated.

Model-based optimization strategy for intensification in the chromatographic purification of oligonucleotides

Oligonucleotides (ONs) are acquiring clinical relevance and their demand is expected to grow. However, the ON production capacity is currently limited by high manufacturing costs. Since the purification of the target ON sequence from molecularly similar variants represents a major bottleneck, this work presents a resource-effective strategy for the optimization of their preparative reversed-phase chromatographic purification. First, a model based on the equilibrium-dispersive theory was introduced to describe the chromatographic operation. Considering a deoxyribose nucleic acid with 20 nucleobases as case study, a genetic algorithm was developed to efficiently determine the adsorption isotherm and mass transfer parameters for the target ON and impurities. After the estimation of these parameters, a strategy for the in-silico optimization of the operation was established. The product collection window, gradient duration, and resin loading were considered as process variables and their influence on yield and productivity was investigated after setting a purity specification of 99.0%. The optimal process parameters identified through this analysis were experimentally verified, confirming the reliability of the model, calibrated with only 5 experimental runs. In addition, this optimal setpoint was exploited to design the multicolumn countercurrent solvent gradient purification (MCSGP) of this ON mixture, which allowed to boost the yield of the process and to work at cyclic steady state, while respecting the purity constraint. This study confirmed the potential of this in-silico optimization strategy in both improving the performance of the traditional single-column operations and in the rapid development of multicolumn processes.

Improved process design for monoclonal antibody charge variants separation with multicolumn counter-current solvent gradient purification

The multicolumn counter-current solvent gradient purification (MCSGP) method has proven effective in addressing the issue of elution profile overlap for difficult-to-separate proteins, leading to improved purity and recovery. However, during the MCSGP process, the flow rate and proportion of loaded proteins undergo changes, causing a significant discrepancy between the elution profiles of batch process design and the actual MCSGP process. This mismatch negatively impacts the purity and recovery of the target protein. To address this challenge, an improved process design (reDesign) was proposed with the first-run MCSGP to mimic the actual continuous process and obtain elution profiles that closely resemble the real ones. The reDesign was demonstrated with both a model protein mixture and a sample of monoclonal antibody (mAb) with charge variants. For model protein mixture, the reDesign-based MCSGP process (reMCSGP) showed a remarkable improvement in recovery, increasing from 83.6% to 97.8% while maintaining a purity of more than 95%. For mAb sample, the recovery of reMCSGP improved significantly to 93.9%, surpassing the performance of normal MCSGP processes at a given purity level of more than 84%. In general, the new process design strategy developed in this work could generate a more representative elution profile that closely mirrors actual conditions in continuous processes, which enhances the separation performance of MCSGP.

Role of the gradient slope during the product internal recycling for the multicolumn countercurrent solvent gradient purification of PEGylated proteins

Protein PEGylation, i.e. functionalization with poly(ethylene glycol) chains, has been demonstrated an efficient way to improve the therapeutic index of these biopharmaceuticals. We demonstrated that Multicolumn Countercurrent Solvent Gradient Purification (MCSGP) is an efficient process for the separation of PEGylated proteins (Kim et al., Ind. and Eng. Chem. Res. 2021, 60, 29, 10764-10776), thanks to the internal recycling of product-containing side fractions. This recycling phase plays a critical role in the economy of MCSGP as it avoids wasting valuable product, but at the same time impacts its productivity extending the overall process duration. In this study, our aim is to elucidate the role of the gradient slope within this recycling stage on the yield and productivity of MCSGP for two case-studies: PEGylated lysozyme and an industrially relevant PEGylated protein. While all the examples of MCSGP in the literature refer to a single gradient slope in the elution phase, for the first time we systematically investigate three different gradient configurations: i) a single gradient slope throughout the entire elution, ii) recycling with an increased gradient slope, to shed light on the competition between volume of the recycled fraction and required inline dilution and iii) an isocratic elution during the recycling phase. The dual gradient elution proved to be a valuable solution for boosting the recovery of high-value products, with the potential for alleviating the pressure on the upstream processing.

Design and economic investigation of a Multicolumn Countercurrent Solvent Gradient Purification unit for the separation of an industrially relevant PEGylated protein

Conjugation of biopharmaceuticals to polyethylene glycol chains, known as PEGylation, is nowadays an efficient and widely exploited strategy to improve critical properties of the active molecule, including stability, biodistribution profile, and reduced clearance. A crucial step in the manufacturing of PEGylated drugs is the purification. The reference process in industrial settings is single-column chromatography, which can meet the stringent purity requisites only at the expenses of poor product recoveries. A valuable solution to this trade-off is the Multicolumn Countercurrent Solvent Gradient Purification (MCSGP), which allows the internal and automated recycling of product-containing side fractions that are typically discarded in the batch processes. In this study, an ad hoc design procedure was applied to the single-column batch purification of an industrially relevant PEGylated protein, with the aim of defining optimal collection window, elution duration and elution buffer ionic strength to be then transferred to the MCSGP. This significantly alleviates the design of the continuous operation, subjected to manifold process parameters. The MCSGP designed by directly transferring the optimal parameters allowed to improve the yield and productivity by 8.2% and 17.8%, respectively, when compared to the corresponding optimized batch process, ensuring a purity specification of 98.0%. Once the efficacy of MCSGP was demonstrated, a detailed analysis of its cost of goods was performed and compared to the case of single-column purification. To the best of our knowledge, this is the first example of a detailed economic investigation of the MCSGP across different manufacturing scenarios and process cadences of industrial relevance, which demonstrated not only the viability of this continuous technology but also its flexibility.