Optimization of ion exchange sigmoidal gradients using hybrid models: Implementation of quality by design in analytical method development

Machine learning in bioprocess development: from promise to practice

Fostered by novel analytical techniques, digitalization, and automation, modern bioprocess development provides large amounts of heterogeneous experimental data, containing valuable process information. In this context, data-driven methods like machine learning (ML) approaches have great potential to rationally explore large design spaces while exploiting experimental facilities most efficiently. Herein we demonstrate how ML methods have been applied so far in bioprocess development, especially in strain engineering and selection, bioprocess optimization, scale-up, monitoring, and control of bioprocesses. For each topic, we will highlight successful application cases, current challenges, and point out domains that can potentially benefit from technology transfer and further progress in the field of ML.

Influence of Mixed Salts on Retention Behavior of Model Proteins in Cation Exchange Chromatography

Mobile phase composition is an important factor for a further improvement of ion exchange chromatography steps of proteins. In this work, the effects of mixed salts on the retention factors of the two model proteins lysozyme (LYZ) and bovine serum albumin (BSA) in cation exchange chromatography (CEC) were investigated and compared to effects previously observed in hydrophobic interaction chromatography (HIC). The model equation describing the effects in HIC was adjusted for linear gradient elution experiments in CEC. The investigated salts were sodium chloride, sodium sulfate, ammonium chloride and ammonium sulfate. By varying binary salt mixtures as well as using pure salts, model parameters were determined. The normalized root mean square error (NRMSE) of the predicted retention factors for the calibration runs was 4.1% for BSA and 3.1% for LYZ. Additional validation experiments proved the ability of the model to describe and predict retention behavior of the proteins for further salt compositions. Hereby, the NRMSE values for BSA and LYZ were 2.0% and 1.5%, respectively. While the retention factors of LYZ changed linearly with the salt composition, non-linearities in the impact of the anion composition were found for BSA. This was contributed to an overlay of a synergetic salt effect on a protein-specific effect by sulfate on BSA with non-specific effects of the ions for CEC. However, the impact of the synergetic effects on protein separation is lower for CEC than for HIC, as mixed salts do not increase the separation of these proteins. The best salt composition for separating BSA and LYZ is pure ammonium sulfate. Thus, synergetic salt effects can also occur in CEC, but they have a lower impact than in HIC.

The use of predictive models to develop chromatography-based purification processes

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Rapid and flexible online desalting using Nafion-coated melamine sponge for mass spectrometry analysis

RATIONALE

The performance of mass spectrometry (MS) analysis is often affected by the presence of salt ions. To achieve optimal MS detection results, desalting is necessary for samples with high salt concentrations. We report a rapid, low-cost and flexible online desalting method using Nafion-coated sponge. This method is easy to perform and can be implemented to a wide range of customized fluidic systems.

METHODS

Nafion-coated melamine sponge was fabricated by soaking a glass tube containing a melamine sponge in Nafion solution and then drying overnight. The online desalting workflow is comprised of three major parts: (1) Syringe pump, which provides a continuous flow for the online fluid system; (2) Nafion sponge in a glass tube, where the online desalting of sample solution happens; (3) Capillary Vibrating Sharp-Edge Spray Ionization (cVSSI), which is an ionization technique to ionize the desalted analytes.

RESULTS

Effective online desalting of a 10 mM NaCl solution was demonstrated for a wide range of molecules including small molecules, peptides, DNAs, and proteins using a flow rate of 10 μL/min. By incorporating multiple pieces of the Nafion-coated sponge, effective desalting for ubiquitin and cytochrome c (Cyt-c) from physiological buffers, including phosphate-buffered saline (PBS) and tris-buffered saline (TBS), were also achieved. For molecules that are sensitive to low pH conditions after desalting, a R-SO3 NH4 -type Nafion-coated sponge was fabricated. Desalting of ubiquitin, oligosaccharide, and DNA oligomers from 10 mM NaCl or 10 mM KCl solutions was demonstrated.

CONCLUSIONS

Flexible, low-cost, and efficient online desalting was achieved by the Nafion-coated sponge. A variety of molecules ranging from small molecules, peptides, proteins to oligosaccharides and DNAs can be desalted for MS analysis. The desalting by Nafion sponge has great potential for desalting applications that require customized fluidic design and rapid analysis.

Investigating the Food and Drug Administration Biotherapeutics Review and Approval Process: Narrative Review

Background

The development, review, and approval process of therapeutic biological products in the United States presents two primary challenges: time and cost. Advancing a biotherapeutic from concept to market may take an average of 12 years, with costs exceeding US $1 billion, and the product may still fail the US Food and Drug Administration (FDA) approval process. Despite the FDA’s practices to expedite the approval of new therapies, seeking FDA approval remains a long, costly, and risky process.

Objective

The objective of this paper is to explore the factors and gaps related to the FDA review and approval process that contribute to process inefficiencies and complexities as well as proposed methods and solutions to address such gaps. This paper also aims to investigate the available modeling efforts for the FDA approval process of therapeutic biological products.

Methods

A narrative review of literature was conducted to understand the scope of published knowledge about challenges, opportunities, and specific methods to address the factors and gaps related to the review and approval of new drugs, including therapeutic biological products. Relevant peer-reviewed journal articles, conference proceedings, book chapters, official reports from public policy professional centers, and official reports and guidelines from the FDA were reviewed.

Results

Of the 23 articles identified in this narrative literature review, none modeled the current FDA review and approval process structure to address issues related to the robustness, reliability, and efficiency of its operations from an external point of view. Although several studies summarize the FDA approval process with clarity, in addition to bringing to light the problems and challenges faced by the regulatory agency, only a few attempts have been made to provide solutions for the problems and challenges identified. In addition, although several reform models have been discussed, these models lack the application of scientific methodologies and modeling techniques in understanding FDA as a complex sociotechnical system. Furthermore, tools and methods to assess the efficacy of the models before implementation are largely absent.

Conclusions

The findings suggest the efficacy of model-based systems engineering approaches for identifying opportunities for significant improvements to the FDA review and approval process. Using this holistic approach will serve several investigative purposes: identify influential sources of variability that cause major delays, including individual, team, and organizational decision making; identify the human-system bottlenecks; identify areas of opportunity for design-driven improvements; study the effect of induced changes in the system; and assess the robustness of the structure of the FDA approval process in terms of enforcement and information symmetry.

High-Throughput Process Development: I-Process Chromatography

Chromatographic separation serves as "a workhorse" for downstream process development and plays a key role in the removal of product-related, host-cell-related, and process-related impurities. Complex and poorly characterized raw materials and feed material, low feed concentration, product instability, and poor mechanistic understanding of the processes are some of the critical challenges that are faced during the development of a chromatographic step. Traditional process development is performed as a trial-and-error-based evaluation and often leads to a suboptimal process. A high-throughput process development (HTPD) platform involves the integration of miniaturization, automation, and parallelization and provides a systematic approach for time- and resource-efficient chromatographic process development. Creation of such platforms requires the integration of mechanistic knowledge of the process with various statistical tools for data analysis. The relevance of such a platform is high in view of the constraints with respect to time and resources that the biopharma industry faces today.This protocol describes the steps involved in performing the HTPD of chromatography steps. It describes the operation of a commercially available device (PreDictor™ plates from GE Healthcare). This device is available in 96-well format with 2 or 6 μL well size. We also discuss the challenges that one faces when performing such experiments as well as possible solutions to alleviate them. Besides describing the operation of the device, the protocol also presents an approach for statistical analysis of the data that are gathered from such a platform. A case study involving the use of the protocol for examining ion exchange chromatography of the Granulocyte Colony Stimulating Factor (GCSF), a therapeutic product, is briefly discussed. This is intended to demonstrate the usefulness of this protocol in generating data that are representative of the data obtained at the traditional lab scale. The agreement in the data is indeed very significant (regression coefficient 0.93). We think that this protocol will be of significant value to those involved in performing the high-throughput process development of the chromatography process.

Design and optimization of a luminescent Samarium complex of isoprenaline: A chemometric approach based on Factorial design and Box-Behnken response surface methodology

A chemometrically optimized procedure has been developed for the determination of isoprenaline (ISO) in the parent substance as well as in its respective pharmaceutical preparation. It is worth mentioning that although spectroscopic determination of Isoprenaline metal complexes has been described in literature, yet, no methods for the quantification of Isoprenaline with Samarium nor any other lanthanide metal have been reported. Fractional factorial design (FFD) was implemented in the initial screening procedure of the four designated factors, namely, reaction time (RT), metal volume (MV), pH and temperature (T) followed by Response Surface Methodology (RSM) optimization tool performed by the aid of Box Behnken design (BBD).The proposed techniques are based on a multivariate approach where a complexation reaction between Isoprenaline (ISO) and Samarium III (Sm³⁺) metal was exploited for the first time to synthesize novel fluorescence and absorbance probes of ISO-Sm. Maximum fluorescence intensity (Y1) as well as maximum absorbance (Y2) of the produced complex were attained at λ_ex/λ_em = 315/450 and λ 295 nm for spectrofluorimetric and spectrophotometric determinations, respectively, against blank solutions. Using assessment quality tools such as, Pareto charts, normal probability plots and statistical analysis of variance testing (ANOVA), significant factors were successfully indicated (p < 0.05). Furthermore, the proposed methods verified specificity and accuracy for the determination of Isoprenaline in its pure and pharmaceutical preparation using spectrofluorimetric (Technique A) and spectrophotometric (Technique B) techniques, respectively. Linearity was obtained in the range of (0.02-0.50 μg/mL) and (2-12 μg/mL) upon employing both techniques A and B, respectively. Furthermore, limit of detection (LOD) and limit of quantification (LOQ), were found to be 5.1877 ∗ 10^-3 μg/mL, 0.01572 μg/mL and 0.5593 μg/mL, 1.6949 μg/mL, upon employing techniques A and B, respectively. Standard addition method was applied for both techniques. The analysis was successfully applied to the assay of pure powder and pharmaceutical dosage forms after which the corresponding mean recoveries were computed and were found to be in the range of 99.546%-100.257% (Technique A) and 99.872%-99.887% (Technique B) with RSD (<1).

An overview of experimental designs in HPLC method development and validation

Chemometric approaches have been increasingly viewed as precious complements to high performance liquid chromatographic practices, since a large number of variables can be simultaneously controlled to achieve the desired separations. Moreover, their applications may efficiently identify and optimize the significant factors to accomplish competent results through limited experimental trials. The present manuscript discusses usefulness of various chemometric approaches in high and ultra performance liquid chromatography for (i) methods development from dissolution studies and sample preparation to detection, considering the progressive substitution of traditional detectors with tandem mass spectrometry instruments and the importance of stability indicating assays (ii) method validation through screening and optimization designs. Choice of appropriate types of experimental designs so as to either screen the most influential factors or optimize the selected factors' combination and the mathematical models in chemometry have been briefly recalled and the advantages of chemometric approaches have been emphasized. The evolution of the design of experiments to the Quality by Design paradigm for method development has been reviewed and the Six Sigma practice as a quality indicator in chromatography has been explained. Chemometric applications and various strategies in chromatographic separations have been described.