Early implementation of QbD in biopharmaceutical development: a practical example

Izokibep: Preclinical development and first-in-human study of a novel IL-17A neutralizing Affibody molecule in patients with plaque psoriasis

Psoriasis, an immune-mediated inflammatory disease, affects nearly 125 million people globally. The interleukin (IL)-17A homodimer is a key driver of psoriasis and other autoimmune diseases, including psoriatic arthritis, axial spondyloarthritis, hidradenitis suppurativa, and uveitis. Treatment with monoclonal antibodies (mAbs) against IL-17A provides an improvement in the Psoriasis Area and Severity Index compared to conventional systemic agents. In this study, the Affibody^Ⓡ technology was used to identify and optimize a novel, small, biological molecule comprising three triple helical affinity domains, izokibep (previously ABY-035), for the inhibition of IL-17A signaling. Preclinical studies show that izokibep, a small 18.6 kDa IL-17 ligand trap comprising two IL-17A-specific Affibody domains and one albumin-binding domain, selectively inhibits human IL-17A in vitro and in vivo with superior potency and efficacy relative to anti-IL-17A mAbs. A Phase 1 first-in-human study was conducted to establish the safety, pharmacokinetics, and preliminary efficacy of izokibep, when administered intravenously and subcutaneously as single doses to healthy subjects, and as single intravenous and multiple subcutaneous doses to patients with psoriasis (NCT02690142; EudraCT No: 2015-004531-13). Izokibep was well tolerated with no meaningful safety concerns identified in healthy volunteers and patients with psoriasis. Rapid efficacy was seen in all psoriasis patients after one dose which further improved in patients receiving multiple doses. A therapeutic decrease in joint pain was also observed in a single patient with concurrent psoriatic arthritis. The study suggests that izokibep has the potential to safely treat IL17A-associated diseases such as psoriasis, psoriatic arthritis, axial spondyloarthritis, hidradenitis suppurativa, and uveitis.

Improved Time Resolved KPI and Strain Characterization of Multiple Hosts in Shake Flasks Using Advanced Online Analytics and Data Science

Shake flasks remain one of the most widely used cultivation systems in biotechnology, especially for process development (cell line and parameter screening). This can be justified by their ease of use as well as their low investment and running costs. A disadvantage, however, is that cultivations in shake flasks are black box processes with reduced possibilities for recording online data, resulting in a lack of control and time-consuming, manual data analysis. Although different measurement methods have been developed for shake flasks, they lack comparability, especially when changing production organisms. In this study, the use of online backscattered light, dissolved oxygen, and pH data for characterization of animal, plant, and microbial cell culture processes in shake flasks are evaluated and compared. The application of these different online measurement techniques allows key performance indicators (KPIs) to be determined based on online data. This paper evaluates a novel data science workflow to automatically determine KPIs using online data from early development stages without human bias. This enables standardized and cost-effective process-oriented cell line characterization of shake flask cultivations to be performed in accordance with the process analytical technology (PAT) initiative. The comparison showed very good agreement between KPIs determined using offline data, manual techniques, and automatic calculations based on multiple signals of varying strengths with respect to the selected measurement signal.

Digital Twin for HIV-Gag VLP Production in HEK293 Cells

The development and adoption of digital twins (DT) for Quality-by-Design (QbD)-based processes with flexible operating points within a proven acceptable range (PAR) and automation through Advanced Process Control (APC) with Process Analytical Technology (PAT) instead of conventional process execution based on offline analytics and inflexible process set points is one of the great challenges in modern biotechnology. Virus-like particles (VLPs) are part of a line of innovative drug substances (DS). VLPs, especially those based on human immunodeficiency virus (HIV), HIV-1 Gag VLPs, have very high potential as a versatile vaccination platform, allowing for pseudotyping with heterologous envelope proteins, e.g., the S protein of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). As enveloped VLPs, optimal process control with minimal hold times is essential. This study demonstrates, for the first time, the use of a digital twin for the overall production process of HIV-1 Gag VLPs from cultivation, clarification, and purification to lyophilization. The accuracy of the digital twins is in the range of 0.8 to 1.4% in depth filtration (DF) and 4.6 to 5.2% in ultrafiltration/diafiltration (UFDF). The uncertainty due to variability in the model parameter determination is less than 4.5% (DF) and less than 3.8% (UFDF). In the DF, a prediction of the final filter capacity was demonstrated from as low as 5.8% (9mbar) of the final transmembrane pressure (TMP). The scale-up based on DT in chromatography shows optimization potential in productivity up to a factor of 2. The schedule based on DT and PAT for APC has been compared to conventional process control, and hold-time and process duration reductions by a factor of 2 have been achieved. This work lays the foundation for the short-term validation of the DT and PAT for APC in an automated S7 process environment and the conversion from batch to continuous production.

Digital Twins for scFv Production in Escherichia coli

Quality-by-Design (QbD) is demanded by regulatory authorities in biopharmaceutical production. Within the QbD frame advanced process control (APC), facilitated through process analytical technology (PAT) and digital twins (DT), plays an increasingly important role as it can help to assure to stay within the predefined proven acceptable range (PAR).This ensures high product quality, minimizes failure and is an important step towards a real-time-release testing (RTRT) that could help to accelerate time-to-market of drug substances, which is becoming even more important in light of dynamical pandemic situations. The approach is exemplified on scFv manufacturing in Escherichia coli. Simulation results from digital twins are compared to experimental data and found to be accurate and precise. Harvest is achieved by tangential flow filtration followed by product release through high pressure homogenization and subsequent clarification by tangential flow filtration. Digital twins of the membrane processes show that shear rate and transmembrane pressure are significant process parameters, which is in line with experimental data. Optimized settings were applied to 0.3 bar and a shear rate of 11,000 s−1. Productivity of chromatography steps were 5.3 g/L/d (Protein L) and 2167 g/L/d (CEX) and the final product concentration was 8 g/L. Based on digital twin results, an optimized process schedule was developed that decreased purification time to one working day, which is a factor-two reduction compared to the conventional process schedule. This work presents the basis for future studies on advanced process control and automation for biologics production in microbials in regulated industries.

In silico prediction of post-translational modifications in therapeutic antibodies

Monoclonal antibodies are susceptible to chemical and enzymatic modifications during manufacturing, storage, and shipping. Deamidation, isomerization, and oxidation can compromise the potency, efficacy, and safety of therapeutic antibodies. Recently, in silico tools have been used to identify liable residues and engineer antibodies with better chemical stability. Computational approaches for predicting deamidation, isomerization, oxidation, glycation, carbonylation, sulfation, and hydroxylation are reviewed here. Although liable motifs have been used to improve the chemical stability of antibodies, the accuracy of in silico predictions can be improved using machine learning and molecular dynamic simulations. In addition, there are opportunities to improve predictions for specific stress conditions, develop in silico prediction of novel modifications in antibodies, and predict the impact of modifications on physical stability and antigen-binding.

Assessment of Therapeutic Antibody Developability by Combinations of In Vitro and In Silico Methods

Although antibodies have become the fastest-growing class of therapeutics on the market, it is still challenging to develop them for therapeutic applications, which often require these molecules to withstand stresses that are not present in vivo. We define developability as the likelihood of an antibody candidate with suitable functionality to be developed into a manufacturable, stable, safe, and effective drug that can be formulated to high concentrations while retaining a long shelf life. The implementation of reliable developability assessments from the early stages of antibody discovery enables flagging and deselection of potentially problematic candidates, while focussing available resources on the development of the most promising ones. Currently, however, thorough developability assessment requires multiple in vitro assays, which makes it labor intensive and time consuming to implement at early stages. Furthermore, accurate in vitro analysis at the early stage is compromised by the high number of potential candidates that are often prepared at low quantities and purity. Recent improvements in the performance of computational predictors of developability potential are beginning to change this scenario. Many computational methods only require the knowledge of the amino acid sequences and can be used to identify possible developability issues or to rank available candidates according to a range of biophysical properties. Here, we describe how the implementation of in silico tools into antibody discovery pipelines is increasingly offering time- and cost-effective alternatives to in vitro experimental screening, thus streamlining the drug development process. We discuss in particular the biophysical and biochemical properties that underpin developability potential and their trade-offs, review various in vitro assays to measure such properties or parameters that are predictive of developability, and give an overview of the growing number of in silico tools available to predict properties important for antibody development, including the CamSol method developed in our laboratory.

Extension of human GCSF serum half-life by the fusion of albumin binding domain

Granulocyte colony stimulating factor (GCSF) can decrease mortality of patients undergo chemotherapy through increasing neutrophil counts. Many strategies have been developed to improve its blood circulating time. Albumin binding domain (ABD) was genetically fused to N-terminal end of GCSF encoding sequence and expressed as cytoplasmic inclusion bodies within Escherichia coli. Biological activity of ABD-GCSF protein was assessed by proliferation assay on NFS-60 cells. Physicochemical properties were analyzed through size exclusion chromatography, circular dichroism, intrinsic fluorescence spectroscopy and dynamic light scattering. Pharmacodynamics and pharmacokinetic properties were also investigated in a neutropenic rat model. CD and IFS spectra revealed that ABD fusion to GCSF did not significantly affect the secondary and tertiary structures of the molecule. DLS and SEC results indicated the absence of aggregation formation. EC50 value of the ABD-GCSF in proliferation of NFS-60 cells was 75.76 pg/ml after 72 h in comparison with control GCSF molecules (Filgrastim: 73.1 pg/ml and PEG-Filgrastim: 44.6 pg/ml). Animal studies of ABD-GCSF represented improved serum half-life (9.3 ± 0.7 h) and consequently reduced renal clearance (16.1 ± 1.4 ml/h.kg) in comparison with Filgrastim (1.7 ± 0.1 h). Enhanced neutrophils count following administration of ABD-GCSF was comparable with Filgrastim and weaker than PEG-Filgrastim treated rats. In vitro and in vivo results suggested the ABD fusion as a potential approach for improving GCSF properties.

Pharmacokinetic Engineering of OX40-Blocking Anticalin Proteins Using Monomeric Plasma Half-Life Extension Domains

Anticalin^® proteins have been proven as versatile clinical stage biotherapeutics. Due to their small size (∼20 kDa), they harbor a short intrinsic plasma half-life which can be extended, e.g., by fusion with IgG or Fc. However, for antagonism of co-immunostimulatory Tumor Necrosis Factor Receptor Superfamily (TNFRSF) members in therapy of autoimmune and inflammatory diseases, a monovalent, pharmacokinetically optimized Anticalin protein format that avoids receptor clustering and therefore potential activation is favored. We investigated the suitability of an affinity-improved streptococcal Albumin-Binding Domain (ABD) and the engineered Fab-selective Immunoglobulin-Binding Domain (IgBD) SpGC3Fab for plasma Half-Life Extension (HLE) of an OX40-specific Anticalin and bispecific Duocalin proteins, neutralizing OX40 and a second co-immunostimulatory TNFRSF member. The higher affinity of ABD fusion proteins to human serum albumin (HSA) and Mouse Serum Albumin (MSA), with a 4 to 5-order of magnitude lower K_D compared with the binding affinity of IgBD fusions to human/mouse IgG, translated into longer terminal plasma half-lives (t_1/2). Hence, the anti-OX40 Anticalin-ABD protein reached t_1/2 values of ∼40 h in wild-type mice and 110 h in hSA/hFcRn double humanized mice, in contrast to ∼7 h observed for anti-OX40 Anticalin-IgBD in wild-type mice. The pharmacokinetics of an anti-OX40 Anticalin-Fc fusion protein was the longest in both models (t_1/2 of 130 h and 146 h, respectively). Protein formats composed of two ABDs or IgBDs instead of one single HLE domain clearly showed longer presence in the circulation. Importantly, Anticalin-ABD and -IgBD fusions showed OX40 receptor binding and functional competition with OX40L-induced cellular reactivity in the presence of albumin or IgG, respectively. Our results suggest that fusion to ABD or IgBD can be a versatile platform to tune the plasma half-life of Anticalin proteins in response to therapeutic needs.

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.

Predicting Antibody Developability Profiles Through Early Stage Discovery Screening

Monoclonal antibodies play an increasingly important role for the development of new drugs across multiple therapy areas. The term 'developability' encompasses the feasibility of molecules to successfully progress from discovery to development via evaluation of their physicochemical properties. These properties include the tendency for self-interaction and aggregation, thermal stability, colloidal stability, and optimization of their properties through sequence engineering. Selection of the best antibody molecule based on biological function, efficacy, safety, and developability allows for a streamlined and successful CMC phase. An efficient and practical high-throughput developability workflow (100 s-1,000 s of molecules) implemented during early antibody generation and screening is crucial to select the best lead candidates. This involves careful assessment of critical developability parameters, combined with binding affinity and biological properties evaluation using small amounts of purified material (<1 mg), as well as an efficient data management and database system. Herein, a panel of 152 various human or humanized monoclonal antibodies was analyzed in biophysical property assays. Correlations between assays for different sets of properties were established. We demonstrated in two case studies that physicochemical properties and key assay endpoints correlate with key downstream process parameters. The workflow allows the elimination of antibodies with suboptimal properties and a rank ordering of molecules for further evaluation early in the candidate selection process. This enables any further engineering for problematic sequence attributes without affecting program timelines.

Immunogenicity Challenges Associated with Subcutaneous Delivery of Therapeutic Proteins

The subcutaneous route of administration has provided convenient and non-inferior delivery of therapeutic proteins compared to intravenous infusion, but there is potential for enhanced immunogenicity toward subcutaneously administered proteins in a subset of patients. Unwanted anti-drug antibody response toward proteins or monoclonal antibodies upon repeated administration is shown to impact the pharmacokinetics and efficacy of multiple biologics. Unique immunogenicity challenges of the subcutaneous route have been realized through various preclinical and clinical examples, although subcutaneous delivery has often demonstrated comparable immunogenicity to intravenous administration. Beyond route of administration as a treatment-related factor of immunogenicity, certain product-related risk factors are particularly relevant to subcutaneously administered proteins. This review attempts to provide an overview of the mechanism of immune response toward proteins administered subcutaneously (subcutaneous proteins) and comments on product-related risk factors related to protein structure and stability, dosage form, and aggregation. A two-wave mechanism of antigen presentation in the immune response toward subcutaneous proteins is described, and interaction with dynamic antigen-presenting cells possessing high antigen processing efficiency and migratory activity may drive immunogenicity. Mitigation strategies for immunogenicity are discussed, including those in general use clinically and those currently in development. Mechanistic insights along with consideration of risk factors involved inspire theoretical strategies to provide antigen-specific, long-lasting effects for maintaining the safety and efficacy of therapeutic proteins.

Challenges and advancements in the pharmacokinetic enhancement of therapeutic proteins

Nowadays, proteins are frequently administered as therapeutic agents in human diseases. However, the main challenge regarding the clinical application of therapeutic proteins is short circulating plasma half-life that leads to more frequent injections for maintaining therapeutic plasma levels, increased therapy costs, immunogenic reactions, and low patient compliance. So, the development of novel strategies to enhance the pharmacokinetic profile of therapeutic proteins has attracted great attention in pharmaceuticals. So far, several techniques, each with their pros and cons, have been developed including chemical bonding to polymers, hyper glycosylation, Fc fusion, human serum albumin fusion, and recombinant PEG mimetics. These techniques mainly classify into three strategies; (i) the endosomal recycling of neonatal Fc receptor which is observed for immunoglobulins and albumin, (ii) decrease in receptor-mediated clearance, and (iii) increase in hydrodynamic radius through chemical and genetic modifications. Recently, novel PEG mimetic peptides like proline/alanine/serine repeat sequences are designed to overcome pitfalls associated with the previous technologies. Biodegradability, lack of or low immunogenicity, product homogeneity, and a simple production process, currently make these polypeptides as the preferred technology for plasma half-life extension of therapeutic proteins. In this review, challenges and pitfalls in the pharmacokinetic enhancement of therapeutic proteins using PEG-mimetic peptides will be discussed in detail.

The Impact of Product and Process Related Critical Quality Attributes on Immunogenicity and Adverse Immunological Effects of Biotherapeutics

The pharmaceutical industry has experienced great successes with protein therapeutics in the last two decades and with novel modalities, including cell therapies and gene therapies, more recently. Biotherapeutics are complex in structure and present challenges for discovery, development, regulatory, and life cycle management. Biotherapeutics can interact with the immune system that may lead to undesired immunological responses, including immunogenicity, hypersensitivity reactions (HSR), injection site reactions (ISR), and others. Many product and process related critical quality attributes (CQAs) have the potential to trigger or augment such immunological responses to the product. Tremendous efforts, both clinically and preclinically, have been invested to understand the impact of product and process related CQAs on adverse immunological effects. The information and knowledge are critical for the implementation of Quality by Design (QbD), which requires risk assessment and establishment of specifications and control strategies for CQAs. A quality target product profile (QTPP) that identifies the key CQAs through process development can help assign severity scores based on safety, immunogenicity, pharmacokinetics (PK) and pharmacodynamics (PD) of the molecule. Gaps and future directions related to biotherapeutics and emerging novel modalities are presented.

Mitigation of liquid-liquid phase separation of a monoclonal antibody by mutations of negative charges on the Fab surface

Some monoclonal antibodies undergo liquid-liquid phase separation owing to self-attractive associations involving electrostatic and other soft interactions, thereby rendering monoclonal antibodies unsuitable as therapeutics. To mitigate the phase separation, formulation optimization is often performed. However, this is sometimes unsuccessful because of the limited time for the development of therapeutic antibodies. Thus, protein mutations with appropriate design are required. In this report, we describe a case study involving the design of mutants of negatively charged surface residues to reduce liquid-liquid phase separation propensity. Physicochemical analysis of the resulting mutants demonstrated the mutual correlation between the sign of second virial coefficient B2, the Fab dipole moment, and the reduction of liquid-liquid phase separation propensity. Moreover, both the magnitude and direction of the dipole moment appeared to be essential for liquid-liquid phase separation propensity, where electrostatic interaction was the dominant mechanism. These findings could contribute to a better design of mutants with reduced liquid-liquid phase separation propensity and improved drug-like biophysical properties.

QSAR Implementation for HIC Retention Time Prediction of mAbs Using Fab Structure: A Comparison between Structural Representations

Monoclonal antibodies (mAbs) constitute a rapidly growing biopharmaceutical sector. However, their growth is impeded by high failure rates originating from failed clinical trials and developability issues in process development. There is, therefore, a growing need for better in silico tools to aid in risk assessment of mAb candidates to promote early-stage screening of potentially problematic mAb candidates. In this study, a quantitative structure–activity relationship (QSAR) modelling workflow was designed for the prediction of hydrophobic interaction chromatography (HIC) retention times of mAbs. Three novel descriptor sets derived from primary sequence, homology modelling, and atomistic molecular dynamics (MD) simulations were developed and assessed to determine the necessary level of structural resolution needed to accurately capture the relationship between mAb structures and HIC retention times. The results showed that descriptors derived from 3D structures obtained after MD simulations were the most suitable for HIC retention time prediction with a R² = 0.63 in an external test set. It was found that when using homology modelling, the resulting 3D structures became biased towards the used structural template. Performing an MD simulation therefore proved to be a necessary post-processing step for the mAb structures in order to relax the structures and allow them to attain a more natural conformation. Based on the results, the proposed workflow in this paper could therefore potentially contribute to aid in risk assessment of mAb candidates in early development.

Optimization of the quality by design approach for gene therapy products: A case study for adeno-associated viral vectors

The development of gene therapy products has been expanding globally, and among them, the recombinant adeno-associated virus (rAAV) vector is one of the most promising vectors for gene transfer. For efficient and rapid development of the manufacturing process and quality control strategy, the quality by design (QbD) approach can be as effective for gene therapy products as it is for gene recombinant proteins, which have been developed for decades. However, prior available knowledge required for the QbD approach is limited in the field of gene therapy. Here, we comprehensively review rAAV study results that can form the basis of QbD-based development and propose a critical quality attribute identification method suitable for gene therapy development. As a case study for rAAV, we propose a series of practical development steps, including a quality target product profile (QTPP) setting, identification of critical quality attributes (CQAs), repetitive risk assessment associated with process optimization, design space (DS) establishment, and control strategy using the QbD method. Our case study, which was based on publicly available literature, is a basic model that can be augmented by unique data pertaining to specific products. An improvement in rAAV development is expected using this model as the first step.

Regulatory and strategic considerations for addressing immunogenicity and related responses in biopharmaceutical development programs

The last three decades have seen the biotherapeutic drug market evolve from promising concept to market dominance in a range of clinical indications. This growth has been spurred by the success of established drug classes like monoclonal antibodies, but also by the introduction of biosimilars, and more recently, multiple novel cell and gene therapies. Biotherapeutic drug development presents many unique challenges, but unintended immune responses are among the most common reasons for program attrition. Anti-drug antibodies can impact the safety and efficacy of drug products, and related immune responses, like the cytokine release syndrome that occurred in the infamous TGN-1412 clinical trial, can be challenging to predict with nonclinical models. For this reason, it is important that development programs proceed with a scientifically grounded and measured approach to these responses. This process begins at the discovery stage with the application of “quality by design,” continues into the clinic with the development of quality assays and management strategies, and culminates in the effective presentation of this information in regulatory documents. This review provides an overview of some of the key strategic and regulatory considerations for biotherapeutics as they pertain to immunogenicity and related responses.

The uniqueness of flow in probing the aggregation behavior of clinically relevant antibodies

The development of therapeutic monoclonal antibodies (mAbs) can be hindered by their tendency to aggregate throughout their lifetime, which can illicit immunogenic responses and render mAb manufacturing unfeasible. Consequently, there is a need to identify mAbs with desirable thermodynamic stability, solubility, and lack of self-association. These behaviors are assessed using an array of in silico and in vitro assays, as no single assay can predict aggregation and developability. We have developed an extensional and shear flow device (EFD), which subjects proteins to defined hydrodynamic forces which mimic those experienced in bioprocessing. Here, we utilize the EFD to explore the aggregation propensity of 33 IgG1 mAbs, whose variable domains are derived from clinical antibodies. Using submilligram quantities of material per replicate, wide-ranging EFD-induced aggregation (9-81% protein in pellet) was observed for these mAbs, highlighting the EFD as a sensitive method to assess aggregation propensity. By comparing the EFD-induced aggregation data to those obtained previously from 12 other biophysical assays, we show that the EFD provides distinct information compared with current measures of adverse biophysical behavior. Assessing a candidate's liability to hydrodynamic force thus adds novel insight into the rational selection of developable mAbs that complements other assays.

Cross-Interaction Chromatography-Based QSAR Model for Early-Stage Screening to Facilitate Enhanced Developability of Monoclonal Antibody Therapeutics

Monoclonal antibodies (mAbs) constitute a rapidly growing biopharmaceutical sector. However, their growth is impeded by developability issues such as polyspecificity and lack of solubility, which leads to attrition as well as manufacturing failures. In this study a multitool hybrid quantitative structure-activity relationship (QSAR) model development framework is described. This framework uses four novel datasets derived from the primary sequences of IgG1-κ-humanized mAbs with varying degrees of resolutions. Unsupervised pattern recognition is first performed on the descriptor sets to visualize any intrinsic property-based clustering, followed by regression of descriptors against cross-interaction chromatography (CIC) retention times. Model optimization is performed via unsupervised variable reduction followed by supervised variable selection. Finally, the models and datasets are benchmarked based on the regression model performance metrics such as R² , Q² , and RMSE. The results show that datasets containing localized descriptors rather than averaged value over the entire protein have better predictive performance of CIC retention behavior with R² > 0.8 and RMSE < 0.3. Furthermore, the results indicate the physicochemical, electronic, and topological properties of hypervariable regions of antibodies that contribute most to the CIC retention times. The results of these studies could contribute to early-stage screening and better design of mAbs.

Evaluation of the Therapeutic Potential of a HER3-Binding Affibody Construct TAM-HER3 in Comparison with a Monoclonal Antibody, Seribantumab

Human epidermal growth factor receptor type 3 (HER3) is recognized to be involved in resistance to HER-targeting therapies. A number of HER3-targeting monoclonal antibodies are under clinical investigation as potential cancer therapeutics. Smaller high-affinity scaffold proteins are attractive non-Fc containing alternatives to antibodies. A previous study indicated that anti-HER3 affibody molecules could delay the growth of xenografted HER3-positive tumors. Here, we designed a second-generation HER3-targeting construct (TAM-HER3), containing two HER3-specific affibody molecules bridged by an albumin-binding domain (ABD) for extension of blood circulation. Receptor blocking activity was demonstrated in vitro. In mice bearing BxPC-3 xenografts, the therapeutic efficacy of TAM-HER3 was compared to the HER3-specific monoclonal antibody seribantumab (MM-121). TAM-HER3 inhibited heregulin-induced phosphorylation in a panel of HER3-expressing cancer cells and was found to be equally as potent as seribantumab in terms of therapeutic efficacy in vivo and with a similar safety profile. Median survival times were 60 days for TAM-HER3, 54 days for seribantumab, and 41 days for the control group. No pathological changes were observed in cytopathological examination. The multimeric HER3-binding affibody molecule in fusion to ABD seems promising for further evaluation as candidate therapeutics for treatment of HER3-overexpressing tumors.

Using extensional flow to reveal diverse aggregation landscapes for three IgG1 molecules

Monoclonal antibodies (mAbs) currently dominate the biopharmaceutical sector due to their potency and efficacy against a range of disease targets. These proteinaceous therapeutics are, however, susceptible to unfolding, mis‐folding, and aggregation by environmental perturbations. Aggregation thus poses an enormous challenge to biopharmaceutical development, production, formulation, and storage. Hydrodynamic forces have also been linked to aggregation, but the ability of different flow fields (e.g., shear and extensional flow) to trigger aggregation has remained unclear. To address this question, we previously developed a device that allows the degree of extensional flow to be controlled. Using this device we demonstrated that mAbs are particularly sensitive to the force exerted as a result of this flow‐field. Here, to investigate the utility of this device to bio‐process/biopharmaceutical development, we quantify the effects of the flow field and protein concentration on the aggregation of three mAbs. We show that the response surface of mAbs is distinct from that of bovine serum albumin (BSA) and also that mAbs of similar sequence display diverse sensitivity to hydrodynamic flow. Finally, we show that flow‐induced aggregation of each mAb is ameliorated by different buffers, opening up the possibility of using the device as a formulation tool. Perturbation of the native state by extensional flow may thus allow identification of aggregation‐resistant mAb candidates, their bio‐process parameters and formulation to be optimized earlier in the drug‐discovery pipeline using sub‐milligram quantities of material.

A new small-molecule KRE2 inhibitor against invasive Candida parapsilosis infection

Aim: To investigate the antifungal activity of MOL3, a small molecule that was selected by virtual screening, against Candida spp. Materials & methods: The antifungal activity of MOL3 was evaluated using standard strains and clinical isolates. Activity was evaluated in both in vitro tests and animal models. Results: The minimum fungicidal concentration of MOL3 against Candida spp. ranged from 16 to 128 mg/l. MOL3 at the sub-minimum fungicidal concentration inhibited hyphal elongation. The remaining yeast cells presented morphological changes and were metabolically inactive. MOL3 was toxicologically inert both in vitro and in the animal model. MOL3 also reduced experimental systemic infection by C. parapsilosis in mice. Conclusion: The selection of MOL3 by virtual screening was successful, revealing a promising antifungal candidate.

Determination of isoelectric points and relative charge variants of 23 therapeutic monoclonal antibodies

Despite the popularity of therapeutic monoclonal antibodies (mAbs), data relative to their ionic physico-chemical properties are very scarce in the literature. In this work, isoelectric points (pIs) of 23 Food and Drug Administration (FDA) and European Medicines Agency (EMA) approved mAbs were determined by imaged capillary isoelectric focusing (icIEF), and ranged from 6.1 to 9.4. The obtained values were in good agreement with those calculated by both Vector NTI and MassLynx softwares. icIEF can therefore be considered as a reference technique for such a determination. The relative percentages of acidic and basic variants determined by cation exchange chromatography (CEX) using both salt- and pH-gradients were comprised between 15% and 30% for most mAbs and were in good agreement with each other, whereas generic icIEF seems to overestimate the amount of acidic charge variants in mAb products. To our knowledge, this is the first study focusing on the ionic properties of a wide range of FDA and EMA approved reference mAbs, using both generic chromatographic and electrophoretic methodologies. To illustrate the interest of the study for mAb developability purposes, ionic properties of a clinical mAb candidate (dalotuzumab) were also investigated.

Affibody molecules as engineered protein drugs

Affibody molecules can be used as tools for molecular recognition in diagnostic and therapeutic applications. There are several preclinical studies reported on diagnostic and therapeutic use of this molecular class of alternative scaffolds, and early clinical evidence is now beginning to accumulate that suggests the Affibody molecules to be efficacious and safe in man. The small size and ease of engineering make Affibody molecules suitable for use in multispecific constructs where AffiMabs is one such that offers the option to potentiate antibodies for use in complex disease.

Discovery and bio-optimization of human antibody therapeutics using the XenoMouse® transgenic mouse platform

Since the late 1990s, the use of transgenic animal platforms has transformed the discovery of fully human therapeutic monoclonal antibodies. The first approved therapy derived from a transgenic platform--the epidermal growth factor receptor antagonist panitumumab to treat advanced colorectal cancer--was developed using XenoMouse(®) technology. Since its approval in 2006, the science of discovering and developing therapeutic monoclonal antibodies derived from the XenoMouse(®) platform has advanced considerably. The emerging array of antibody therapeutics developed using transgenic technologies is expected to include antibodies and antibody fragments with novel mechanisms of action and extreme potencies. In addition to these impressive functional properties, these antibodies will be designed to have superior biophysical properties that enable highly efficient large-scale manufacturing methods. Achieving these new heights in antibody drug discovery will ultimately bring better medicines to patients. Here, we review best practices for the discovery and bio-optimization of monoclonal antibodies that fit functional design goals and meet high manufacturing standards.

A comparison of biophysical characterization techniques in predicting monoclonal antibody stability

With the rapid growth of biopharmaceutical product development, knowledge of therapeutic protein stability has become increasingly important. We evaluated assays that measure solution-mediated interactions and key molecular characteristics of 9 formulated monoclonal antibody (mAb) therapeutics, to predict their stability behavior. Colloidal interactions, self-association propensity and conformational stability were measured using effective surface charge via zeta potential, diffusion interaction parameter (kD) and differential scanning calorimetry (DSC), respectively. The molecular features of all 9 mAbs were compared to their stability at accelerated (25°C and 40°C) and long-term storage conditions (2-8°C) as measured by size exclusion chromatography. At accelerated storage conditions, the majority of the mAbs in this study degraded via fragmentation rather than aggregation. Our results show that colloidal stability, self-association propensity and conformational characteristics (exposed tryptophan) provide reasonable prediction of accelerated stability, with limited predictive value at 2-8°C stability. While no correlations to stability behavior were observed with onset-of-melting temperatures or domain unfolding temperatures, by DSC, melting of the Fab domain with the CH2 domain suggests lower stability at stressed conditions. The relevance of identifying appropriate biophysical assays based on the primary degradation pathways is discussed.