Pharmaceutical research is complicated and costly. Digital technologies, either physics based models or data driven methods, can accelerate innovation through predictive models and better understanding of the data. In this presentation, we show how free energy perturbation, a physics based method, can accurately predict protein thermostability. Additionally we demonstrate case studies where sequence and structure-based descriptors in combination with machine learning are able to provide guidance to protein design

The worldwide pandemic caused by SARS-CoV-2 is unprecedented and continues to be devastating. The Spike protein, the main immunogen of this virus, displays a highly dynamic trimeric structure that presents a challenge for therapeutic development. Here, guided by the structure of the Spike trimer, we rationally design new Spike constructs that show a uniquely high stability profile while simultaneously remaining locked into the immunogen-desirable prefusion state. Furthermore, our approach emphasizes the relationship between the highly conserved S2 region and structurally dynamic Receptor Binding Domains to enable vaccine development as well as the generation of antibodies able to resist viral mutation.

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The stability of bioproduct is defined by the rate of change over time of a critical quality attribute (CQA) under specific conditions. We used ‘Good Modeling Practices’ to fit the stability data obtained under recommended storage (2-8°C) and accelerated (> +25°C) conditions by computed kinetic parameters, and finally, to predict valuable long term stability and degradation extend of biotherapeutics and vaccines during temperature excursions (cold chain breaks). Various cases illustrated the ability of this method to accurately predict shelf life of products, rank formulations, compare batches and monitoring real-time shelf-life of products.

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The Aura system counts, sizes, and ID subvisible particles for all biologics for protein, gene or cell-based therapies. Fluorescence membrane microscopy identifies different particle species providing an advanced understanding of their derivation. In this presentation, we demonstrate how to assess for protein stability/aggregation including formulation excipient degradation which all should be evaluated for all therapeutics to ensure product quality and patient safety, in a high throughput, low volume workflow. 

We describe a new method for screening protein-protein interaction of biopharmaceutical molecules at dilute concentrations to predict development issues at high concentration. The method is based on Asymmetrical Flow Field-Flow Fractionation (AF4) measurements using well known effects of protein-protein attraction on the fractionation profile due to elevated protein concentrations occurring close to the membrane. The results are insensitive to the concentration or buffer composition of the sample solution and only depend on the absolute amount of protein loaded and on the running buffer. This makes the method highly suitable for developability assessment in a compound discovery workflow.

Surface Plasmon Resonance (SPR) allows the label-free analysis of the kinetics for a broad spectrum of interactions. The new SPR Pro platform fuses maximal flexibility with industry-leading throughput. A highly sensitive detection system combined with robust microfluidics allows the measurement of all types of samples, from crude lysates to fragments. The feature-rich system enables a complete drug development campaign from quantification to mode-of-action studies for both low and high sample numbers.

In the process of developing biotherapeutics, early developability and manufacturability assessment is crucial to select the best candidate for the CMC phase. Therefore, we focus on miniaturized screening approaches which allow us to predict stability and rank lead candidates for further development. This talk will give insights on an interfacial stress assay for the screening of candidates and formulations.

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The presentation highlights gaps in understanding stability of frozen and freeze-dried biologicals, with several questions raised: (i) Is there a theoretical basis for a “safe” storage temperature for frozen and freeze-dried biologicals? (ii) What is a scientific justification for assigning shelf life for frozen/dried biologicals using shorter-term stability data? (iii) What are appropriate acceleration storage conditions for frozen solutions and freeze-dried formulations? 

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Aggregation and particle formation are quality attributes that can be impacted by careful selection of formulation excipients.  Predictability of this behaviour from structural information is desirable to the formulator.  The increased measurement sensitivity and reproducibility of Microfluidic Modulation Spectroscopy over standard techniques for secondary structure determination is investigated in this case study and utilised to rank potential formulations.  We also highlight how MMS analyzes high concentration moieties in complex backgrounds.

Monitoring of host cell proteins (HCPs) plays an important role during the development of biosimilars to ensure consistency to the reference product. In this respect, there is a growing need for identifying single HCPs to support process optimization. Here, LCMS provides a robust and sensitive orthogonal method to ELISA. The supportive role of LCMS for HCP analysis during biosimilar development is demonstrated by a case study.

Discovery and development of monoclonal antibodies and other biologic therapeutics relies heavily on analytical methods to capture molecular attributes, assess development risks and optimize complex drug substance mixtures. With many methods to choose from, NMR spectroscopy is uniquely sensitive to low affinity transient interactions, lowly populated states; able to simultaneously detect proteins, small molecule excipients, and their interactions. We will present several case studies, demonstrating NMR impact on development programs.

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Identification of mAbs with low levels of self-association has traditionally required relatively concentrated protein solutions, confounding identification of such molecules during early discovery campaigns. We have developed charge-stabilized self-interaction nanoparticle spectroscopy (CS-SINS), a colormetric assay that measures colloidal self-interaction of antibodies in ultra-dilute solutions (0.01 mg/mL). CS-SINS results are predictive of high concentration properties such as viscosity and opalescence, which only emerge at orders of magnitude higher concentrations (100+ mg/mL).

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