While science and technology are now more innovative and successful than ever, their translation into novel treatments and therapeutics to address key health problems remains a challenge. Recognizing that to close the industry/academia divide, we created the SPARK AT Stanford program, in which scientists from both sides work more closely together. SPARK, created thirteen years ago, is a partnership between Stanford University and volunteers from the local biotechnology, pharmaceutical, and health care investment industries. SPARK’s mission is three-fold: first, to help academic investigators overcome the obstacles intrinsic to moving research discoveries from bench to bedside; second, to educate faculty and trainees about the translational research process so that development of promising new discoveries becomes second nature, and so that trainees are better prepared for potential industry careers; and third, to promote efficient, costeffective, and innovative approaches to discovery and development. So far, 60% of the ~80 project have been licensed to companies and/or entered clinical trials. Through weekly meetings, SPARK’s activities conducted on campus, provide a rich learning experience that is open to faculty, staff, students, and postdoctoral fellows; this ensures that the know-how remains here and that the out-of-the-box and risktaking attitude of academia is maintained, while industry’s real-life experience is implemented. We also began ‘exporting’ SPARK to other academic institutions and formed a Global SPARK community to promote translational medical research in over two dozen academic institutions on five continents. I will discuss how SPARK works and lessons learned from our experience.

Backgrounded membrane imaging (BMI) is an automated, 96-well plate-based imaging technique for the analysis of particles in the size range above 2 µm. Following the basic principle of the compendial microscopic particle count test specified in the ICH harmonized USP chapter , BMI was first introduced to the field of subvisible particle analysis in 2017. Within the talk the results from our comprehensive scientific evaluation of the technique covering aspects like image quality, linear concentration range, impact of formulation refractive index on measured particle concentration, or separation of solid particles from liquid droplets (silicone oil) will be shown [1]. Also, a first case study will be presented in which subvisible particle analysis in three different drug products was performed and results from BMI and flow imaging microscopy (FIM) were compared. In the absence of silicone oil droplets, BMI and FIM showed good agreement in total particle concentrations (particle diameter ≥2 µm), while for pre-filled syringe products removal of silicone oil in BMI sample processing was demonstrated. The second case study addresses the application of BMI as an orthogonal technique to FIM to study protein stability in the presence of intact and degraded polysorbate 80 (PS80). Protein stability was amongst others assessed by the analysis of subvisible particles in mechanically stressed protein samples containing varying concentrations of intact and degraded PS80. In samples with degraded PS80, BMI could successfully be applied to verify trends in (protein) particle concentrations reported by FIM as in BMI liquid droplets assigned to the PS80 degradant oleic acid were removed from the analyzed samples during the vacuum suction step required for sample application.

[1] Helbig C, Ammann G, Menzen T, Friess W, Wuchner K, Hawe A. 2020. Backgrounded Membrane Imaging (BMI) for High-Throughput Characterization of Subvisible Particles During Biopharmaceutical Drug Product Development. J Pharm Sci. 109(1):264-276.

Molecular attributes resulting from changes in folding, conformation, oligomerization or aggregation can alter the quality of monoclonal antibody (mAb) drugs. The term, conformer, was coined to dub a molecular attribute of mAb drugs with significant decrease in potency upon exposure to ambient light during cell culture. Characterizations of the conformer by routine analytical methods hinted possible change in the conformation, while no significant chemical modification accountable for the loss of potency could be identified. Here we take structure-based approaches and find no significant variations in the (1) secondary structure, (2) surface hydrophobicity or (3) packing in the core structure for the conformer as compared to the non-modified main species, indicating no significant conformational changes in the conformer. Instead, modified peptide mapping reveals previously undetected extensive degradations of the solvent-accessible tryptophan (Trp). We find that riboflavin, which is a critical component of the cell-culture media, degrades the accessible Trp under ambient light. These findings highlight the applicability of structure-based approaches in attribute analysis that can provide control strategy for drug development.

The higher order structure (HOS) attribute is critical for protein therapeutic efficacy and safety. Currently there is emerging use of high-resolution NMR spectroscopy to characterize protein drug products (DP), e.g., insulin. However, a quantification metrics has been missing. The newly developed metrics toward HOS comparisons among US marketed insulin DPs is presented. The principal component analysis (PCA) on 1D 1H spectra of DP established the similarity metrics of Mahalanobis distance (DM) of 3.3. The 2D 1H-13C HSQC spectral comparison on insulin glargine DPs revealed similarity metrics of chemical shift difference (Dd) and methyl peak profile, i.e., 4 ppb for 1H, 15 ppb for 13C and 98% peaks with equivalent peak height. Application of NMR on therapeutic protein is moving toward quantitative similarity assessment on DP with achievable similarity metrics, not only for protein structure characterization.

Analytical Ultracentrifugation (AUC) has been the gold standard in macromolecular characterization for over 90 years in the research and development space. Even as a gold standard, AUC has been under-utilized mainly due to the complexities of the calculations. With the emergence of AAV and other viral vectors in the Gene Therapy space, a renewed interest in AUC has begun. AUC is the only analytical technique that can accurately calculate the capsid species, aggregates and impurities from first principles in a single experiment.

More recently, AUC has moved from the R&D into the cGXP space. This movement has been has been long overdue given the robustness and accuracy of the calculated hydrodynamic parameter and absolute quantitation obtained from a AUC experiment. This talk will be focused on the multi-faceted approaches of AUC, the ruggedness of the AUC experiments and the wealth of information that can be obtained for viral vectors both in the R&D and cGXP spaces.

During this presentation, I will introduce you to the concept of studying refoldability to select antibodies with lower aggregation propensity during storage.

I will show you two straightforward approaches to assess refoldability – the ReFOLD assay and modulated scanning fluorimetry (MSF).

Here we applied MSF and ReFOLD to study 13 therapeutic antibody candidates. MSF yielded the temperatures that start causing irreversible unfolding of the proteins. The ReFOLD assay provided information about the ability of the antibodies to refold to monomers after unfolding with chemical denaturants. The information from these two assays was used to classify the candidates based on their refoldability. Subsequently, storage stability studies at 40 °C with size-exclusion chromatography (SEC) showed that the antibodies with high refoldability were resistant to aggregation during storage.

Complex biotherapeutics may require additional characterization or stability testing in vivo to best inform clinical developability, safety, and efficacy. In this case study, a bispecific antibody with several product quality attributes was screened from an in-life rat study.

Samples were screened for multiple product attributes by MS detection of intact mass species and selected antibody variable region peptides generated from tryptic digestion.

Risks monitored at the intact mass level included homodimers, clipped species, intact glycation, and unpaired half-antibody fragments. From tryptic digestion, masses of sequences containing Met, Asn, or Asp residues were monitored for modified/unmodified forms, extending the multi-attribute method (MAM) to in-life samples.

Proper folding of the protein amino acid sequence during cell culture ensures intact higher order structure (HOS). The intricate folding of protein sequence gives rise to multiple levels of HOS and ultimately defines the protein function. Proteins undergo various post-translational modifications, which can significantly affect HOS and as a result their function. Circular dichroism (CD) spectroscopy is a widely used technique for assessing protein higher order structure (HOS), but remains difficult to assess HOS with high fidelity due to lack of sensitivity towards subtle structural perturbations. This presentation will discuss these challenges and an effective experimental method for CD measurements with the relevant examples from analytical comparability for process change and forced degradation studies for establishing critical quality attributes.

Several basal insulins are available for treatment of diabetes patients. A variety of mechanisms are utilized to enhance the in-vivo time of action of these molecules. Acylation at the B-chain of insulin is such an example approach. The acyl moiety binds to serum albumin thereby increasing the time insulin spends in circulation. However, acylation can lead to unique higher order structure properties for insulins. This talk will highlight the approach to characterizing the higher order structures of two acylated insulin molecules in drug product matrix and simulated subcutaneous conditions. The potential biological consequences of the differences in higher order structure will be discussed.

The next generation of medicines will rely heavily upon our ability to quickly assess the structures and stabilities of such complex macromolecular machines, as well as the influence of large libraries of conformationally-selective small molecule binders and protein-based biotherapeutics. Such endeavors are nearly insurmountable with current tools. In this presentation, I discuss recent developments surrounding collision induced unfolding (CIU) methods that aim to bridge this technology gap. CIU uses ion mobility-mass spectrometry (IM-MS) to measure the stability and unfolding pathways of gas-phase proteins, without the need for covalent labels or tagging, and consuming 10-100 times less sample than almost any other label-free technology. Recent developments in high-throughput CIU screening methods, their ability to track alterations in monoclonal antibody structure as a function of stress, and software developments that seek to enhance CIU information content will be discussed.

Antibody engineering frequently involves optimization of molecules to improve affinity towards target protein. Several biochemical and biophysical techniques ranging from SPR, BLI, ELISA and MSD are often utilized to assess antibody affinities. Solid-surface based techniques such as SPR are commonly used to determine antibody affinities due to wide affinity range, minimal material requirement and relatively high throughout nature. However, these solid-surface based methods often involve immobilization of the antibody or antigen, which may lead to specific conformational bias in the data generated. In this case study, an antibody was engineered to have high affinity towards aggregated protein, while preserving low affinity for monomeric protein. Assessing antibody affinity to monomer by SPR led to biased affinities due to one-dimensional electrostatic interactions between antibody and antigen. While seldomly used for antibody-antigen interaction studies, the solution based thermodynamic method ITC was able to decipher the mode of interaction between the protein monomer and the affinity optimized antibody. Our results suggest that solution-based techniques such as ITC could be a good alternative when solid-surface based methods have critical limitations.

We report a case study in which liquid-liquid phase separation (LLPS) negatively impacted the downstream manufacturability of a therapeutic mAb. Process parameter optimization partially mitigated the LLPS, but limitations remained for large-scale manufacturing. Electrostatic interaction driven self-associations and the resulting formation of high-order complexes are established critical properties that led to LLPS. Through chain swapping substitutions with a well-behaved antibody and subsequent study of their solution behaviors, we found the self-association interactions between the light chains (LCs) of this mAb are responsible for the LLPS behavior. With the aid of in silico homology modeling and charged-patch analysis, seven charged residues in the LC complementarity-determining regions (CDRs) were selected for mutagenesis, then evaluated for self-association and LLPS properties. Two charged residues in the light chain (K30 and D50) were identified as the most significant to the LLPS behaviors and to the antigen-binding affinity. Four adjacent charged residues in the light chain (E49, K52, R53, and R92) also contributed to self-association, and thus to LLPS. Molecular engineering substitution of these charged residues with a neutral or oppositely-charged residue disrupted the electrostatic interactions. A double-mutation in CDR2 and CDR3 resulted in a variant that retained antigen-binding affinity and eliminated LLPS. This study demonstrates the critical nature of surface charged resides on LLPS, and highlights the applied power of in silico protein design when applied to improving physiochemical characteristics of therapeutic antibodies. Our study indicates that in silico design and effective protein engineering may be useful in the development of mAbs that encounter similar LLPS issues.

Biotherapeutics are proteinaceous products generated using recombinant DNA technology and manufactured in cells of prokaryotic or eukaryotic lineage. It is often said that “the process is the product” and thereby the effect of the manufacturing process is etched on the final product in the form of its heterogeneity. For any biotherapeutic, the acceptable range for the critical quality attributes (CQAs) is defined based on the expected impact a specific variation is likely to have on the product stability, safety and efficacy. For a biosimilar to receive regulatory approval, the manufacturer must demonstrate analytical and clinical comparability. As this is mandatory, every biosimilar manufacturer performs this exercise for each biosimilar product under development. However, not many reports of thorough evaluation of the quality of biosimilar products are available in the literature.

Here we present 2 case studies where we evaluated structural and functional comparability of biosimilars of trastuzumab and Rituximab monoclonal antibody (mAb) biotherapeutic. The originator product for each mAb, was used for quality evaluation of 4 marketed trastuzumab biosimilars and 5 rituximab biosimilars.

Structural comparability was established using mass spectrometry (MS) and spectroscopic techniques such as Fourier Transform Infra-Red spectroscopy (FTIR), Differential Light Scattering (DLS), Circular Dichroism (CD) and fluorescence spectroscopy. Comparability in stability was evaluated by performing accelerated thermal stress studies. Functional comparability was established via surface plasmon resonance (SPR) and biological assays such as Antibody Dependent Cellular Cytotoxicity (ADCC) and Complement Dependent Cytotoxicity (CDC).

Overall, the results indicate that while there is general similarity with respect to structure and function, variations exist with respect to size heterogeneity, charge heterogeneity, and glycosylation pattern in each of the biosimilars.