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Fourth Annual
Protein Aggregation and Emerging Analytical Tools:
Overcoming Analytic, Formulation, Manufacturing, and Regulatory Challenges
January 24-25, 2013 


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This annual conference covers latest trends and challenges in protein aggregation. It features in-depth case studies and interactive discussions on mechanisms of aggregation, detection and quantitation of aggregates, characterization tools, visible and sub-visible protein aggregation detection and analysis techniques, prevention of particles, impact of aggregation on production, and aggregates as an inducing factor for immunogenicity, and rational design of protein solutions. 


1:00-2:00 pm Conference Registration


Mechanisms of Aggregation 

1:45 Chairperson’s Opening Remarks

Peter Nielsen, Ph.D., Scientific Director, Protein Chemistry, Novo Nordisk


1:50 Role of Protein Charge in Native State Aggregation

Paul DublinPaul Dubin, Ph.D., Professor, Chemistry, University of Massachusetts-Amherst

Unfolding aggregation is highly protein-specific because many intermediates arise from the various interactions among the groups that are exposed when secondary and tertiary structures are de-stabilized. On the other hand, aggregation of folded proteins is controlled only by interactions at surfaces, and certain rules can be developed based on the disposition of surface charges. One particular form of charge-controlled aggregation predominates at pH near pI, and has been called “isoelectric precipitation” because long-range inter-protein repulsion may be minimized at pH~pI. However, strong suppression of this aggregation by salt proves that the attraction is also electrostatic. Such attraction could not exist if charges were uniform; “patches” of charge are responsible for this short-range attraction, which is better described as “Electrostatic Aggregation.”

Two signatures of electrostatic aggregation are asymmetric pH effects (aggregation at pI+ delta pH ≠ aggregation at pI- delta pH), and strong suppression by salt; we measure these using automated high-precision turbidimetry (%T±1 ppt). Proper modeling of protein charge anisotropy quantitatively explains the different pH- and ionic strength (I)- dependence of aggregation rates for insulin, serum albumin, β-lactoglobulin and antithrombin, proteins with very different charge symmetry. Beyond simple visualization, modeling of protein surface potentials can both explain and predict aggregation behavior. Combining modeling with kinetic studies based on DLS and high-precision turbidimetry, makes it possible to identify aggregation mechanisms. Without such information the roles of excipients cannot be established.

2:35 Dynamic Protein-Protein Interaction Modeling in Highly Concentrated Solutions: Aggregation, Stability, and Viscosity Impact

John Tsavalas, Ph.D., Assistant Professor, Materials Science, University of New Hampshire

The behavior of biomolecules in solution at high concentration, primarily in terms of their interaction potential and the resultant impact on solution viscosity, has become an increasingly important topic over the last decade. Humanized monoclonal antibodies (mAbs) serve as a great example with the focus shifting from oral delivery of low concentration solutions to subcutaneous delivery of more highly concentrated solutions (faster delivery time, less compliance issues, and patient convenience). The movement toward higher concentration solutions (> 100 mg/mL) inherently leads to the case where molecular crowding and intermolecular collisions become more probable as the protein-protein separation distance is markedly reduced. Non-idealities in the solution behavior present themselves as a result of these increased collisions and molecular interactions including protein aggregation, phase separation, and non-linear rheological behavior. Aggregation can lead to increased immunogenicity, which may result in loss of drug effectiveness or, even worse, anaphylactic shock. Most literature appropriately ascribes this solution behavior at higher concentration to the reduced separation distance between the biomolecules, their charge and response to pH, and the ionic strength of the solution. In this work, a dynamic model is presented that can evaluate and predict this behavior of proteins in concentrated solutions as a function of their charge, charge distribution, and resultant interaction potential. In particular, the viscosity response to the stability of the proteins in solution is discussed as a dynamic output during the simulation. The modeling of an anisotropic charge distribution (including charge-dipole, and dipole-dipole induced interactions) is hypothesized to help explain some of the non-ideal behavior observed in experiment that cannot be explained solely by the aggregated or phase separated state of unstable protein clusters.

3:05 Hydrophobic Patches Promote Attraction - Why and How, and Do They Really?

Michael Brunsteiner, Ph.D., Senior Researcher, Institute of Biotechnology and Biochemical Engineering, Research Center Pharmaceutical Engineering

A major hurdle for the efficient development of protein formulations is the fact that we are facing a multi-dimensional optimization problem, requiring a large number of time-consuming experiments for a thorough exploration of parameter space. We designed a protein model that is realistic enough to perform simulations of protein-protein interactions of unprecedented accuracy, yet simple enough to allow for the generation of a comprehensive set of results. The relative influence of hydrophobicity, net-charge and dipole moment on aggregation rates were determined, the results suggesting that the choice of descriptors used in common methods for the in-silico estimation of aggregation propensities should be reconsidered.

3:35 Sponsored Presentation (Opportunity Available)

3:50 Refreshment Break in the Exhibit Hall with Poster Viewing

4:30 Understanding Molecular Origins of Aggregation in Biotherapeutics

Sandeep Kumar, Ph.D., Principal Scientist, Biotherapeutics Pharmaceutical Sciences R&D, Pfizer, Inc.

Aggregation and immunogenicity are major hurdles to overcome during the development of biotherapeutic drug products. This talk shall provide an overview of computational efforts to understand the molecular level origins of aggregation and its consequences for biotherapeutic product development. Computational methods that can be utilized to identify potential physiochemical vulnerabilities associated with biotherapeutic drug candidates at early drug discovery and formulation stages will be presented. This will be followed by a description of our efforts to identify potentially ‘active’ aggregation prone regions in monoclonal antibodies and statistical analyses which suggest a coupling between aggregation and immunogenicity via an overlap between aggregation prone regions and immune epitopes. Results will be presented as they relate to improving the manufacturability and safety of biotherapeutic drug products.


5:00 Using Sedimentation Velocity Analytical Ultracentrifugation to Assess Relative Binding Affinities of Protein Biotherapeutics

Steve ShireSandeep YadavSteve Shire, Ph.D., Staff Scientist & Group Leader, Late Stage Pharmaceutical Development, Genentech, Inc.

Sandeep Yadav, Ph.D., Scientist, Late Stage Product Development, Genentech, Inc.

Binding of therapeutic proteins to targets is often evaluated using surface plasmon resonance methods, which require binding of one of the analytes to a solid support. If not done properly this type of analysis can lead to erroneous results. Evaluation of relative binding affinities in solution can be accomplished using sedimentation velocity analytical ultracentrifugation in a competitive binding mode. Here we present some examples and show how this technology can be useful in protein biotherapeutic development.

6:00 End of Day

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