Cambridge Healthtech Instituteの第11回年次会議
Rapid Methods to Assess Stability and Impurities in Biologics
2023年8月14 - 15日、EDT（米国東部標準時）
Registration and Morning Coffee8:00 am
AI/MACHINE LEARNING, PREDICTIVE TECHNIQUES FOR DEVELOPABILITY AND STABILITY
Use of Biophysical Techniques and Other Predictive Parameters during Late Phase Formulation Development of Drug Products
Alejandro D'Aquino, PhD, Principal Investigator, GSK
nDSF has been successfully utilized to determine differences in stability between formulations differing only in pH or initial %HWWS. Differences in shape of nDSF samples as well as calculated and predictive methods, such as kD, have been used to predict the long-term stability of 90 mg/mL to 150 mg/mL formulations of the drug product. The results obtained allow the use of this approach to determine relative stability as early as 1 month during long-term stability studies in the development of drug products.
Machine Learning Predictions of Chemical Stability in Early Stages of Antibody Discovery
Kyle A. Barlow, PhD, Scientist, Computational Biology, Adimab LLC
Chemical modifications such as deamidation, isomerization, and oxidation can affect the function of antibody therapeutics and complicate development. Given that experimental assessment is resource-intensive, we present machine learning models, trained on data from over 700 antibody samples, that predict sites where liabilities are likely to occur from sequence input alone. These models can be run throughout the discovery and lead optimization process, allowing for proactive removal of sequence liabilities.
Tailoring Antibody Developability Assays for Machine Learning to Speed up Lead Optimization
Dennis Asberg, PhD, Senior Scientist, Biophysics and Injectable Formulation, Novo Nordisk A/S, Denmark
In silico assessment of antibody developability have the potential to speed up antibody development, especially the lead optimization. However, advances in computational tools such as machine learning models are often limited by the lack of suitable training data sets of high quality. Here, I present improvements of common antibody developability assays; e.g., AC-SINS, with the aim of enabling optimal data for modelling. Important parameters like dynamic range, calibration and data processing are discussed.
Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own12:00 pm
Session Break12:30 pm
TOOLS AND METHODS FOR SCREENING DEVELOPABILITY AND STABILITY
Predictive Nature of High-Throughput Assays in ADC Formulation Screening
Siyuan Ren, PhD, Senior Scientist I, Global Pharmaceutical R&D, AbbVie Inc.
High-throughput screening techniques for biophysical properties analysis of molecules in early screening studies is warranted due to limited amount of material and large number of molecules. Predictability of early screening results to long-term storage stability is critical as it assists in defining the design space for long-term study. In this study, biophysical properties and 8-week stability of two ADCs in 16 formulations were evaluated, and the predictive capabilities of screening methods were assessed. The study demonstrated that Tagg and B22 is more predictive than conformational stability read-outs (Tm) for long-term storage stability. High-throughput assays also identified poor performing formulations.
Investigations of a Bispecific Antibody Dimerization via Hydroxyl Radical Footprinting
Harsha Gunawardena, PhD, Senior Scientist, Mass Spectrometry, Janssen Pharmaceutical Companies of Johnson & Johnson
Aggregation of recombinant proteins is a major consideration in their developability, safety, and immunogenicity. While detection of aggregates and analysis of their basic properties is routine, understanding the molecular mechanism involved is much more challenging. Structural mass spectrometry techniques such as hydroxyl radical protein footprinting (HRPF) was used to decipher mechanism of aggregate in biotherapeutics development to reduce development timelines
Networking Refreshment Break2:25 pm
A NIST-FDA Initiative to Benchmark Methods for Profiling and Predicting the Stability of mAbs
John P. Marino, PhD, Group Leader, Biomolecular Structure & Function Group, NIST
The benefits of predicting the quality and stability of formulated monoclonal antibodies (mAbs) under storage and transport conditions are widely recognized in the biopharma industry and by regulators and efforts to predict these properties of biologics are long-standing. To this end, a robust framework will be described for accelerating understanding and confidence in the performance of experimental approaches and models proposed for profiling and predicting the thermal stability of mAbs.
Characterizing the Stability and Its in vitro/in vivo Translatability of Novel Large Molecule Modalities Using Complementary Bioanalytical Tools
Cong Wu, PhD, Senior Scientist, Biochemical & Cellular Pharmacology, Genentech, Inc.
Novel large molecule therapeutic modalities are emerging to deliver sophisticated mechanism of actions to modulate the “undruggable” targets where canonical antibodies fall short. However, little is known about the in vivo stability liabilities (i.e. biotransformation) with these new large molecule modalities. Additionally, the stability findings from in vitro stress conditions may not fully translate in vivo. Here we report a multi-pronged approach using LC-MS and capillary electrophoresis-based methods to characterize and quantify biotransformation liabilities and the in vitro/ex vivo vs. in vivo translatability, including but not limited to linker deconjugation, clipping, and amino acid level modifications.
Session Break and Transition to Plenary Keynote Session3:40 pm
PLENARY KEYNOTE: SOLVING TODAY'S CHALLENGES
Overcoming the Challenges of Bioprocesses: The Future of Biomanufacturing
Glen R Bolton, PhD, Executive Director, Late Stage Bioprocess Development, Amgen Inc
Novel therapies and technologies are emerging to meet the needs of patients; however, the manufacturing of biopharmaceuticals remains a complex and challenging process. As demand for biopharmaceuticals grows, the industry faces new challenges in terms of scalability, cost, and process robustness. The implementation of innovative technologies to improve process efficiency and the importance of process control and data analytics in ensuring process robustness are key levers to meet these challenges.
Commercializing Gene Therapies - The Combined Power of Patient Advocacy and Cost-Effective Manufacturing
Rachel Salzman, DVM, Founder, The Stop ALD Foundation & Global Head, Corporate Strategy, Armatus Bio
There is only a very small handful of FDA-approved gene therapies. This presentation will examine the development of an FDA-approved gene therapy where patient advocacy played a critical role resulting in the first-ever clinical use of a lentiviral vector. Although manufacturing continues to represent a significant challenge throughout the entire R&D journey, there are opportunities for advocacy and manufacturing communities to seek alignment and combine their collective powers to achieve the common goal of increasing patient access to transformative medicines.
Welcome Reception in the Exhibit Hall with Poster Viewing5:30 pm
Close of Day6:30 pm
Registration and Morning Coffee7:30 am
PROTEIN AGGREGATION, PROCESS IMPURITIES, AND IMPURITY CONTROL
Protein Aggregation Under Flow: Mechanisms and Applications
Leon Willis, PhD, Postdoctoral Research Fellow, School of Molecular and Cellular Biology, University of Leeds
Therapeutic proteins are susceptible to aggregation throughout their lifetime, with hydrodynamic forces and interfacial stresses being major culprits. We have developed a low-volume extensional flow device (EFD) to understand the kinetic mechanism underpinning flow-induced aggregation. Armed with this knowledge, we can then apply the device as a screening tool for formulations which promote long-term stability under storage conditions.
Machine Learning Methods for the Design and Engineering of Protein Therapeutics
Philip M. Kim, PhD, Professor, The Donnelly Centre for Cellular and Biomolecular Research, Department of Molecular Genetics Department of Computer Science, University of Toronto
I will present methodologies developed in my lab for the design and engineering of antibodies. We use machine learning for de novo design and make use of modern technologies to ensure all our designs are developable. We show high yields and other developability criteria of our hit antibodies.
Analytical Procedure Development and Validation - Apply New ICH Guidelines to Biotech QC Lifecycle Management
Kevin Zen, PhD, Senior Director, IGM Biosciences
Analytical Quality by Design offers a systematic and robust approach to the development of analytical procedures involving all stages of the product’s lifecycle. The presentation will overview the new draft ICH guidelines on analytical procedure development, validation, and lifecycle management. Special emphasis will be placed on the analytical procedures commonly used in biotherapeutics for DS and DP GMP release and stability.
Sponsored Presentation (Opportunity Available)9:30 am
Coffee Break in the Exhibit Hall with Poster Viewing10:00 am
Breakout discussions provide an opportunity to discuss a focused topic with peers from around the world in an open, collegial setting. Select from the list of topics available and join the moderated discussion to share ideas, gain insights, establish collaborations or commiserate about persistent challenges. Please visit the breakout discussions page on the conference website for a complete listing of topics and descriptions.
PROTEIN AGGREGATION, PROCESS IMPURITIES, AND IMPURITY CONTROL (CONT.)
Co-Presentation: Development of a Platform Approach for the Affinity Capture and Characterization of Problematic Host Cell Proteins (HCPs)
Despite of the advances in protein purification, host cell proteins (HCPs) remain a potential concern in protein therapeutics, as they may affect both product quality and immunogenicity in patients. Deeper understanding of the chemical nature of HCPs will guide rational design for their control and removal. In this talk, we will discuss our new approaches to enrich HCPs for their subsequent characterization.
Characterization of Therapeutic Antibody Charge Variants in Drug Development by Microfluidic Native Capillary Electrophoresis-Mass Spectrometry
Zhijie Abe Wu, PhD, Scientist, Analytical Chemistry, Regeneron Pharmaceuticals, Inc.
Therapeutic antibodies are a major class of biopharmaceuticals that can treat a variety of diseases. As an important type of product-related impurities, charge variants and their related heterogeneity arising from post-translational modifications and truncations can affect the stability, efficacy, and safety of the drug product. In this study, we present the development and application of native microfluidic capillary electrophoresis (CE)-mass spectrometry (MS) to monitor the charge variants in therapeutic antibody drug candidates. The ZipChip CE couples front-end charge variant separation with MS for charge variant identifications, and this analysis is applicable for various applications in drug development.
Sponsored Presentation (Opportunity Available)12:30 pm
Luncheon Presentation (Sponsorship Opportunity Available) or Enjoy Lunch on Your Own1:00 pm
Refreshment Break in the Exhibit Hall with Poster Viewing1:30 pm
ANALYTICAL TOOLS AND CHARACTERIZATION STRATEGIES FOR VACCINES
Advances in Quality Control Standards for Polysaccharide Conjugate Vaccines
John Cipollo, PhD, Senior Principal Scientist and Team Lead, USP
Polysaccharide Conjugate vaccines are the most successful preventatives against bacterial disease and are composed of defined polysaccharides individually conjugated to carrier protein. This presentation will provide an update on standards and tools to support vaccine quality from raw materials through release testing. The recent revisions to General Chapter <198>, focused on NMR for bacterial polysaccharide for identity, and reference materials to support testing of quality attributes will be discussed.
Characterization Methods for Vaccines
Marina Kirkitadze, PhD, Head Bioprocess Support & PAT Platform, Analytical Sciences, Sanofi Pasteur
The topic of the presentation is a physico-chemical characterization of vaccine products. Several methods used to measure product attributes at different stages of manufacturing will be discussed. The output can be used for process monitoring, product characterization, and potentially for real-time release.
Single-Particle Imaging to Quantitate Biophysical Properties of mRNA Lipid Nanoparticles and Engineer Improved Vaccines
Sabrina Leslie, PhD, Associate Professor, Physics and Astronomy Department, The University of British Columbia
We present a quantitative single-particle imaging platform that enables simultaneous measurements of the size, mRNA-payload, and dynamic properties of vaccines in cell-like conditions. We investigate the dependence of mRNA-lipid-nanoparticle structure and fusion dynamics on formulation, using commercially available formulations as a starting point. These measurements are made on confined, freely diffusing particles, and during reagent-exchange such as in response to solution pH, in order to emulate intracellular dynamics in a controlled setting. Over the long term and in collaboration with health scientists, we propose to correlate multi-scale data sets including single-particle measurements made in vitro as well as in cells and tissues, with clinical results, to create a throughline of understanding of vaccine effectiveness from the microscopic to clinical scale, to enable and optimize their rational design and engineering.
Refreshment Break in the Exhibit Hall with Poster Viewing3:45 pm
Size Characterization of Vaccine Antigens: Ensemble vs. Single Particle Analysis Approach
Rahul Misra, PhD, Scientist, Biophysics and Process Analytical Technology, Sanofi
Light scattering techniques (DLS) for protein size characterization takes an ensemble-based approach to particle sizing. Although being a gold standard, this approach may not accurately distinguish particle sizes in a multimodal sample where the diameter of particles is similar or when particle size distributions are broad. Additionally, concentration of large particles can be overestimated thereby skewing the particle size distribution of the sample. On the other hand, single particle analysis approach involves tunable resistive pulse sensing (TRPS) technology which measures the size of individual particles passing through a nanopore and claims to provide more accurate particle size distribution data within a sample. Particle concentration analysis is also based on single-particle measurements thereby ensuring highly accurate calculations for each size band compared to the ensemble-based approach. The present study performs the comparative analysis of size distribution of vaccine antigens to evaluate the performance of these methods.
Microfluidic Electrophoresis-Based Detection and Characterization of dsRNA Contaminants in mRNA Vaccines
Adriana Coll De Pena, Graduate Student, Biomedical Engineering, Tripathi Lab, Brown University
Despite the recent groundbreaking advancements in mRNA vaccine development, analytical methods have not evolved at the same rate, leaving a significant need for highly sensitive and rapid purity assessment methods. Here, we propose a dual dynamic staining high-throughput microfluidic electrophoresis analytical method for the detection and characterization of dsRNA contaminants in mRNA vaccines. With an mRNA maximum loading capacity of 13 ng/μL, we can detect dsRNA contaminants as low as 0.1-0.6% of the total concentration.
Close of Rapid Methods to Assess Stability Conference5:30 pm