Abstract Since the efficiency and speed of computing has increased significantly in the last decades, in silico‐approaches, e.g., quasi‐experimental analyses based on mechanistic simulations combined with Monte Carlo (MC) methods, are on the rise for uncertainty analyses and estimation of uncertainty propagation. The power and convenience of these approaches for high‐throughput processes will be demonstrated with a case study including miniaturized screenings on robotic platforms: a binding study for lysozyme on the adsorbent SP Sepharose FF in 96‐well format. All relevant uncertainties during the experimental preparations and automated high‐throughput experimentation were identified, quantified, and then embedded in a simulation algorithm for the calculation of uncertainty propagation based on MC sampling. A proof‐of‐concept for this approach is then followed by the simulation‐based analysis of various case scenarios. The MC‐based approach can easily be transferred to uncertainty analyses in other high‐throughput processes.
This report provides a high-level summary of the key outcomes and gaps based on the research presented at the Viral Clearance Symposium 2017 and identifies new areas for future study and improvements. The 2017 conference structure extended the framework from the preceding conferences, focusing on the key gaps and associated developments and including the additional focus areas of facility risk mitigation and continuous processing, and ways to improve the efficiency of the overall adventitious agent strategy. LAY ABSTRACT: This report provides a high-level summary of the key outcomes and gaps based on the research presented at the Viral Clearance Symposium 2017 and identifies new areas for future study and improvements.
Abstract A main requirement for the implementation of model‐based process development in industry is the capability of the model to predict high protein load densities. The frequently used steric mass action isotherm assumes a thermodynamically ideal system and, hence constant activity coefficients. In this manuscript, an industrial antibody purification problem under high load conditions is considered where this assumption does not hold. The high protein load densities, as commonly applied in industrial downstream processing, may lead to complex elution peak shapes. Using Mollerup's generalized ion‐exchange isotherm (GIEX), the observed elution peak shapes could be modeled. To this end, the GIEX isotherm introduced two additional parameters to approximate the asymmetric activity coefficient. The effects of these two parameters on the curvature of the adsorption isotherm and the resulting chromatogram are investigated. It could be shown that they can be determined by inverse peak fitting and conform with the mechanistic demands of model‐based process development.
Abstract Biopharmaceutical product and process development do not yet take advantage of predictive computational modeling to nearly the degree seen in industries based on smaller molecules. To assess and advance progress in this area, spirited coopetition (mutually beneficial collaboration between competitors) was successfully used to motivate industrial scientists to develop, share, and compare data and methods which would normally have remained confidential. The first “Highland Games” competition was held in conjunction with the October 2018 Recovery of Biological Products Conference in Ashville, NC, with the goal of benchmarking and assessment of the ability to predict development‐related properties of six antibodies from their amino acid sequences alone. Predictions included purification‐influencing properties such as isoelectric point and protein A elution pH, and biophysical properties such as stability and viscosity at very high concentrations. Essential contributions were made by a large variety of individuals, including companies which consented to provide antibody amino acid sequences and test materials, volunteers who undertook the preparation and experimental characterization of these materials, and prediction teams who attempted to predict antibody properties from sequence alone. Best practices were identified and shared, and areas in which the community excels at making predictions were identified, as well as areas presenting opportunities for considerable improvement. Predictions of isoelectric point and protein A elution pH were especially good with all‐prediction average errors of 0.2 and 1.6 pH unit, respectively, while predictions of some other properties were notably less good. This manuscript presents the events, methods, and results of the competition, and can serve as a tutorial and as a reference for in‐house benchmarking by others. Organizations vary in their policies concerning disclosure of methods, but most managements were very cooperative with the Highland Games exercise, and considerable insight into common and best practices is available from the contributed methods. The accumulated data set will serve as a benchmarking tool for further development of in silico prediction tools.
This article introduces the white paper from the 2017 Viral Clearance Symposium. The 5th Viral Clearance Symposium in Penzberg, Germany, addressed regulatory perspectives presented by officials from Health Canada, the US Food and Drug Administration, and Paul-Ehrlich-Institut as well as upstream and facility risk mitigation, downstream unit operations, and viral clearance strategies to support novel molecule formats, accelerated scenarios, and continuous processing. LAY ABSTRACT: This article introduces the summarized findings and next steps from the 2017 Viral Clearance Symposium in Penzberg, Germany.
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