Model-based risk analysis of coupled process steps.

A section of a biopharmaceutical manufacturing process involving the enzymatic coupling of a polymer to a therapeutic protein was characterized with regards to the process parameter sensitivity and design space. To minimize the formation of unwanted by-products in the enzymatic reaction, the substrate was added in small amounts and unreacted protein was separated using size-exclusion chromatography (SEC) and recycled to the reactor. The quality of the final recovered product was thus a result of the conditions in both the reactor and the SEC, and a design space had to be established for both processes together. This was achieved by developing mechanistic models of the reaction and SEC steps, establishing the causal links between process conditions and product quality. Model analysis was used to complement the qualitative risk assessment, and design space and critical process parameters were identified. The simulation results gave an experimental plan focusing on the "worst-case regions" in terms of product quality and yield. In this way, the experiments could be used to verify both the suggested process and the model results. This work demonstrates the necessary steps of model-assisted process analysis, from model development through experimental verification.

Robust mechanistic modeling of protein ion-exchange chromatography.

Mechanistic models for ion-exchange chromatography of proteins are well-established and a broad consensus exists on most aspects of the detailed mathematical and physical description. A variety of specializations of these models can typically capture the general locations of elution peaks, but discrepancies are often observed in peak position and shape, especially if the column load level is in the non-linear range. These discrepancies may prevent the use of models for high-fidelity predictive applications such as process characterization and development of high-purity and -productivity process steps. Our objective is to develop a sufficiently robust mechanistic framework to make both conventional and anomalous phenomena more readily predictable using model parameters that can be evaluated based on independent measurements or well-accepted correlations. This work demonstrates the implementation of this approach for industry-relevant case studies using both a model protein, lysozyme, and biopharmaceutical product monoclonal antibodies, using cation-exchange resins with a variety of architectures (SP Sepharose FF, Fractogel EMD SO3-, Capto S and Toyopearl SP650M). The modeling employs the general rate model with the extension of the surface diffusivity to be variable, as a function of ionic strength or binding affinity. A colloidal isotherm that accounts for protein-surface and protein-protein interactions independently was used, with each characterized by a parameter determined as a function of ionic strength and pH. Both of these isotherm parameters, along with the variable surface diffusivity, were successfully estimated using breakthrough data at different ionic strengths and pH. The model developed was used to predict overloads and elution curves with high accuracy for a wide variety of gradients and different flow rates and protein loads. The in-silico methodology used in this work for parameter estimation, along with a minimal amount of experimental data, can help the industry adopt model-based optimization and control of preparative ion-exchange chromatography with high accuracy.

Pooling control in variable preparative chromatography processes.

Preparative chromatographic columns that run at high loads are highly sensitive to batch-to-batch disturbances of the process parameters, placing high demands on the strategy used for pooling of the product fractions. A new approach to pooling control is presented in a proof-of-concept study. A model-based sensitivity analysis was performed identifying the critical process parameters to product purity and optimal cut points. From this, the robust fixed cut points were found and pooling control strategies for variations in the critical parameters were designed. Direct measurements and indirect measurements based on the UV detector signal were used as control signals. The method is demonstrated for two case studies of preparative protein chromatography: hydrophobic interaction and reversed phase chromatography. The yield improved from 88.18 to 92.88% when changing from fixed to variable pooling in hydrophobic interaction chromatography, and from 35.15 to 76.27% in the highly sensitive reversed phase chromatography.

Through Internet and Friends: Translation of Air Pollution Research in Malmö Municipality, Sweden.

Air pollution is estimated to cause more than 7000 deaths annually in Sweden alone. To reduce the impact of air pollution and to plan and build sustainable cities, it is vital that research is translated into efficient decisions and practice. However, how do civil servants in a municipality access research results? How do they normally find relevant information, and what obstacles are there to accessing and applying research results? As part of the collaborative and transdisciplinary research project Air Pollution Research in Local Environmental Planning (ARIEL), these questions were explored through interviews and seminars with civil servants within the Malmö Municipality Environmental Office. We found that the civil servants generally have proficiency in processing research results, but often do not use such results as part of their everyday decision making and practices. Instead, the data and measurements used are mostly produced case-by-case within the municipal sector itself. Information about best practices is also collected via a number of knowledge access practices, involving the Internet or social networks within other municipalities. Lack of time, paywalls, and the insufficient applicability of research hinder the dissemination of up-to-date results. This slows down the process whereby research, funded by tax-money, can be put to best practice in the effort to create healthy and sustainable cities.

Multi-column displacement chromatography for separation of charge variants of monoclonal antibodies.

Native forms of therapeutic monoclonal antibodies (mAbs) coexist with various acidic and basic charge variants throughout process development and into drug product formulation. During downstream purification, a product's charge variant composition is controlled, as necessary, primarily through peak fractionation and pooling of elution fractions using cation-exchange chromatography (CEX). This can be a cumbersome process with poor resolution and it may result in a significant reduction in product yield. In the present work, separation and enrichment of the native form of a mAb and of basic and acidic variants is achieved using self-displacement chromatography in a multi-column continuous chromatography set-up. Basic mAb variants are more strongly retained in CEX owing to their higher charge, and can displace the native and the acidic variants. Similarly, the native variant can displace the acidic variants if the amount loaded exceeds the total resin capacity. To this end, we utilized a three-column continuous system to consecutively displace acidic, native and basic charge variants of a therapeutic mAb in the order of increasing binding strength during product loading. Using our optimized operating parameters, we were able to enrich the native variant from 65% to 90% while loading above the capacity of the column, with a process yield of above 90%. This method and approach will help to control and reduce in particular the charged variant heterogeneity, and, in general, aid in the separation of charged proteins at preparative scale.

Harnessing photoinduced electron transfer to optically determine protein sub-nanoscale atomic distances.

Proteins possess a complex and dynamic structure, which is influenced by external signals and may change as they perform their biological functions. We present an optical approach, distance-encoding photoinduced electron transfer (DEPET), capable of the simultaneous study of protein structure and function. An alternative to FRET-based methods, DEPET is based on the quenching of small conjugated fluorophores by photoinduced electron transfer: a reaction that requires contact of the excited fluorophore with a suitable electron donor. This property allows DEPET to exhibit exceptional spatial and temporal resolution capabilities in the range pertinent to protein conformational change. We report the first implementation of DEPET on human large-conductance K+ (BK) channels under voltage clamp. We describe conformational rearrangements underpinning BK channel sensitivity to electrical excitation, in conducting channels expressed in living cells. Finally, we validate DEPET in synthetic peptide length standards, to evaluate its accuracy in measuring sub- and near-nanometer intramolecular distances.

Estimated health benefits of exhaust free transport in the city of Malmö, Southern Sweden.

Air pollution is responsible for one in eight premature deaths worldwide, and thereby a major threat to human health. Health impact assessments of hypothetic changes in air pollution concentrations can be used as a mean of assessing the health impacts of policy, plans and projects, and support decision-makers in choices to prevent disease. The aim of this study was to estimate health impacts attributable to a hypothetical decrease in air pollution concentrations in the city of Malmö in Southern Sweden corresponding to a policy on-road transportations without tail-pipe emissions in the municipality. We used air pollution data modelled for each of the 326,092 inhabitants in Malmö by a Gaussian dispersion model combined with an emission database with >40,000 sources. The dispersion model calculates Nitrogen Oxides (NOx) (later transformed into Nitrogen Dioxide (NO2)) and particulate matter with an aerodynamic diameter < 2.5 µg/m3 (PM2.5) with high spatial and temporal resolution (85 m and 1 h, respectively). The average individual reduction was 5.1 (ranging from 0.6 to 11.8) µg/m3 in NO2, which would prevent 55 (2% of all deaths) to 93 (4%) deaths annually, depending on dose-response function used. Furthermore, we estimate that the NO2 reduction would result in 21 (6%) fewer cases of incident asthma in children, 95 (10%) fewer children with bronchitis every year, 30 (1%) fewer hospital admissions for respiratory disease, 87(4%) fewer dementia cases, and 11(11%) fewer cases of preeclampsia every year. The average reduction in PM2.5 of 0.6 (ranging from 0.1 till 1.7) µg/m3 would mean that 2729 (0.3%) work days would not be lost due to sick-days and that there would be 16,472 fewer restricted activity days (0.3%) that year had all on-road transportations been without tail-pipe emissions. Even though the estimates are sensitive to the dose-response functions used and to exposure misclassification errors, even the most conservative estimate of the number of prevented deaths is 7 times larger than the annual traffic fatalities in Malmö, indicating a substantial possibility to reduce the health burden attributed to tail-pipe emissions in the study area.

Modeling and robust pooling design of a preparative cation-exchange chromatography step for purification of monoclonal antibody monomer from aggregates.

This study has implemented and calibrated a model that describes the separation of the monomer of monoclonal antibodies from the dimer and larger oligomers on preparative-scale using cation-exchange chromatography. A general rate model with temperature dependent diffusion was coupled to a pH- and temperature-dependent steric mass action model. The model was shown to predict the retention of the monomer, dimer, and oligomer at low loadings for different pH levels and temperatures. Additionally, the model was shown to adequately predict the elution behavior of the monomer and soluble aggregates at high loadings within the same ranges with some limitations. The model was not able to accurately describe the shape of the product break-through curves or the slight levels of co-elution of the dimer and oligomer with the monomer at higher pH. The model was used to predict how 12 process variations impact the separation. The model is used to establish an elution end collection criterion such that the step can robustly provide the target purity of monomers.