The use of predictive models to develop chromatography-based purification processes.

Chromatography is the workhorse of biopharmaceutical downstream processing because it can selectively enrich a target product while removing impurities from complex feed streams. This is achieved by exploiting differences in molecular properties, such as size, charge and hydrophobicity (alone or in different combinations). Accordingly, many parameters must be tested during process development in order to maximize product purity and recovery, including resin and ligand types, conductivity, pH, gradient profiles, and the sequence of separation operations. The number of possible experimental conditions quickly becomes unmanageable. Although the range of suitable conditions can be narrowed based on experience, the time and cost of the work remain high even when using high-throughput laboratory automation. In contrast, chromatography modeling using inexpensive, parallelized computer hardware can provide expert knowledge, predicting conditions that achieve high purity and efficient recovery. The prediction of suitable conditions in silico reduces the number of empirical tests required and provides in-depth process understanding, which is recommended by regulatory authorities. In this article, we discuss the benefits and specific challenges of chromatography modeling. We describe the experimental characterization of chromatography devices and settings prior to modeling, such as the determination of column porosity. We also consider the challenges that must be overcome when models are set up and calibrated, including the cross-validation and verification of data-driven and hybrid (combined data-driven and mechanistic) models. This review will therefore support researchers intending to establish a chromatography modeling workflow in their laboratory.

Spherical nanoparticles can be used as non-penetrating tracers to determine the extra-particle void volume in packed-bed chromatography columns.

The optimization of downstream processing in silico can accelerate bioprocess development by limiting experiments to the most promising separation conditions that have been identified using chromatography models. Such models describe protein binding and mass transport in packed-bed columns and thus require precise knowledge about the columns and the resins they contain. One important set of properties is the resin porosities, often determined using combinations of penetrating and non-penetrating tracers. However, the former can be disproportionately small, providing data of limited practical relevance, and the latter can undergo unwanted interactions with the resin, interfering with porosity calculations. Here we characterize and minimize the interactions of three novel hard-sphere non-penetrating tracers with the model resin Q Sepharose HP under various conditions and determine the corresponding inter-particle porosities. We found that conductivities > 100 mS cm-1 were necessary to suppress tracer-resin interactions despite them sharing the same surface charge. We combined these data with those from proteins studied under non-binding conditions, which can be used as authentic penetrating tracers, to determine both the intra-particle and total porosities. Furthermore, we found that the inter-particle porosity was below the theoretical limit of dense sphere packing (25.95%) and provide experimental data showing that the discrepancy is caused by resin particle deformation during the packing of columns under pressure.

Precision analysis for the determination of steric mass action parameters using eight tobacco host cell proteins.

Plants are advantageous as biopharmaceutical manufacturing platforms because they allow the economical and scalable upstream production of proteins, including those requiring post-translational modifications, but do not support the replication of human viruses. However, downstream processing can be more labor-intensive compared to fermenter-based systems because the product is often mixed with abundant host cell proteins (HCPs). Modeling chromatographic separation can minimize the number of process development experiments and thus reduce costs. An important part of such modeling is the sorption isotherm, such as the steric mass action (SMA) model, which describes the multicomponent protein-salt equilibria established in ion-exchange systems. Here we purified ten HCPs, including 2-Cys-peroxiredoxin, from tobacco (Nicotiana tabacum and N. benthamiana). For eight of these HCPs, we obtained sufficient quantities to determine the SMA binding parameters (KSMA and ν) under different production-relevant conditions. We studied the parameters for 2-Cys-peroxiredoxin on Q-Sepharose HP in detail, revealing that pH, resin batch and buffer batch had little influence on KSMA and ν, with coefficients of variation (COVs) less than 0.05 and 0.21, respectively. In contrast, the anion-exchange resins SuperQ-650S, Q-Sepharose FF and QAE-550C led to COVs of 0.69 for KSMA and 0.05 for ν, despite using the same quaternary amine functional group as Q-Sepharose HP. Plant cultivation in summer vs winter resulted in COVs of 0.09 for KSMA and 0.02 for ν, revealing a small impact compared to COVs of 17.15 for KSMA and 0.20 for ν when plants were grown in different settings (climate-controlled phytotron vs greenhouse). We conclude that plant cultivation can substantially affect protein properties and the resulting SMA parameters. Accordingly, plant growth but also protein purification and characterization for chromatography model building should be tightly controlled and well documented.

Environmental and mucosal microbiota and their role in childhood asthma.

BACKGROUND: High microbial diversity in the environment has been associated with lower asthma risk, particularly in children exposed to farming. It remains unclear whether this effect operates through an altered microbiome of the mucosal surfaces of the airways. METHODS: DNA from mattress dust and nasal samples of 86 school age children was analyzed by 454 pyrosequencing of the 16S rRNA gene fragments. Based on operational taxonomic units (OTUs), bacterial diversity and composition were related to farm exposure and asthma status. RESULTS: Farm exposure was positively associated with bacterial diversity in mattress dust samples as determined by richness (P = 8.1 × 10-6 ) and Shannon index (P = 1.3 × 10-5 ). Despite considerable agreement of richness between mattress and nasal samples, the association of richness with farming in nasal samples was restricted to a high gradient of farm exposure, that is, exposure to cows and straw vs no exposure at all. In mattress dust, the genera Clostridium, Facklamia, an unclassified genus within the family of Ruminococcaceae, and six OTUs were positively associated with farming. Asthma was inversely associated with richness [aOR = 0.48 (0.22-1.02)] and Shannon index [aOR = 0.41 (0.21-0.83)] in mattress dust and to a lower extent in nasal samples [richness aOR 0.63 = (0.38-1.06), Shannon index aOR = 0.66 (0.39-1.12)]. CONCLUSION: The stronger inverse association of asthma with bacterial diversity in mattress dust as compared to nasal samples suggests microbial involvement beyond mere colonization of the upper airways. Whether inhalation of metabolites of environmental bacteria contributes to this phenomenon should be the focus of future research.

Prevalence of superficial siderosis following singular, acute aneurysmal subarachnoid hemorrhage.

INTRODUCTION: Superficial siderosis is presumably a consequence of recurrent bleeding into the subarachnoid space. The objective of this study was to assess the prevalence of superficial siderosis after singular, aneurysmal subarachnoid hemorrhage (SAH) in the long term. METHODS: We retrospectively identified all patients who presented with a singular, acute, aneurysmal SAH at our institution between 2010 and 2013 and in whom a magnetic resonance imaging (MRI) including T2*-weighted imaging was available at least 4 months after the acute bleeding event. MRI scans were judged concerning the presence and distribution of superficial siderosis. Influence of clinical data, Fisher grade, localization, and cause of SAH as well as the impact of neurosurgical interventions on the occurrence of superficial siderosis was tested. RESULTS: Seventy-two patients with a total of 117 MRIs were included. Mean delay between SAH and the last available MRI was 47.4 months (range 4-129). SAH was Fisher grade 1 in 2 cases, 2 in 4 cases, 3 in 10 cases, and 4 in 56 cases. Superficial siderosis was detected in 39 patients (54.2%). In all patients with more than one MRI scan, localization and distribution of superficial siderosis did not change over time. Older age (p = 0.02) and higher degree of SAH (p = 0.03) were significantly associated with the development of superficial siderosis. CONCLUSION: Superficial siderosis develops in approximately half of patients after singular, aneurysmal SAH and might be more common in patients with an older age and a greater amount of blood. However, additional factors must play a role in whether a patient is prone to develop superficial siderosis or not.

Lack of association between venous hemodynamics, venous morphology and the postthrombotic syndrome after upper extremity deep venous thrombosis.

OBJECTIVES: To explore the association of the postthrombotic syndrome with venous hemodynamics and morphological abnormalities after upper extremity deep venous thrombosis. METHODS: Thirty-seven patients with a history of upper extremity deep venous thrombosis treated with anticoagulation alone underwent a single study visit (mean time after diagnosis: 44.4 ± 28.1 months). Presence and severity postthrombotic syndrome were classified according to the modified Villalta score. Venous volume and venous emptying were determined by strain-gauge plethysmography. The arm veins were assessed for postthrombotic abnormalities by ultrasonography. The relationship between postthrombotic syndrome and hemodynamic and morphological sequelae was evaluated using univariate significance tests and Spearman's correlation analysis. RESULTS: Fifteen of 37 patients (40.5%) developed postthrombotic syndrome. Venous volume and venous emptying of the arm affected by upper extremity deep venous thrombosis did not correlate with the Villalta score (rho = 0.17 and 0.19; p = 0.31 and 0.25, respectively). Residual morphological abnormalities, as assessed by ultrasonography, did not differ significantly between patients with and without postthrombotic syndrome (77.3% vs. 86.7%, p = 0.68). CONCLUSIONS: Postthrombotic syndrome after upper extremity deep venous thrombosis is not associated with venous hemodynamics or residual morphological abnormalities.

Hyperattenuated intracerebral lesions after mechanical recanalization in acute stroke.

BACKGROUND AND PURPOSE: Following mechanical recanalization of an acute intracranial vessel occlusion, hyperattenuated lesions are frequently found on postinterventional cranial CT. They represent either blood or-more frequently-enhancement of contrast agent. Here, we aimed to evaluate the prognostic value of these hyperattenuated intracerebral lesions. MATERIALS AND METHODS: One hundred one consecutive patients with acute stroke in the anterior circulation who underwent mechanical recanalization were included. Risk factors for hyperattenuated intracerebral lesions were assessed, and lesion volume was compared with the volume of final infarction. Clinical outcome and relative risk of secondary hemorrhage were determined in patients with and without any hyperattenuated lesions and compared. RESULTS: The frequency of hyperattenuated lesions was 84.2%. Risk factors for hyperattenuated lesions were female sex, higher NIHSS score on admission, and higher amount of contrast agent applied. On follow-up, 3 patients showed no infarction; 53 patients, an ischemic infarction; and 45 patients, a hemorrhagic infarction. In all except 1 case, final volume of infarction (median = 92.4 mL) exceeded the volume of hyperattenuated intracerebral lesions (median = 5.6 mL). Patients with hyperattenuated lesions were at a 4 times higher relative risk for hemorrhagic transformation but had no significantly worse clinical outcome. CONCLUSIONS: Our data show that the extent of postinterventional hyperattenuated intracerebral lesions underestimates the volume of final infarction. Although hyperattenuated lesions indicate a higher risk of secondary hemorrhagic transformation, their presence seems not to be of any prognostic value regarding clinical outcome.

Application of microarray analysis on computer cluster and cloud platforms.

BACKGROUND: Analysis of recent high-dimensional biological data tends to be computationally intensive as many common approaches such as resampling or permutation tests require the basic statistical analysis to be repeated many times. A crucial advantage of these methods is that they can be easily parallelized due to the computational independence of the resampling or permutation iterations, which has induced many statistics departments to establish their own computer clusters. An alternative is to rent computing resources in the cloud, e.g. at Amazon Web Services. OBJECTIVES: In this article we analyze whether a selection of statistical projects, recently implemented at our department, can be efficiently realized on these cloud resources. Moreover, we illustrate an opportunity to combine computer cluster and cloud resources. METHODS: In order to compare the efficiency of computer cluster and cloud implementations and their respective parallelizations we use microarray analysis procedures and compare their runtimes on the different platforms. RESULTS: Amazon Web Services provide various instance types which meet the particular needs of the different statistical projects we analyzed in this paper. Moreover, the network capacity is sufficient and the parallelization is comparable in efficiency to standard computer cluster implementations. CONCLUSION: Our results suggest that many statistical projects can be efficiently realized on cloud resources. It is important to mention, however, that workflows can change substantially as a result of a shift from computer cluster to cloud computing.