Assessment of immunogenicity and drug activity in patient sera by flow-induced dispersion analysis.

Biopharmaceuticals have revolutionized the treatment of many diseases such as diabetes, cancer, and autoimmune disorders. These complex entities provide unique advantages like high specificity towards their target. Unfortunately, biopharmaceuticals are also prone to elicit undesired immunogenic responses (immunogenicity), compromising treatment efficacy as well as patient safety due to severe adverse effects including life threatening conditions. Current immunogenicity assays are hampered by immobilization procedures, complicated sample pre-treatment, or rely on cell-based methods which all prevent reliable and continuous monitoring of patients. In this work, we present Flow Induced Dispersion Analysis (FIDA) for assessment of immunogenicity and drug activity in serum samples from arthritis patients receiving adalimumab. FIDA is a first principle technique for size-based characterization of biomolecules and their complexes under biologically relevant conditions. The FIDA methodology rely on an absolute and quantitative readout (hydrodynamic radius) thus reducing the need for positive and negative controls. Here, FIDA is applied for evaluating active adalimumab in serum by studying the interaction with its target tumor necrosis factor alpha (TNF-α). We report proof of principle for a quantitative approach for stratifying patients exhibiting presence of neutralizing and non-neutralizing antibodies based on their individual drug activity pattern. Further, it can be applied to any biopharmaceutical having soluble drug targets and it holds potential in a companion diagnostics setting.

Evaluating Commutability of Control Materials in Three Nordic External Quality Assessment Schemes for Lipoproteins.

BACKGROUND: The quality of control materials is crucial for evaluating external quality assessment (EQA) results. To detect method differences, the EQA material should behave the same as a patient sample, meaning the material must be commutable. Noncommutable materials may cause misinterpretations of EQA results. Here, we examined the commutability of EQA materials used in 3 Nordic EQA schemes for lipids. METHODS: The study was designed according to the procedures recommended for assessing commutability by the International Federation of Clinical Chemistry and Laboratory Medicine. Commutability was assessed based on the difference in bias between a control material (CM) and clinical samples (CS) consisting of human plasma using 2 different measurement procedures (MPs). Measurands: LDL-cholesterol (LDL-C), total cholesterol (TC), HDL-cholesterol (HDL-C), and triglycerides (TG). Four CMs (CM1-4) were assessed for commutability by using 40 CS and 3 MPs (Abbott Architect, Roche Cobas, and Siemens Atellica). RESULTS: Unmodified native CMs (CM1 and CM3), stored at -80 °C, were commutable for all included measurands, except for LDL-C that was indeterminate, when comparing MPs pairwise. Modified CM2 was noncommutable for HDL-C, LDL-C, non-HDL-C, and LDL-C calculations. Unmodified native CM4, stored at -20°C, was noncommutable for LDL-C. CONCLUSIONS: Unmodified serum samples stored at -80 °C were commutable for lipids on the evaluated MPs, and therefore suitable as CMs in EQA schemes. Moreover, the study demonstrated that minor modifications of samples may lead to noncommutability.

Size-based characterization of adalimumab and TNF-α interactions using flow induced dispersion analysis: assessment of avidity-stabilized multiple bound species.

The understanding and characterization of protein interactions is crucial for elucidation of complicated biomolecular processes as well as for the development of new biopharmaceutical therapies. Often, protein interactions involve multiple binding, avidity, oligomerization, and are dependent on the local environment. Current analytical methodologies are unable to provide a detailed mechanistic characterization considering all these parameters, since they often rely on surface immobilization, cannot measure under biorelevant conditions, or do not feature a structurally-related readout for indicating formation of multiple bound species. In this work, we report the use of flow induced dispersion analysis (FIDA) for in-solution characterization of complex protein interactions under in vivo like conditions. FIDA is an immobilization-free ligand binding methodology employing Taylor dispersion analysis for measuring the hydrodynamic radius (size) of biomolecular complexes. Here, the FIDA technology is utilized for a size-based characterization of the interaction between TNF-α and adalimumab. We report concentration-dependent complex sizes, binding affinities (Kd), kinetics, and higher order stoichiometries, thus providing essential information on the TNF-α-adalimumab binding mechanism. Furthermore, it is shown that the avidity stabilized complexes involving formation of multiple non-covalent bonds are formed on a longer timescale than the primary complexes formed in a simple 1 to 1 binding event.

Protein Characterization in 3D: Size, Folding, and Functional Assessment in a Unified Approach.

Assessment of protein stability and function is key to the understanding of biological systems and plays an important role in the development of protein-based drugs. In this work, we introduce an integrated approach based on Taylor dispersion analysis (TDA), flow induced dispersion analysis (FIDA), and in-line intrinsic fluorescence which enables rapid and detailed assessment of protein stability and unfolding. We demonstrate that the new platform is able to efficiently characterize chemically induced protein unfolding of human serum albumin (HSA) in great detail. The combined platform enables local structural changes to be probed by monitoring changes in intrinsic fluorescence and loss of binding of a low-molecular weight ligand. Simultaneously, the size of the unfolding HSA is obtained by TDA on the same samples. The integration of the methodologies enables a fully automated characterization of HSA using only a few hundred nanoliters of sample. We envision that the presented methodology will find applications in fundamental biophysics and biology as well as in stability screens of protein-based drug candidates.

Explicit Theoretical Analysis of How the Rate of Exocytosis Depends on Local Control by Ca2+ Channels.

Hormones and neurotransmitters are released from cells by calcium-regulated exocytosis, and local coupling between Ca2+ channels (CaVs) and secretory granules is a key factor determining the exocytosis rate. Here, we devise a methodology based on Markov chain models that allows us to obtain analytic results for the expected rate. First, we analyze the property of the secretory complex obtained by coupling a single granule with one CaV. Then, we extend our results to a more general case where the granule is coupled with n CaVs. We investigate how the exocytosis rate is affected by varying the location of granules and CaVs. Moreover, we assume that the single granule can form complexes with inactivating or non-inactivating CaVs. We find that increasing the number of CaVs coupled with the granule determines a much higher rise of the exocytosis rate that, in case of inactivating CaVs, is more pronounced when the granule is close to CaVs, while, surprisingly, in case of non-inactivating CaVs, the highest relative increase in rate is obtained when the granule is far from the CaVs. Finally, we exploit the devised model to investigate the relation between exocytosis and calcium influx. We find that the quantities are typically linearly related, as observed experimentally. For the case of inactivating CaVs, our simulations show a change of the linear relation due to near-complete inactivation of CaVs.

Analytical performance specifications for external quality assessment - definitions and descriptions.

External Quality Assurance (EQA) is vital to ensure acceptable analytical quality in medical laboratories. A key component of an EQA scheme is an analytical performance specification (APS) for each measurand that a laboratory can use to assess the extent of deviation of the obtained results from the target value. A consensus conference held in Milan in 2014 has proposed three models to set APS and these can be applied to setting APS for EQA. A goal arising from this conference is the harmonisation of EQA APS between different schemes to deliver consistent quality messages to laboratories irrespective of location and the choice of EQA provider. At this time there are wide differences in the APS used in different EQA schemes for the same measurands. Contributing factors to this variation are that the APS in different schemes are established using different criteria, applied to different types of data (e.g. single data points, multiple data points), used for different goals (e.g. improvement of analytical quality; licensing), and with the aim of eliciting different responses from participants. This paper provides recommendations from the European Federation of Laboratory Medicine (EFLM) Task and Finish Group on Performance Specifications for External Quality Assurance Schemes (TFG-APSEQA) and on clear terminology for EQA APS. The recommended terminology covers six elements required to understand APS: 1) a statement on the EQA material matrix and its commutability; 2) the method used to assign the target value; 3) the data set to which APS are applied; 4) the applicable analytical property being assessed (i.e. total error, bias, imprecision, uncertainty); 5) the rationale for the selection of the APS; and 6) the type of the Milan model(s) used to set the APS. The terminology is required for EQA participants and other interested parties to understand the meaning of meeting or not meeting APS.

Concise Whole-Cell Modeling of BKCa-CaV Activity Controlled by Local Coupling and Stoichiometry.

Large-conductance Ca2+-dependent K+ (BKCa) channels are important regulators of electrical activity. These channels colocalize and form ion channel complexes with voltage-dependent Ca2+ (CaV) channels. Recent stochastic simulations of the BKCa-CaV complex with 1:1 stoichiometry have given important insight into the local control of BKCa channels by fluctuating nanodomains of Ca2+. However, such Monte Carlo simulations are computationally expensive, and are therefore not suitable for large-scale simulations of cellular electrical activity. In this work we extend the stochastic model to more realistic BKCa-CaV complexes with 1:n stoichiometry, and analyze the single-complex model with Markov chain theory. From the description of a single BKCa-CaV complex, using arguments based on timescale analysis, we derive a concise model of whole-cell BKCa currents, which can readily be analyzed and inserted into models of cellular electrical activity. We illustrate the usefulness of our results by inserting our BKCa description into previously published whole-cell models, and perform simulations of electrical activity in various cell types, which show that BKCa-CaV stoichiometry can affect whole-cell behavior substantially. Our work provides a simple formulation for the whole-cell BKCa current that respects local interactions in BKCa-CaV complexes, and indicates how local-global coupling of ion channels may affect cell behavior.

Bargaining for health: a case study of a collective agreement-based health program for manual workers.

This paper examines the short- and medium-term effects of the PensionDanmark Health Scheme, the largest privately administered health program for workers in Denmark, which provides prevention and early management of work-related injuries. We use a difference-in-differences approach that exploits a natural variation in the program rollout across collective agreement areas in the construction sector and over time. The results show only little evidence of an effect on the prevention of injuries requiring medical attention in the first 3 years after the program was introduced. Despite this, we find evidence of significant positive effects on several labor market outcomes, suggesting that the program enables some work-injured individuals to maintain their work and earnings capacity. In view of its low costs, the program appears to be cost-effective overall.

To what extent does employer-paid health insurance reduce the use of public hospitals?

OBJECTIVE: This study examines the extent to which employer-paid health insurance has led to substitution of public with private hospital use in Denmark. METHODS: Individual-person-level data for the entire Danish privately employed, full-time working population is used in an observational design. The effect of having employer-paid health insurance on the utilisation of public hospitals is estimated using propensity score matching in order to control for risk selection, based on a number of individual- and company-level characteristics. The outcome is defined as the total consumption of health care services provided by public hospitals. RESULTS: The effect of employer-paid health insurance is estimated to correspond to a significant 10% reduction in the total use of public hospitals. The effect appears to be robust to alternative methodological specifications and is supported from the analysis of alternative outcome measures. CONCLUSION: The rise in the number of individuals with employer-paid health insurance seems to have alleviated the pressure on public hospitals in Denmark. Future studies should confirm the magnitude of this effect, preferably based on empirical data with repeated measurements of insurance status.