Martin N. Fransson

A Minimum Data Set for Sharing Biobank Samples, Information, and Data: MIABIS

Numerous successful scientific results have emerged from projects using shared biobanked samples and data. In order to facilitate the discovery of underutilized biobank samples, it would be helpful if a global biobank register containing descriptive information about the samples existed. But first, for shared data to be comparable, it needs to be harmonized. In compliance with the aim of BBMRI (Biobanking and Biomolecular Resources Research Infrastructure), to harmonize biobanking across Europe, and the conclusion that the move towards a universal information infrastructure for biobanking is directly connected to the issues of semantic interoperability through standardized message formats and controlled terminologies, we have developed an updated version of the minimum data set for biobanks and studies using human biospecimens. The data set called MIABIS (Minimum Information About BIobank data Sharing) consists of 52 attributes describing a biobanks content. The aim is to facilitate data discovery through harmonization of data elements describing a biobank at the aggregate level. As many biobanks across Europe possess a tremendous amount of samples that are underutilized, this would help pave the way for biobank networking on a national and international level, resulting in time and cost savings and faster emergence of new scientific results.

Toward a common language for biobanking

To encourage the process of harmonization, the biobank community should support and use a common terminology. Relevant terms may be found in general thesauri for medicine, legal instruments or specific glossaries for biobanking. A comparison of the use of these sources has so far not been conducted and would be a useful instrument to further promote harmonization and data sharing. Thus, the purpose of the present study was to investigate the preference of definitions important for sharing biological samples and data. Definitions for 10 terms –[human] biobank, sample/specimen, sample collection, study, aliquot, coded, identifying information, anonymised, personal data and informed consent–were collected from several sources. A web-based questionnaire was sent to 560 European individuals working with biobanks asking to select their preferred definition for the terms. A total of 123 people participated in the survey, giving a response rate of 23%. The result was evaluated from four aspects: scope of definitions, potential regional differences, differences in semantics and definitions in the context of ontologies, guided by comments from responders. Indicative from the survey is the risk of focusing only on the research aspect of biobanking in definitions. Hence, it is recommended that important terms should be formulated in such a way that all areas of biobanking are covered to improve the bridges between research and clinical application. Since several of the terms investigated here within can also be found in a legal context, which may differ between countries, establishing what is a proper definition on how it adheres to law is also crucial.

Influence of Cremophor EL and genetic polymorphisms on the pharmacokinetics of paclitaxel and its metabolites using a mechanism-based model.

The formulation vehicle Cremophor EL has previously been shown to affect paclitaxel kinetics, but it is not known whether it also affects the kinetics of paclitaxel metabolites. This information may be important for understanding paclitaxel metabolism in vivo and in the investigation of the role of genetic polymorphisms in the metabolizing enzymes CYP2C8 and CYP3A4/CYP3A5 and the ABCB1 transporter. In this study we used the population pharmacokinetic approach to explore the influence of predicted Cremophor EL concentrations on paclitaxel (Taxol) metabolites. In addition, correlations between genetic polymorphisms and enzyme activity with clearance of paclitaxel, its two primary metabolites, 6α-hydroxypaclitaxel and p-3′-hydroxypaclitaxel, and its secondary metabolite, 6α-p-3′-dihydroxypaclitaxel were investigated. Model building was based on 1156 samples from a study with 33 women undergoing paclitaxel treatment for gynecological cancer. Total concentrations of paclitaxel were fitted to a model described previously. One-compartment models characterized unbound metabolite concentrations. Total concentrations of 6α-hydroxypaclitaxel and p-3′-hydroxypaclitaxel were strongly dependent on predicted Cremophor EL concentrations, but this association was not found for 6α-p-3′-dihydroxypaclitaxel. Clearance of 6α-hydroxypaclitaxel (fraction metabolized) was significantly correlated (p < 0.05) to the ABCB1 allele G2677T/A. Individuals carrying the polymorphisms G/A (n = 3) or G/G (n = 5) showed a 30% increase, whereas individuals with polymorphism T/T (n = 8) showed a 27% decrease relative to those with the polymorphism G/T (n = 17). The correlation of G2677T/A with 6α-hydroxypaclitaxel has not been described previously but supports other findings of the ABCB1 transporter playing a part in paclitaxel metabolism.

Developing a semantically rich ontology for the biobank-administration domain

BackgroundBiobanks are a critical resource for translational science. Recently, semantic web technologies such as ontologies have been found useful in retrieving research data from biobanks. However, recent research has also shown that there is a lack of data about the administrative aspects of biobanks. These data would be helpful to answer research-relevant questions such as what is the scope of specimens collected in a biobank, what is the curation status of the specimens, and what is the contact information for curators of biobanks. Our use cases include giving researchers the ability to retrieve key administrative data (e.g. contact information, contacts affiliation, etc.) about the biobanks where specific specimens of interest are stored. Thus, our goal is to provide an ontology that represents the administrative entities in biobanking and their relations. We base our ontology development on a set of 53 data attributes called MIABIS, which were in part the result of semantic integration efforts of the European Biobanking and Biomolecular Resources Research Infrastructure (BBMRI). The previous work on MIABIS provided the domain analysis for our ontology. We report on a test of our ontology against competency questions that we derived from the initial BBMRI use cases. Future work includes additional ontology development to answer additional competency questions from these use cases.ResultsWe created an open-source ontology of biobank administration called Ontologized MIABIS (OMIABIS) coded in OWL 2.0 and developed according to the principles of the OBO Foundry. It re-uses pre-existing ontologies when possible in cooperation with developers of other ontologies in related domains, such as the Ontology of Biomedical Investigation. OMIABIS provides a formalized representation of biobanks and their administration. Using the ontology and a set of Description Logic queries derived from the competency questions that we identified, we were able to retrieve test data with perfect accuracy. In addition, we began development of a mapping from the ontology to pre-existing biobank data structures commonly used in the U.S.ConclusionsIn conclusion, we created OMIABIS, an ontology of biobank administration. We found that basing its development on pre-existing resources to meet the BBMRI use cases resulted in a biobanking ontology that is re-useable in environments other than BBMRI. Our ontology retrieved all true positives and no false positives when queried according to the competency questions we derived from the BBMRI use cases. Mapping OMIABIS to a data structure used for biospecimen collections in a medical center in Little Rock, AR showed adequate coverage of our ontology.

Physiologically-based Toxicokinetic Model for Cadmium Using Markov-Chain Monte Carlo Analysis of Concentrations in Blood, Urine, and Kidney Cortex from Living Kidney Donors

The health effects of low-level chronic exposure to cadmium are increasingly recognized. To improve the risk assessment, it is essential to know the relation between cadmium intake, body burden, and biomarker levels of cadmium. We combined a physiologically-based toxicokinetic (PBTK) model for cadmium with a data set from healthy kidney donors to re-estimate the model parameters and to test the effects of gender and serum ferritin on systemic uptake. Cadmium levels in whole blood, blood plasma, kidney cortex, and urinary excretion from 82 men and women were used to calculate posterior distributions for model parameters using Markov-chain Monte Carlo analysis. For never- and ever-smokers combined, the daily systemic uptake was estimated at 0.0063 μg cadmium/kg body weight in men, with 35% increased uptake in women and a daily uptake of 1.2 μg for each pack-year per calendar year of smoking. The rate of urinary excretion from cadmium accumulated in the kidney was estimated at 0.000042 day(-1), corresponding to a half-life of 45 years in the kidneys. We have provided an improved model of cadmium kinetics. As the new parameter estimates derive from a single study with measurements in several compartments in each individual, these new estimates are likely to be more accurate than the previous ones where the data used originated from unrelated data sets. The estimated urinary excretion of cadmium accumulated in the kidneys was much lower than previous estimates, neglecting this finding may result in a marked under-prediction of the true kidney burden.

Semi-physiologically based pharmacokinetic modeling of paclitaxel metabolism and in silico-based study of the dynamic sensitivities in pathway kinetics

PURPOSE To build a semi-physiologically based pharmacokinetic model describing the uptake, metabolism and efflux of paclitaxel and its metabolites and investigate the effect of hypothetical genetic polymorphisms causing reduced uptake, metabolism or efflux in the pathway by model simulation and sensitivity analysis. METHODS A previously described intracellular pharmacokinetic model was used as a starting point for model development. Kinetics for metabolism, transport, binding and systemic and output compartments were added to mimic a physiological model with hepatic elimination. Model parameters were calibrated using constraints postulated as ratios of concentrations and amounts of metabolites and drug in the systemic plasma and output compartments. The sensitivity in kinetic parameters was tested using dynamic sensitivity analysis. RESULTS Predicted plasma concentrations of drug and metabolites were in the range of what has been observed in clinical studies. Given the final model, plasma concentrations of paclitaxel seems to be relatively little affected by changes in metabolism or transport, while its main metabolite may be largely affected even by small changes. If metabolites prove to be clinically relevant, genetic polymorphisms may play an important role for individualizing paclitaxel treatment.