nanoSTAIR: a new strategic proposal to impulse standardization in nanotechnology research

Nanotechnology is considered one of the key technologies of the 21st century within Europe and a Key-Enabling Technology (KET) by Horizon 2020. Standardization has been identified in H2020 as one of the innovation-support measures by bridging the gap between research and the market, and helping the fast and easy transfer of research results to the European and international market. The development of new and improved standards requires high quality technical information, creating a fundamental interdependency between the standardization and research communities. In the frame of project nanoSTAIR (GA 319092), the present paper describes the European scenario on research and standardization in nanotechnology and presents a proposal of a European strategy (nanoSTAIR) to impulse direct "pipelines" between research and standardization. In addition, strategic actions focused on integration of standardization in the R&D projects, from the early stages of the design of a future business (Project Proposal), are also described.European Commission, through the Seventh Framework Programme (GA 319092)

Apixaban and rivaroxaban's physiologically-based pharmacokinetic model validation in hospitalized patients: A first step for larger use of a priori modeling approach at bed side

When used in real-world conditions, substantial interindividual variations in direct oral anticoagulant (DOAC) plasma concentrations are observed for a given dose, leading to a risk of over- or under-exposure and clinically significant adverse events. Physiologically-based pharmacokinetic (PBPK) models could help physicians to tailor DOAC prescriptions in vulnerable patient populations, such as those in the hospital setting. The present study aims to validate prospectively PBPK models for rivaroxaban and apixaban in a large cohort of elderly, polymorbid, and hospitalized patients. In using a model of geriatric population integrating appropriate physiological parameters into models first optimized with healthy volunteer data, observed plasma concentration collected in hospitalized patients on apixaban (n = 100) and rivaroxaban (n = 100) were adequately predicted (ratio predicted/observed area under the concentration curve for a dosing interval [AUCtau] = 0.97 [0.96-0.99] geometric mean, 90% confidence interval, ratio predicted/observed AUCtau = 1.03 [1.02-1.05]) for apixaban and rivaroxaban, respectively. Validation of the present PBPK models for rivaroxaban and apixaban in in-patients represent an additional step toward the feasibility of bedside use

Virtual twin approach using physiologically based pharmacokinetic modelling in hospitalized patients treated with apixaban or rivaroxaban.

In a large cohort of hospitalized patients, previously validated physiologically based pharmacokinetic (PBPK)-based models for apixaban and rivaroxaban are being assessed for their performance in predicting individual pharmacokinetics, aiming to identify patients at high risk of under- or overdosing based on demographic, physiological and CYP-related phenotypic characteristics. Clinical data were collected from hospitalized patients treated with apixaban (n = 100) or rivaroxaban (n = 100) at the Geneva University Hospitals (HUG). These patients were recruited in the OptimAT trial (NCT03477331). PBPK modelling created virtual twins for each patient, integrating demographic, kidney function, P-glycoprotein (Pgp) and cytochrome P450 (CYP450) 3A phenotyping. Individual PK profiles were simulated for every patient and compared to actual drug exposure, as assessed with LC/MS-MS. Mean fold error (MFE) (95% CI) for the apixaban and rivaroxaban models integrating demographic and kidney function was within the pre-required bioequivalency criteria with 1.10 (1.04-1.16) and 0.97 (0.93-1.02), respectively. Adding individual Pgp and CYP3A phenotypes led to a slight overprediction 1.25 (1.17-1.33) and 1.30 (1.21-1.39), but patients at risk for bleeding were correctly predicted with MFEs of 0.90 (0.76-1.04) and 1.15 (1.11-1.20). In a large cohort of hospitalized patients, a PBPK model incorporating demographic characteristics and kidney function can accurately predict, within bioequivalency criteria, an individual's apixaban and rivaroxaban plasma exposure. The added value of individual Pgp and 3A phenotypes on the predictive performance need to be further explored, although patients at higher risk for bleeding may benefit. This innovative approach represents an important step towards the application of PBPK at bedside