Malvern Instruments Ltd | Date: 2017-01-11
A method of determining a relationship between a mutual diffusion co-efficient D_(m) and the concentration c of a solute within a solvent. The method comprises: obtaining a Taylorgram (100) comprising a plurality of measurements of solute concentration c; and deriving from the Taylorgram (200) a plurality of mutual diffusion coefficient values D_(m) corresponding with a plurality of different concentrations c of solute in the solvent.
Malvern Instruments Ltd | Date: 2015-10-09
An instrument and a method for measuring the characteristics of particles in a sample. The instrument comprises a light source operable to provide a light beam and defining an illumination axis; a sample cell placed on the illumination axis; a scattered light detector positioned to receive scattered light along a detection path from a sample in the sample cell, the scattered light produced by the interaction of the light beam with the sample; and a filter changer positioned between the sample cell and the scattered light detector. The filter changer comprises at least one optical filter and an actuator. The actuator is operable to move each of the at least one optical filter between a first position in which the detection path does not pass through the optical filter, and a second position in which the detection path passes through the optical filter
Malvern Instruments Ltd | Date: 2017-02-01
A method of Raman spectroscopic structure investigation of a sample that includes a dispersed chemical species, in particular a protein, in a liquid phase and an apparatus for performing said method are described. The method comprises: providing the sample; providing marker particles in the sample; exciting the sample with a light source; receiving Raman-scattered light from the dispersed chemical species in the sample; detecting, from the received Raman-scattered light, Raman scattering from the dispersed chemical species in the sample; detecting movement of the marker particles in the sample; and extracting at least one characteristic of the dispersed chemical species in the sample from both the step of detecting Raman scattering and the step of detecting movement of the particles.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: NMP-28-2014 | Award Amount: 11.30M | Year: 2015
Concept: NanoFASE will deliver an integrated Exposure Assessment Framework, including methods, parameter values, model and guidance that will allow Industry to assess the full diversity of industrial nano-enabled products to a standard acceptable in regulatory registrations. Methods to assess how use phases, waste streams and environmental compartments (air, soil, water biota) act as reactors in modifying and transporting ENMs will be developed and used to derive parameter values. Our nanospecific models will be integrated with the existing multi-media fate model SimpleBox4Nano for use in EUSES and also develop into a flexible multi-media model for risk assessment at different scales and complexities. Information on release form, transformation and transport processes for product relevant ENMs will allow grouping into Functional Fate Groups according to their most probable fate pathways as a contribution to safe-by-design based on fate. Methodology: Inventories of material release forms along the product value chain are established. We then study how released ENMs transform from initial reactive states to modified forms with lower energy states in which nanospecific properties may be lost. Transport studies assess material fluxes within/between compartments. The experimental work underpins models describing ENM transformation and transport. Open access is provided to the models suitable for incorporation into existing exposure assessment tools (e.g. SimpleBox4Nano) and for more detailed assessment. Framework completeness is validated by case studies. Impact: Identified links between ENM material properties and fate outcome (e.g. safe-by-design). Improved representation of nanospecific processes in existing key fate and exposure assessment tools (e.g. SimpleBox4Nano in EUSES). Contribution to standardization. GIS framework to support predictive assessment, catchment and point source management of ENM releases.
Malvern Instruments Incorporated | Date: 2016-06-24
Automated isothermal titration micro calorimetry (ITC) system comprising a micro calorimeter with a sample cell and a reference cell, the sample cell is accessible via a sample cell stem and the reference cell is accessible via a reference cell stem. The system further comprises an automatic pipette assembly comprising a syringe with a titration needle arranged to be inserted into the sample cell for supplying titrant, the pipette assembly comprises an activator for driving a plunger in the syringe, a pipette translation unit supporting the pipette assembly and being arranged to place pipette in position for titration, washing and filling operations, a wash station for the titrant needle, and a cell preparation unit arranged to perform operations for replacing the sample liquid in the sample cell when the pipette is placed in another position than the position for titration.
Malvern Instruments Ltd | Date: 2016-04-26
A particle characterisation apparatus is disclosed comprising: a first light source; a second light source, a sample cell; a first detector and a second detector. The first light source is operable to illuminate a first region of a sample comprising dispersed particles within the sample cell with a first light beam along a first light beam axis so as to produce scattered light by interactions of the first light beam with the sample. The first detector is configured to detect the scattered light. The second light source is operable to illuminate a second region of the sample with a second light beam along a second light beam axis. The second detector is an imaging detector, configured to image the particles along an imaging axis using the second light beam. The first light beam axis is at an angle of at least 5 degrees to the second light beam axis.
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: NMBP-26-2016 | Award Amount: 10.76M | Year: 2016
An increasing number of nanomaterials (NMs) are entering the market in every day products spanning from health care and leisure to electronics, cosmetics and foodstuff. Nanotechnology is a truly enabling technology, with unlimited potential for innovation. However, the novelty in properties and forms of NMs makes the development of a well-founded and robust legislative framework to ensure safe development of nano-enabled products particularly challenging. At the heart of the challenge lies the difficulty in the reliable and reproducible characterisation of NMs given their extreme diversity and dynamic nature, particularly in complex environments, such as within different biological, environmental and technological compartments. Two key steps can resolve this: 1) the development of a holistic framework for reproducible NM characterisation, spanning from initial needs assessment through method selection to data interpretation and storage; and 2) the embedding of this framework in an operational, linked-up ontological regime to allow identification of causal relationships between NMs properties, be they intrinsic, extrinsic or calculated, and biological, (eco)toxicological and health impacts fully embedded in a mechanistic risk assessment framework. ACEnano was conceived in response to the NMBP 26 call with the aim to comprehensively address these two steps. More specifically ACEnano will introduce confidence, adaptability and clarity into NM risk assessment by developing a widely implementable and robust tiered approach to NM physico-chemical characterisation that will simplify and facilitate contextual (hazard or exposure) description and its transcription into a reliable NMs grouping framework. This will be achieved by the creation of a conceptual toolbox that will facilitate decision-making in choice of techniques and SOPs, linked to a characterisation ontology framework for grouping and risk assessment and a supporting data management system.
Malvern Instruments Ltd | Date: 2016-09-28
A method of estimating a parameter for fitting a multi-component Taylorgram model (603, 604, 605, 606) to Taylorgram data g(t) is disclosed. The data (601, 602) comprises a multi-component Taylorgram peak or front at t = t. The method comprises: evaluating a value of an integration or differential of the data; determining the parameter, based on an analytical expression that includes the value of the integral or differential of the data, the parameter corresponding with a physical property of a sample from which the Taylorgram data was obtained.
Malvern Instruments Ltd | Date: 2016-11-02
A particle characterisation apparatus is disclosed comprising: a first light source (101); a second light source (102), a sample cell (105); a first detector (111) and a second detector (112). The first light source (101) is operable to illuminate a first region of a sample (150) comprising dispersed particles within the sample cell (105) with a first light beam (121) along a first light beam axis (131) so as to produce scattered light by interactions of the first light beam (131) with the sample (150). The first detector (111) is configured to detect the scattered light. The second light source (102) is operable to illuminate a second region of the sample (150) with a second light beam (122) along a second light beam axis (132). The second detector (102) is an imaging detector, configured to image the particles along an imaging axis (135) using the second light beam (122). The first light beam axis (131) is at an angle of at least 5 degrees to the second light beam axis (132).
Agency: European Commission | Branch: H2020 | Program: RIA | Phase: NMBP-10-2016 | Award Amount: 6.00M | Year: 2017
The overall objective of B-SMART is: 1. to design modular nanoparticles, 2. to manufacture them via a quality-by-design protocol, 3. to achieve delivery of therapeutic RNAs to the brain and treat neurodegenerative diseases. I. To design modular nanoparticles consisting of o an active RNA payload o established (lipid-based), emerging (trigger-responsive polymer-based) or exploratory (extracellular vesicle-based) nanoparticles o a targeting ligand consisting of the variable domain of heavy chain only antibodies (also known as VHHs or nanobodies), which are coupled to the carrier platform II. To manufacture the modular nanoparticles using a microfluidic assembly system that will ensure quality-by-design: uniform nanoparticles across research sites and excellent control over the physico-chemical parameters. III. To test pre-clinical activity of formulations with promising in vitro activity with good cell/blood compatibility and to select the best RNA-formulation for clinical translation to treat neurodegenerative diseases. Pre-clinical efficacy is tested after o local injection o nasal administration o systemic administration The neurodegenerative diseases carry a high burden for patients since they are without exception progressive. But they also carry a substantial socio-economic burden with estimated costs of 130 billion euro. per year (2008). IV. The technical work in B-SMART will be supported by project management. It ensures that the project is coordinated in a clear, unambiguous and mutually acceptable manner and that the project achieves its objectives, within the given financial and time constraints. in B-SMART we expect to arrive at a scale-able nanoparticle formulation with uniform characteristics that shows strong pre-clinical evidence of therapeutic efficacy and is ready for clinical translation.