78,414 research outputs found
Development and Validation of an InâLine API Quantification Method Using AQbD Principles Based on UVâVis Spectroscopy to Monitor and Optimise Continuous Hot Melt Extrusion Process
open access journalA key principle of developing a new medicine is that quality should be built in, with a
thorough understanding of the product and the manufacturing process supported by appropriate
process controls. Quality by design principles that have been established for the development of
drug products/substances can equally be applied to the development of analytical procedures. This
paper presents the development and validation of a quantitative method to predict the
concentration of piroxicam in KollidonÂź VA 64 during hot melt extrusion using analytical quality
by design principles. An analytical target profile was established for the piroxicam content and a
novel inâline analytical procedure was developed using predictive models based on UVâVis
absorbance spectra collected during hot melt extrusion. Risks that impact the ability of the analytical
procedure to measure piroxicam consistently were assessed using failure mode and effect analysis.
The critical analytical attributes measured were colour (L* lightness, b* yellow to blue colour
parametersâinâprocess critical quality attributes) that are linked to the ability to measure the API
content and transmittance. The method validation was based on the accuracy profile strategy and
ICH Q2(R1) validation criteria. The accuracy profile obtained with two validation sets showed that
the 95% ÎČâexpectation tolerance limits for all piroxicam concentration levels analysed were within
the combined trueness and precision acceptance limits set at ±5%. The method robustness was tested
by evaluating the effects of screw speed (150â250 rpm) and feed rate (5â9 g/min) on piroxicam
content around 15% w/w. Inâline UVâVis spectroscopy was shown to be a robust and practical PAT
tool for monitoring the piroxicam content, a critical quality attribute in a pharmaceutical HME
process
Optimal receptor-cluster size determined by intrinsic and extrinsic noise
Biological cells sense external chemical stimuli in their environment using
cell-surface receptors. To increase the sensitivity of sensing, receptors often
cluster, most noticeably in bacterial chemotaxis, a paradigm for signaling and
sensing in general. While amplification of weak stimuli is useful in absence of
noise, its usefulness is less clear in presence of extrinsic input noise and
intrinsic signaling noise. Here, exemplified on bacterial chemotaxis, we
combine the allosteric Monod-Wyman- Changeux model for signal amplification by
receptor complexes with calculations of noise to study their
interconnectedness. Importantly, we calculate the signal-to-noise ratio,
describing the balance of beneficial and detrimental effects of clustering for
the cell. Interestingly, we find that there is no advantage for the cell to
build receptor complexes for noisy input stimuli in absence of intrinsic
signaling noise. However, with intrinsic noise, an optimal complex size arises
in line with estimates of the sizes of chemoreceptor complexes in bacteria and
protein aggregates in lipid rafts of eukaryotic cells.Comment: 15 pages, 12 figures,accepted for publication on Physical Review
Noise control and utility: From regulatory network to spatial patterning
Stochasticity (or noise) at cellular and molecular levels has been observed
extensively as a universal feature for living systems. However, how living
systems deal with noise while performing desirable biological functions remains
a major mystery. Regulatory network configurations, such as their topology and
timescale, are shown to be critical in attenuating noise, and noise is also
found to facilitate cell fate decision. Here we review major recent findings on
noise attenuation through regulatory control, the benefit of noise via
noise-induced cellular plasticity during developmental patterning, and
summarize key principles underlying noise control
Krypton assay in xenon at the ppq level using a gas chromatographic system and mass spectrometer
We have developed a new method to measure krypton traces in xenon at
unprecedented low concentrations. This is a mandatory task for many near-future
low-background particle physics detectors. Our system separates krypton from
xenon using cryogenic gas chromatography. The amount of krypton is then
quantified using a mass spectrometer. We demonstrate that the system has
achieved a detection limit of 8 ppq (parts per quadrillion) and present results
of distilled xenon with krypton concentrations below 1 ppt.Comment: 7 pages, 4 figure
Signals on Graphs: Uncertainty Principle and Sampling
In many applications, the observations can be represented as a signal defined
over the vertices of a graph. The analysis of such signals requires the
extension of standard signal processing tools. In this work, first, we provide
a class of graph signals that are maximally concentrated on the graph domain
and on its dual. Then, building on this framework, we derive an uncertainty
principle for graph signals and illustrate the conditions for the recovery of
band-limited signals from a subset of samples. We show an interesting link
between uncertainty principle and sampling and propose alternative signal
recovery algorithms, including a generalization to frame-based reconstruction
methods. After showing that the performance of signal recovery algorithms is
significantly affected by the location of samples, we suggest and compare a few
alternative sampling strategies. Finally, we provide the conditions for perfect
recovery of a useful signal corrupted by sparse noise, showing that this
problem is also intrinsically related to vertex-frequency localization
properties.Comment: This article is the revised version submitted to the IEEE
Transactions on Signal Processing on May, 2016; first revision was submitted
on January, 2016; original manuscript was submitted on July, 2015. The work
includes 16 pages, 8 figure
- âŠ