ABSTRACT:Estimating the unbound fraction of drugs in brain has become essential for the evaluation and interpretation of the pharmacokinetics and pharmacodynamics of new central nervous system drug candidates. Dialysis-based methods are considered to be accurate for estimating the fraction unbound in brain; however, these techniques are hampered by a low throughput. In this study, we present a novel, matrix-free, high-throughput method for estimating the unbound fraction, based on a sample pooling approach combining the TRANSIL brain absorption assay with liquid chromatography-mass spectrometry. The base measurement of the TRANSIL approach is the affinity to brain membranes, and this method is used directly to predict the free fraction in brain.
Within
this work, 12 different pharmaceutical compounds were analyzed
by the single-frequency ultrasound measurement technique for its applicability
to determine concentrations, as an important process parameter during
crystallization processes, or to determine the metastable zone widths,
as an important precondition for the development of crystallization
processes. The results were compared to the applicability of inorganic
and nonpharmaceutical compounds that have been discussed in the literature.
It was found that according to the change of ultrasound velocity and
adiabatic compressibility, a grouping of compounds can be derived.
From this grouping it can be concluded that some organic compounds
and especially inorganic compounds show an excellent applicability
for concentration determination, while the application for pharmaceutical
compounds is most often limited. Furthermore, a cost- and time-efficient
possibility is shown for the integration of this technique in a pilot-plant-scale
setup. A direct transferability of calibration models developed at
the laboratory scale was found as long as the influence of undissolved
air/gas was low in the pilot-plant setup.
In this study it was demonstrated that the usage of an
access unit connected to a pump-around loop cycle is a good solution
for the integration of various online analytical measurement techniques
in pilot-plant or industrial-scale reactors without time and cost
intensive modifications of the existing setup. As a model system the
crystallization as well as the polymorphic transition of α-
and β-l-glutamic acid (LGA) was investigated in real-time
by Raman-, NIR-, and UV–vis spectroscopy. All three techniques
have been shown to be powerful tools for the process optimization
of crystallizations. While all three techniques can be used for the
detection of the dissolution point and the crystallization end point,
Raman-spectroscopy has the advantage of being able to provide quantitative
information on the actual polymorph solid fraction in the solid product.
In this work special interest was put into the possibility to transfer
quantitative spectroscopic models, which were established on laboratory
scale, to pilot-plant scale. Furthermore, it was successfully shown
that it is possible to use spectroscopic models, which originated
from the calibration of solid mixtures of the polymorphs by off-line
Raman spectroscopy, for the evaluation of Raman spectra recorded in
suspensions during the crystallization processes. In case of the quantification
of α- and β polymorph content in LGA samples peak integration
(PI) as well as partial-least-squares (PLS) models were established
for solid binary mixtures using the software PEAXACT (S-PACT GmbH).
It was possible to transfer the PI model (valid for solid mixtures)
also for evaluation of the spectra of suspensions. Consequently, the
model can be applied not only in a lab scale but also for pilot plant
or industrial scales.
An advanced particle analyzing system (APAS) was applied to track information on size, shape, and number of particles in suspension. The measurement principle is based on laser reflection. In comparison to conventional laser reflection methods like focused beam reflectance measurement which determines chord/arc lengths, APAS sensors allow to measure exposed particle surface areas (EPSA). Furthermore, APAS is capable to collect information on the particle shape by evaluation of the reflection raw signals. The technique was tested for two different application fields to monitor crystallization and fermentation processes in case studies with L-glutamic acid as well as with cancer cells and Escherichia coli bacteria. It could be demonstrated that improvements in design and technology, coupled with the use of new software, permit to track changes of particle shape, size, and density as well as to analyze features such as cell vitality by the obscuration factor, cell proliferation, and growth effects by the distance of particles. The case studies proved that the innovations of the APAS, i.e., EPSA and particle shape, offer specific enhancement, enabling users to understand, monitor, and optimize products and processes more effectively.
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