Investigation of drug distribution in tablets using surface enhanced Raman chemical imaging

This paper reports the first application of surface enhanced Raman chemical imaging on pharmaceutical tablets containing the active ingredient (API) in very low concentrations.Taking advantage of the extremely intensive Raman signals in the presence of silver colloids,image aquisition time was radically decreased. Moreover, the investigation of drug distribution below the detection limit of regular micro-Raman spectrometry was made feasible. The characteristics of different manufacturing technologies could be revealed at very low API concentrations by using chemometric methods for processing and evaluating the large number of varying spectra provided with this imaging method

DETERMINATION OF 2-CYANO-4'-BROMOMETHYL BIPHENYL GENOTOXIC IMPURITY IN IRBESARTAN DRUG SUBSTANCES USING HPLC TECHNIQUE

Objective: The objective of present study was to develop and validate a specific and sensitive HPLC method for the quantitative determination of genotoxic impurity 2-cyano-4'-bromomethyl biphenyl present in irbesartan drug substance.Methods: The development activity was conducted by HPLC with UV as a detector. The impurity was separated on Kromasil C18 250 x 4.6 mm, 5 µm analytical column with a mobile phase consisting of buffer pH 3.2 and acetonitrile in the ratio of 60:40 v/v at a flow rate 1.5 ml/min. The effluent was monitored by UV detection at 258 nm with column temperature maintained at 40 °C and the injection volume 30 μl. Acetonitrile was selected as diluent.Results: Validation activity was planned and completed based on the ICH guideline. The LOD and LOQ value were found to be 0.167 µg/g and 0.506 µg/g and accuracy results were well in the range 98.34 to 103.46 %. The linearity curve showed the correlation coefficient of 0.9999 and method very sensitive.Conclusion: From validation data, it was confirmed that the developed method is specific, sensitive, linear, precise and accurate for the determination of 2-cyano-4'-bromomethyl biphenyl genotoxic impurity in irbesartan drug substances

Use of high-throughput tools to optimise polishing-chromatography sequences for complex feed mixtures

Polishing chromatography is a critical element of a bioprocess, because it is currently the only scalable separation technique that can remove process-related impurities, thereby achieving the high purity required of a biotherapeutic. Optimising the polishing chromatography of complex feeds has not been systematically addressed in the literature. This thesis identified a novel, academically affordable ternary protein mixture and systematically developed an optimal two-column polishing train for it. The ternary protein feed mixture was selected using many criteria, but had no special feature to aid identification, such as a chromophore, making it more difficult to characterise. The resulting analytical chromatogram could not be fully resolved, which is typical of industrially relevant products, such as glycoproteins. The selected HPLC column produced fast separations, resulting in a comparatively rapid quantification of preparative chromatograms. Many chromatographic resins and operating conditions were screened, resulting in the non-obvious sequence a hydrophobic interaction (HIC) followed by an anion-exchange (AX) adsorbent. Systematic experimental studies optimised the sequence with respect to yield, purity and amount recovered. Although the loading exceeded the binding capacity of the HIC column, runs at extremely high loadings (60 — 150 g/L) gave very efficient separation in an unusual combination of flow-through and bind-and-elute modes. It was found to achieve >200 mg of acceptably pure product from a single run. A variety of problems were encountered during the development of this polishing train, to which solutions were developed. While these problems are not uncommon, the literature does not contain systematic solutions to them. Examples include decisions about sequence design, protein solubility issues, and the detailed characterisation of samples from preparative runs (not achieved by analytical HPLC). In particular, a system-specific deconvolution methodology was developed that allowed complete characterisation of the mixture; the approach is likely to be widely applicable to industrially relevant biological feed mixtures

AMDORAP: Non-targeted metabolic profiling based on high-resolution LC-MS

<p>Abstract</p> <p>Background</p> <p>Liquid chromatography-mass spectrometry (LC-MS) utilizing the high-resolution power of an orbitrap is an important analytical technique for both metabolomics and proteomics. Most important feature of the orbitrap is excellent mass accuracy. Thus, it is necessary to convert raw data to accurate and reliable <it>m/z </it>values for metabolic fingerprinting by high-resolution LC-MS.</p> <p>Results</p> <p>In the present study, we developed a novel, easy-to-use and straightforward <it>m/z </it>detection method, AMDORAP. For assessing the performance, we used real biological samples, <it>Bacillus subtilis </it>strains 168 and MGB874, in the positive mode by LC-orbitrap. For 14 identified compounds by measuring the authentic compounds, we compared obtained <it>m/z </it>values with other LC-MS processing tools. The errors by AMDORAP were distributed within ±3 ppm and showed the best performance in <it>m/z </it>value accuracy.</p> <p>Conclusions</p> <p>Our method can detect <it>m/z </it>values of biological samples much more accurately than other LC-MS analysis tools. AMDORAP allows us to address the relationships between biological effects and cellular metabolites based on accurate <it>m/z </it>values. Obtaining the accurate <it>m/z </it>values from raw data should be indispensable as a starting point for comparative LC-orbitrap analysis. AMDORAP is freely available under an open-source license at <url>http://amdorap.sourceforge.net/</url>.</p

Automated mass spectrometry-based metabolomics data processing by blind source separation methods

Una de les principals limitacions de la metabolòmica és la transformació de dades crues en informació biològica. A més, la metabolòmica basada en espectrometria de masses genera grans quantitats de dades complexes caracteritzades per la co-elució de compostos i artefactes experimentals. L'objectiu d'aquesta tesi és desenvolupar estratègies automatitzades basades en deconvolució cega del senyal per millorar les capacitats dels mètodes existents que tracten les limitacions de les diferents passes del processament de dades en metabolòmica. L'objectiu d'aquesta tesi és també desenvolupar eines capaces d'executar el flux de treball del processament de dades en metabolòmica, que inclou el preprocessament de dades, deconvolució espectral, alineament i identificació. Com a resultat, tres nous mètodes automàtics per deconvolució espectral basats en deconvolució cega del senyal van ser desenvolupats. Aquests mètodes van ser inclosos en dues eines computacionals que permeten convertir automàticament dades crues en informació biològica interpretable i per tant, permeten resoldre hipòtesis biològiques i adquirir nous coneixements biològics.Una de les principals limitacions de la metabolòmica és la transformació de dades crues en informació biològica. A més, la metabolòmica basada en espectrometria de masses genera grans quantitats de dades complexes caracteritzades per la co-elució de compostos i artefactes experimentals. L'objectiu d'aquesta tesi és desenvolupar estratègies automatitzades basades en deconvolució cega del senyal per millorar les capacitats dels mètodes existents que tracten les limitacions de les diferents passes del processament de dades en metabolòmica. L'objectiu d'aquesta tesi és també desenvolupar eines capaces d'executar el flux de treball del processament de dades en metabolòmica, que inclou el preprocessament de dades, deconvolució espectral, alineament i identificació. Com a resultat, tres nous mètodes automàtics per deconvolució espectral basats en deconvolució cega del senyal van ser desenvolupats. Aquests mètodes van ser inclosos en dues eines computacionals que permeten convertir automàticament dades crues en informació biològica interpretable i per tant, permeten resoldre hipòtesis biològiques i adquirir nous coneixements biològics.Una de las principales limitaciones de la metabolómica es la transformación de datos crudos en información biológica. Además, la metabolómica basada en espectrometría de masas genera grandes cantidades de datos complejos caracterizados por la co-elución de compuestos y artefactos experimentales. El objetivo de esta tesis es desarrollar estrategias automatizadas basadas en deconvolución ciega de la señal para mejorar las capacidades de los métodos existentes que tratan las limitaciones de los diferentes pasos del procesamiento de datos en metabolómica. El objetivo de esta tesis es también desarrollar herramientas capaces de ejecutar el flujo de trabajo del procesamiento de datos en metabolómica, que incluye el preprocessamiento de datos, deconvolución espectral, alineamiento e identificación. Como resultado, tres nuevos métodos automáticos para deconvolución espectral basados en deconvolución ciega de la señal fueron desarrollados. Estos métodos fueron incluidos en dos herramientas computacionales que permiten convertir automáticamente datos crudos en información biológica interpretable y por lo tanto, permiten resolver hipótesis biológicas y adquirir nuevos conocimientos biológicos.One of the major bottlenecks in metabolomics is to convert raw data samples into biological interpretable information. Moreover, mass spectrometry-based metabolomics generates large and complex datasets characterized by co-eluting compounds and with experimental artifacts. This thesis main objective is to develop automated strategies based on blind source separation to improve the capabilities of the current methods that tackle the different metabolomics data processing workflow steps limitations. Also, the objective of this thesis is to develop tools capable of performing the entire metabolomics workflow for GC--MS, including pre-processing, spectral deconvolution, alignment and identification. As a result, three new automated methods for spectral deconvolution based on blind source separation were developed. These methods were embedded into two computation tools able to automatedly convert raw data into biological interpretable information and thus, allow resolving biological answers and discovering new biological insights

Optimized expression of the Starmerella bombicola lactone esterase in Pichia pastoris through temperature adaptation, codon-optimization and co-expression with HAC1

The Starmerella bombicola lactone esterase (SBLE) is a novel enzyme that, in vivo, catalyzes the intramolecular esterification (lactonization) of acidic sophorolipids in an aqueous environment. In fact, this is an unusual reaction given the unfavorable conditions for dehydration. This characteristic strongly contributes to the potential of SBLE to become a 'green' tool in industrial applications. Indeed, lactonization occurs normally in organic solvents, an application for which microbial lipases are increasingly used as biocatalysts. Previously, we described the production of recombinant SBLE (rSBLE) in Pichia pastoris (syn. Komagataella phaffii). However, expression was not optimal to delve deeper into the enzyme's potential for industrial application. In the current study, we explored codon-optimization of the SBLE gene and we optimized the rSBLE expression protocol. Temperature reduction had the biggest impact followed by codon-optimization and co-expression of the HAC1 transcription factor. Combining these approaches, we achieved a 32-fold improvement of the yield during rSBLE production (from 0.75 mg/l to 24 mg/L culture) accompanied with a strong reduction of contaminants after affinity purification

Downstream processing development of enveloped viruses for clinical applications: innovative tools for rational process optimization

Dissertation presented to obtain a Ph.D. degree in Engineering and Technology Sciences, Biotechnology at the Instituto de Tecnologia Química e Biológica, Universidade Nova de LisboaViral vectors and virus-like particles hold a tremendous potential in various clinical applications in the areas of gene therapy and/or vaccination, drawing the attention of biotechnology and pharmaceutical companies. The majority of these products are manufactured in animal cell cultures, inherently making the process costly. A great deal of effort is taking place to generate optimized biological and engineering strategies to find scalable and cost-effective processes, easily transferable to cGMP facilities. However, the implementation of robust downstream processes generating this type of biopharmaceuticals in the amounts required for pre-clinical and clinical trials is still lacking and lagging. By including a labile lipid membrane layer harboring glycoproteins (often critical for infection) over the viral capsid, enveloped viruses bring extra challenges in terms of their bioprocessing particularly downstream. The work developed during this thesis aimed at improving the state-of-the-art purification processes for these types of viral particles. The rationale was to integrate process understanding with product characterization, still scarce in such biological systems.(...

Generating Peptide Mass Spectrometry Ground Truth Data

Very few quantitative evaluations exist for precursor mass spectrometry data due to the lack of tools for enabling the manual feature finding necessary to generate this data. Other lacks the ability to capture, edit, save, and view precursor mass spectrometry data. We present JS-MS 2.0, a software suite that provides a dependency-free, browser-based, one click, cross-platform solution for creating precursor ground truth. The software retains the first version’s capacity for loading, viewing, and navigating MS1 data in 2- and 3-D, and adds tools for capturing, editing, saving and viewing isotopic envelope and extracted isotopic chromatogram features. The software can also be used to view and explore the results of feature finding algorithms. JS-MS 2.0 enables faster creation and inspection of precursor mass spectrometry ground truth data. It is publicly available with a GPL 2.0 license at github.com/optimusmoose/jsms