This thesis is based on five papers addressing variance reduction in different ways. The papers have in common that they all present new numerical methods. Paper I investigates quantitative structure-retention relationships from an image processing perspective, using an artificial neural network to preprocess three-dimensional structural descriptions of the studied steroid molecules. Paper II presents a new method for computing free energies. Free energy is the quantity that determines chemical equilibria and partition coefficients. The proposed method may be used for estimating, e.g., chromatographic retention without performing experiments. Two papers (III and IV) deal with correcting deviations from bilinearity by so-called peak alignment. Bilinearity is a theoretical assumption about the distribution of instrumental data that is often violated by measured data. Deviations from bilinearity lead to increased variance, both in the data and in inferences from the data, unless invariance to the deviations is built into the model, e.g., by the use of the method proposed in paper III and extended in paper IV. Paper V addresses a generic problem in classification; namely, how to measure the goodness of different data representations, so that the best classifier may be constructed. Variance reduction is one of the pillars on which analytical chemistry rests. This thesis considers two aspects on variance reduction: before and after experiments are performed. Before experimenting, theoretical predictions of experimental outcomes may be used to direct which experiments to perform, and how to perform them (papers I and II). After experiments are performed, the variance of inferences from the measured data are affected by the method of data analysis (papers III-V).

Amyotrophic lateral sclerosis (ALS), also known as Charcot’s disease, motor neuron disease (MND) and Lou Gehrig’s disease, is a deadly, adult-onset neurodegenerative disorder characterized by progressive loss of upper and lower motor neurons, resulting in evolving paresis of the linked muscles. ALS is defined by classical features of the disease, but may present as a wide spectrum of phenotypes. About 10% of all ALS cases have been reported as familial, of which about 20% have been associated with mutations in the gene encoding for CuZn superoxide dismutase (SOD1). The remaining cases are regarded as sporadic. Research has advanced our understanding of the disease, but the cause is still unknown, no reliable diagnostic test exists, no cure has been found and the current therapies are unsatisfactory. Riluzole (Rilutek®) is the only registered drug for the treatment of ALS. The drug has shown only a modest effect in prolonging life and the mechanism of action of riluzole is not yet fully understood. ALS is diagnosed by excluding diseases with similar symptoms. At an early stage, there are numerous possible diseases that may present with similar symptoms, thereby making the diagnostic procedure cumbersome, extensive and time consuming with a significant risk of misdiagnosis. Biomarkers that can be developed into diagnostic test of ALS are therefore needed. The high number of unsuccessful attempts at finding a single diseasespecific marker, in combination with the complexity of the disease, indicates that a pattern of several markers is perhaps more likely to provide a diagnostic signature for ALS. Metabolomics, in combination with chemometrics, can be a useful tool with which to study human disease. Metabolomics can screen for small molecules in biofluids such as cerebrospinal fluid (CSF) and chemometrics can provide structure and tools in order to handle the types of data generated from metabolomics. In this thesis, ALS has been studied using a combination of metabolomics and chemometrics. Collection and storage of CSF in relation to metabolite stability have been extensively evaluated. Protocols for metabolomics on CSF samples have been proposed, used and evaluated. In addition, a new feature of data processing allowing new samples to be predicted into existing models has been tested, evaluated and used for metabolomics on blood and CSF. A panel of potential biomarkers has been generated for ALS and subtypes of ALS. An overall decrease in metabolite concentration was found for subjects with ALS compared to their matched controls. Glutamic acid was one of the metabolites found to be decreased in patients with ALS. A larger metabolic heterogeneity was detected among SALS cases compared to FALS. This was also reflected in models of SALS and FALS against their respective matched controls, where no significant difference from control was found for SALS while the FALS samples significantly differed from their matched controls. Significant deviating metabolic patterns were also found between ALS subjects carrying different mutations in the gene encoding SOD1.

The general aim of this thesis was to evaluate a newly designed and constructed miniaturized rotating disk apparatus for in vitro dissolution rate measurements of different drug substances from all of the classes in the Biopharmaceutical Classification System (BCS). The new equipment is based on a low volume flow-through cell of Plexiglas, a gold plated magnetic bar and a special designed press. The disk of drug substance (approx. 5 mg) is placed eccentrically in the bar. Rotation speeds were set with a graded magnetic stirrer. An external HPLC pump delivered a continuous flow of aqueous medium to the flow-through cell during dissolution testing. A reversed phase high-performance liquid chromatography system using diode array detection (RP-HPLC-DAD) was coupled online to the new equipment. The injections from the miniaturized rotating disk outlet into the quantifying HPLC system were controlled by a six-position switching valve. The injection volumes from the valve and the autosampler, used for the external standards, were statistically evaluated to match each other volumetrically. No analyses were longer than three minutes, using isocratic mode. A traditional USP rotating disk apparatus was used as a reference system and the two instruments were shown to be statistically dissimilar in the numerical dissolution rate values probably due to different hydrodynamics, but had approximately the same precision/repeatability. When correlating the logarithmic values of the in vitro dissolution rate (G) with the apparent solubility (S), using shake-flask methodology in the solubility studies, the two apparatuses gave the same correlation patterns. Further correlation studies were done where the media components were altered by the use of different buffer species or additives into the buffers, such as inorganic salts. Chemometric tools, e.g. orthogonal partial least squares (OPLS), were used to better evaluate the most influential factors for G and S in different media. The most significant factor for a model basic drug substance (terfenadine) was pH, followed by the ionic strength (I) and added sodium chloride in one of the media. However, the surfactants in the Fasted State Simulated Intestinal Fluid (FaSSIF-V2) were found to be insignificant for G and S in this study (using a 95% confidence interval). The new miniaturized apparatus is a promising prototype for in vitro dissolution rate measurements both for early screening purposes and in dissolution testing during drug development, but needs further instrumental improvements.

No description available.

Η φασματοσκοπία Raman είναι τεχνική ανελαστικής σκέδασης φωτός, ικανή να ανιχνεύει και να χαρακτηρίζει μόρια σε ποικιλία υδατικών διαλυμάτων. Σκοπός της εργασίας είναι η ανάπτυξη μιας μη επεμβατικής, μη καταστροφικής φασματοσκοπικής μεθόδου για την ανίχνευση και τον ποσοτικό προσδιορισμό τόσο φαρμακευτικών ουσιών (π.χ αντιβιοτικών) όσο και φυσιολογικών ουσιών (π.χ γλυκόζη) στο υδατοειδές υγρό οφθαλμού. Στο πλαίσιο της παρούσας εργασίας αναπτύχθηκε μια νέα γεωμετρική οπτική διάταξη για την καθοδήγηση της δέσμης του laser στον οφθαλμό, που προσαρμόζεται σε φασματοσκόπιο Raman με ανιχνευτή CCD, δίνει τη δυνατότητα επιλεκτικής συλλογής του σκεδαζόμενου φωτός, σαρώνοντας τον εμπρόσθιο θάλαμο, σε γεωμετρία σκέδασης 90 μοιρών. Τα πειράματα πραγματοποιήθηκαν (α) σε χοιρινούς οφθαλμούς in-vitro, max 24 ώρες μετά τη θανάτωση των ζώων και την αφαίρεση του βολβού, μετά την έγχυση στον εμπρόσθιο θάλαμο μορίων κεφταζιδίμης, αμφοτερισίνης Β και γλυκόζης και (β) σε μοντέλο πρόσθιου θαλάμου (AAC) σε συνδυασμό με κερατοειδή χιτώνα χοιρινών οφθαλμών μετά την έγχυση μορίων κεφταζιδίμης, αμφοτερισίνης, θειικής αμικασίνης και σιπροφλοξασίνης. Επιπλέον, χρησιμοποιήθηκε χημειομετρικός αλγόριθμος μερικών ελαχίστων τετραγώνων (PLS) για να προβλέψει τη συγκέντρωση των αντιβιοτικών στο μοντέλο του πρόσθιου θαλάμου. Με τον νεό αυτό σχεδιασμό αποφεύγεται η απευθείας έκθεση βασικών οφθαλμικών ιστών, όπως του φακού και του αμφιβληστροειδούς, στη δέσμη του laser, ενώ παράλληλα επιτυγχάνονται βέλτιστες συνθήκες συλλογής του σκεδαζόμενου φωτός βελτιώνοντας το λόγο σήματος/θορύβου των φασμάτων. Ανιχνεύτηκαν συγκεντρώσεις στην περιοχή της μέσης ανασταλτικής πυκνότητας για τα αντιβιοτικά τόσο στο υδατοειδές υγρό χοιρινών οφθαλμών όσο και στο μοντέλο του πρόσθιου θαλάμουֹ η γλυκόζη ανιχνεύτηκε σε συγκέντρωση κοντά στα παθολογικά επίπεδα των διαβητικών ασθενών. Με βάση και το σφάλμα RMS της ποσοτικής ανάλυσης PLS, προσδοκάται βάσιμα ότι η μέθοδος είναι δυνατό χρησιμοποιηθεί στον τομέα της οφθαλμολογίας για τη μελέτη της φαρμακοκινητικής καθώς και για την έγκαιρη διάγνωση ασθενειών (π.χ. σακχαρώδης διαβήτης). / Laser Raman spectroscopy is an inelastic light scattering technique able to characterize molecules in aqueous environments. The purpose of this work is to develop a non-contact and non-invasive spectroscopic method to identify and eventually quantify the presence of medicines (e.g. antibiotics) and physiological substances (e.g. glucose) in the aqueous humor of the eye. Α new laser light delivery probe has been developed and adapted to a Raman spectroscopic system with the ability of favorable collection of the Raman light at 90o scattering geometry while scanning the anterior chamber of the eye. The technique is applied both, to porcine eyes in-vitro, max. 24 hours after death and extraction, for ceftazidime, amphotericin B and glucose and to a commercially available artificial anterior chamber (AAC) fitted with corneas of porcine eyes for ceftazidime, amphotericin B, amikacin sulphate and ciprofloxacin. Finally, a PLS chemometric algorithm has been developed to predict the concentration of antibiotics in AAC. This special illumination design gives the opportunity of reducing the direct exposure of the basic cordial ocular tissues, like lens and retina, to the laser beam, while at the same time an optimum collection of scattered light is accomplished. Concentrations close to the minimum inhibitory concentration (MIC) have been detected for antibiotics both in porcine eyes and AAC; the detection of glucose has been realized at concentrations close to the early pathological levels of patients with diabetes. Furthermore, the quantification of concentration of antibiotics in AAC is accomplished by a partial least-squares (PLS) chemometric regression algorithm and the RMS error of the validation procedure further emphasize the promising prospect of the application of the Raman spectroscopy to the Ophthalmology.

New techniques and approaches for organic synthesis, purification and biological testing are enabling pharmaceutical industries to produce and test increasing numbers of compounds every year. Surprisingly, this has not led to more new drugs reaching the market, prompting two questions – why is there not a better correlation between their efforts and output, and can it be improved? One possible way to make the drug discovery process more efficient is to ensure, at an early stage, that the tested compounds are diverse, representative and of high quality. In addition the biological evaluation systems have to be relevant and reliable. The diversity of the tested compounds could be ensured and the reliability of the biological assays improved by using Design Of Experiments (DOE) more frequently and effectively. However, DOE currently offers insufficient options for these purposes, so there is a need for new, tailor-made DOE strategies. The aim of the work underlying this thesis was to develop and evaluate DOE approaches for diverse compound selection and efficient assay optimisation. This resulted in the publication of two new DOE strategies; D-optimal Onion Design (DOOD) and Rectangular Experimental Designs for Multi-Unit Platforms (RED-MUP), both of which are extensions to established experimental designs. D-Optimal Onion Design (DOOD) is an extension to D-optimal design. The set of possible objects that could be selected is divided into layers and D-optimal selection is applied to each layer. DOOD enables model-based, but not model-dependent, selections in discrete spaces to be made, since the selections are not only based on the D-optimality criterion, but are also biased by the experimenter’s prior knowledge and specific needs. Hence, DOOD selections provide controlled diversity. Assay development and optimisation can be a major bottleneck restricting the progress of a project. Although DOE is a recognised tool for optimising experimental systems, there has been widespread unwillingness to use it for assay optimisation, mostly because of the difficulties involved in performing experiments according to designs in 96-, 384- and 1536- well formats. The RED-MUP framework combines classical experimental designs orthogonally onto rectangular experimental platforms, which facilitates the execution of DOE on these platforms and hence provides an efficient tool for assay optimisation. In combination, these two strategies can help uncovering the crossroads between biology and chemistry in drug discovery as well as lead to higher information content in the data received from biological evaluations, providing essential information for well-grounded decisions as to the future of the project. These two strategies can also help researchers identify the best routes to take at the crossroads linking biological and chemical elements of drug discovery programs.

Human health is a complex and wide-ranging subject far beyond nutrition and physical exercise. Still, these factors have a huge impact on global health by their ability to prevent diseases and thus promote health. Thus, to identify health risks and benefits, it is necessary to reveal the underlying mechanisms of nutrition and exercise, which in many cases follows a complex chain of events. As a consequence, current health research is generating massive amounts of data from anthropometric parameters, genes, proteins, small molecules (metabolites) et cetera, with the intent to understand these mechanisms. For the study of health responses, especially related to physical exercise and nutrition, alterations in small molecules (metabolites) are in most cases immediate and located close to the phenotypic level and could therefore provide early signs of metabolic imbalances. Since there are roughly as many different responses to exercise and nutrients as there are humans, this quest is highly multifaceted and will benefit from an interpretation of treatment effects on a general as well as on an individual level. This thesis involves the application of chemometric methods to the study of global metabolic reactions, i.e. metabolomics, in a strategy coined predictive metabolomics. Via the application of predictive metabolomics an extensive hypothesis-free biological interpretation has been carried out of metabolite patterns in blood, acquired using gas chromatography-mass spectrometry (GC-MS), related to physical exercise, nutrition and diet, all in the context of human health. In addition, the chemometrics methodology have computational benefits concerning the extraction of relevant information from information-rich data as well as for interpreting general treatment effects and individual responses, as exemplified throughout this work. Health concerns all lifestages, thus this thesis presents a strategic framework in combination with comprehensive interpretations of metabolite patterns throughout life. This includes a broad range of human studies revealing metabolic patterns related to the impact of physical exercise, macronutrient modulation and different fitness status in young healthy males, short and long term dietary treatments in overweight post menopausal women as well as metabolic responses related to probiotics treatment and early development in infants. As a result, the studies included in the thesis have revealed metabolic patterns potentially indicative of an anti-catabolic response to macronutrients in the early recovery phase following exercise. Moreover, moderate differences in the metabolome associated with cardiorespiratory fitness level were detected, which could be linked to variation in the inflammatory and antioxidaive defense system. This work also highlighted mechanistic information that could be connected to dietary related weight loss in overweight and obese postmenopausal women in relation to short as well as long term dietary effects based on different macronutrient compositions. Finally, alterations were observed in metabolic profiles in relation to probiotics treatment in the second half of infancy, suggesting possible health benefits of probiotics supplementation at an early age. / Embargo until 2012-06-01

Thesis (MSc Food Sc)--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: The use of near infrared (NIR) hyperspectral imaging for distinguishing between pre-germinated and non pre-germinated barley, wheat and sorghum kernels and, the effect of kernel shape on hyperspectral images, have been investigated. Two sample sets were imaged. The first sample set was divided into six subsets; these subsets were treated with water and left to pre-germinate for different times (0, 6, 9, 12, 18 and 24 hrs). Subset viability was determined with the tetrazolium test. The second sample set was divided into seven subsets, treated with water and left to pre-germinate for 0, 3, 6, 9, 12, 18, 24 or 30 hrs. Individual kernel viability was determined with the tetrazolium test. NIR hyperspectral images were acquired using two different SisuCHEMA hyperspectral imaging systems. The first system acquired images with a 150 9m spatial resolution (first sample set) and the second system acquired images with a 30 9m spatial resolution (second sample set). Principal component analysis (PCA) was performed and a distinction between pre-germinated and non pre-germinated kernels was illustrated in PCA score images. Loading line plots showed that the main compounds contributing to spectral variation were starch, water and protein. These compounds were related to starch and protein hydrolysis. The distinction between pre-germinated and non pre-germinated kernels observed in the 30 9m spatial resolution images indicated NIR hyperspectral imaging was perhaps sensing incomplete endosperm degradation. Some kernels determined as pre-germinated by the tetrazolium test had the same chemical composition according to the score image as non pre-germinated kernels in the 30 9m spatial resolution images. A partial least squares discriminant analysis (PLS-DA) model with two classes (pre- germinated and non pre-germinated) was developed for each of the cultivars of the first sample set. The two classes were assigned in principal component (PC) 1 vs. PC 5 score plots. The model created for the barley cultivars resulted in excessive false positives and false negatives. The prediction results of wheat cultivars revealed that the model had a classification rate of 81% for the non pre-germinated class and 93% for the pre-germinated class. The sorghum prediction results revealed that the model correctly predicted 97% of the non pre-germinated class and 93% of the pre-germinated class. Two different PLS-DA models were developed for one image of each cultivar of the 30 9m spatial resolution images. The first model was developed by assigning each kernel in the score image and the second model was developed by assigning pixels in the score plot to either the pre- germinated or non pre-germinated class. Model 1 resulted in excessive false negatives. Model 2 resulted in excessive false positives. The differences between pre-germinated and non pre-germinated kernels were only observed in higher (PC 5 and 6) order PCs of the 150 9m spatial resolution images. The lower (PCs 1 to 4) order PCs (of each commodity) were subsequently examined with the aid of classification gradients. Kernel shape effects were observed in these PCs. The use of NIR hyperspectral imaging for distinguishing between pre-germinated and non pre-germinated grain kernels shows promise. / AFRIKAANSE OPSOMMING: Die gebruik van naby infrarooi (NIR) hiperspektrale beeld-analise is geëvalueer om onderskeid te tref tussen voor-ontkiemde en nie-voor-ontkiemde gars, koring en sorghum korrels. Die effek van korrelvorm op hiperspektrale beelde is ook geëvalueer. Die eerste stel graan-monsters is gebruik vir 150 9m ruimtelike resolusie beelde en die tweede stel is gebruik vir 30 9m ruimtelike resolusie beelde. Die eerste kultivar stel is verdeel in ses sub-stelle en met gedistilleerde water behandel vir 0, 6, 9, 12, 18 en 24 hr. Sub-stel lewensvatbaarheid is met die tetrazolium toets vasgestel. Elke kultivar in die tweede stel is in sewe sub-stelle verdeel en is vir 0, 3, 6, 9, 12, 18, 24 of 30 hr geïnkubeer. Individuele korrel lewensvatbaarheid is met die tetrazolium toets vasgestel. NIR hiperspektrale beelde is verkry deur gebruik te maak van twee verskillende SisuCHEMA kameras. Die verskillende kameras is gebruik om verskillende resolusie (30 en 150 9m ruimtelike resolusie) beelde te verkry. Hoofkomponent analise (HKA) is uitgevoer en ’n verskil tussen voor- ontkiemde en nie-voor-ontkiemde korrels is waargeneem in die 150 9m ruimtelike resolusie beelde. HK ladings stippe het water, stysel en proteïene uitgesonder as die verbindings wat bydrae het tot spektrale variasie. ’n Verskil tussen die voor-ontkiemde korrels en nie-voor-ontkiemde korrels is ook gesien vir die 30 9m ruimtelike resolusie beelde. Dit is egter ook waargeneem dat sommige korrels as voor-ontkiem bepaal is deur die tetrazolium toets, maar dié korrels het dieselfde chemiese samestelling volgens die punte beeld as nie-voor-ontkiemde korrels. Onvolledige endosperm hidrolise is ’n moontlike verduideliking vir die verskynsel. Die verbindings wat bygedra het tot die variasie is water, stysel en proteïene. ’n Parsiële kleinste kwadrate diskriminant analise (PKW-DA) model met twee klasse is ontwikkel vir elke kultivar van die 150 9m ruimtelike resolusie beelde. Die klasse is aangewys in the punte stip. Die model met die hoogste variasie in Y is gekies om die ander kultivars van dieselfde kommoditeit te voorspel. The PKW-DA resultate vir die gars kultivars het getoon dat die model vals positiewes en vals negatiewes opgelewer het. Die koring PKW-DA model het ’n klassifikasie koers van 81% vir die nie-voor-ontkiemde klasse en 93% vir die voor-ontkiemde klasse opgelewer. The PKW-DA resultate vir sorghum het getoon dat die model ’n klassifikasie koers van 97% vir die nie-voor-ontkiemde klasse en 93% vir die voor-ontkiemde klasse opgelewer. Twee verskillende PKW-DA modelle is ontwikkel vir elke beeld van elke kultivar van die 30 9m ruimtelike resolusie beelde. Die eerste model is ontwikkel deur elke korrel in die punte beeld aan te wys tot een van twee klasse en die tweede model is ontwikkel deur die beeldelemente in die punte stip tot een van twee klasse toe te skryf. Model 1 het vals negatiewes opgelewer en model 2 vals positiewes. Die verskille tussen die nie-voor-ontkiemde en voor-ontkiemde korrels is eers verduidelik in hoër orde HK van die 150 9m ruimtelike resolusie beelde. Die laer orde HK is dus ondersoek vir hul bydrae tot spektrale variasie met die hulp van klassifikasie gradiënte. Korrel vorm effekte is waargeneem. Die gebruik van NIR hiperspektrale beelding om onderskeid te tref tussen voor-ontkiemde en nie-voor-ontkiemde graan korrels, lyk belowend.

Thesis (MSc Food Sc)--University of Stellenbosch, 2011. / ENGLISH ABSTRACT: Near infrared hyperspectral imaging (NIR HSI) in conjunction with multivariate image analysis was evaluated for the detection of millet and buckwheat flour in ground black pepper. Additionally, midinfrared (MIR) spectroscopy was used for the quantification of millet and buckwheat flour in ground black pepper. These techniques were applied as they allow non-destructive, invasive and rapid analysis. Black pepper and adulterant (either millet or buckwheat flour) mixtures were made in 5% (w/w) increments spanning the range 0-100% (w/w). The mixtures were transferred to eppendorf tube holders and imaged with a sisuChema short wave infrared (SWIR) pushbroom imaging system across the spectral range of 1000–2498 nm. Principal component analysis (PCA) was applied to pseudo-absorbance images for the removal of unwanted data (e.g. background, shading effects and bad pixels). PCA was subsequently applied to the ‘cleaned’ data. An adulterant concentration related gradient was observed in principal component one (PC1) and a difference between black pepper adulterated with buckwheat and millet was noted in PC4. Four absorption peaks (1461, 2241, 2303 and 2347 nm) were identified in the loading line plot of PC1 that are associated with protein and oil. The loading line plot of PC4 revealed absorption peaks at 1955, 1999, 2136 and 2303 nm, that are related to protein and oil. Partial least squares discriminant analysis (PLS-DA) was applied to NIR HSI images for discrimination between black pepper adulterated with varying amounts of adulterant (millet or buckwheat). The model created with millet adulterated black pepper samples had a classification accuracy of 77%; a classification accuracy of 70% was obtained for the buckwheat adulterated black pepper samples. An average spectrum was calculated for each sample in the NIR HSI images and the resultant spectra were used for the quantification of adulterant (millet or buckwheat) in ground black pepper. All samples were also analysed using an attenuated total reflectance (ATR) Fourier transform (FT) – infrared (IR) instrument and MIR spectra were collected between 576 and 3999 cm-1. PLS regression was employed. NIR based predictions (r2 = 0.99, RMSEP = 3.02% (w/w), PLS factor = 4) were more accurate than MIR based predictions (r2 = 0.56, RMSEP = 19.94% (w/w), PLS factors = 7). Preprocessed NIR spectra revealed adulterant specific absorption bands (1743, 2112 and 2167 nm) whereas preprocessed MIR spectra revealed a buckwheat specific signal at 1574 cm-1. NIR HSI has great promise for both the qualitative and quantitative analysis of powdered food products. Our study signals the beginning of incorporating hyperspectral imaging in the analysis of powdered food substances and results can be improved with advances in instrumental development and better sample preparation. / AFRIKAANSE OPSOMMING: Die gebruik van naby infrarooi hiperspektrale beelding (NIR HB) tesame met veelvoudige beeldanalise is ondersoek vir die opsporing van stysel-verwante produkte (giers en bokwiet) in gemaalde swart pepper. Middel-infrarooi (MIR) spektroskopie is addisioneel gebruik vir die kwantifisering van hierdie stysel-verwante produkte in swart pepper. Albei hierdie tegnieke is toegepas aangesien dit deurdringend van aard is en dit bied nie-destruktiewe sowel as spoedige analise. Swart pepper en vervalsingsmiddel (giers of bokwiet) mengsels is uitgevoer in 5% (m/m) inkremente tussen 0 en 100% (m/m). Eppendorfbuishouers is met die mengsels gevul en hiperspektrale beelde is verkry deur die gebruik van ‘n sisuChema SWIR (kortgolf infrarooi) kamera met ‘n spektrale reikwydte van 1000–2498 nm. Hoofkomponent-analise (HK) is toegepas op pseudo-absorbansie beelde vir die verwydering van ongewenste data (bv. agtergrond, skadu en dooie piksels). Hoofkomponent-analise is vervolgens toegepas op die ‘skoon’ data. Hoofkomponent (HK) een (HK1) het die aanwesigheid van ‘n vervalsingsmiddel konsentrasie verwante gradient getoon terwyl HK4 ‘n verskil getoon het tussen swart pepper vervals met giers en bokwiet. Vier absorpsiepieke (1461, 2241, 2303 en 2347 nm) was geïdentifiseer binne die HK lading stip van HK1 wat met proteïen en olie geassosieer kon word. Die HK lading stip van HK4 het absorpsipieke by 1955, 1999, 2136 en 2303 nm aangedui wat verband hou met proteïen en olie. Parsiële kleinste waarde diskriminant-analise (PKW-DA) is toegepas op die hiperspektrale beelde vir die moontlike onderskeiding tussen swart pepper vervals met verskeie hoeveelhede vervalsingsmiddel (giers of bokwiet). ‘n Klassifikasie koers van 77% is verkry vir die model ontwikkel met giers vervalsde swart pepper terwyl die model ontwikkel met bokwiet vervalsde swarte pepper ‘n klassifikasie koers van 70% bereik het. ‘n Gemiddelde spektrum is bereken vir elke monster in die hiperspektrale beelde en die resulterende spektra is gebruik vir die kwantifisering van vervalsingsmiddels (giers of bokwiet) in gemaalde swart pepper. ‘n ATR FT-IR instrument met spektrale reikwydte van 576-3999 cm-1 is additioneel gebruik vir die analise van alle monsters. Parsiële kleinste waarde regressie is gebruik vir kwantifikasie doeleindes. NIR gebasseerde voorspellings (r2 = 0.99, RMSEP = 3.02% (m/m), PLS faktore = 4) was meer akkuraat as die MIR gebasseerde voorspellings (r2 = 0.56, RMSEP = 19.94% (m/m), PLS faktore = 7). Vooraf behandelde NIR spektra het vervalsingsmiddel verwante absorpsiepieke (1743, 2112 en 2167 nm) aangetoon terwyl vooraf behandelde MIR spektra ‘n bokwiet verwante absorpsiepiek by 1574 cm-1 aangedui het. NIR HB toon goeie potensiaal vir beide kwalitatiewe en kwantitatiewe analise van gepoeierde voedsel produkte. Ons studie kan gesien word as die begin van die inkorporasie van hiperspektrale beelding in die analise van gepoeierde voedsel material en verbeterde resulte kan verkry word deur die vordering in instrumentasie ontwikkeling en verbeterde monstervoorbereiding.

Les bioprocédés industriels mettant en œuvre la culture de cellules animales sont devenus incontournables pour la production d’anticorps monoclonaux (AcM). Cependant, l'état physiologique des cellules et la qualité des AcM produits, en particulier leur glycosylation, sont tributaires des variations intervenant au cours du procédé. Il en découle des risques d'altération de l'efficacité et de la sûreté des AcM. C'est pourquoi, depuis quelques années, l'initiative Process Analytical Technology (PAT) encourage le développement du suivi en ligne de ces procédés, avec l'objectif de mieux les maîtriser et d'assurer la qualité finale des produits. Dans ce contexte, cette thèse propose des approches innovantes pour le suivi en ligne de procédés de culture de cellules CHO (Chinese Hamster Ovary) en bioréacteur, basées sur l'utilisation de trois types de spectroscopies in situ (diélectrique, Raman, proche infrarouge(NIR)). Le premier chapitre présente une nouvelle démarche permettant de prédire en temps réel l'état physiologique des cellules, au travers de la vitesse spécifique de croissance cellulaire (μ). A partir de la mesure en ligne de la permittivité grâce à la spectroscopie diélectrique, la µ a été calculée en temps réel, permettant de détecter le moment critique correspondant au moment où μ diminue. Comparée à une démarche hors ligne, l'utilisation de cette méthode pour le pilotage de cultures en mode recharge-récolte, permet d’assurer à la fois la quantité et la qualité de glycosylation des AcM. Le second chapitre aborde l'utilisation des spectroscopies NIR et Raman in situ combinées à des méthodes chimiométriques. Les performances de ces deux spectroscopies ont été comparées en parallèle. Des modèles en ligne ont été développés pour prédire la concentration de différents paramètres (cellules viables, glucose, lactate, glutamine, ions ammonium, anticorps). L'évaluation de ces modèles par facteurs de mérite (FOM), a révélé certains avantages de la spectroscopie Raman. La combinaison de ces deux spectroscopies par diverses stratégies de fusion de données a été également évaluée. Dans le troisième chapitre, l'intérêt de la spectroscopie Raman a été démontré pour le suivi en ligne, non seulement, de la concentration, mais aussi, de la glycosylation des AcM. Des modèles ont été développés pour la prédiction en ligne, à la fois, de la macro-hétérogénéité (sites de glycosylation), et de la micro-hétérogénéité (structures glycanniques) de la glycosylation des AcM dans le cas de cultures en mode discontinu et recharge-récolte. Le dernier chapitre a utilisé les spectroscopies NIR et diélectrique, en les intégrant à un « capteur logiciel » combinant des équations de bilans de matière. Ce « capteur logiciel », mis en œuvre au cours d'une culture en mode semi-continu pour le contrôle automatique du débit d'alimentation, a conduit à une augmentation de la productivité du procédé ainsi qu'à une meilleure glycosylation des AcM produits / Bioprocesses of mammalian cell culture have become essential for the production of therapeutic recombinant proteins, such as monoclonal antibodies (mAb). However, the physiological state of the cells and the quality of the mAb produced, in particular their glycosylation, may vary during the process, and may lead to the alteration of the safety and efficacy of the final product. Consequently, the Process Analytical Technology (PAT) initiative has encouraged the development of online monitoring techniques, with the aim to better control the process and ensure the quality of the final product. In this context, this thesis proposes innovative approaches for online monitoring of CHO (Chinese Hamster Ovary) cells bioreactor cultures, by using three types of in situ spectroscopic measurements (dielectric, Raman, near infrared (NIR)). The first chapter presents a novel approach to predict in real-time one of the major cell physiological state parameters, the specific growth rate (µ). Based on online permittivity measured by in situ dielectric spectroscopy, the cell concentration was estimated and µ was calculated in real-time, making possible to detect the critical moment when µ begins to decrease significantly. Compared to an offline approach, this online approach allowed to maintain the cells in a stable physiological state, ensuring the glycosylation of the mAb produced in feed-harvest cultures. The second chapter shows the use of in situ NIR and Raman spectroscopies combined with chemometric methods. For the first time, the performances of these two spectroscopies were compared in parallel in the same cultures. Online models were developed to predict in real-time the concentration of different parameters (viable cells, glucose, lactate, glutamine, ammonium ions and antibodies). The evaluation of these models by the multivariate Figures of Merit (FOM) revealed some of the advantages of Raman spectroscopy. The combination of the two spectroscopies by various data fusion strategies has also been evaluated. In the third chapter, the interest of Raman spectroscopy for the online monitoring of both the quantity and the glycosylation of the mAb was demonstrated. Models were developed for online prediction of both macroheterogeneity (glycosylation site occupancy) and microheterogeneity (glycan structures) of mAb glycosylation in batch and feed-harvest cultures. The last chapter used models previously developed for NIR and dielectric spectroscopies, to integrate into a “soft sensor” by combining with cell metabolic and mass balance equations. This “soft sensor”, implemented in a fed-batch cell culture for the automatic control of the feed rate, leads to an increased mAb productivity and better mAb glycosylation