La séquence d’IRM de perfusion pondérée T1 après injection de Gadolinium (Gd), appelée dynamic contrast enhanced magnetic resonance imaging (DCE-MRI) fait partie du protocole d’IRM multiparamétrique (IRM-mp) réalisée pour le bilan d’extension du cancer prostatique (CaP). Le rationnel pour l’utilisation de cette séquence est d’une part le rôle capital de la néoangiogénèse dans le développement et la dissémination du CaP et d’autre part la possibilité d’imager l’angiogénèse in vivo et de façon non invasive. L’analyse quantitative nécessite un post-traitement multi-étapes complexe, dont le principe repose sur la modélisation pharmacocinétique (PC) de la biodistrubtion du Gd. Elle permet de calculer des paramètres PC reflétant la perméabilité capillaire et/ou la perfusion. Dans le CaP, ces paramètres PC ont montré leur potentiel pour évaluer l’agressivité tumorale, le pronostic, l’efficacité d’un traitement et/ou pour déterminer la dose efficace d’une nouvelle molécule anti-angiogéniques ou antivasculaires en cours de développement. Néanmoins, ils manquent de reproductibilité, notamment du fait des différentes techniques de quantifications utilisées par les logiciels de post-traitement.Nous avons développé au sein du laboratoire un outil de quantification capable de calculer une cartographie T1(0) à partir de la méthode des angles de bascule variables, nécessaire pour convertir les courbes du signal en courbe de concentration du Gd (Ct); de déterminer la fonction d’entrée artérielle (AIF – arterial input function) dans l’artère fémorale (Indivuduelle – Ind) ou lorsque cela n’était pas possible, d’utiliser une AIF issue de la littérature, telle que celle de Weinmann (W) ou de Fritz-Hansen (FH) ; et d’utiliser deux modèles PC, celui de Tofts et celui de Tofts modifié. Le logiciel a été validé sur des données simulées et sur une petite série clinique.Nous avons ensuite étudié l’impact du choix de la fonction d’entrée artériel sur les paramètres PC et notamment sur leur capacité à distinguer le CaP du tissu sain. 38 patients avec un CaP (>0,5cc) de la zone périphérique (ZP) ont été rétrospectivement inclus. Chaque patient avait bénéficié d’une IRM-mp sur laquelle deux régions d’intérêt (RI) : une tumorale et une bénigne ont été sélectionnées en utilisant une corrélation avec des cartes histo-morphométriques obtenues après prostatectomie radicale. En utilisant trois logiciels d’analyse quantitative différents, les valeurs moyennes de Ktrans (constante de transfert), ve (fraction du volume interstitiel) and vp (fraction du volume plasmatique) dans les RI ont été calculées avec trois AIF différentes (AIF Ind, AIF de W et AIF de FH). Ktrans était le paramètre PC qui permettait de mieux distinguer le CaP du tissu sain et ses valeurs étaient significativement supérieures dans le CaP, quelque soit l’AIF ou le logiciel. L’AIF de W donnait des aires sous les courbes ROC (Receiver Operating Characteristic) significativement plus grandes que l’AIF de FH (0.002≤p≤0.045) et plus grandes ou égales à l’AIF Ind (0.014≤p≤0.9). L’AIF Ind et de FH avaient des aires sous les courbes ROC comparables (0.34≤p≤0.81). Nous avons donc montré que les valeurs de Ktrans et sa capacité à distinguer CaP du tissu sain variaient significativement avec le choix de l’AIF et que les meilleures performances étaient obtenues avec l’AIF de W. / Dynamic contrast enhanced (DCE)-MRI is a T1 weighted sequence performed before, during and after a bolus injection of a contrast agent (CA). It is included in the multi-parametric prostate MRI (mp-MRI) protocol using to assess the extent of prostate cancer (PCa). The rationale for using DCE-MRI in PCa is that on one hand angiogenesis has been shown to play a central role in the PCa development and metastasis and on the other hand that DCE-MRI is a non invasive method able to depict this angiogenesis in vivo. The quantitative analysis of DCE-MRI data is a complex and multi-step process. The principle is to use a pharmacokinetic (PK) model reflecting the theoretical distribution of the CA in a tissue to extract PK parameters that describe the perfusion and capillary permeability. These parameters are of growing interest, especially in the field of oncology, for their use in assessing the aggressiveness, the prognosis and the efficacy of anti-angiogenic or anti-vascular treatments. The potential utility of these parameters is significant; however, the parameters often lack reproducibility, particularly between different quantitative analysis software programs.Firstly, we developed a quantitative analysis software solution using the variable flip angle method to estimate the T1 mapping which is needed to convert the signal-time curves to CA concentration-time curves; using three different arterial input functions (AIF): an individual AIF (Ind) measured manually in a large artery, and two literature population average AIFs of Weinmann (W) and of Fritz-Hansen (FH); and using two PK models (Tofts and modified Tofts). The robustness of the software programs was assessed on synthetic DCE-MRI data set and on a clinical DCE-MRI data set. Secondly, we assessed the impact of the AIF selection on the PK parameters to distinguish PCa from benign tissue. 38 patients with clinically important peripheral PCa (≥0.5cc) were retrospectively included. These patients underwent 1.5T multiparametric prostate MR with PCa and benign regions of interest (ROI) selected using a visual registration with morphometric reconstruction obtained from radical prostatectomy. Using three pharmacokinetic (PK) analysis software programs, the mean Ktrans, ve and vp of ROIs were computed using three AIFs: Ind-AIF, W-AIF and FH-AIF. The Ktrans provided higher area under the receiver operating characteristic curves (AUROCC) than ve and vp. The Ktrans was significantly higher in the PCa ROIs than in the benign ROIs. AUROCCs obtained with W-AIF were significantly higher than FH-AIF (0.002≤p≤0.045) and similar to or higher than Ind-AIF (0.014≤p≤0.9). Ind-AIF and FH-AIF provided similar AUROCC (0.34≤p≤0.81).We have then demonstrated that the selection of AIF can modify the capacity of the PK parameter Ktrans to distinguish PCa from benign tissue and that W-AIF yielded a similar or higher performance than Ind-AIF and a higher performance than FH-AIF.

Resistance against anti-malarial drugs remains one of the greatest obstacles to the effective control of malaria. The current first-line treatment regimen for uncomplicated P.falciparum malaria is based on artemisinin combination therapies (ACTs). However, reports of an increase in tolerance of the malaria parasite to artemisinins used in ACTs have alarmed the malaria community. The spread of artemisinin-resistant parasites would impact negatively on malaria control. Chloroquine and amodiaquine are 4-aminoquinolines. Chloroquine and amodiaquine were evaluated in a primate model by comparing the bioavailability of these compounds in a reference formulation and also in a Pheroid® formulation. In vivo pharmacokinetic studies were conducted for chloroquine, and in vitro and in vivo drug metabolism and pharmacokinetic (DMPK) studies were conducted for amodiaquine. Pheroid® technology forms the basis of a colloidal drug delivery system, and it is the potential application of this technology in combination with the 4-aminoquinolines that was the focus of this thesis. Pheroid® is a registered trademark but for ease of reading will be referred to as pheroid(s) or pro-pheroid(s) throughout the rest of the thesis. The non-human primate model used for evaluation of the pharmacokinetic parameters was the vervet monkey (Chlorocebus aethiops). Chloroquine was administered orally at 20 mg/kg. A sensitive and selective LC-MS/MS method was developed to analyze the concentration of chloroquine in both whole blood and plasma samples. The Cmax obtained for whole blood was 1039 ± 251.04 ng/mL for the unformulated reference sample of chloroquine and 1753.6 ± 382.8 ng/mL for the pheroid formulation. The AUC0-inf was 37365 ± 6383 ng.h/mL (reference) and 52047 ± 11210 ng.h/mL (pheroid). The results indicate that the use of pheroid technology enhances the absorption of chloroquine. The effect of pheroid technology on the bioavailability of amodiaquine and N-desethylamodiaquine was determined in two groups of vervet monkeys, with the reference group receiving capsules containing the hydrochloride salt of amodiaquine and the test group receiving capsules containing a pro-pheroid formulation of amodiaquine. Amodiaquine was administered at 60 mg/kg. Blood concentrations of amodiaquine and N-desethylamodiaquine samples were monitored over 13 time points from 0.5 to 168 hours. Amodiaquine and pro-pheroid formulated amodiaquine were incubated in vitro with human and monkey liver (HLM and MLM) and intestinal (HIM and MIM) microsomes and recombinant cytochrome P450 enzymes. The in vitro metabolism studies confirm the rapid metabolism of amodiaquine to the main metabolite N-desethylamodiaquine in monkeys. Although the pharmacokinetic parameters varied greatly, parameters for both the parent compound and main metabolite were lower in the test formulation compared to the reference formulation. For HLM, MLM and CYP2C8, the pro-pheroid test formulation showed significantly longer amodiaquine clearance and slower formation of N-desethylamodiaquine. However, the effect was reversed in MIM. Pheroid technology impacts differently on the bioavailability of the various pharmaceutical classes of anti-malarials. Pheroid technology did not enhance the bioavailability of amodiaquine or N-desethylamodiaquine. This is contrary to the observed effects of pheroid technology on the pharmacokinetics of other drugs such as artemisone and chloroquine where it increases the area under the curve and prolongs the drug half-life. / Thesis (PhD (Pharmaceutics))--North-West University, Potchefstroom Campus, 2013.

Resistance against anti-malarial drugs remains one of the greatest obstacles to the effective control of malaria. The current first-line treatment regimen for uncomplicated P.falciparum malaria is based on artemisinin combination therapies (ACTs). However, reports of an increase in tolerance of the malaria parasite to artemisinins used in ACTs have alarmed the malaria community. The spread of artemisinin-resistant parasites would impact negatively on malaria control. Chloroquine and amodiaquine are 4-aminoquinolines. Chloroquine and amodiaquine were evaluated in a primate model by comparing the bioavailability of these compounds in a reference formulation and also in a Pheroid® formulation. In vivo pharmacokinetic studies were conducted for chloroquine, and in vitro and in vivo drug metabolism and pharmacokinetic (DMPK) studies were conducted for amodiaquine. Pheroid® technology forms the basis of a colloidal drug delivery system, and it is the potential application of this technology in combination with the 4-aminoquinolines that was the focus of this thesis. Pheroid® is a registered trademark but for ease of reading will be referred to as pheroid(s) or pro-pheroid(s) throughout the rest of the thesis. The non-human primate model used for evaluation of the pharmacokinetic parameters was the vervet monkey (Chlorocebus aethiops). Chloroquine was administered orally at 20 mg/kg. A sensitive and selective LC-MS/MS method was developed to analyze the concentration of chloroquine in both whole blood and plasma samples. The Cmax obtained for whole blood was 1039 ± 251.04 ng/mL for the unformulated reference sample of chloroquine and 1753.6 ± 382.8 ng/mL for the pheroid formulation. The AUC0-inf was 37365 ± 6383 ng.h/mL (reference) and 52047 ± 11210 ng.h/mL (pheroid). The results indicate that the use of pheroid technology enhances the absorption of chloroquine. The effect of pheroid technology on the bioavailability of amodiaquine and N-desethylamodiaquine was determined in two groups of vervet monkeys, with the reference group receiving capsules containing the hydrochloride salt of amodiaquine and the test group receiving capsules containing a pro-pheroid formulation of amodiaquine. Amodiaquine was administered at 60 mg/kg. Blood concentrations of amodiaquine and N-desethylamodiaquine samples were monitored over 13 time points from 0.5 to 168 hours. Amodiaquine and pro-pheroid formulated amodiaquine were incubated in vitro with human and monkey liver (HLM and MLM) and intestinal (HIM and MIM) microsomes and recombinant cytochrome P450 enzymes. The in vitro metabolism studies confirm the rapid metabolism of amodiaquine to the main metabolite N-desethylamodiaquine in monkeys. Although the pharmacokinetic parameters varied greatly, parameters for both the parent compound and main metabolite were lower in the test formulation compared to the reference formulation. For HLM, MLM and CYP2C8, the pro-pheroid test formulation showed significantly longer amodiaquine clearance and slower formation of N-desethylamodiaquine. However, the effect was reversed in MIM. Pheroid technology impacts differently on the bioavailability of the various pharmaceutical classes of anti-malarials. Pheroid technology did not enhance the bioavailability of amodiaquine or N-desethylamodiaquine. This is contrary to the observed effects of pheroid technology on the pharmacokinetics of other drugs such as artemisone and chloroquine where it increases the area under the curve and prolongs the drug half-life. / Thesis (PhD (Pharmaceutics))--North-West University, Potchefstroom Campus, 2013.