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Tuberculosis (TB) is the world’s most deadly infectious disease and causes enormous public health problems. The comorbidity with HIV and the rise of multidrug-resistant TB strains impede successful therapy through drug-drug interactions and the lack of efficient second-line treatments. The aim of this thesis was to support the improvement of anti-TB therapy through development of pharmacometric models, specifically focusing on the novel drug bedaquiline, pharmacokinetic interactions and methods for pooled population analyses. A population pharmacokinetic model of bedaquiline and its metabolite M2, linked to semi-mechanistic models of body weight and albumin concentrations, was developed and used for exposure-response analysis. Treatment response was quantified by measurements of mycobacterial load and early bedaquiline exposure was found to significantly impact the half-life of bacterial clearance. The analysis represents the first successful characterization of a concentration-effect relationship for bedaquiline. Single-dose Phase I studies investigating potential interactions between bedaquiline and efavirenz, nevirapine, ritonavir-boosted lopinavir, rifampicin and rifapentine were analyzed with a model-based approach. Substantial effects were detected in several cases and dose-adjustments mitigating the impact were suggested after simulations. The interaction effects of nevirapine and ritonavir-boosted lopinavir were also confirmed in patients with multidrug-resistant TB on long-term treatment combining the antiretrovirals and bedaquiline. Furthermore, the outcomes from model-based analysis were compared to results from conventional non-compartmental analysis in a simulation study. Non-compartmental analysis was found to consistently underpredict the interaction effect when most of the concentration-time profile was not observed, as commonly is the case for compounds with very long terminal half-life such as bedaquiline. To facilitate pooled analyses of individual patient data from multiple sources a structured development procedure was outlined and a fast diagnostic tool for extensions of the stochastic model components was developed. Pooled analyses of nevirapine and rifabutin pharmacokinetics were performed; the latter generating comprehensive dosing recommendations for combined administration of rifabutin and antiretroviral protease inhibitors. The work presented in this thesis demonstrates the usefulness of pharmacometric techniques to improve treatment of TB and especially contributes evidence to inform optimized dosing regimens of new and old anti-TB drugs in various clinical contexts.

<p> Malaria, Human Immunodeficiency Virus (HIV) and tuberculosis (TB) are global health problems having their worst situation in sub-Saharan Africa. Consequently, concomitant use of antimalarial, antiretroviral and antitubercular drugs may be needed, resulting in a potential risk of drug-drug interactions.</p><p>Cytochrome P-450 (CYP) enzyme induction/inhibition may lead to drug-drug interactions and can be detected by probe drugs. An analytical method was developed for the quantitation of mephenytoin, CYP2B6 and CYP2C19 probe, and its metabolites. </p><p>Induction/inhibition of principal CYP enzymes by the antimalarials; artemisinin, dihydroartemisinin, arteether, artemether and artesunate, was evaluated using the 4-hour plasma concentration ratios of probe drugs and their metabolites along with modelling the population pharmacokinetics of S-mephenytoin and its metabolites. The extent of change in enzymatic activities was different among the antimalarials, with artemisinin having strongest capacity for induction and inhibition, consequently, the strongest potential risk for drug-drug interactions. </p><p>Drug-drug interactions between the antitubercular rifampicin and the antiretrovirals nevirapine and lopinavir were assessed, in TB/HIV patients, by developing population pharmacokinetic models. Rifampicin increased nevirapine oral clearance. Simulations suggested that increasing the nevirapine dose to 300 mg twice daily when co-administered with rifampicin, would result in nevirapine concentrations above subtherapeutic levels, with minimum exposure above the recommended maximum concentration. Lopinavir is co-formulated with ritonavir in the ratio of 4:1. In children, increasing ritonavir dose four times did not completely compensate the enhancement of lopinavir oral clearance caused by rifampicin. However, the predicted lopinavir trough concentration was above the recommended minimum therapeutic concentration.</p><p>The work presented in this thesis followed an investigation line though not done for a particular drug. First the CYP enzymes involved in the interaction are identified. Afterwards, the expected drug-drug interaction is investigated where the potentially interacting drugs are concomitantly administered and an adjustment in the dose regimen is proposed that is subsequently evaluated.</p>

Malaria, Human Immunodeficiency Virus (HIV) and tuberculosis (TB) are global health problems having their worst situation in sub-Saharan Africa. Consequently, concomitant use of antimalarial, antiretroviral and antitubercular drugs may be needed, resulting in a potential risk of drug-drug interactions. Cytochrome P-450 (CYP) enzyme induction/inhibition may lead to drug-drug interactions and can be detected by probe drugs. An analytical method was developed for the quantitation of mephenytoin, CYP2B6 and CYP2C19 probe, and its metabolites. Induction/inhibition of principal CYP enzymes by the antimalarials; artemisinin, dihydroartemisinin, arteether, artemether and artesunate, was evaluated using the 4-hour plasma concentration ratios of probe drugs and their metabolites along with modelling the population pharmacokinetics of S-mephenytoin and its metabolites. The extent of change in enzymatic activities was different among the antimalarials, with artemisinin having strongest capacity for induction and inhibition, consequently, the strongest potential risk for drug-drug interactions. Drug-drug interactions between the antitubercular rifampicin and the antiretrovirals nevirapine and lopinavir were assessed, in TB/HIV patients, by developing population pharmacokinetic models. Rifampicin increased nevirapine oral clearance. Simulations suggested that increasing the nevirapine dose to 300 mg twice daily when co-administered with rifampicin, would result in nevirapine concentrations above subtherapeutic levels, with minimum exposure above the recommended maximum concentration. Lopinavir is co-formulated with ritonavir in the ratio of 4:1. In children, increasing ritonavir dose four times did not completely compensate the enhancement of lopinavir oral clearance caused by rifampicin. However, the predicted lopinavir trough concentration was above the recommended minimum therapeutic concentration. The work presented in this thesis followed an investigation line though not done for a particular drug. First the CYP enzymes involved in the interaction are identified. Afterwards, the expected drug-drug interaction is investigated where the potentially interacting drugs are concomitantly administered and an adjustment in the dose regimen is proposed that is subsequently evaluated.

<p>Drug-drug interactions (DDIs) occur when multiple drugs are used concurrently. Caused by one drug inhibiting or inducing the metabolism of a second drug, DDIs often alter plasma concentrations and could seriously impact efficacy and safety of co-administered medications. Cytochrome P450 (CYP), a superfamily of enzymes, plays an important role in metabolizing a majority of FDA approved drugs currently on the market. 70% of predicable DDIs are associated with CYP enzymes inhibition. In-silico methods are increasingly adopted as a cost-effective complement to guide and prioritize efforts in drug discovery. Recent emerging applications of artificial intelligence algorithms have demonstrated promising results capable of prioritizing the selection of large chemical libraries, thereby outlining the future of in-silico methods assisting in drug discovery. Nevertheless, current methods rely on molecular descriptors that almost exclusively focus on chemical properties and atomic structures that fail to capture critical conformation and biological interaction related properties. There is also a lack of trainable molecular descriptors with feature specificity that reflect detailed protein-ligand binding energy and enable biological activity prediction. The overall objective of this dissertation is to understand molecular biological binding activity through electronic structure-based local descriptors derived from quantum based conceptual density functional theory (CDFT). This method will be used to assess the correlation of intermolecular interaction energy with ligand-protein binding with 2D feature maps reduced from the 4D molecular surfaces of the binding site and ligand (3D molecular surface with 1D electronic property). Additionally, it will be used to explore the possibility of predicting CYP related DDIs using descriptors generated using first principles including protein-ligand binding with specificity and strength and deep learning algorithms. Using quantum chemistry to interpret topological molecular information residing on 3D molecular surface permits the extraction of interacting features directly from the ligand structure. To achieve that, a set of curatable data containing consistent measurements was accessed through publicly accessible libraries. A series of novel Manifold Embedding of Molecular Surface (MEMS) descriptors were generated containing local electronic properties residing on the 3D molecule structure surface of each ligand using manifold learning. Major information were captured featuring electronic characteristics on the molecular 3D surface. Shape context was employed to derive transnational invariance feature vectors from MEMS with high granularity, thus preserving molecular information with specificity. DeepSet was utilized to perform permutation equivariance model training and validation. Powerful model learning is observed with an F-measure for all targets above 75% with the highest of 87% from external testing. Despite their promising prediction performance, molecular conformation changes and analytical featurization methods need to be implemented to expand model applicability and improve model reliability.</p>

This study set out to review and analyse aspects of antidepressant prescribing in children and adolescents in a section of the private health care sector of South Africa. The research was conducted in two phases, namely a literature review and an empirical investigation. The aim of the literature review was to provide background to the study by conceptualising antidepressants. The empirical review followed a retrospective, descriptive, observational design. The data employed in the study was obtained from the medicine claims database of a South African Pharmaceutical Benefit Management (PBM) company. The study population consisted of 3 611 children and adolescents receiving ≥1 antidepressants from 1 January 2010 to 31 December 2010. Basic descriptive statistics, such as frequency, prevalence, average, weighted average, standard deviation, weighted standard deviation, median, effect sizes, prescribed daily dosages and DU95% methodology were used to characterise the study sample, and were calculated using the Statistical Analysis System SAS® for Windows 9.3® program. The data were used to determine the prescribing patterns of antidepressants with regard to age, gender, geographic area, type of prescriber, the comparison of prescribed daily dosages vs. recommended daily dosages, and the prevalence of potential drug-drug interactions. Potential drug-drug interactions were identified and compiled by using various interaction compendia, whereas recommended daily dosages were identified by cross-referencing various dosage compendia. The study population consisted of 1 850 girls and 1 761 boys. The mean age of girls was 13.7 ± 3.9 years, vs. 12.3 ± 3.8 years for boys (d = 0.4). A total of 11 735 prescriptions containing 12 272 antidepressants were documented in 2010. Results of the study furthermore showed that the average number of prescriptions claimed per patient increased with age, from an average of 1.0 ± 0.28 among those up to the age of 2 years, to an average of 3.4 ± 3.21 among those 16 to 18 years of age. Prescribing with regard to age groups differed, rising gradually from birth and peaking at middle childhood for boys, whereas antidepressant use in girls increased from birth up to 6 years of age, reaching a plateau and increases again from age 13 and onward. Approximately 25% (n = 12 272) of antidepressants prescribed were either not indicated in children, or the dosages were deemed too high. More than 50% (n = 12 272) of antidepressants prescribed were in the Gauteng province. The SSRIs (selective serotonin re-uptake inhibitors) and the TCAs (tricyclic antidepressants) were the most prescribed antidepressants in both gender groups. The male-to-female ratio for the selective serotonin re-uptake inhibitors was 0.9, compared to 1.2 for the tricyclic antidepressants. The top three antidepressants prescribed were imipramine (21.8%), citalopram (15.3%) and escitalopram (14.7%, n = 12 272). Potential DDIs were observed on 284 (2.4%) (n = 11 743) prescriptions. The drug pairs with potential drug-drug interactions prescribed most, were imipramine with methylphenidate [43 cases (15.1%)] and valproic acid [38 cases (13.4%)], and followed by methylphenidate in combination with fluoxetine and sertraline [both documenting 32 cases (11.3%), respectively. The TCAs accounted for 182 (64.1%) cases of possible DDIs (drug-drug interactions), whereas combination therapy of SSRIs and TCAs accounted for 21.4% of potential DDIs. In conclusion, this study determined that there were a number of differences with regard to antidepressant prescribing in children and adolescents. Recommendations for future studies were made. / MPharm (Pharmacy Practice), North-West University, Potchefstroom Campus, 2014

This study set out to review and analyse aspects of antidepressant prescribing in children and adolescents in a section of the private health care sector of South Africa. The research was conducted in two phases, namely a literature review and an empirical investigation. The aim of the literature review was to provide background to the study by conceptualising antidepressants. The empirical review followed a retrospective, descriptive, observational design. The data employed in the study was obtained from the medicine claims database of a South African Pharmaceutical Benefit Management (PBM) company. The study population consisted of 3 611 children and adolescents receiving ≥1 antidepressants from 1 January 2010 to 31 December 2010. Basic descriptive statistics, such as frequency, prevalence, average, weighted average, standard deviation, weighted standard deviation, median, effect sizes, prescribed daily dosages and DU95% methodology were used to characterise the study sample, and were calculated using the Statistical Analysis System SAS® for Windows 9.3® program. The data were used to determine the prescribing patterns of antidepressants with regard to age, gender, geographic area, type of prescriber, the comparison of prescribed daily dosages vs. recommended daily dosages, and the prevalence of potential drug-drug interactions. Potential drug-drug interactions were identified and compiled by using various interaction compendia, whereas recommended daily dosages were identified by cross-referencing various dosage compendia. The study population consisted of 1 850 girls and 1 761 boys. The mean age of girls was 13.7 ± 3.9 years, vs. 12.3 ± 3.8 years for boys (d = 0.4). A total of 11 735 prescriptions containing 12 272 antidepressants were documented in 2010. Results of the study furthermore showed that the average number of prescriptions claimed per patient increased with age, from an average of 1.0 ± 0.28 among those up to the age of 2 years, to an average of 3.4 ± 3.21 among those 16 to 18 years of age. Prescribing with regard to age groups differed, rising gradually from birth and peaking at middle childhood for boys, whereas antidepressant use in girls increased from birth up to 6 years of age, reaching a plateau and increases again from age 13 and onward. Approximately 25% (n = 12 272) of antidepressants prescribed were either not indicated in children, or the dosages were deemed too high. More than 50% (n = 12 272) of antidepressants prescribed were in the Gauteng province. The SSRIs (selective serotonin re-uptake inhibitors) and the TCAs (tricyclic antidepressants) were the most prescribed antidepressants in both gender groups. The male-to-female ratio for the selective serotonin re-uptake inhibitors was 0.9, compared to 1.2 for the tricyclic antidepressants. The top three antidepressants prescribed were imipramine (21.8%), citalopram (15.3%) and escitalopram (14.7%, n = 12 272). Potential DDIs were observed on 284 (2.4%) (n = 11 743) prescriptions. The drug pairs with potential drug-drug interactions prescribed most, were imipramine with methylphenidate [43 cases (15.1%)] and valproic acid [38 cases (13.4%)], and followed by methylphenidate in combination with fluoxetine and sertraline [both documenting 32 cases (11.3%), respectively. The TCAs accounted for 182 (64.1%) cases of possible DDIs (drug-drug interactions), whereas combination therapy of SSRIs and TCAs accounted for 21.4% of potential DDIs. In conclusion, this study determined that there were a number of differences with regard to antidepressant prescribing in children and adolescents. Recommendations for future studies were made. / MPharm (Pharmacy Practice), North-West University, Potchefstroom Campus, 2014

Numerous natural products are widely used as first-line/alternative therapeutics and dietary supplements in both western and eastern society. However, the safety and efficacy profiles for herbal products are still limited. Organic anion transporters (OATs; SLC22 family) are expressed in many barrier organs and mediate in vivo body disposition of a broad array of endogenous substances and clinically important drugs. As some dietary flavonoids and phenolic acids were previously demonstrated to interact with OATs, it is necessary to explore the potential interaction of such components found in natural products in order to avoid potential OAT-mediated drug-drug interactions (DDIs). The inhibitory effects of 23 natural products were assessed on the function of human (h) OATs, hOAT1 (SLC22A6), hOAT3 (SLC22A7), and hOAT4 (SLC22A11) and/or the murine (m) orthologs mOat1 and mOat3. For compounds exhibiting marked inhibition at initial screening, dose-response curves (IC50 values) and DDI indices were determined. At the initial screening concentrations, 14, 19, and 2 test compounds exhibited significant inhibition on hOAT1, hOAT3, and hOAT4, respectively. Additionally, all test Danshen (a Chinese herbal medicine) hydrophilic components significantly reduced mOat1- and mOat3-mediated substrate uptake at 1 mM. For selected compounds, the IC50 and Ki values were estimated to be in the micromolar or even nanomolar range. Considering the clinical plasma concentration and unbound fraction in plasma, DDI indices for gallic acid, gentisic acid, lithospermic acid, protocatechuic acid, rosmarinic acid, salvianolic acid B, and tanshinol indicated DDIs may occur in vivo in situations of co-administration of these compounds and clinical therapeutics known to be OAT substrates. Finally, a new, rapid, and sensitive liquid chromatography-tandem mass spectrometry (LC-MS/MS) method was developed and validated to quantify gallic acid and gentisic acid in cell lysates in order to measure cellular uptake of these compounds in mOat1- or mOat3-expressing cells. Significant cellular uptake of gallic acid was observed in mOat1-expressing cells, compared with background control cells. The absorptive uptake was completely blocked by probenecid (known OAT inhibitor) at 1 mM. These results indicate that gallic acid is a substrate for mOat1 and suggest that human OAT1 might be involved in the active renal secretion of gallic acid.

A (-)- grandisina (GRA) é um produto natural da classe das lignanas e é encontrada em muitas espécies de plantas das regiões Norte e Nordeste do Brasil. Por apresentar diversas propriedades biológicas, como atividade tripanocida, anti-inflamatória, antinociceptiva, e principalmente atividade antileucêmica e antitumoral contra tumores de Ehrlich, a GRA pode ser considerada um potencial candidato a fármaco. Porém, para que a GRA se torne um fármaco são necessárias diversas etapas de estudos, incluindo estudos pré-clínicos de interações medicamentosas (DDI). As DDI ocorrem principalmente devido a inibições diretas e tempo-dependentes das enzimas do citocromo P450 (CYP450), uma superfamília de enzimas responsável por metabolizar cerca de 75% dos fármacos em uso. Os estudos pré-clínicos de DDI envolvem o conhecimento do potencial inibitório do candidato a fármaco sobre essas enzimas e esses estudos podem ser realizados empregando diversos modelos in vitro, como, por exemplo, microssomas hepáticos de humanos (HLM). Assim, nesse estudo foi avaliado o efeito inibitório da GRA sobre a atividade das principais isoformas do CYP450 e também foram determinadas as isoformas que contribuem para a formação dos metabólitos da GRA. Os resultados demonstraram que múltiplas isoformas participam da formação dos metabólitos da GRA, com destaque para a CYP2C9, que participa da formação de todos os metabólitos. Em relação aos estudos de inibição, foi possível concluir que a GRA é um inibidor fraco da CYP1A2 e CYP2D6, com valores de IC50 maiores do que 200 µM e 100 µM, respectivamente, e um inibidor moderado e competitivo da CYP2C9, com IC50 igual a 40,85 µM e Ki igual a 50,60 µM. Para a CYP3A4 o potencial inibitório da GRA foi avaliado utilizando dois substratos distintos. A GRA demonstrou ser tanto um inibidor dose-dependente moderado e competitivo dessa isoforma, quanto um inibidor tempo-dependente baseado em mecanismo com potencial de inativação equiparável ao do irinotecano, inibidor baseado em mecanismo clinicamente significativo. Utilizando a nifedipina como substrato os valores de IC50 e Ki foram 78,09 µM e 48,71 µM, respectivamente. Já os valores dos parâmetros cinéticos de inativação foram KI= 6,40 µM, kinact= 0,037 min-1 e Clinact= 5,78 mL min-1 µmol-1. Para os ensaios empregando o midazolam os valores de IC50 e Ki foram 48,87 µM e 31,25 µM, respectivamente, e os valores dos parâmetros cinéticos de inativação foram KI= 31,53 µM, kinact= 0,049 min-1 e Clinact= 1,55 mL min-1 µmol-1. Com relação a CYP2E1, por sua vez, foi possível observar que a GRA tem capacidade de aumentar a atividade dessa isoforma significativamente a partir da concentração de 4 µM. Portanto, conclui-se que não há risco da GRA apresentar interações medicamentosas com fármacos metabolizados pela CYP1A2 e CYP2D6, enquanto que para a CYP2C9, apesar da GRA ser um inibidor moderado dessa isoforma, o risco é baixo. Já para medicamentos metabolizados pela CYP2E1 e CYP3A4 o risco de DDI existe e isso deve ser cuidadosamente monitorado in vivo, principalmente porque a CYP3A4 é a isoforma responsável por catalisar o metabolismo da maioria dos fármacos. / (-)-grandisin (GRA) is a lignanic natural product found in many species of plants from North and Northeast of Brazil. This compound has several biological properties, such as trypanocide, anti-inflammatory, antinociceptive, antileukemia activity and antitumor activity against Ehrlich tumor. Because of these biological properties, GRA is considered a potential drug candidate, however, before becoming a new drug, GRA has to undergo various tests, including preclinical drug-drug interactions (DDI) studies. Most of the times, DDI occur because of direct and time-dependent inhibitions of cytochrome P450 (CYP450) enzymes, an enzyme superfamily responsible for metabolizing the vast majority of drugs administered. Preclinical drug-drug interactions studies involve the evaluation of the potential of a drug candidate to inhibit this superfamily of enzymes and these studies can be conducted using in vitro models, such as human liver microsomes (HLM). Therefore, in this project, the inhibitory effect of GRA on the activity of some CYP450 isoforms was evaluated and the isoforms that catalyze the formation of GRA\'s metabolites were also determined. Results showed that multiple CYP450 isoforms participate in the GRA\'s metabolites formation, highlighting CYP2C9, which catalyzes the formation of all metabolites. The inhibition studies showed that GRA is a weak inhibitor of CYP1A2 and CYP2D6, with IC50 values greater than 200 µM and 100 µM, respectively, and a moderate and competitive inhibitor of CYP2C9, with IC50 value equal to 40.85 µM and Ki value equal to 50.60 µM. The capability of GRA to inhibit CYP3A4 was evaluated using two different substrates. GRA showed to be a moderate and competitive dose- dependent inhibitor of this isoform and also a mechanism-based time-dependent inhibitor with potential of inactivation comparable to irinotecan, a clinically significant mechanism-based inhibitor. IC50 and Ki values obtained using nifedipine as substrate were 78.09 µM and 48.71 µM, respectively, and inactivation kinetics parameters were KI= 6.40 µM, kinact= 0,037 min-1 e Clinact= 5.78 mL min-1 µmol-1. On the other hand, IC50 and Ki values using midazolam as substrate were 48.87 µM and 31.25 µM, respectively, and the values of inactivation kinetics parameters were KI= 31.53 µM, kinact= 0,049 min-1 and Clinact= 1.55 mL min-1 µmol-1. With respect to CYP2E1, it was observed that GRA increases its activity significantly from a concentration of 4 µM. Therefore, it is possible to conclude that there is no risk of DDI between GRA and drugs metabolized by CYP1A2 and CYP2D6, while for CYP2C9, although GRA is a moderate inhibitor of this isoform, the risk is low. Finally, for drugs metabolized by CYP3A4 and CYP2E1 there is risk of DDI and this should be carefully monitored in humans, mainly because CYP3A4 is an isoform responsible for catalyzing the metabolism of most drugs in use.