Design, conduct, and analyses of Breast International Group (BIG) 1-98: a randomized, double-blind, phase-III study comparing letrozole and tamoxifen as adjuvant endocrine therapy for postmenopausal women with receptor-positive, early breast cancer.

BACKGROUND: Aromatase inhibitors provide superior disease control when compared with tamoxifen as adjuvant therapy for postmenopausal women with endocrine-responsive early breast cancer. PURPOSE: To present the design, history, and analytic challenges of the Breast International Group (BIG) 1-98 trial: an international, multicenter, randomized, double-blind, phase-III study comparing the aromatase inhibitor letrozole with tamoxifen in this clinical setting. METHODS: From 1998-2003, BIG 1-98 enrolled 8028 women to receive monotherapy with either tamoxifen or letrozole for 5 years, or sequential therapy of 2 years of one agent followed by 3 years of the other. Randomization to one of four treatment groups permitted two complementary analyses to be conducted several years apart. The first, reported in 2005, provided a head-to-head comparison of letrozole versus tamoxifen. Statistical power was increased by an enriched design, which included patients who were assigned sequential treatments until the time of the treatment switch. The second, reported in late 2008, used a conditional landmark approach to test the hypothesis that switching endocrine agents at approximately 2 years from randomization for patients who are disease-free is superior to continuing with the original agent. RESULTS: The 2005 analysis showed the superiority of letrozole compared with tamoxifen. The patients who were assigned tamoxifen alone were unblinded and offered the opportunity to switch to letrozole. Results from other trials increased the clinical relevance about whether or not to start treatment with letrozole or tamoxifen, and analysis plans were expanded to evaluate sequential versus single-agent strategies from randomization. LIMITATIONS: Due to the unblinding of patients assigned tamoxifen alone, analysis of updated data will require ascertainment of the influence of selective crossover from tamoxifen to letrozole. CONCLUSIONS: BIG 1-98 is an example of an enriched design, involving complementary analyses addressing different questions several years apart, and subject to evolving analytic plans influenced by new data that emerge over time.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Regulation of mass and function of pancreatic β-cells: identification of anti-apoptotic peptides and role of GLP-1

Résumé La masse de cellules β sécrétrices d'insuline est un tissu dynamique qui s'adapte aux variations de la demande métabolique pour assurer une normoglycémie. Cette adaptation se fait par un changement de sécrétion d'insuline et de la masse totale des cellules β. Une perte complète ou partielle des cellules β conduit respectivement à un diabète de type 1 et de type 2. Les mécanismes qui régulent la masse de cellules β et maintiennent leur phénotype differencié sont encore peu connus. Leur identification est nécessaire pour comprendre le développement du diabète et développer des stratégies de traitement. La greffe d'îlots est une approche thérapeutique prometteuse pour le diabète de type 1, mais est limitée par une perte précoce des cellules β due à une apoptose induite par des cytokines. Afin d'améliorer la survie des cellules β lors de la greffe d'îlots, le premier but était de trouver des peptides pouvant bloquer l'apoptose induite par FasL et TNF-α. Pour ce faire, deux librairies de phages ont été criblées pour sélectionner des peptides se liant au Fas DD ou au TNFRl DD. Nous avons identifié six peptides différents. Cependant, aucun d'entre eux n'était capable de protéger les cellules de l'apoptose induite par FasL ou TNF-α. Deuxièmement, le GLP-1 est une hormone qui stimule la sécrétion d'insuline, et est impliquée dans la prolifération des cellules β, la différentiation, et inhibe l'apoptose. Nous avons fait l'hypothèse que le GLP-1 joue un rôle crucial dans le contrôle de la masse et de la fonction des cellules β. Afin de l'évaluer, une analyse par puce à ADN a été réalisée en comparant des cellules βTC-Tet traitées avec du GLP-1 à des cellules non-traitées. 376 gènes régulés ont été identifiés, dont RGS2, CREM, ICERI et DUSP14, augmentés significativement par le GLP-1. Nous avons confirmé que le GLP-1 augmente l'expression de ces gènes, aussi bien au niveau des transcripts que des protéines. De plus, nous avons montré que le GLP-1 induit leur expression par activation de la voie cAMP/PKA, et nécessite l'entrée de calcium extracellulaire. D'après leur fonction biologique, nous avons ensuite supposé que ces gènes pourraient agir comme régulateurs négatifs de la signalisation du GLP-l, et donc freiner son effet proliférateur. Pour vérifier notre hypothèse, des siRNAs contre ces gènes ont été développés, et leurs effets sur la prolifération des cellules β seront évalués ultérieurement. Abstract The pancreatic β-cell mass is a dynamic tissue which adapts to variations in metabolic demand in order to ensure normoglycemia. This adaptation occurs through a change in both insulin secretion and the total mass of ,β-cells. An absolute or relative loss of β-cells leads to type 1 and type 2 diabetes, respectively. The mechanisms that regulate the pancreatic β-cell mass and maintain the fully differentiated phenotype of the insulin-secreting β-cells are only poorly defined. Their identification is required to understand the progression of diabetes, but also to design strategies for the treatment of diabetes. Islet transplantation is a promising therapeutic approach for type 1 diabetes, but it is still limited by an early graft loss due to cytokine-induced apoptosis. In order to improve β-cell survival during islet transplantation, our first goal was to find novel blockers of FasL- and TNF-α-mediated cell death in the form of peptides. To that end, we screened two phage display libraries to select Fas DD- or TNFR1 DD-binding peptides. We identified six different small peptides. However, none of these peptides was able to prevent cells from FasL- or TNF-α-mediated apoptosis. Secondly, GLP-1 is a hormone that has been shown to stimulate insulin secretion and to be involved in β-cell proliferation, differentiation and inhibition of apoptosis. We hypothesized that GLP-1 plays a crucial role to control mass and function of β-cells. To evaluate this hypothesis, we performed a cDNA microarray analysis with GLP-1-treated βTC-Tet cells compared to untreated cells. We found 376 regulated genes, among these, RGS2, CREM, ICERI and DUSP14, which were significantly upregulated by GLP-1. We confirmed that both their mRNA and protein levels were strongly and rapidly increased after GLP-1 treatment. Moreover, we found that GLP-1 activates their expression mainly through the activation of the cAMP/PKA signaling pathway, and requires extracellular calcium entry. According to their biological function, we then hypothesized that these genes might act as negative regulators of the GLP-1 signaling. In particular, they might brake the effects of GLP-1 on β-cell proliferation. To verify this hypothesis, siRNAs against these genes were developed. The effect of these siRNAs on GLP-1-induced β-cell proliferation will be evaluated later.

Trials using a crossover design and ambulatory blood pressure recordings to determine the efficacy of antihypertensive agents in individual patients.

The antihypertensive effects of the beta-blocking agent betaxolol and the calcium entry blocker verapamil were compared in a crossover single-blind trial. Seventeen patients with uncomplicated essential hypertension took either betaxolol or a slow-release formulation of verapamil for two consecutive 6-week periods. The sequence of treatment phases was randomly allocated and a 2-week washout period preceded each treatment. The antihypertensive effect of the test drugs was assessed both at the physician's office and during everyday activities using a portable blood pressure recorder. The crossover design of the trial made it possible to evaluate the antihypertensive efficacy of betaxolol and verapamil both in the group as a whole and in the individual patient. The individual patient response to one of these agents was not a reliable indicator of the same patient's response to the alternative agent. Betaxolol brought both office and ambulatory recorded blood pressures under control in a larger fraction of patients than verapamil, although the magnitude of the blood pressure fall in the responders was equal for each drug. These observations stress the need for an individualized approach to the evaluation of antihypertensive therapy. The present results also demonstrate that optimal antihypertensive therapy is still a matter of trial and error. The precise methodology that ought to characterize crossover trials may make it possible to improve the therapeutic approach to hypertensive patients.

Business model design: an evaluation of paper-based and computer-aided canvases

In recent years, Business Model Canvas design has evolved from being a paper-based activity to one that involves the use of dedicated computer-aided business model design tools. We propose a set of guidelines to help design more coherent business models. When combined with functionalities offered by CAD tools, they show great potential to improve business model design as an ongoing activity. However, in order to create complex solutions, it is necessary to compare basic business model design tasks, using a CAD system over its paper-based counterpart. To this end, we carried out an experiment to measure user perceptions of both solutions. Performance was evaluated by applying our guidelines to both solutions and then carrying out a comparison of business model designs. Although CAD did not outperform paper-based design, the results are very encouraging for the future of computer-aided business model design.

Effect of humeral stem design on humeral position and range of motion in reverse shoulder arthroplasty.

PURPOSE: The impacts of humeral offset and stem design after reverse shoulder arthroplasty (RSA) have not been well-studied, particularly with regard to newer stems which have a lower humeral inclination. The purpose of this study was to analyze the effect of different humeral stem designs on range of motion and humeral position following RSA. METHODS: Using a three-dimensional computer model of RSA, a traditional inlay Grammont stem was compared to a short curved onlay stem with different inclinations (155°, 145°, 135°) and offset (lateralised vs medialised). Humeral offset, the acromiohumeral distance (AHD), and range of motion were evaluated for each configuration. RESULTS: Altering stem design led to a nearly 7-mm change in humeral offset and 4 mm in the AHD. Different inclinations of the onlay stems had little influence on humeral offset and larger influence on decreasing the AHD. There was a 10° decrease in abduction and a 5° increase in adduction between an inlay Grammont design and an onlay design with the same inclination. Compared to the 155° model, the 135° model improved adduction by 28°, extension by 24° and external rotation of the elbow at the side by 15°, but led to a decrease in abduction of 9°. When the tray was placed medially, on the 145° model, a 9° loss of abduction was observed. CONCLUSIONS: With varus inclination prostheses (135° and 145°), elevation remains unchanged, abduction slightly decreases, but a dramatic improvement in adduction, extension and external rotation with the elbow at the side are observed.