Multiobjective strategies for New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline. Formally, the NPD problem can be stated as follows: select a set of R&D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while coping with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGAII type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. This work is illustrated with a study case involving nine interdependent new product candidates targeting three diseases. An analysis is performed for this test bench on the different pairs of criteria both for the bi- and tricriteria optimization: large portfolios cause resource queues and delays time to launch and are eliminated by the bi- and tricriteria optimization strategy. The optimization strategy is thus interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Parasitismo Intestinal en Población Infantil de las Regiones Atlánticas de Nicaragua

La presente Tesis Doctoral tiene como objetivo establecer el espectro parasitario intestinal de la costa Atlántica de Nicaragua, concretamente de la Región Autónoma del Atlántico Norte (RAAN) y la Región Autónoma del Atlántico Sur (RAAS). Para ello, se ha estudiado un total de 1878 escolares (1009 niñas y 869 niños), con edades comprendidas entre <1 y 14 años de edad. Se ha detectado un espectro parasitario total de al menos 18 especies parásitas (10 protozoos y 8 helmintos), con una prevalencia de parasitación total de 93.7%, observándose mayor prevalencia de protozoos que de helmintos (85.3% vs 61%). Las especies más prevalentes detectadas fueron Blastocystis spp. (68.2%), seguido de T. trichiura (54.3%) y G. intestinalis (34.4%). El multiparasitismo ha destacado sobre el monoparasitismo (77.5% vs 15.9%) en toda la zona Atlántica, detectándose un caso de parasitación de hasta 10 especies parásitas diferentes a la vez. Aunque el estado anémico basal de los escolares no reflejó asociación directa con la parasitación por geohelmintos, se evidencia que la mayoría de escolares anémicos presentó parasitación por geohelmintos. Los resultados parasitológicos obtenidos fueron analizados en función del sexo, edad, zona poblacional, intensidad de parasitación (carga helmíntica) y en función de distintas variables socio-económicas e higiénico-sanitarias, detectándose correlación estadísticamente significativa en algunas de estas variables. Los resultados han sido comparados con la bibliografía existente hasta el momento sobre parasitismo intestinal en población infantil de Nicaragua y con la de países centroamericanos y de entornos insulares caribeños. El presente estudio permite reflejar la situación parasitológica que presenta la población infantil de las Regiones Autónomas nicaragüenses, concluyendo que se debe seguir empleando campañas de desparasitación por helmintos en población infantil de las zonas más marginadas de la zona Atlántica de Nicaragua.The aim of this Doctoral Thesis is to determine the intestinal parasitic spectrum from the Atlantic coast of Nicaragua, which includes the North Atlantic Autonomous Region (RAAN) and the South Atlantic Autonomous Region (RAAS). For this purpose, a total of 1878 schoolchildren (1009 girls and 869 boys), aged between <1 and 14 years old have been studied. The total parasitic spectrum consisted of at least 18 different species (10 protozoa and 8 helminths), detecting an overall prevalence of infection of 93.7%, with a higher prevalence of protozoa than helminths (85.3% vs 61%). The most prevalent species were Blastocystis spp. (68.2%), followed by T. trichiura (54.3%) and G. intestinalis (34.4%). Polyparasitism predominated over monoparasitism (77.5% vs 15.9%) in the entire Atlantic area, detecting a case of infection up to 10 different parasitic species at the same time. Although the baseline anaemic state of the schoolchildren did not reflect a direct association with soil-transmitted helminth infections, it is noteworthy that the majority of anaemic schoolchildren presented geohelminth infection. The parasitological results obtained were analysed according to sex, age, population area, parasitic intensity (helminthic load) and according to different socio-economic and hygienic-sanitary variables, detecting statistically significant differences in some of these variables. The results have been compared with the existing bibliography to date on intestinal parasites in child population from Nicaragua and other Central American countries as well as Caribbean environments. Our study reflects the current parasitological situation in children of the Autonomous Regions of Nicaragua, highlighting that deworming campaigns need to be implemented especially in the most marginalized areas of the Atlantic coast of Nicaragua

Multiobjective optimization of New Product Development in the pharmaceutical industry

New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline, namely, the presence of uncertainty, the high level of the involved capital costs, the interdependency between projects, the limited availability of resources, the overwhelming number of decisions due to the length of the time horizon (about 10 years) and the combinatorial nature of a portfolio. Formally, the NPD problem can be stated as follows: select a set of R and D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while copying with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGA II type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. An object-oriented model previously developed for batch plant scheduling and design is then extended to embed the case of new product management, which is particularly adequate for reuse of both structure and logic. Two case studies illustrate and validate the approach. From this simulation study, three performance evaluation criteria must be considered for decision making: the Net Present Value (NPV) of a sequence, its associated risk defined as the number of positive occurrences of NPV among the samples and the time to market. Theyv have been used in the multiobjective optimization formulation of the problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. NSGA II has been adapted to the treated case for taking into account both the number of products in a sequence and the drug release order. From an analysis performed for a representative case study on the different pairs of criteria both for the bi- and tricriteria optimization, the optimization strategy turns out to be efficient and particularly elitist to detect the sequences which can be considered by the decision makers. Only a few sequences are detected. Among theses sequences, large portfolios cause resource queues and delays time to launch and are eliminated by the bicriteria optimization strategy. Small portfolio reduces queuing and time to launch appear as good candidates. The optimization strategy is interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Optimisation du développement de nouveaux produits dans l'industrie pharmaceutique par algorithme génétique multicritère

Le développement de nouveaux produits constitue une priorité stratégique de l'industrie pharmaceutique, en raison de la présence d'incertitudes, de la lourdeur des investissements mis en jeu, de l'interdépendance entre projets, de la disponibilité limitée des ressources, du nombre très élevé de décisions impliquées dû à la longueur des processus (de l'ordre d'une dizaine d'années) et de la nature combinatoire du problème. Formellement, le problème se pose ainsi : sélectionner des projets de Ret D parmi des projets candidats pour satisfaire plusieurs critères (rentabilité économique, temps de mise sur le marché) tout en considérant leur nature incertaine. Plus précisément, les points clés récurrents sont relatifs à la détermination des projets à développer une fois que les molécules cibles sont identifiées, leur ordre de traitement et le niveau de ressources à affecter. Dans ce contexte, une approche basée sur le couplage entre un simulateur à événements discrets stochastique (approche Monte Carlo) pour représenter la dynamique du système et un algorithme d'optimisation multicritère (de type NSGA II) pour choisir les produits est proposée. Un modèle par objets développé précédemment pour la conception et l'ordonnancement d'ateliers discontinus, de réutilisation aisée tant par les aspects de structure que de logique de fonctionnement, a été étendu pour intégrer le cas de la gestion de nouveaux produits. Deux cas d'étude illustrent et valident l'approche. Les résultats de simulation ont mis en évidence l'intérêt de trois critères d'évaluation de performance pour l'aide à la décision : le bénéfice actualisé d'une séquence, le risque associé et le temps de mise sur le marché. Ils ont été utilisés dans la formulation multiobjectif du problème d'optimisation. Dans ce contexte, des algorithmes génétiques sont particulièrement intéressants en raison de leur capacité à conduire directement au front de Pareto et à traiter l'aspect combinatoire. La variante NSGA II a été adaptée au problème pour prendre en compte à la fois le nombre et l'ordre de lancement des produits dans une séquence. A partir d'une analyse bicritère réalisée pour un cas d'étude représentatif sur différentes paires de critères pour l'optimisation bi- et tri-critère, la stratégie d'optimisation s'avère efficace et particulièrement élitiste pour détecter les séquences à considérer par le décideur. Seules quelques séquences sont détectées. Parmi elles, les portefeuilles à nombre élevé de produits provoquent des attentes et des retards au lancement ; ils sont éliminés par la stratégie d'optimistaion bicritère. Les petits portefeuilles qui réduisent les files d'attente et le temps de lancement sont ainsi préférés. Le temps se révèle un critère important à optimiser simultanément, mettant en évidence tout l'intérêt d'une optimisation tricritère. Enfin, l'ordre de lancement des produits est une variable majeure comme pour les problèmes d'ordonnancement d'atelier. ABSTRACT : New Product Development (NPD) constitutes a challenging problem in the pharmaceutical industry, due to the characteristics of the development pipeline, namely, the presence of uncertainty, the high level of the involved capital costs, the interdependency between projects, the limited availability of resources, the overwhelming number of decisions due to the length of the time horizon (about 10 years) and the combinatorial nature of a portfolio. Formally, the NPD problem can be stated as follows: select a set of R and D projects from a pool of candidate projects in order to satisfy several criteria (economic profitability, time to market) while copying with the uncertain nature of the projects. More precisely, the recurrent key issues are to determine the projects to develop once target molecules have been identified, their order and the level of resources to assign. In this context, the proposed approach combines discrete event stochastic simulation (Monte Carlo approach) with multiobjective genetic algorithms (NSGA II type, Non-Sorted Genetic Algorithm II) to optimize the highly combinatorial portfolio management problem. An object-oriented model previously developed for batch plant scheduling and design is then extended to embed the case of new product management, which is particularly adequate for reuse of both structure and logic. Two case studies illustrate and validate the approach. From this simulation study, three performance evaluation criteria must be considered for decision making: the Net Present Value (NPV) of a sequence, its associated risk defined as the number of positive occurrences of NPV among the samples and the time to market. Theyv have been used in the multiobjective optimization formulation of the problem. In that context, Genetic Algorithms (GAs) are particularly attractive for treating this kind of problem, due to their ability to directly lead to the so-called Pareto front and to account for the combinatorial aspect. NSGA II has been adapted to the treated case for taking into account both the number of products in a sequence and the drug release order. From an analysis performed for a representative case study on the different pairs of criteria both for the bi- and tricriteria optimization, the optimization strategy turns out to be efficient and particularly elitist to detect the sequences which can be considered by the decision makers. Only a few sequences are detected. Among theses sequences, large portfolios cause resource queues and delays time to launch and are eliminated by the bicriteria optimization strategy. Small portfolio reduces queuing and time to launch appear as good candidates. The optimization strategy is interesting to detect the sequence candidates. Time is an important criterion to consider simultaneously with NPV and risk criteria. The order in which drugs are released in the pipeline is of great importance as with scheduling problems

Enfoque de las estrategias de reproducción social: Un estudio de caso de las mujeres jornaleras en Zacatecas

Ante la necesidad de satisfacer y/o complementar el ingreso económico para cubrir las necesidades básicas de las unidades domésticas, la mujer trata de buscar formas para cambiar la condición de vida de su familia integrándose al mercado laboral (subempleo) y en la medida en que ésta se incorpora vendrá con ello una serie de alteraciones en función del papel que desempeña la mujer dentro la unidad doméstica y la sociedad. Uno de los cambios que más están incidiendo en la nueva dinámica de vida de las familias rurales, es la cada vez mayor incorporación de las mujeres al ámbito laboral, y los nuevos roles que desempeñan los integrantes de las familiar rurales. En este trabajo presentamos el concepto de estrategia de reproducción social como una alternativa metodológica, destacando sus virtudes y limitaciones, para estudiar y comprender los cambios que se experimentan al interior de las familias rurales ante la cada vez mayor incorporación de las mujeres al ámbito laboral en condición de jornaleras agrícolas, así como presentar un estudio de caso en una comunidad rural del estado de Zacatecas, México. Para ello hemos organizado el documento de la siguiente manera: en primer lugar discutimos algunos de los principales cambios de roles de las mujeres al interior de las familias rurales, enseguida documentamos el concepto de estrategias de reproducción en el ámbito latinoamericano, posteriormente incluimos las críticas del enfoque, sus limitaciones y sus alcances, continuamos con un análisis sobre los alcances de la herramienta analítica de las estrategias de reproducción, finalmente presentamos su aplicación a un estudio de caso realizado a las mujeres jornaleras de una comunidad del estado de Zacatecas

Observaciones biométricas de Crocodylus acutus (Cuvier, 1807) recién nacidos en cautiverio, Tumbes, Perú

In this paper, length and weigth measurements of 20 newborn Crocodylus acutus (Cuvier, 1807) hached in a pilot farm-bred of the aquaculture center La Tuna Carranza, Puerto Pizarro, Tumbes, Peru, in 2001 are presented. The information is compared with similar reports from others places.Se presentan las medidas de longitud y peso de 20 crías de Crocodylus acutus (Cuvier, 1807) recién nacidas en cautiverio en el zoocriadero piloto del Centro de Acuicultura La Tuna Carranza, Puerto Pizarro, Tumbes, Perú, en el año 2001. Esta información es comparada con la procedente de otros lugares para la misma especie

Notas sobre la reproducción en cautiverio de Crocodylus acutus (Cuvier, 1807) en el Perú

Observations about reproduction of Crocodylus acutus (Cuvier, 1807) were recorded during the years 2001 and 2002 in the Fishery Center «La Tuna Carranza» (Puerto Pizarro, Tumbes, Peru). The minimum size of a female nesting was 2,30 m. The percentage of viability and birthrate/natality were 61,71% and 93,15%, respectively.Durante los años 2001 y 2002 se realizaron observaciones sobre la reproducción de Crocodylus acutus (Cuvier, 1807) en el Centro de Acuicultura La Tuna Carranza, localizado en Puerto Pizarro, departamento de Tumbes. El tamaño mínimo de una hembra anidando fue de 2,30 m. El porcentaje de viabilidad y natalidad fue de 61,71% y 93,15% respectivamente