Los orígenes de Zeltia / The origins of Zeltia

Se presentan en este trabajo los orígenes del proceso que culminó en la creación de la empresa Zeltia S.A., buque insignia de la industria farmacéutica gallega. Sus antecedentes aparecen en la constitución formal en Vigo del Instituto Bio-Químico Miguel Servet, en abril de 1936, si bien el farmacéutico Rubira y el médico Obella habían estado trabajando en el proyecto al menos desde 1929. El levantamiento militar del 36 impacta directamente en las primeras etapas del laboratorio. Mientras unos socios se posicionan a favor del levantamiento, a otros les afectan seriamente las medidas represivas del nuevo régimen. En cualquier caso, entre unos y otros se establecen lazos de cooperación y se crean lealtades. Incluso, durante la Guerra Civil, se incorporan al laboratorio profesionales y técnicos represaliados por su ideología política. Finalizada la contienda, cuando las circunstancias predecían el comienzo de un periodo de mayor estabilidad para el desarrollo del negocio, se produce una grave crisis en el accionariado, relacionada en gran medida con la influencia que tenía en Vigo el colectivo alemán y la fractura social existente frente a los germanófilos. En estas circunstancias se fragmenta la sociedad. Rubira continua al frente del Servet, al que terminaría incorporándose el alemán Boehme, con el que ya compartía previamente otros negocios, mientras Obella buscaba nuevos socios, con mayor afinidad ideológica, para fundar Zeltia S.A. en agosto de 1939. (AU)

The origins of the process that culminated in the creation of the company Zeltia S.A., flagship of the Galician pharmaceutical industry, are presented in this paper. Its precedents appear in the formal constitution in Vigo of the Miguel Servet Biochemical Institute, in April 1936, although the pharmacist Rubira and the doctor Obella had been working on the project since at least 1929. The military uprising of 1936 had a direct impact on the early stages of the laboratory. While some partners are positioned in favor of the uprising, others are seriously affected by the repressive measures of the new regime. In any case, between one and the other, bonds of cooperation are established and loyalties are created. Even during the Civil War, professionals and technicians retaliated for their political ideology joined the laboratory. At the end of the fight, when the circumstances predicted the beginning of a period of greater stability for the development of the business, a serious crisis occurred in the shareholding, largely related to the influence that the German collective had in Vigo and the existing social fracture. against the Germanophiles. In these circumstances society is fragmented. Rubira continues to lead the Servetus, which the German Boehme would end up joining, with whom he had previously shared other businesses, while Obella was looking for new partners, with greater ideological affinity, to found Zeltia S.A. in August 1939. (AU)

On strategic choices faced by large pharmaceutical laboratories and their effect on innovation risk under fuzzy conditions.

OBJECTIVES: We develop a fuzzy evaluation model that provides managers at different responsibility levels in pharmaceutical laboratories with a rich picture of their innovation risk as well as that of competitors. This would help them take better strategic decisions around the management of their present and future portfolio of clinical trials in an uncertain environment. Through three structured fuzzy inference systems (FISs), the model evaluates the overall innovation risk of the laboratories by capturing the financial and pipeline sides of the risk. METHODS AND MATERIALS: Three FISs, based on the Mamdani model, determine the level of innovation risk of large pharmaceutical laboratories according to their strategic choices. Two subsystems measure different aspects of innovation risk while the third one builds on the results of the previous two. In all of them, both the partitions of the variables and the rules of the knowledge base are agreed through an innovative 2-tuple-based method. With the aid of experts, we have embedded knowledge into the FIS and later validated the model. RESULTS: In an empirical application of the proposed methodology, we evaluate a sample of 31 large pharmaceutical laboratories in the period 2008-2013. Depending on the relative weight of the two subsystems in the first layer (capturing the financial and the pipeline sides of innovation risk), we estimate the overall risk. Comparisons across laboratories are made and graphical surfaces are analyzed in order to interpret our results. We have also run regressions to better understand the implications of our results. CONCLUSIONS: The main contribution of this work is the development of an innovative fuzzy evaluation model that is useful for analyzing the innovation risk characteristics of large pharmaceutical laboratories given their strategic choices. The methodology is valid for carrying out a systematic analysis of the potential for developing new drugs over time and in a stable manner while managing the risks involved. We provide all the necessary tools and datasets to facilitate the replication of our system, which also may be easily applied to other settings.

Measuring the efficiency of large pharmaceutical companies: an industry analysis.

This paper evaluates the relative efficiency of a sample of 37 large pharmaceutical laboratories in the period 2008-2013 using a data envelopment analysis (DEA) approach. We describe in detail the procedure followed to select and construct relevant inputs and outputs that characterize the production and innovation activity of these pharmaceutical firms. Models are estimated with financial information from Datastream, including R&D investment, and the number of new drugs authorized by the European Medicines Agency (EMA) and the US Food and Drug Administration (FDA) considering the time effect. The relative performances of these firms-taking into consideration the strategic importance of R&D-suggest that the pharmaceutical industry is a highly competitive sector given that there are many laboratories at the efficient frontier and many inefficient laboratories close to this border. Additionally, we use data from S&P Capital IQ to analyze 2071 financial transactions announced by our sample of laboratories as an alternative way to gain access to new drugs, and we link these transactions with R&D investment and DEA efficiency. We find that efficient laboratories make on average more financial transactions, and the relative size of each transaction is larger. However, pharmaceutical companies that simultaneously are more efficient and invest more internally in R&D announce smaller transactions relative to total assets.