Who Develops Innovations in Medicine for the Poor? Trends in Patent Applications Related to Medicines for HIV/AIDS, Tuberculosis, Malaria and Neglected Diseases

Who invents medicines for the poor of the world? This question becomes very important where the WTO allows low income countries to be unbound by the TRIPS agreement. This agreement concerns medicines for infectious diseases such as HIV/AIDS, tuberculosis and malaria. These diseases cause serious damage to low income countries. Under these circumstances, some scholars wonder if anyone will continue innovative activities related to treating these diseases. This paper sought to answer this question by collecting and analyzing patent data of medicines and vaccines for diseases using the database of the Japan Patent Office. Results indicate that private firms have led in innovation not only for global diseases such as HIV/AIDS but also diseases such as malaria that are spreading exclusively in low income countries. Innovation for the three infectious diseases is diverse among firms, and frequent patent applications by high-performing pharmaceutical firms appear prominent even after R&D expenditure, economies of scale, and economies of scope are taken into account.

A multinational SDI-based system to facilitate disaster risk management in the Andean Community

A useful strategy for improving disaster risk management is sharing spatial data across different technical organizations using shared information systems. However, the implementation of this type of system requires a large effort, so it is difficult to find fully implemented and sustainable information systems that facilitate sharing multinational spatial data about disasters, especially in developing countries. In this paper, we describe a pioneer system for sharing spatial information that we developed for the Andean Community. This system, called SIAPAD (Andean Information System for Disaster Prevention and Relief), integrates spatial information from 37 technical organizations in the Andean countries (Bolivia, Colombia, Ecuador, and Peru). SIAPAD was based on the concept of a thematic Spatial Data Infrastructure (SDI) and includes a web application, called GEORiesgo, which helps users to find relevant information with a knowledge-based system. In the paper, we describe the design and implementation of SIAPAD together with general conclusions and future directions which we learned as a result of this work.

Practica medicine Arnaldi de Villanoua

Pié de imp. tomado de colofón

p-medicine: a medical informatics platform for integrated large scale heterogeneous patient data

Secure access to patient data is becoming of increasing importance, as medical informatics grows in significance, to both assist with population health studies, and patient specific medicine in support of treatment. However, assembling the many different types of data emanating from the clinic is in itself a difficulty, and doing so across national borders compounds the problem. In this paper we present our solution: an easy to use distributed informatics platform embedding a state of the art data warehouse incorporating a secure pseudonymisation system protecting access to personal healthcare data. Using this system, a whole range of patient derived data, from genomics to imaging to clinical records, can be assembled and linked, and then connected with analytics tools that help us to understand the data. Research performed in this environment will have immediate clinical impact for personalised patient healthcare.

An Ant Colony System adaptation to deal with accessibility issues after a disaster

One of the main problems relief teams face after a natural or man-made disaster is how to plan rural road repair work tasks to take maximum advantage of the limited available financial and human resources. Previous research focused on speeding up repair work or on selecting the location of health centers to minimize transport times for injured citizens. In spite of the good results, this research does not take into account another key factor: survivor accessibility to resources. In this paper we account for the accessibility issue, that is, we maximize the number of survivors that reach the nearest regional center (cities where economic and social activity is concentrated) in a minimum time by planning which rural roads should be repaired given the available financial and human resources. This is a combinatorial problem since the number of connections between cities and regional centers grows exponentially with the problem size, and exact methods are no good for achieving an optimum solution. In order to solve the problem we propose using an Ant Colony System adaptation, which is based on ants? foraging behavior. Ants stochastically build minimal paths to regional centers and decide if damaged roads are repaired on the basis of pheromone levels, accessibility heuristic information and the available budget. The proposed algorithm is illustrated by means of an example regarding the 2010 Haiti earthquake, and its performance is compared with another metaheuristic, GRASP.

Sistema para integrar automáticamente datos públicos del NCBI en la plataforma de medicina personalizada p-medicine

En los últimos años ha habido un gran aumento de fuentes de datos biomédicos. La aparición de nuevas técnicas de extracción de datos genómicos y generación de bases de datos que contienen esta información ha creado la necesidad de guardarla para poder acceder a ella y trabajar con los datos que esta contiene. La información contenida en las investigaciones del campo biomédico se guarda en bases de datos. Esto se debe a que las bases de datos permiten almacenar y manejar datos de una manera simple y rápida. Dentro de las bases de datos existen una gran variedad de formatos, como pueden ser bases de datos en Excel, CSV o RDF entre otros. Actualmente, estas investigaciones se basan en el análisis de datos, para a partir de ellos, buscar correlaciones que permitan inferir, por ejemplo, tratamientos nuevos o terapias más efectivas para una determinada enfermedad o dolencia. El volumen de datos que se maneja en ellas es muy grande y dispar, lo que hace que sea necesario el desarrollo de métodos automáticos de integración y homogeneización de los datos heterogéneos. El proyecto europeo p-medicine (FP7-ICT-2009-270089) tiene como objetivo asistir a los investigadores médicos, en este caso de investigaciones relacionadas con el cáncer, proveyéndoles con nuevas herramientas para el manejo de datos y generación de nuevo conocimiento a partir del análisis de los datos gestionados. La ingestión de datos en la plataforma de p-medicine, y el procesamiento de los mismos con los métodos proporcionados, buscan generar nuevos modelos para la toma de decisiones clínicas. Dentro de este proyecto existen diversas herramientas para integración de datos heterogéneos, diseño y gestión de ensayos clínicos, simulación y visualización de tumores y análisis estadístico de datos. Precisamente en el ámbito de la integración de datos heterogéneos surge la necesidad de añadir información externa al sistema proveniente de bases de datos públicas, así como relacionarla con la ya existente mediante técnicas de integración semántica. Para resolver esta necesidad se ha creado una herramienta, llamada Term Searcher, que permite hacer este proceso de una manera semiautomática. En el trabajo aquí expuesto se describe el desarrollo y los algoritmos creados para su correcto funcionamiento. Esta herramienta ofrece nuevas funcionalidades que no existían dentro del proyecto para la adición de nuevos datos provenientes de fuentes públicas y su integración semántica con datos privados.---ABSTRACT---Over the last few years, there has been a huge growth of biomedical data sources. The emergence of new techniques of genomic data generation and data base generation that contain this information, has created the need of storing it in order to access and work with its data. The information employed in the biomedical research field is stored in databases. This is due to the capability of databases to allow storing and managing data in a quick and simple way. Within databases there is a variety of formats, such as Excel, CSV or RDF. Currently, these biomedical investigations are based on data analysis, which lead to the discovery of correlations that allow inferring, for example, new treatments or more effective therapies for a specific disease or ailment. The volume of data handled in them is very large and dissimilar, which leads to the need of developing new methods for automatically integrating and homogenizing the heterogeneous data. The p-medicine (FP7-ICT-2009-270089) European project aims to assist medical researchers, in this case related to cancer research, providing them with new tools for managing and creating new knowledge from the analysis of the managed data. The ingestion of data into the platform and its subsequent processing with the provided tools aims to enable the generation of new models to assist in clinical decision support processes. Inside this project, there exist different tools related to areas such as the integration of heterogeneous data, the design and management of clinical trials, simulation and visualization of tumors and statistical data analysis. Particularly in the field of heterogeneous data integration, there is a need to add external information from public databases, and relate it to the existing ones through semantic integration methods. To solve this need a tool has been created: the term Searcher. This tool aims to make this process in a semiautomatic way. This work describes the development of this tool and the algorithms employed in its operation. This new tool provides new functionalities that did not exist inside the p-medicine project for adding new data from public databases and semantically integrate them with private data.