Mapping Collaborative Work and Innovation in Biomedicine

Abstract

This paper analyses a major episode in contemporary biomedical research using a new semi-quantitative approach. In the late 1970s, immunologists began producing new kinds of antibodies targeting molecules on the surface of normal and malignant blood cells. These tools quickly transformed biomedical research in immunology and oncology-hematology. Laboratories worldwide produced thousands of these new reagents and reorganized the classification, diagnosis, and prognosis of diseases such as leukemia and the lymphomas. The rapid development of these reagents initially generated considerable confusion. To avoid the impending chaos, researchers in the field, officially supported by the World Health Organization and the International Union of Immunological Societies, launched an ongoing series of distributed workshops that led to the establishment of a nomenclature of antibody reagents and cell surface molecules. The First Workshop (1981-82) mobilized 54 research groups from 14 countries and resulted in the establishment of 15 antibody/molecule categories. By the late 1990s the number of these categories had increased to more than 247 and the number of participating laboratories had risen to more than 500. Sociological analyses of this kind of large-scale collaborative research usually adopt one of two equally unsatisfactory alternatives: either they provide thick descriptions of selected sites, thus missing the figurational dimension of the collaborative network, or they attempt to account for figurational complexity by reducing it to a few quantitative indicators, thus destroying for all practical purposes the very phenomena under investigation. To avoid these two alternatives, we opted for a combination of ethnographic methods (interviews, content analysis) and a computer-based analysis of the more than 6000 antibodies examined during the first six workshops, using Réseau-Lu, a software program specifically designed for the treatment of heterogeneous relational data.