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  • Biomedical Computing: Digitizing Life in the United States by Joseph November
  • Grischa Metlay
Joseph November. Biomedical Computing: Digitizing Life in the United States. Baltimore: Johns Hopkins University Press, 2012. xvi + 344 pp. Ill. $60.00 (978-1-4214-0468-4).

Today, computers have become as central to the work of biologists and medical professionals as pipettes and syringes. It is probably not too much of a stretch to claim that computers are now constitutive of what it means to conduct biological research and practice modern medicine. As such, Joseph November’s Biomedical Computing offers an important entree into a set of questions that have been previously overlooked by historians of biomedicine: How did computers make their way into biomedical research laboratories, hospitals, and doctors’ offices? What types of changes did they catalyze?

In raising these questions, November contributes to a growing and vibrant field of scholarship on biomedicine in the second half of the twentieth century. Through studies of laboratory techniques (e.g., tissue culture and immunopheno-typing) and diseases (e.g., cancer and multiple personality disorder), historians, sociologists, and anthropologists are beginning to identify the salient characteristics of the transition from scientific medicine to biomedicine. At the leading edge of this literature, scholars are turning their attention away from particular discoveries and looking more closely at the “biomedical platforms” or “infrastructures” that make discovery possible.1 While they differ in their empirical and normative conclusions, scholars of contemporary biomedicine agree that the transition has brought about closer alignments between biology and medicine, and that the rise of biomedicine cannot be meaningfully understood apart from the creation of tighter connections among industry, the state, the laboratory, and the clinic. [End Page 296]

Biomedical Computing speaks to many of the themes that run through work on contemporary biomedicine. Though computers made valuable contributions to some lines of highly quantitative biological research in the late-1940s (chapter 1), November traces the rise of biomedical computing to the National Institutes of Health in the 1950s. Chapter 2 shows that a small group of government bureaucrats were able to convince James Shannon, the director of NIH, to promote the use of computers in NIH’s intramural and extramural programs, despite the resistance of institute directors, who thought that computers represented an expensive and misguided initiative to mathematize biology. Chapter 3 examines the rise of two competing models of biomedical computing that coexisted in tension with one another (i.e., a centralized model that revolved around the shared use of powerful computers and a decentralized model that brought flexible but less powerful machines into individual laboratories). November suggests that NIH administrators and university scientists faced steep resistance because the promotion of computers was tied to a novel, and subversive, vision of the future of biology—a vision that imposed quantification and centralized administration on a field that remained attached to description and loosely coordinated small science. Although this new vision was by no means established during the period that November examines, his story shows that its ascendency was made possible by NIH initiatives that taught biologists how to use computers, along with advertising campaigns launched by computer companies (chapter 4). These efforts stimulated a demand for computers that did not exist beforehand, and once computers entered biomedical research laboratories, the process was irreversible.

November’s story is able to capture the mundane but highly consequential activities that shape biomedical platforms because it revolves around scientific administrators and programmatic visionaries. The result provides a nice illustration of some of the central lessons emerging from scholarship on the development of contemporary biomedicine—that novel techniques reorganize the practice of science in the process of opening up new avenues of inquiry, that competing platforms represent alternative models of scientific progress, and that the centralized initiatives of powerful institutions are often needed to force technological advancements on reluctant groups of practitioners. By detailing the activities of key individuals and institutions, Biomedical Computing lays the groundwork for future research on the variety of uses that biologists found for computers, the extent to which computers transformed biology into a mathematical endeavor, and the way that computers helped standardize medicine. Although November occasionally falls short of the ambitious goals that...

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