Technology transfer in Britain: the case of monoclonal antibodies

In 1975 two Cambridge scientists published a short article in Nature which announced the discovery of monoclonal antibodies. The article concluded ‘Such cultures could be valuable for medical and industrial use’. The interest which developed by the end of the decade in the industrial and financial possibilities of the new prospects opening up in biotechnology was to throw the apparent ‘failure’ to follow‐up the potentialities of this discovery into a public prominence rarely achieved by scientific discoveries. By the time Mrs Thatcher came to power it had become a scandal, another example of Britain's apparent inability to exploit effectively the brilliance of its scientific base. It was to explore both the process of scientific discovery and the conditions in Cambridge which nurtured it, and the issues which this particular discovery raised in the area of technology transfer (and the changes of policy that ensued), that the Wellcome Trust's History of Twentieth Century Medicine Group and the Institute of Contemporary British History organised this special witness seminar. It was held at the Wellcome Trust in London on 24 September 1993. The seminar was chaired by Sir Christopher Booth and introduced by Dr Robert Bud of the Science Museum. Those participating included the two authors of the Nature article, Dr César Milstein and Dr Georges Köhler, who received a Nobel Prize for their research, Dr Basil Bard (National Research Development Corporation [NRDC] 1950–74), Sir James Gowans (Secretary of the Medical Research Council [MRC] 1977–87), Sir John Gray (Secretary of the MRC 1968–77), John Newell (BBC World Service science correspondent 1969–79), Dr David Owen (MRC), and Dr David Secher (Laboratory of Molecular Biology [LMB], Cambridge). There were also contributions from Dr Ita Askonas (former head of immunology at the National Institute for Medical Research), Dr John Galloway (former member of MRC headquarters staff), Dr David Tyrrell (former Director, MRC Common Cold Unit), Professor Miles Weatherall (head of Therapeutic Research Division, Wellcome Research Laboratories 1967–75), Dr Guil Winchester (post‐doctoral fellow, Wellcome Institute for the History of Medicine), and Dr Peter Williams (former Director of the Wellcome Trust). The organisers would like to thank the Wellcome Trust for hosting and sponsoring the seminar. We would like to dedicate this publication to the memory of Georges Köhler, who sadly died in April 1995 before this could appear.

3D Reconstruction of Medical Images from Slices Automatically Landmarked with Growing Neural Models

In this study, we utilise a novel approach to segment out the ventricular system in a series of high resolution T1-weighted MR images. We present a brain ventricles fast reconstruction method. The method is based on the processing of brain sections and establishing a fixed number of landmarks onto those sections to reconstruct the ventricles 3D surface. Automated landmark extraction is accomplished through the use of the self-organising network, the growing neural gas (GNG), which is able to topographically map the low dimensionality of the network to the high dimensionality of the contour manifold without requiring a priori knowledge of the input space structure. Moreover, our GNG landmark method is tolerant to noise and eliminates outliers. Our method accelerates the classical surface reconstruction and filtering processes. The proposed method offers higher accuracy compared to methods with similar efficiency as Voxel Grid.

Analyzing and Modeling Medical Data on Distributed Computing Infrastructures

Researchers want to analyse Health Care data which may requires large pools of compute and data resources. To have them they need access to Distributed Computing Infrastructures (DCI). To use them it requires expertise which researchers may not have. Workflows can hide infrastructures. There are many workflow systems but they are not interoperable. To learn a workflow system and create workflows in a workflow system may require significant effort. Considering these efforts it is not reasonable to expect that researchers will learn new workflow systems if they want to run workflows of other workflow systems. As a result, the lack of interoperability prevents workflow sharing and a vast amount of research efforts is wasted. The FP7 Sharing Interoperable Workflow for Large-Scale Scientific Simulation on Available DCIs (SHIWA) project developed the Coarse-Grained Interoperability (CGI) to enable workflow sharing. The project created the SHIWA Simulation Platform (SSP) to support CGI as a production-level service. The paper describes how the CGI approach can be used for analysis and simulation in Health Care.

Image, video and 3D data registration: medical, satellite and video processing applications with quality metrics

Data registration refers to a series of techniques for matching or bringing similar objects or datasets together into alignment. These techniques enjoy widespread use in a diverse variety of applications, such as video coding, tracking, object and face detection and recognition, surveillance and satellite imaging, medical image analysis and structure from motion. Registration methods are as numerous as their manifold uses, from pixel level and block or feature based methods to Fourier domain methods. This book is focused on providing algorithms and image and video techniques for registration and quality performance metrics. The authors provide various assessment metrics for measuring registration quality alongside analyses of registration techniques, introducing and explaining both familiar and state–of–the–art registration methodologies used in a variety of targeted applications.