Balancing Incentives: The Tension Between Basic and Applied Research

This paper presents empirical evidence that the intensity of research workers' incentives for the distinct tasks of basic and applied research are positively associated with each other. We relate this finding to the prediction of the theoretical literature that when effort is multi-dimensional, firms will balance' the provision of incentives; when incentives are strong along one dimension, firms will set high-powered incentives for effort along other dimensions which compete for the worker's effort and attention (Holmstrom and Milgrom, 1991). We test for this effect in the context of pharmaceutical research using detailed data on individual research programs financed by private firms. Consistent with the complementarity hypothesis, we find strong evidence that firms who provide strong promotion-based incentives for individuals to invest in fundamental or basic' research also provide more intense incentives for success in applied research through the capital budgeting process. The intensity of these bonus' incentives is weaker in firms who use a more centralized research budgeting process. We interpret this latter finding as providing support for theories which emphasize substitutability between contractible and non-contractible signals of effort (Baker, Gibbons, and Murphy, 1994).

The Diffusion of Science-Driven Drug Discovery: Organizational Change in Pharmaceutical Research

Recent work linking the adoption of key organizational practices to productivity raises an important question: if adoption increases productivity so dramatically, why does adoption across an industry take so long? This paper explores this question in the context of one particularly interesting practice, the adoption of science driven drug discovery by the modern pharmaceutical industry. Over the past two decades, the established pharmaceutical industry has slowly shifted towards a more science-oriented drug discovery: (a) adopters experienced substantially higher rates of R&D after the late 1970s and (b) the rate of adoption across the industry was extremely slow. Motivated by the apparent contradiction between large boosts in performance and slow rates of adoption, this paper characterizes the sources of differences in rates of adoption between 1980 and 1993. The principal finding is that adoption of a science-oriented research approach was a function of initial conditions, or subject to 'state dependence': some firms simply began the sample period at a much higher level of science orientation. Moreover, while these effects attenuated over time, our empirical results suggest that it took more than ten years before adoption was unrelated to initial conditions. In addition, consistent with theories developed in the context of technology adoption, we find that relative diffusion rates depend on the product market positioning of firms. More surprisingly, adoption rates are seperately driven by the composition of sales within the firm. This latter finding suggests the potential importance of differences among firms in terms of the internal structure of power and attention, an area which has received only a small amount of theoretical attention.

Text Mining for Chemical Compounds

Exploring the chemical and biological space covered by patent and journal publications is crucial in early- stage medicinal chemistry activities. The analysis provides understanding of compound prior art, novelty checking, validation of biological assays, and identification of new starting points for chemical exploration. Extracting chemical and biological entities from patents and journals through manual extraction by expert curators can take substantial amount of time and resources. Text mining methods can help to ease this process. In this book, we addressed the lack of quality measurements for assessing the correctness of structural representation within and across chemical databases; lack of resources to build text-mining systems; lack of high performance systems to extract chemical compounds from journals and patents; and lack of automated systems to identify relevant compounds in patents. The consistency and ambiguity of chemical identifiers was analyzed within and between small- molecule databases in Chapter 2 and Chapter 3. In Chapter 4 and Chapter 7 we developed resources to enable the construction of chemical text-mining systems. In Chapter 5 and Chapter 6, we used community challenges (BioCreative V and BioCreative VI) and their corresponding resources to identify mentions of chemical compounds in journal abstracts and patents. In Chapter 7 we used our findings in previous chapters to extract chemical named entities from patent full text and to classify the relevancy of chemical compounds

Do Stronger Patents Induce More Innovation? Evidence from the 1988 Japanese Patent Law Reforms

Does an expansion of patent scope induce more innovative effort by firms? This article provides evidence on this question by examining firm responses to the Japanese patent reforms of 1988. Interviews with practitioners suggest the reforms significantly expanded the scope of patent rights in Japan, but that the average response in terms of additional R&D effort and innovative output was quite modest. Interviews also suggest that firm organizational structure is an important determinant of the level of response. Econometric analysis using Japanese and U.S. patent data on 307 Japanese firms confirms that the magnitude of the response is quite small.

Automatic identification of relevant chemical compounds from patents

In commercial research and development projects, public disclosure of new chemical compounds often takes place in patents. Only a small proportion of these compounds are published in journals, usually a few years after the patent. Patent authorities make available the patents but do not provide systematic continuous chemical annotations. Content databases such as Elsevier’s Reaxys provide such services mostly based on manual excerptions, which are time-consuming and costly. Automatic text-mining approaches help overcome some of the limitations of the manual process. Different text-mining approaches exist to extract chemical entities from patents. The majority of them have been developed using sub-sections of patent documents and focus on mentions of compounds. Less attention has been given to relevancy of a compound in a patent. Relevancy of a compound to a patent is based on the patent’s context. A relevant compound plays a major role within a patent. Identification of relevant compounds reduces the size of the extracted data and improves the usefulness of patent resources (e.g. supports identifying the main compounds). Annotators of databases like Reaxys only annotate relevant compounds. In this study, we design an automated system that extracts chemical entities from patents and classifies their relevance. The goldstandard set contained 18 789 chemical entity annotations. Of these, 10% were relevant compounds, 88% were irrelevant and 2% were equivocal. Our compound recognition system was based on proprietary tools. The performance (F-score) of the system on compound recognition was 84% on the development set and 86% on the test set. The relevancy classification system had an F-score of 86% on the development set and 82% on the test set. Our system can extract chemical compounds from patents and classify their relevance with high performance. This enables the extension of the Reaxys database by means of automation

DRIVER Technology Watch Report

This report is part of the Discovery Workpackage (WP4) and is the third report out of four deliverables. The objective of this report is to give an overview of the latest technical developments in the world of digital repositories, digital libraries and beyond, in order to serve as theoretical and practical input for the technical DRIVER developments, especially those focused on enhanced publications. This report consists of two main parts, one part focuses on interoperability standards for enhanced publications, the other part consists of three subchapters, which give a landscape picture of current and surfacing technologies and communities crucial to DRIVER. These three subchapters contain the GRID, CRIS and LTP communities and technologies. Every chapter contains a theoretical explanation, followed by case studies and the outcomes and opportunities for DRIVER in this field

Useless Information: Genetic Patenting, the Usefulness Requirement, and the Effect on the “Big Freeze”

This note considers the current state of affairs regarding patentability in the field of biotechnology, especially that of genes and DNA. Part II gives a brief background of patents in general, including the requirements that must be met for a patent to be granted, the way in which the patent process works, and the options available to a patent holder once a patent has been granted. Part III explores the history of biotechnology patents. Part IV takes a look at the relationship between patents and biotechnology, and sheds light on some of the common arguments both in favor of and against the patenting of genetic material. Part V investigates solutions proposed to remedy the problems raised in Part III, and considers a different approach to fixing the patent system as it relates to biotechnology. Part VI concludes this note by proposing a slight adaptation to the existing patent system

Chemical Information Bulletin

Periodic supplement for "the regular journals of the American Chemical Society," containing annotated bibliographies of chemical documentation literature as well as information about meetings, conferences, awards, scholarships, and other news from the American Chemical Society (ACS) Division of Chemical Literature