شبکه سازی دانش برای حمایت از توسعه محصول جدید پزشکی
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|2715||2007||19 صفحه PDF||سفارش دهید||10824 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : Decision Support Systems, Volume 43, Issue 4, August 2007, Pages 1255–1273
New product development (NPD) in the pharmaceutical industry is very knowledge intensive. Knowledge generated and used during medical NPD processes is fragmented and distributed across various phases and artifacts. Many challenges in medical NPD can be addressed by the integration of this fragmented knowledge. We propose the creation and use of knowledge networks to address these challenges. Based on a case study conducted in a leading pharmaceutical company, we have developed a knowledge framework that represents knowledge fragments that need to be integrated to support medical NPD. We have also developed a prototype system that supports knowledge integration using knowledge networks. We illustrate the capabilities of the system through scenarios drawn from the case study. Qualitative validation of our approach is also presented.
The pharmaceutical industry occupies an important position in developed economies both due to the tremendous impact it has on the daily life as well as its extremely capital intensive nature. In the USA, Food and Drug Administration (FDA) alone regulates over $1 trillion worth of medical devices, drugs, biologics, and food products . According to Association of the British Pharmaceutical Industry (ABPI), pharmaceuticals are one of Britain's leading manufacturing sectors, bringing in a trade surplus of £3.6 billion with exports valued at £11.9 billion . As it represents a significant component of the developed economies, any improvements in the management of critical processes in this industry are likely to have enormous economic impact. Pharmaceutical firms depend heavily upon their ability to rapidly develop and introduce new products into the market. In fact, product development speed directly impacts their financial bottom-line as well as their ability to satisfy unmet medical needs of patients. However, development of new medical products is complex and time-consuming. It takes anywhere between 7 and 17 years and several millions to billions of dollars to launch new medical products . Some of the factors contributing to the length, cost, and uncertainty of this process include: • The stringent regulatory requirements of governmental entities like the FDA requiring the maintenance of design history for every medical product to show that the products were developed as per the approved plan and with extensive clinical trials, • Medical products are used to treat human beings whose well-being and safety are of utmost importance. Failure of the product can have serious consequences. • Increasing possibilities for therapeutic intervention brought about by newer technologies, and • Enormous investments required in research and development, and testing. The regulatory load faced by pharmaceutical new product development (NPD) organizations is increasing to the point of overload. More records of increasing complexity will be under the scrutiny of a number of authorities as emerging markets develop . For example, manufacturers have to satisfy different sets of requirements for the products marketed in the European Union which may be significantly different from those of the FDA. Furthermore, this industry faces very low success rate in NPD; vast majority of investigational products that enter clinical trials fail . As a result of these challenges, medical NPD teams are constantly seeking novel ways to improve development processes, while at the same time ensuring the safety of the products under development. Effective knowledge management offers potential for such improvements in this knowledge intensive industry which draws on a variety of knowledge sources . As the knowledge capital acquired by the firms during the development process is the primary source of competitiveness in this industry, it is critical to capture, communicate, and reuse this knowledge gained from various sources . However, long development time-frames and the distributed nature of the research and development process across organizational and geographical boundaries exacerbate the fragmentation of knowledge generated and used across the different phases of the NPD life cycle . Currently, pharmaceutical product development organizations use commercial document management systems to record NPD design history . These systems place significant restrictions on the type and granularity of knowledge that can be recorded. Also, these systems do not provide adequate support to integrate knowledge that is scattered throughout the various phases and artifacts of the NPD process . Our research is based on the premise that, in order to effectively manage knowledge in the medical NPD process, techniques to integrate fragmented knowledge chunks are essential. A critical problem in facilitating the integration of knowledge to support NPD is that there has been little attention focused on providing specific guidelines to medical product developers on how to effectively integrate essential knowledge elements so that they are useful throughout the product life cycle . In this research, we address this issue by developing an approach to seamlessly integrate fragmented knowledge using knowledge networks. Semantic knowledge networks provide the ability to describe and follow the life of a physical or conceptual artifact. These have been used as effective solutions to support knowledge integration in knowledge intensive processes in multiple domains . Motivated by their effectiveness in supporting knowledge intensive processes, we propose the creation and use of knowledge networks to facilitate integration of knowledge fragments that are generated and used in medical NPD. The development of a knowledge network should be guided by the unique characteristics of the medical NPD domain. Based on this premise, we address the following key research questions: (1) What are the elements of a knowledge network that can facilitate knowledge integration in medical NPD? and (2) What functionalities should be provided in a system that supports the creation and use of knowledge networks to facilitate knowledge integration in medical NPD? The paper is organized as follows: Section 2 provides the background on the process of medical NPD, along with unique issues in this area. We draw from the literature on knowledge integration for supporting medical NPD. We then present knowledge networking as an approach for knowledge integration to support NPD in this domain. This is followed by the description of a case study in Section 3. Based on our case study and literature review, we draw the requirements that must be satisfied by the proposed approach. We then present our knowledge integration framework. Section 4 presents our prototype system. In Section 5, we present the preliminary qualitative evaluation of the usefulness of our approach. Section 6 presents the contributions of our approach and concludes with limitations and future research.
نتیجه گیری انگلیسی
6.1. Contributions Our approach to knowledge integration contributes to the current research and practice in the following ways: 1. It proposes a novel approach to knowledge integration in the medical NPD process 2. It presents the HLK as a ‘proof of concept’ to support knowledge integration in medical NPD 3. It provides preliminary evaluation of the usefulness of our approach in improving medical NPD. This study is among the first to examine knowledge integration in detail in this domain. Knowledge integration is one of the major challenges in pharmaceutical industry because of the tremendous impact it has on NPD process. Our knowledge integration framework provides support for a wide range of NPD processes to accommodate regulatory standards and guidelines specified for various phases. Also, it allows customization to accommodate the needs of individual scientists and designers interested in different aspect of the medical NPD process. Further, it provides a mechanism for integrating various sources of knowledge generated and used throughout the medical NPD process. This knowledge is captured along with the wide range of contextual factors and rationale which allows for contextual interpretation of information enhancing re-usability of the knowledge. The layered approach proposed here provides an excellent mechanism to abstract out the details while simultaneously providing the capability to customize the framework for situated knowledge capture and use. With access to integrated knowledge networks, project participants can get a comprehensive crosscutting view of the entire medical NPD process which can enhance their ability to see how their decisions affect wide range of other decisions and artifacts. It is likely to help in the early identification and mitigation of the risks that threaten the product development. By capturing FDA guidelines in the knowledge framework, record-keeping of various decisions is made more manageable. This can allow for rapid review and approval process by regulatory agencies for ensuring new product efficacy and safety. Furthermore, reuse of knowledge can speed up the development process by reducing time-to-market, a critical factor that underlies the financial bottom-line of pharmaceutical organizations. The knowledge framework facilitated by our prototype provides an excellent mechanism to fully integrate knowledge fragmented across the large array of diverse information technologies to address diverse information needs of stakeholders involved in the process. 6.2. Limitations and future research Organizational issues such as the development of an organizational climate that promotes knowledge sharing and the role of incentives in this process have not been addressed in our research. Though overhead involved in managing and integrating vast amounts of knowledge is significant, since NPD in this domain is regulated and the cost of errors is extremely high, this poses a much lesser concern when compared to NPD in other domains. However, the examination of the impact of overhead involved in documenting knowledge during NPD is the focus of future research. The identification of technical, organizational, and environmental factors that facilitate and impede the development of knowledge networks is a topic for future research. Furthermore, issues around security, administrative processes, data ownership, access, responsibility and control need to be addressed . When operating in heavily regulated environment, one needs to find the right balance between information transparency and intellectual property rights, confidentiality, and legal concerns. We are currently planning a detailed empirical evaluation of the effectiveness of the framework and prototype in improving the process of NPD. Future field research will also focus on investigating the impact of similarity in shared knowledge content and length of communications paths  on knowledge integration using knowledge networks.