{"title":"药物开发的生产力:一个系统的回顾","authors":"Takeshi Akiyama, S. Sengoku","doi":"10.23919/PICMET.2019.8893968","DOIUrl":null,"url":null,"abstract":"The evaluation of the productivity of research and development (R&D) is crucial for the management of pharmaceutical businesses, and various methods, indicators, and proposals for R&D improvement have been investigated; however, there is no consensus on a unified criteria. To resolve this issue, we present a comprehensive review of previous studies on the topic. Publication databases were searched for all relevant studies related to the following: the pharmaceutical industry, R&D, and productivity; a total of 6,357 publications were obtained. Through in-depth screening, 190 publications were selected and subsequently reviewed. As a result, methods for the evaluation of pharmaceutical R&D were classified into four major approaches: R&D cost, regression analysis, ratio analysis and data envelope analysis (DEA). The characteristics of each of these approaches were examined from the following three perspectives: the pharmaceutical industry-level, company-level, and project-level. Furthermore, several elements were identified that explain the significant decrease in pharmaceutical R&D productivity: the sustainability of a business model; increase in R&D expenditure; effectiveness of outsourcing; size of the company; and premiums and amortization with mergers and acquisition (M&A). By forming an intellectual basis for the evaluation procedures, the present study has contributed to the theory of R&D management and to the practices used in the pharmaceutical industry.","PeriodicalId":390110,"journal":{"name":"2019 Portland International Conference on Management of Engineering and Technology (PICMET)","volume":"40 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2019-08-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","resultStr":"{\"title\":\"The Productivity of Drug Development: A Systematic Review\",\"authors\":\"Takeshi Akiyama, S. Sengoku\",\"doi\":\"10.23919/PICMET.2019.8893968\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The evaluation of the productivity of research and development (R&D) is crucial for the management of pharmaceutical businesses, and various methods, indicators, and proposals for R&D improvement have been investigated; however, there is no consensus on a unified criteria. To resolve this issue, we present a comprehensive review of previous studies on the topic. Publication databases were searched for all relevant studies related to the following: the pharmaceutical industry, R&D, and productivity; a total of 6,357 publications were obtained. Through in-depth screening, 190 publications were selected and subsequently reviewed. As a result, methods for the evaluation of pharmaceutical R&D were classified into four major approaches: R&D cost, regression analysis, ratio analysis and data envelope analysis (DEA). The characteristics of each of these approaches were examined from the following three perspectives: the pharmaceutical industry-level, company-level, and project-level. Furthermore, several elements were identified that explain the significant decrease in pharmaceutical R&D productivity: the sustainability of a business model; increase in R&D expenditure; effectiveness of outsourcing; size of the company; and premiums and amortization with mergers and acquisition (M&A). By forming an intellectual basis for the evaluation procedures, the present study has contributed to the theory of R&D management and to the practices used in the pharmaceutical industry.\",\"PeriodicalId\":390110,\"journal\":{\"name\":\"2019 Portland International Conference on Management of Engineering and Technology (PICMET)\",\"volume\":\"40 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2019-08-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"3\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2019 Portland International Conference on Management of Engineering and Technology (PICMET)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.23919/PICMET.2019.8893968\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2019 Portland International Conference on Management of Engineering and Technology (PICMET)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.23919/PICMET.2019.8893968","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The Productivity of Drug Development: A Systematic Review
The evaluation of the productivity of research and development (R&D) is crucial for the management of pharmaceutical businesses, and various methods, indicators, and proposals for R&D improvement have been investigated; however, there is no consensus on a unified criteria. To resolve this issue, we present a comprehensive review of previous studies on the topic. Publication databases were searched for all relevant studies related to the following: the pharmaceutical industry, R&D, and productivity; a total of 6,357 publications were obtained. Through in-depth screening, 190 publications were selected and subsequently reviewed. As a result, methods for the evaluation of pharmaceutical R&D were classified into four major approaches: R&D cost, regression analysis, ratio analysis and data envelope analysis (DEA). The characteristics of each of these approaches were examined from the following three perspectives: the pharmaceutical industry-level, company-level, and project-level. Furthermore, several elements were identified that explain the significant decrease in pharmaceutical R&D productivity: the sustainability of a business model; increase in R&D expenditure; effectiveness of outsourcing; size of the company; and premiums and amortization with mergers and acquisition (M&A). By forming an intellectual basis for the evaluation procedures, the present study has contributed to the theory of R&D management and to the practices used in the pharmaceutical industry.