An Analysis of the Patent Linkage System and Development of the Biosimilar Industry in Taiwan

In 2019, as an effort to join the Trans-Pacific Partnership (TPP) Agreement (now Comprehensive and Progressive Agreement for Trans-Pacific Partnership (CPTPP)), Taiwan has implemented the patent linkage system which covers both small molecule generic drugs and large molecule biosimilar into the Pharmaceutical Affair Act. The system modeled after the U.S.’s patent linkage system designed for small molecule drugs under the Hatch Waxman Act (HWA). Based on the experience of the patent linkage system under the HWA, biosimilar industry representatives in Taiwan contended that the adoption of the patent linkage system will be detrimental to the development of local industry. By adopting patent linkage system, foreign biologics company would implement evergreening strategies to delay the marketing of locally produced biosimilar, conduct improper patent listing, and to abuse the granting of automatic stays. This article critically evaluates whether Taiwan’s patent linkage system could serve the dual goal of fostering biologic innovation and promoting biosimilar industry development by examining patent linkage systems for biosimialrs in the U.S, South Korea and Taiwan. This article argues that this dual goal could be achieved if the method of manufacturing patents could be included in patent listings and through a wider institutional collaboration between Taiwan Food and Drug Regulation Agency and Taiwan Intellectual Property Office

Progressor: Social navigation support through open social student modeling

The increased volumes of online learning content have produced two problems: how to help students to find the most appropriate resources and how to engage them in using these resources. Personalized and social learning have been suggested as potential ways to address these problems. Our work presented in this paper combines the ideas of personalized and social learning in the context of educational hypermedia. We introduce Progressor, an innovative Web-based tool based on the concepts of social navigation and open student modeling that helps students to find the most relevant resources in a large collection of parameterized self-assessment questions on Java programming. We have evaluated Progressor in a semester-long classroom study, the results of which are presented in this paper. The study confirmed the impact of personalized social navigation support provided by the system in the target context. The interface encouraged students to explore more topics attempting more questions and achieving higher success rates in answering them. A deeper analysis of the social navigation support mechanism revealed that the top students successfully led the way to discovering most relevant resources by creating clear pathways for weaker students. © 2013 Taylor and Francis Group, LLC

QuizMap: Open social student modeling and adaptive navigation support with TreeMaps

In this paper, we present a novel approach to integrate social adaptive navigation support for self-assessment questions with an open student model using QuizMap, a TreeMap-based interface. By exposing student model in contrast to student peers and the whole class, QuizMap attempts to provide social guidance and increase student performance. The paper explains the nature of the QuizMap approach and its implementation in the context of self-assessment questions for Java programming. It also presents the design of a semester-long classroom study that we ran to evaluate QuizMap and reports the evaluation results. © 2011 Springer-Verlag Berlin Heidelberg

Motivational Social Visualizations for Personalized E-Learning

A large number of educational resources is now available on the Web to support both regular classroom learning and online learning. However, the abundance of available content produces at least two problems: how to help students find the most appropriate resources, and how to engage them into using these resources and benefiting from them. Personalized and social learning have been suggested as potential methods for addressing these problems. Our work presented in this paper attempts to combine the ideas of personalized and social learning. We introduce Progressor + , an innovative Web-based interface that helps students find the most relevant resources in a large collection of self-assessment questions and programming examples. We also present the results of a classroom study of the Progressor +  in an undergraduate class. The data revealed the motivational impact of the personalized social guidance provided by the system in the target context. The interface encouraged students to explore more educational resources and motivated them to do some work ahead of the course schedule. The increase in diversity of explored content resulted in improving students’ problem solving success. A deeper analysis of the social guidance mechanism revealed that it is based on the leading behavior of the strong students, who discovered the most relevant resources and created trails for weaker students to follow. The study results also demonstrate that students were more engaged with the system: they spent more time in working with self-assessment questions and annotated examples, attempted more questions, and achieved higher success rates in answering them