@article{oai:nagoya.repo.nii.ac.jp:02002124, author = {Takahara, Shizuko and Saito, Toshiki I. and Imai, Yasuhito and Kawakami, Takahiro and Murayama, Toshinori}, issue = {1}, journal = {Nagoya Journal of Medical Science}, month = {Feb}, note = {Submitting data compliant with the Clinical Data Interchange Standards Consortium (CDISC) standards is mandatory for new drug applications (NDAs). The standards set by CDISC are widely adopted in the pharmaceutical business world. Introduction of CDISC standards in academia can be necessary to reduce labor, resolve the shortage of data managers in academia, and gain new knowledge through standardized data accumulation. However, the introduction of CDISC standards has not progressed in communities within the academia that do not apply for NDAs. Therefore, herein, we created study data tabulation model (SDTM)-compliant datasets within the academia, without outsourcing, to reduce costs associated with investigator-initiated clinical trials. First, we input data from paper case report forms (CRFs) into an electronic data capture system with minimal function for paper CRFs, “Ptosh,” which is compatible with SDTM. Then, we developed a generic program to convert data exported from Ptosh into fully SDTM-compliant datasets. The consistency was then verified with an SDTM validator, Pinnacle21 Community V3.0.1 (P21C). This resulted in generation of SDTM datasets, resolving all “Rejects” in P21C, thereby achieving the required quality level. Although Ptosh directly exports data in SDTM format, manual mapping of items on CRFs to SDTM variables prepared in Ptosh is necessary. SDTM mapping requires extensive knowledge and skills, and it was assumed that mapping is challenging for the staff without in-depth knowledge of CDISC standards and datasets. Therefore, for CDISC dissemination in academia, it is crucial to secure the staff, time, and funding to acquire the knowledge.}, pages = {120--132}, title = {A use-case analysis of Clinical Data Interchange Standards Consortium/Study Data Tabulation Model in academia in an investigator-initiated clinical trial}, volume = {84}, year = {2022} }