Specific pathologist responses for Standard for Exchange of Nonclinical Data (SEND).

The Standard for Exchange of Nonclinical Data (SEND), introduced by the US Food and Drug Administration (FDA), is a scheme for the computerization, electronic application, and screening of preclinical data. Since its establishment, related organizations have been working together to implement SEND. However, it is difficult for individual pharmaceutical companies that often outsource to achieve complete compliance with SEND; hence, the cooperation of contract research organizations (CROs) and SEND Registered Solution Providers (RSPs) is indispensable. In SEND, most data, including those on pathology findings, are converted into controlled terminology (CT), but it is not a simple process to convert findings or levels of severity in the field of pathology, which is a descriptive science. The authors have successfully completed an FDA trial submission for a toxicology test conducted at a CRO and in doing so acquired important knowledge. This article presents a clear picture of such important knowledge from a pathologist's viewpoint.

Therapeutic Area Data Standards for Autosomal Dominant Polycystic Kidney Disease: A Report From the Polycystic Kidney Disease Outcomes Consortium (PKDOC).

Data standards provide a structure for consistent understanding and exchange of data and enable the integration of data across studies for integrated analysis. There is no data standard applicable to kidney disease. We describe the process for development of the first-ever Clinical Data Interchange Standards Consortium (CDISC) data standard for autosomal dominant polycystic kidney disease (ADPKD) by the Polycystic Kidney Disease Outcomes Consortium (PKDOC). Definition of common data elements and creation of ADPKD-specific data standards from case report forms used in long-term ADPKD registries, an observational cohort (Consortium for Radiologic Imaging Studies of Polycystic Kidney Disease [CRISP] 1 and 2), and a randomized clinical trial (Halt Progression of Polycystic Kidney Disease [HALT-PKD]) are described in detail. This data standard underwent extensive review, including a global public comment period, and is now available online as the first PKD-specific data standard (www.cdisc.org/therapeutic). Submission of clinical trial data that use standard data structures and terminology will be required for new electronic submissions to the US Food and Drug Administration for all disease areas by the end of 2016. This data standard will allow for the mapping and pooling of available data into a common data set in addition to providing a foundation for future studies, data sharing, and long-term registries in ADPKD. This data set will also be used to support the regulatory qualification of total kidney volume as a prognostic biomarker for use in clinical trials. The availability of consensus data standards for ADPKD has the potential to facilitate clinical trial initiation and increase sharing and aggregation of data across observational studies and among completed clinical trials, thereby improving our understanding of disease progression and treatment.

Responses to the Standard for Exchange of Nonclinical Data (SEND) in non-US countries.

The Standard for the Exchange of Nonclinical Data (SEND), adopted by the US FDA, is part of a set of regulations and guidances requiring the submission of standardized electronic study data for nonclinical and clinical data submissions. SEND is the nonclinical implementation of SDTM (Study Data Tabulation Model), the standard electronic format for clinical regulatory submissions to FDA. SEND, SDTM, and the associated Controlled Terminology have been developed by CDISC (Clinical Data Interchange Standards Consortium). In order to successfully implement SEND, interdisciplinary contributions between sponsors and CROs, need a model for task allocation. This is being undertaken by the Pharmaceutical Users Software Exchange (PhUSE). Because SEND is currently the preferred submission format of the US FDA only and will become required by it starting in December 2016, only American academic societies and companies are actively involved. An exception to this is the INHAND initiative, which leads the way in standardizing terminology for toxicological pathology. On the other hand, international globalization of other clinical and nonclinical practices is not feasible because there are substantial differences between the US and non-US countries in CRO involvement in drug development. Thus, non-US countries must consider and develop approaches to SEND that meet their needs. This paper summarizes the activities of the major organizations involved in SEND development and implementation, discusses the effective use of SEND, and details a compliance scheme (research material of the Showa University School of Medicine) illustrating how pharmaceutical companies can complete a large amount of work up to an FDA application with the effective utilization of CROs and solution providers.

Automated Modeling of Clinical Narrative with High Definition Natural Language Processing Using Solor and Analysis Normal Form.

OBJECTIVE: One important concept in informatics is data which meets the principles of Findability, Accessibility, Interoperability and Reusability (FAIR). Standards, such as terminologies (findability), assist with important tasks like interoperability, Natural Language Processing (NLP) (accessibility) and decision support (reusability). One terminology, Solor, integrates SNOMED CT, LOINC and RxNorm. We describe Solor, HL7 Analysis Normal Form (ANF), and their use with the high definition natural language processing (HD-NLP) program. METHODS: We used HD-NLP to process 694 clinical narratives prior modeled by human experts into Solor and ANF. We compared HD-NLP output to the expert gold standard for 20% of the sample. Each clinical statement was judged "correct" if HD-NLP output matched ANF structure and Solor concepts, or "incorrect" if any ANF structure or Solor concepts were missing or incorrect. Judgements were summed to give totals for "correct" and "incorrect". RESULTS: 113 (80.7%) correct, 26 (18.6%) incorrect, and 1 error. Inter-rater reliability was 97.5% with Cohen's kappa of 0.948. CONCLUSION: The HD-NLP software provides useable complex standards-based representations for important clinical statements designed to drive CDS.