Table of contents
  1. Story
  2. Slides
    1. Slide 1 Data Science for FDA RFI
    2. Slide 2 Overview
    3. Slide 3 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: FedBizOpps.gov
    4. Slide 4 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: Word
    5. Slide 5 Drugs @ FDA
    6. Slide 6 Drug Approvals and Databases
    7. Slide 7 FDA Acronyms & Abbreviations
    8. Slide 8 NIH NIDA Data Share: Home
    9. Slide 9 NIH NIDA Data Share: Data Share Files
    10. Slide 10 Data Science for FDA RFI: MindTouch Knowledge base
    11. Slide 11 Data Science for FDA RFI: MindTouch Attachments
    12. Slide 12 Data Science for FDA RFI: File Folder
    13. Slide 13 Data Science for FDA RFI: Excel Knowledge Base
    14. Slide 14 TIBCO Spotfire: Opening Screen
    15. Slide 15 TIBCO Spotfire: Add Data Tables
    16. Slide 16 TIBCO Spotfire: Make Inspired Discoveries About Your Data
    17. Slide 17 TIBCO Spotfire: Recommended Visualizations 1
    18. Slide 18 TIBCO Spotfire: Recommended Visualizations 2
    19. Slide 19 TIBCO Spotfire: Cover Page
    20. Slide 20 TIBCO Spotfire: PD Visualizations
    21. Slide 21 TIBCO Spotfire: PD Data
    22. Slide 22 Some Conclusions and Recommendations
  3. Spotfire Dashboard
  4. Research Notes
  5. Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data
    1. 1.0 Background
    2. 2.0 Purpose and Objectives
    3. 3.0 Functional Requirements
    4. 4.0 Non-functional Requirements
    5. 5.0 Additional Capabilities
    6. 6.0 Technical Information
    7. 7.0 RFI Requested Information
    8. 8.0 RFI Response Addenda
    9. 9.0 Response Instructions
  6. NIDA Data Share
    1. Purpose
    2. Protection of Human Subjects
    3. Data Formats
    4. Registration
  7. About NIDA
    1. Division of Pharmacotherapies and Medical Consequences of Drug Abuse (DPMCDA)
    2. Center for Clinical Trials Network (CCTN)
  8. Data Share Files
  9. Assessments Main Page
    1. By Assessment
    2. By Protocol
  10. Guidelines
    1. Registration Agreement
    2. Data Share Policy
  11. Other Links
  12. Frequently Asked Questions
    1. Do I need IRB approval to download data?
    2. How do I download data?
    3. Can I open the CSV data files using Excel?
    4. Can I open/import SAS XPT files using SPSS?
    5. How do I download multiple data files?
  13. Contact Us
  14. NIDA-CPU-0016
  15. Data Download
  16. Drug Approvals and Databases
    1. FDA Acronyms & Abbreviations
      1. Acronyms & Abbreviations File Download
  17. Drugs@FDA
    1. Drugs@FDA Frequently Asked Questions
      1. 1. What is the purpose of Drugs@FDA, and what are its main uses? 
      2. 2. What drug products are in Drugs@FDA? 
      3. 3. What drug products are not in Drugs@FDA?
      4. 4. Why doesn't Drugs@FDA include dietary supplements?
      5. 5. How can I find out if a generic drug is available for an innovator drug?
      6. 6. What information is available for each drug product in Drugs@FDA?
      7. 7. How can I search Drugs@FDA?
      8. 8. How do searches work in Drugs@FDA?
      9. 9. How often do you update Drugs@FDA?
      10. 10. Where does the information in Drugs@FDA come from?
      11. 11. How does Drugs@FDA compare with the Orange Book?
      12. 12.  What do the Chemical Type and Review Classification codes stand for?
      13. 13. Can I get a copy of the Drugs@FDA database?
      14. 14. How can I get further assistance?
  18. NEXT

Data Science for FDA RFI

Last modified
Table of contents
  1. Story
  2. Slides
    1. Slide 1 Data Science for FDA RFI
    2. Slide 2 Overview
    3. Slide 3 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: FedBizOpps.gov
    4. Slide 4 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: Word
    5. Slide 5 Drugs @ FDA
    6. Slide 6 Drug Approvals and Databases
    7. Slide 7 FDA Acronyms & Abbreviations
    8. Slide 8 NIH NIDA Data Share: Home
    9. Slide 9 NIH NIDA Data Share: Data Share Files
    10. Slide 10 Data Science for FDA RFI: MindTouch Knowledge base
    11. Slide 11 Data Science for FDA RFI: MindTouch Attachments
    12. Slide 12 Data Science for FDA RFI: File Folder
    13. Slide 13 Data Science for FDA RFI: Excel Knowledge Base
    14. Slide 14 TIBCO Spotfire: Opening Screen
    15. Slide 15 TIBCO Spotfire: Add Data Tables
    16. Slide 16 TIBCO Spotfire: Make Inspired Discoveries About Your Data
    17. Slide 17 TIBCO Spotfire: Recommended Visualizations 1
    18. Slide 18 TIBCO Spotfire: Recommended Visualizations 2
    19. Slide 19 TIBCO Spotfire: Cover Page
    20. Slide 20 TIBCO Spotfire: PD Visualizations
    21. Slide 21 TIBCO Spotfire: PD Data
    22. Slide 22 Some Conclusions and Recommendations
  3. Spotfire Dashboard
  4. Research Notes
  5. Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data
    1. 1.0 Background
    2. 2.0 Purpose and Objectives
    3. 3.0 Functional Requirements
    4. 4.0 Non-functional Requirements
    5. 5.0 Additional Capabilities
    6. 6.0 Technical Information
    7. 7.0 RFI Requested Information
    8. 8.0 RFI Response Addenda
    9. 9.0 Response Instructions
  6. NIDA Data Share
    1. Purpose
    2. Protection of Human Subjects
    3. Data Formats
    4. Registration
  7. About NIDA
    1. Division of Pharmacotherapies and Medical Consequences of Drug Abuse (DPMCDA)
    2. Center for Clinical Trials Network (CCTN)
  8. Data Share Files
  9. Assessments Main Page
    1. By Assessment
    2. By Protocol
  10. Guidelines
    1. Registration Agreement
    2. Data Share Policy
  11. Other Links
  12. Frequently Asked Questions
    1. Do I need IRB approval to download data?
    2. How do I download data?
    3. Can I open the CSV data files using Excel?
    4. Can I open/import SAS XPT files using SPSS?
    5. How do I download multiple data files?
  13. Contact Us
  14. NIDA-CPU-0016
  15. Data Download
  16. Drug Approvals and Databases
    1. FDA Acronyms & Abbreviations
      1. Acronyms & Abbreviations File Download
  17. Drugs@FDA
    1. Drugs@FDA Frequently Asked Questions
      1. 1. What is the purpose of Drugs@FDA, and what are its main uses? 
      2. 2. What drug products are in Drugs@FDA? 
      3. 3. What drug products are not in Drugs@FDA?
      4. 4. Why doesn't Drugs@FDA include dietary supplements?
      5. 5. How can I find out if a generic drug is available for an innovator drug?
      6. 6. What information is available for each drug product in Drugs@FDA?
      7. 7. How can I search Drugs@FDA?
      8. 8. How do searches work in Drugs@FDA?
      9. 9. How often do you update Drugs@FDA?
      10. 10. Where does the information in Drugs@FDA come from?
      11. 11. How does Drugs@FDA compare with the Orange Book?
      12. 12.  What do the Chemical Type and Review Classification codes stand for?
      13. 13. Can I get a copy of the Drugs@FDA database?
      14. 14. How can I get further assistance?
  18. NEXT

  1. Story
  2. Slides
    1. Slide 1 Data Science for FDA RFI
    2. Slide 2 Overview
    3. Slide 3 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: FedBizOpps.gov
    4. Slide 4 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: Word
    5. Slide 5 Drugs @ FDA
    6. Slide 6 Drug Approvals and Databases
    7. Slide 7 FDA Acronyms & Abbreviations
    8. Slide 8 NIH NIDA Data Share: Home
    9. Slide 9 NIH NIDA Data Share: Data Share Files
    10. Slide 10 Data Science for FDA RFI: MindTouch Knowledge base
    11. Slide 11 Data Science for FDA RFI: MindTouch Attachments
    12. Slide 12 Data Science for FDA RFI: File Folder
    13. Slide 13 Data Science for FDA RFI: Excel Knowledge Base
    14. Slide 14 TIBCO Spotfire: Opening Screen
    15. Slide 15 TIBCO Spotfire: Add Data Tables
    16. Slide 16 TIBCO Spotfire: Make Inspired Discoveries About Your Data
    17. Slide 17 TIBCO Spotfire: Recommended Visualizations 1
    18. Slide 18 TIBCO Spotfire: Recommended Visualizations 2
    19. Slide 19 TIBCO Spotfire: Cover Page
    20. Slide 20 TIBCO Spotfire: PD Visualizations
    21. Slide 21 TIBCO Spotfire: PD Data
    22. Slide 22 Some Conclusions and Recommendations
  3. Spotfire Dashboard
  4. Research Notes
  5. Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data
    1. 1.0 Background
    2. 2.0 Purpose and Objectives
    3. 3.0 Functional Requirements
    4. 4.0 Non-functional Requirements
    5. 5.0 Additional Capabilities
    6. 6.0 Technical Information
    7. 7.0 RFI Requested Information
    8. 8.0 RFI Response Addenda
    9. 9.0 Response Instructions
  6. NIDA Data Share
    1. Purpose
    2. Protection of Human Subjects
    3. Data Formats
    4. Registration
  7. About NIDA
    1. Division of Pharmacotherapies and Medical Consequences of Drug Abuse (DPMCDA)
    2. Center for Clinical Trials Network (CCTN)
  8. Data Share Files
  9. Assessments Main Page
    1. By Assessment
    2. By Protocol
  10. Guidelines
    1. Registration Agreement
    2. Data Share Policy
  11. Other Links
  12. Frequently Asked Questions
    1. Do I need IRB approval to download data?
    2. How do I download data?
    3. Can I open the CSV data files using Excel?
    4. Can I open/import SAS XPT files using SPSS?
    5. How do I download multiple data files?
  13. Contact Us
  14. NIDA-CPU-0016
  15. Data Download
  16. Drug Approvals and Databases
    1. FDA Acronyms & Abbreviations
      1. Acronyms & Abbreviations File Download
  17. Drugs@FDA
    1. Drugs@FDA Frequently Asked Questions
      1. 1. What is the purpose of Drugs@FDA, and what are its main uses? 
      2. 2. What drug products are in Drugs@FDA? 
      3. 3. What drug products are not in Drugs@FDA?
      4. 4. Why doesn't Drugs@FDA include dietary supplements?
      5. 5. How can I find out if a generic drug is available for an innovator drug?
      6. 6. What information is available for each drug product in Drugs@FDA?
      7. 7. How can I search Drugs@FDA?
      8. 8. How do searches work in Drugs@FDA?
      9. 9. How often do you update Drugs@FDA?
      10. 10. Where does the information in Drugs@FDA come from?
      11. 11. How does Drugs@FDA compare with the Orange Book?
      12. 12.  What do the Chemical Type and Review Classification codes stand for?
      13. 13. Can I get a copy of the Drugs@FDA database?
      14. 14. How can I get further assistance?
  18. NEXT

Story

Data Science for FDA RFI

Some excerpts from the recent FDA RFI are:

The Food and Drug Administration, (FDA), Center for Drug Evaluation and Research, (CDER), Office of Computational Science, (OCS) is requesting information regarding the market availability, technical characteristics, and functionality of solutions, tools, or products for the advanced analysis and visualization of both clinical and non-clinical drug application data. The OCS invites all interested parties to submit a written response to this Request for Information (RFI).

In particular, the OCS is focused on changing how data from regulatory submissions are received, stored, and analyzed in order to provide more high-quality quantitative analysis of review information regarding efficacy, safety and product quality over the product life-cycle.

Provide standard multivariate graphs such as bar, scatter matrix, box plot co-occurrence, histogram, area, line, and hierarchial plots for analysis of study data. Ensure user manipulation, customization, and creation of these visualizations.

Skills and Certifications: Provide unique technical skills and relevant certifications your staff and company possesses, which demonstrates capability to perform the tasks.

Support Adverse Events analyses on all levels of the MedDRA (Medical Dictionary for Drug Regulatory Affairs) hierarchy. Examples of these and other analyses can be found at http://www.accessdata.fda.gov/script...er/drugsatfda/ or http://www.fda.gov/Drugs/Information...gs/default.htm

Publicly available datasets for demonstration use or testing may be found at https://datashare.nida.nih.gov/

The Response Due Date was changed to: Apr 01, 2015 11:59 pm Eastern

The RFI is primarily technology and lacks focus on the critical need for Data Science in the US Government as evidenced by President Obama's recent appointment of the first chief data scientist, Dr. DJ Patil, whose top priority is Precision Medicine in support of the Administration’s Precision Medicine Initiative, which focuses on utilizing advances in data and health care to provide clinicians with new tools, knowledge, and therapies to select which treatments will work best for which patients, while protecting patient privacy.

So this data scientist/data journalist is not going to respond to the detailed technology requirements of the RFI, but focus on the data science aspects using the the NIDA Data Share web site which is described as follows:

An electronic environment that allows data from completed clinical trials to be distributed to investigators and the public in order to promote new research, encourage further analyses, and disseminate information to the community. Secondary analyses produced from data sharing multiply the scientific contribution of the original research. NIH expects and supports the timely release and sharing of final research data from NIH-supported studies for use by other researchers to expedite the translation of research results into knowledge, products and procedures to improve human health.
(see http://grants1.nih.gov/grants/guide/...OD-03-032.html).

This website was created in order to make the NIDA Clinical Trial data available to as wide an audience as possible. As studies are completed and their data become available, this web site will be linked to those data. The following information will be posted per protocol:

  • Study protocol
  • Reference to study publication of primary outcome
  • Data sets (SAS and ASCII )
  • Annotated case report forms
  • Define file (also known as Data Dictionary)
  • Study-specific de-identification notes

I followed the six step data mining process of the Cross-Industry Data Mining Standard Process (See the Wikipedia page on the CRISP-DM process model as follows:

  • Business Understanding: Study protocol and Reference to study publication of primary outcome
  • Data Understanding: Data sets (SAS and ASCII ) and Define file (also known as Data Dictionary) and Metadata: Annotated case report forms and Study-specific de-identification notes
  • Data Preparation: Downloaded and Imported Data into Spotfire
  • Modeling: Spotfire Tools and Guided Analysis
  • Evaluation: Data Science Data Publication: How was the data collected? Where is the data stored?, What are the results?; and Why should we believe them?
  • Deployment: Knowledge Base in MindTouch (Wiki) and Analytics and Visualizations in Spotfire in the Amazon Cloud

The results for one of the 39 NIH NIDA Data Share studies are an example of a data science data publication that documents the six steps and answers the four questions in the slides, semantic knowledge base, and Spotfire visualizations below.

Some Conclusions and Recommendations are:

  • The FedBizOpps.Gov FDA RFI was mined for unstructured and structured content.
  • Data Science for FDA RFI was to put the FDA RFI unstructured and structured content into a MindTouch Knowledge Base with file attachments and an Excel spreadsheet.
  • The Excel spreadsheet (5 tabs) and sample NIH NIDA Data Share spreadsheets (27) were imported into TIBCO Spotfire for Exploratory Data Analysis.
  • TIBCO Spotfire Recommendations to Make Inspired Discoveries About Your Data are illustrated.
  • The same data science mining and visualization process could be used for the other 38 NIH NIDA Data Share studies.

The results for the sample and the other 38 NIH NIDA Data Share studies could be converted to RDF for SPARQL queries and network analytics like our work with Semantic Medline and other graph technologies in the Federal Big Data Working Group Meetup.

The FDA RFI will be discussed at our Twenty-seventh Meetup, Monday, April 6, 6:30 p.m. entitled: Data Science for HealthData.gov Developers & Family Caregivers We have previously analyzed and discussed the FDA Adverse Drug Event Data and a Data Science Data Publication (Gallery) for FDA Data for Dr. Taha Kass-Hout, FDA’s First Chief Health Informatics Officer (CHIO), FDA Data Innovation Laboratory.

Slides

Slides

Slide 1 Data Science for FDA RFI

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Slide 2 Overview

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Slide 3 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: FedBizOpps.gov

BrandNiemann04062015Slide3.PNG

Slide 4 Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data: Word

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Slide 5 Drugs @ FDA

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Slide 6 Drug Approvals and Databases

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Slide 7 FDA Acronyms & Abbreviations

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Slide 8 NIH NIDA Data Share: Home

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Slide 9 NIH NIDA Data Share: Data Share Files

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Slide 10 Data Science for FDA RFI: MindTouch Knowledge base

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Slide 11 Data Science for FDA RFI: MindTouch Attachments

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Slide 12 Data Science for FDA RFI: File Folder

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Slide 13 Data Science for FDA RFI: Excel Knowledge Base

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Slide 14 TIBCO Spotfire: Opening Screen

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Slide 15 TIBCO Spotfire: Add Data Tables

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Slide 16 TIBCO Spotfire: Make Inspired Discoveries About Your Data

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Slide 17 TIBCO Spotfire: Recommended Visualizations 1

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Slide 18 TIBCO Spotfire: Recommended Visualizations 2

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Slide 19 TIBCO Spotfire: Cover Page

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Slide 20 TIBCO Spotfire: PD Visualizations

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Slide 21 TIBCO Spotfire: PD Data

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Slide 22 Some Conclusions and Recommendations

BrandNiemann04062015Slide22.PNG

Spotfire Dashboard

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Research Notes

Advanced Analysis and Visualization of Both Clinical and Non-clinical Drug Application Data

Source: https://www.fbo.gov/index?s=opportun...=core&_cview=1

Solicitation Number: FDA-SOL-15-1143182

Agency: Department of Health and Human Services
Office: Food and Drug Administration
Location: Office of Acquisitions and Grants Services
 
Contracting Office Address:
5630 Fishers Lane, Room 2129
Rockville, Maryland 20857-0001 
Place of Performance:
5630 Fishers Lane
Rockville, Maryland 20850 
United States 
Primary Point of Contact.:
Trevor R. Edwards
trevor.edwards@fda.hhs.gov
Phone: 240-402-7529

February 23, 2015

To:       All Interested Vendors

Re:       Request for Information

The Food and Drug Administration, (FDA), Center for Drug Evaluation and Research, (CDER), Office of Computational Science, (OCS) is requesting information regarding the market availability, technical characteristics, and functionality of solutions, tools, or products for the advanced analysis and visualization of both clinical and non-clinical drug application data. The OCS invites all interested parties to submit a written response to this Request for Information (RFI).

This RFI is being sought strictly for the purpose of gaining knowledge of services and supplies available with an estimate of their corresponding costs and should not be construed as intent, commitment, or promise to acquire services, supplies, or solutions offered. This Request for Information (RFI) is for information, planning and market research purposes only and shall not be construed as either a solicitation or obligation on the part of the FDA or its Centers. The purpose of this RFI is to help the FDA understand the market availability, technical characteristics, and functionality of solutions, tools, or products capable of satisfying the technical, functional, and/or operational characteristics described in this RFI. FDA will use this market research information to assess the market's capability to provide a comprehensive solution to the requirements described in the RFI. FDA welcomes responses from all interested parties. FDA does not intend to make a selection decision or award a contract on the basis of responses nor otherwise pay for the preparation of any information submitted or FDA’s use of such information.  Acknowledgment of receipt of responses will not be made, nor will respondents be notified of the outcome of the FDA's evaluation of the information received.  Additionally, the FDA does not intend to hold discussions concerning this RFI with any interested parties. However, FDA reserves the right to contact vendors if additional information is required.  Information submitted in response to this RFI will become the property of the FDA.

RFI responses must be received prior to March 13, 2015 at the following address:  E-mail Address: Trevor.Edwards@fda.hhs.gov

1.0 Background

The Food and Drug Administration’s Center for Drug Evaluation and Research (CDER) has the challenging task of providing regulatory oversight to the world’s largest and most technologically advanced pharmaceutical and biotechnology industries. The oversight of global operations for new drug development is heavily reliant on the availability and analysis of electronic data at every stage of the drug life-cycle. Thus, the Center for Drug Evaluation and Research established the Office of Computational Science (OCS) in the Office of Translational Science (OTS) to support the needs of the review community, their scientific review processes, and associated scientific computing efforts. The OCS was formed to provide services supporting the submission and use of high quality data and access to analytical tools, technology, and training thus improving efficiency and effectiveness of the overall regulatory review process. In particular, the OCS is focused on changing how data from regulatory submissions are received, stored, and analyzed in order to provide more high-quality quantitative analysis of review information regarding efficacy, safety and product quality over the product life-cycle. The OCS is committed to exploring new tools and technology to meet the demands of the modern review process. FDA recognizes that access to electronic structured scientific data about regulated products improves science-based regulatory decision making. Furthermore, it is expected that both clinical and nonclinical data will be increasingly submitted in electronic standard format as the pharmaceutical and related industries adopt electronic formats and standards for data warehousing and transfer. FDA, in conjunction with industry, has developed standards for these data types and published guidance accordingly. As FDA transitions to a 21st century review process, the ability to analyze, manipulate and display electronic study data derived from both clinical trial and non-clinical drug development studies is critical to fulfilling CDER’s mission. In light of this, OCS seeks to purchase, customize, and put into production a data analysis toolset to support the reviewers’ scientific review of this study data.

2.0 Purpose and Objectives

  1. The purpose of this RFI is to obtain information regarding the availability of either a Commercial Off the Shelf (COTS) platform and/or vendor services provided via open-source software, that provides regulatory reviewers the capabilities to perform advanced quantitative analysis and visualization of standardized study data sets from both the clinical and nonclinical domains submitted as part of investigational and new drug applications (IND & NDA).  In conjunction with the platform, FDA seeks to obtain information regarding the availability of services for the operations and maintenance of the associated solution, including but not limited to the application(s), integral data repositories, and all third-party software that supports the full functionality of the platform, as well as the development, maintenance, and operationalization of standardized analyses and reports. The functional requirements of this system are listed in section 3.
  2. Additional information regarding the development of enhancements, additions to the standard catalog, as well as ability to process, analyze, and visualize additional types of clinical and non-clinical data, such as patient narratives, post market data, and genetic data, such as viral genomics, are also requested. The FDA is particularly interested in open source solutions for advanced visualizations of additional data types of possible interest to reviewers operating in the regulatory domain. In conjunction with these additional analyses, FDA seeks information regarding the availability of customization services for open source solutions. This represents a secondary query of lesser importance than 2.1.

3.0 Functional Requirements

  1. Data visualization tools should be able to create graphical representations of study data, with the goal of providing the viewer with a qualitative understanding of the information contents.
  2. Ingest, process, and tabulate, visualize, and analyze safety and efficacy data, to include adverse event analyses on data from clinical trials.
  3. Provide dynamic study visualizations and analytics for toxicology studies, adverse event data, and other data frames as needed.
  4. Utilize standardized data from Electronic Common Technical Document (eCTD) submissions These shall include:
    1. SDTM (Study Data Tabulation Model) Study Data Tabulation Model defines a standard structure for human clinical trial (study) data tabulations that are to be submitted as part of a product application to a regulatory authority. SDTM is built around the concept of observations collected about subjects who participated in a clinical study. Each observation can be described by a series of variables, corresponding to a row in a dataset or table. Each variable can be classified according to its Role. A Role determines the type of information conveyed by the variable about each distinct observation and how it can be used. Variable in SDTM “variables” are used to describe observations. Such describing variables have roles that determine the type of information conveyed by the variable about each observation and how it can be used. Case Report Forms (CRFs) are used to collect subject data during the conduct of a clinical trial. These CRFs can be designed to capture data in a standardized way.
    2. ADaM (Analysis Data Model) ADaM data sets are designed to complement SDTM and provides the data elements needed to perform key analyses. ADaM liberates data from the SDTM domain structure combining elements with derived variables needed to support a specific analysis.
    3. SEND (Standard for Exchange of Nonclinical Data) SEND is an implementation of the Study Data Tabulation Model SDTM for non–clinical studies. These types of studies are typically related to animal testing as part of pre–clinical (pre–Phase 1) clinical trials. This standard was developed to establish a standard that can be used for the exchange and submission of non–clinical data collected from animal toxicology studies.
  5. Data also includes human clinical trial and animal toxicology study data existing in the SAS transport (.XPT) file format.
  6. Support for integration of FAERS (FDA Adverse Event Reporting System) data. FAERS is a transactional database; FAERS contains post market adverse event reports associated with drugs and biologic products. These adverse event reports are submitted to FDA by manufacturers, healthcare professionals, and consumers.
  7. Ability of software or system to interact or integrate with FDA data sources/stores such as PORTES (SAS Drug Development repository) and CTR (Clinical Trial Repository)
  8. Support cross-study metadata and tracking of pooled studies through all levels of analysis
  9. Support Adverse Events analyses on all levels of the MedDRA (Medical Dictionary for Drug Regulatory Affairs) hierarchy. Examples of these and other analyses can be found at http://www.accessdata.fda.gov/scripts/cder/drugsatfda/ or http://www.fda.gov/Drugs/InformationOnDrugs/default.htm
  10. Categorize adverse event data across system and organ class hierarchal modalities
  11. Integrate analysis for Adverse Events, laboratory test results, patient demographics data, and study subject characteristics.
  12. Develop, maintain and operationalize standard analyses; create additional analysis panels for inclusion into the toolset and the FDA Standard analysis
  13. Provide standard multivariate graphs such as bar, scatter matrix, box plot co-occurrence, histogram, area, line, and hierarchal plots for analysis of study data. Ensure user manipulation, customization, and creation of these visualizations.
  14. Ability to search and identify data points for visualization and exploration.
  15. Ability to manipulate study data (study data, analysis data, and associated metadata), graphical entities and attributes to allow for interactive data exploration
  16. Provide for printable and exportable visualizations of study data analyses
  17. Provide user mechanisms to export delimited data for use in SAS, and MS Office products
  18. Produce reports for incorporation in MS Office based tools and PDF from study data analyses
  19. Availability of templates and/or user-creation of templates that could easily be used to  generate graphical analyses and reports
  20. Provide user application of filters and constraints across data sets
  21. Provide for combinatorial cross study analyses for users to quickly and easily conduct safety assessments on both clinical and nonclinical data.
  22. Provide for trackable annotations within the toolset, which enable users to log, comment on, tag, and annotate their workflow and thought process throughout the analysis and reporting cycle. These annotations will be transferable with the associated exports for use in PDF format reports and MS Office products.
  23. User friendliness of design to include drag and drop capabilities or other web-interface style features for data and graphical entities.
  24. Solutions must be capable of being 508 compliant, see http://www.section508.gov/

4.0 Non-functional Requirements

  1. Solutions must be capable of complying with FDA and HHS security standards and best practices.
  2. Solutions must be capable of complying with PIV card enabled Single sign-on mechanisms.
  3. Describe the type and method of Helpdesk style support provided with the solution and its structure.
  4. Describe the type and method of O&M support for the solution that is offered or included, and how it is provided.

5.0 Additional Capabilities

  1. Please also describe any additional or unique features of the product such as but not limited to:
  2. BRIDG (Biomedical Research Integrated Domain Group) compliant systems. The BRIDG Model is a domain analysis model representing the realm of protocol-driven biomedical/clinical research.
  3. Employment of Resource Description Framework (RDF) with directed graph data structure in a triple store framework for data.
  4. Employment of SPARQL or SOLR querying methods.
  5. Semantic search, graph search, or other advanced querying options.
  6. Integration point with R for statistics analysis and reports
  7. Use of GPU-accelerated computing for analytics
  8. Ability to connect to, or any existing connections to other data sources such as: COSMIC, PUB CHEM
  9. SNOMED integration, SNOMED, Systematized Nomenclature of Medicine is a systematic, computer-processable collection of medical terms
  10. Any use of OWL, tranSMART/ compatible ontologies, such as OBO foundry, OBI, DOID, or PRO. Compatibility with HL7 data standard models or FHIR employment.
  11. CDASH compliance or use of CDISC Operational Data Model (ODM). ODM is designed to facilitate the regulatory-compliant acquisition, archive and interchange of metadata and data for clinical research studies
  12. Use of NLP or Semantic enhancement functionalities for non-structured data
  13. Collaborative tools or capabilities within the system, as well as any method for sharing analyses and data between users.

6.0 Technical Information

Please also provide information that will allow us to understand the technical requirements for implementation of the solutions. This should include a description of the existing installation options (server-based, workstation, desktop, etc.) as well as the system requirements for each of these options. Provide a detailed description of how the system functions and possible use cases for regulatory review. Please provide graphic examples such as screen captures or demonstration videos of the GUI for proposed solutions. All such graphic presentations should demonstrate the functionality of the proposed system and the methodology behind the analyses and visualizations. Also, please provide additional information about the licensing options, such as site licensing, virtual-server licensing, or user licensing. Please also describe the systems data transport and modeling methodologies.

7.0 RFI Requested Information

  1. Provide a suggested available COTS solution and/or vendor supported open source solutions that may meet the FDA’s objectives as listed above and general rationale for suggested solutions.
  2. Please advise what FDA requirements listed above are included out of the box, and which can be developed with configuration or as a customization.
  3. Please note whether your COTS software tool is a perpetual or a term license.
  4. Please note whether what if any service licenses apply to any open source components and their terms.
  5. Provide a written explanation for points that standard marketing or technical reference materials do not explain about your suggested solution(s). Please see the Functional Requirements table above.
  6. Detail whether the solutions are purchased directly from the manufacturer or are if they are available through licensed resellers. Disclose whether your business is in the manufacturing of the product/solution or if your business is a reseller or third party.
  7. If the products are only offered by the manufacturer, detail whether there licensed small businesses, 8a, women-owned, veteran-owned, HUB Zone vendors, etc. that are available to provide training and customizations.
  8. Would it be beneficial for the Government in using the detailed solution to issue two (2) or more contracts such as one for the purchase of license/maintenance; and the others for configuration, training, and customization to promote competition and fair opportunity?
  9. What acquisition vehicles are available to purchase proposed software tools and services that would make the acquisition process more efficient? (GSA, GWACs, NASA, SWEP, etc.)
  10. Please provide any additional input on how the FDA can best procure the software licenses.
  11. Detail what tasks are associated with implementing your suggested solution(s).
  12. Detail what information would be helpful in determining the level of effort for the implementation of the software tool.
  13. Detail what standardized support is provided by the manufacturer with purchase of the proposed COTS tool.
  14. Detail what standardized support is provided by the vendor in conjunction with the use of the proposed open source components if applicable.
  15. Explain if the solution suggests the FDA purchase customized support in addition to the standardized support, and if so, what type of customized support is offered for suggested solutions.
  16. Detail what information would be helpful in determining the level of effort for customized support of the software.
  17. Explain the standardized training and/or online help that will be available to the end users with the product or solution.
  18. If the standardized training is not sufficient explain why and if it is possible to customize the standardized training to meet the FDA’s needs.
  19. Provide publicly available pricing information, price lists, pricing strategies, discount strategies, etc. Provide and explain pricing model(s) (i.e., license-based, user based, number of documents, peak queries per second (qps), average qps, size of all documents/files/text within documents, size of index file(s), other. Include annual maintenance model. Provide the pricing model for training offered. Provide the pricing model for any professional services offering. Please identify product modules that are included in your pricing
  20. Explain whether or not your product adheres to Section 508 Accessibility Requirements which requires Federal agencies to ensure that individuals with disabilities who are members of the public or Federal employees have access to and use of electronic and information technology (EIT) that is comparable to that provided to individuals without disabilities.
  21. Explain how the suggested solutions are compatible with FDA’s Technical Environment or can be configured to be compatible. Identify risks that shall be associated with configuring the software to be compatible with the FDA environment.
  22. List of where product/solution is currently in use. Provide point of contact, telephone number, contract number, period of performance, organization supported, indication of whether a prime or subcontractor, contract value, and a brief description of how the contract referenced relates to the technical services described herein.
  23. Skills and Certifications: Provide unique technical skills and relevant certifications your staff and company possesses, which demonstrates capability to perform the tasks.

8.0 RFI Response Addenda

The FDA is not interested in simple extensions to existing OCS programs or minor improvements to current operational capability. Rather, OCS is seeking innovative concepts that will provide either an entirely new capability or will enhance existing capability by orders of magnitude (based on demonstrable relevant metrics). The FDA is asking all interested parties to submit a response containing your interest in providing the software or system and a brief description of past experience providing similar software or systems. Please provide a list of potential problems or risks that the FDA may encounter using this software or systems.  List your best estimated price range to provide the software or systems as stated herein, lowest estimate to highest estimate, as well as your best estimated time frame for completing the installation and integration of the software or systems. Publicly available datasets for demonstration use or testing may be found at https://datashare.nida.nih.gov/

9.0 Response Instructions

  1. For purposes of the RFI, the capabilities statement shall not exceed 15 pages of text; graphics do not count toward the page limit.
  2. The document(s) shall be prepared using Times New Roman 12-point font style for printing on 8.5 X 11 inch paper. Each page shall identify the submitting respondent and page number.
  3. Page Margins shall be no less than 0.5” on all sides.
  4. All information submitted in response to this announcement is voluntary; the United States Government will not pay for information requested nor will it compensate any respondent for any cost incurred in developing information provided to the United States Government. The Government will also consider the information provided in the responses when determining the best possible contracting method and vehicle for a possible acquisition, provided the information contained in the submissions meets the FDA’s needs and requirements for a regulatory review platform. Questions concerning this announcement may be addressed to Trevor.Edwards@fda.hhs.gov.

NIDA Data Share

Source: https://datashare.nida.nih.gov/index

Purpose

The NIDA Data Share web site is an electronic environment that allows data from completed clinical trials to be distributed to investigators and the public in order to promote new research, encourage further analyses, and disseminate information to the community. Secondary analyses produced from data sharing multiply the scientific contribution of the original research. NIH expects and supports the timely release and sharing of final research data from NIH-supported studies for use by other researchers to expedite the translation of research results into knowledge, products and procedures to improve human health.
(see http://grants1.nih.gov/grants/guide/notice-files/NOT-OD-03-032.html).

This website was created in order to make the NIDA Clinical Trial data available to as wide an audience as possible. As studies are completed and their data become available, this web site will be linked to those data. The following information will be posted per protocol:

  1. Study protocol
  2. Reference to study publication of primary outcome
  3. Data sets (SAS and ASCII )
  4. Annotated case report forms
  5. Define file (also known as Data Dictionary)
  6. Study-specific de-identification notes

Protection of Human Subjects

Our primary concern in sharing data is the protection of human subjects. The rights and privacy of people who participate in NIH-sponsored research must be protected at all times. Thus, data on this site have been completely de-identified to prevent linkages to individual research participants. This includes removal of all Personal Health Information (PHI) and indirect identifiers that are not listed as PHI but could lead to “deductive disclosure” such as comment fields and site numbers. Study specific de-identification methods are documented with each protocol.

Data Formats

Data are available in either a Clinical Data Interchange Standards Consortium (CDISC) format or a Case Report Form (CRF) format. For some studies, both formats are available. For the CDISC format, prior to de-identifying the data, all data files are converted from their native format to a modified Study Data Tabulation Model (SDTM) standard format. This facilitates the pooling of shared data across completed studies, as the variable names are consistent across studies. For the CRF format, separate data files are created for each CRF collected in the study. This will make it easier for researchers interested in looking at all data from a single CRF in one data file, as the data files match the CRF exactly

Data files are available for download in two formats: SAS (transport files or .sas7bdat) and ASCII (CSV files). Documentation regarding the data and corresponding study that generated the data are also available under each completed protocol page. This includes the annotated case report form (CRF); a define.xml file outlining the structure, variables, and contents of each dataset; and SDTM mapping for the CDISC data and de-identification rules.

Disclaimer: The trial data sets available on this NIDA Data Share website are derived from the complete trial database. Analysis data sets such as those utilized to develop publications are not included on this website. Please see the primary manuscript or contact the lead investigator for details.

Registration

Prior to downloading any study data, the user will be prompted to complete a registration agreement for data use. Users will have to register a name, position, affiliation, valid e-mail address, and country of origin in order to download data to and to accept their responsibility for using data in accordance with the NIDA Data Share Agreement.

About NIDA

Source: https://datashare.nida.nih.gov/about-us

NIDA's mission is to lead the Nation in bringing the power of science to bear on drug abuse and addiction.

This charge has two critical components. The first is the strategic support and conduct of research across a broad range of disciplines. The second is ensuring the rapid and effective dissemination and use of the results of that research to significantly improve prevention and treatment and to inform policy as it relates to drug abuse and addiction.

Division of Pharmacotherapies and Medical Consequences of Drug Abuse (DPMCDA)

The Division of Pharmacotherapies and Medical Consequences of Drug Abuse plans and directs studies necessary to identify, evaluate, and develop medications to treat substance use disorders (SUDs). The Division develops and administers a program of basic and clinical research to develop innovative pharmacological (both chemical and biological) approaches to treat SUDs . This program is implemented through collaborations with academia, industry (pharmaceutical and biotechnology companies), and other government institutions (e.g., the Veterans Administration and the FDA). The Division also coordinates and provides leadership in the area of medical conditions associated with SUDs, including but not limited to HIV/AIDS.

The Medications Development Program of DPMCDA is unique, created by congressional mandate in 1990 to establish a program to develop medications for the treatment of heroin and cocaine dependence. This charge has been expanded to now include developing medications to treat nicotine, cannabis, methamphetamine, and prescription opioid dependence. DPMCDA funds research through grants, cooperative agreements, and contracts. The Division continues to establish scientific collaborations with investigators from academic centers, the pharmaceutical and biotechnology sectors, and government agencies at both the national and international levels.

Center for Clinical Trials Network (CCTN)

The Center for Clinical Trials Network (CCTN) manages NIDA's National Drug Abuse Treatment Clinical Trials Network (CTN), a multi-site research project of behavioral, pharmacological, and integrated treatment interventions to determine effectiveness across a broad range of community-based treatment settings and diversified patient populations. The CCTN is responsible for the scientific, administrative, budgetary, and operational management of the CTN. Together the CTN and the CCTN provide a foundation for conducting research with the primary goal of bridging the gap between the science of drug treatment and its practice through the study of scientifically based interventions in real world settings.

The CTN provides an enterprise in which the National Institute on Drug Abuse, treatment researchers, and community-based service providers cooperatively develop, validate, refine, and deliver new treatment options to patients in community-level clinical practice. This unique partnership between community treatment providers and academic research leaders aims to achieve the following objectives:

  • Conducting studies of behavioral, pharmacological, and integrated behavioral and pharmacological treatment interventions of therapeutic effect in rigorous, multi-site clinical trials to determine effectiveness across a broad range of community-based treatment settings and diversified patient populations; and.
  • Ensuring the transfer of research results to physicians, clinicians, providers, and patients.

Data Share Files

Source: https://datashare.nida.nih.gov/protocol/data

Click on Protocol Number of interest to view study-related documentation or download data files.
(DPMC data files are under development.)
Division Study Number Study Title Investigator Release Date
DPMC NIDA-CPU-0016 Double-Blind, Placebo-Controlled Assessment Of Potential Interactions Between Intravenous Methamphetamine And Osmotic-Release Methylphenidate (Oros-Mph) 12/04/2014
DPMC NIDA-CSP-1008A A Multicenter Efficacy/Safety Trial of Buprenorphine/Naloxone for the Treatment of Opiate Dependence 12/04/2014
DPMC NIDA-CSP-1008B A Multicenter Safety Trial of Buprenorphine/Naloxone for the Treatment of Opiate Dependence 12/04/2014
CTN NIDA-CTN-0001 Buprenorphine/Naloxone versus Clonidine for Inpatient Opiate Detoxification 05/08/2006
CTN NIDA-CTN-0002 Buprenorphine/Naloxone versus Clonidine for Outpatient Opiate Detoxification 07/26/2006
CTN NIDA-CTN-0003 Suboxone (Buprenorphine/Naloxone) Taper: A Comparison of Two Schedules 05/29/2008
CTN NIDA-CTN-0004 MET to Improve Treatment Engagement and Outcome in Subjects Seeking Treatment for Substance Abuse 10/03/2007
CTN NIDA-CTN-0005 MI (Motivational Interviewing) to Improve Treatment Engagement and Outcome in Subjects Seeking Treatment for Substance Abuse 09/08/2006
CTN NIDA-CTN-0006 Motivational Incentives for Enhanced Drug Abuse Recovery: Drug Free Clinics 10/31/2006
CTN NIDA-CTN-0007 Motivational Incentives for Enhanced Drug Abuse Recovery: Methadone Clinics 12/13/2006
CTN NIDA-CTN-0008 Assessment of the National Drug Abuse Clinical Trials Network: A Baseline for Investigating Diffusion of Innovation 01/25/2007
CTN NIDA-CTN-0009 Smoking Cessation Treatment with Transdermal Nicotine Replacement Therapy in Substance Abuse Rehabilitation Programs 12/03/2007
CTN NIDA-CTN-0010 Buprenorphine/Naloxone-Facilitated Rehabilitation for Opioid Dependent Adolescents/Young Adults 07/30/2009
CTN NIDA-CTN-0011 A Feasibility Study of a Telephone Enhancement Procedure (TELE) to Improve Participation in Continuing Care Activities 05/18/2007
CTN NIDA-CTN-0012 Characteristics of Screening, Evaluation, and Treatment of HIV/AIDS, Hepatitis C Viral Infections, and Sexually Transmitted Infections in Substance Abuse Treatment Programs 06/11/2007
CTN NIDA-CTN-0013 Motivational Enhancement Therapy (MET) to Improve Treatment Utilization and Outcome in Pregnant Substance Users 05/27/2008
CTN NIDA-CTN-0014 Brief Strategic Family Therapy (BSFT) For Adolescent Drug Abusers 03/02/2010
CTN NIDA-CTN-0015 Women's Treatment for Trauma and Substance Use Disorders 05/01/2009
CTN NIDA-CTN-0016 Patient Feedback: A Performance Improvement Study in Outpatient Addiction Treatment 08/01/2007
CTN NIDA-CTN-0017 HIV and HCV Risk Reduction Interventions in Drug Detoxification and Treatment Settings 12/23/2008
CTN NIDA-CTN-0018 Reducing HIV/STD Risk Behaviors: A Research Study for Men in Drug Abuse Treatment 10/02/2008
CTN NIDA-CTN-0019 Reducing HIV/STD Risk Behaviors: A Research Study for Women in Drug Abuse Treatment 10/28/2008
CTN NIDA-CTN-0020 Job Seekers Training for Patients with Drug Dependence 02/27/2009
CTN NIDA-CTN-0021 Motivational Enhancement Treatment to Improve Treatment Engagement and Outcome for Spanish-Speaking Individuals Seeking Treatment for Substance Abuse 07/30/2008
CTN NIDA-CTN-0031 Stimulant Abuser Groups to Engage in 12-Step (STAGE-12): Evaluation of a Combined Individual-Group Intervention to Reduce Stimulant and Other Drug Use by Increasing 12-Step Involvement 02/06/2012
CTN NIDA-CTN-0027 Starting Treatment with Agonist Replacement Therapies (START) 06/06/2012
CTN NIDA-CTN-0046 Smoking-Cessation and Stimulant Treatment (S-CAST): Evaluation of the Impact of Concurrent Outpatient Smoking-Cessation and Stimulant Treatment on Stimulant-Dependence Outcomes 11/19/2013
CTN NIDA-CTN-0031A An Evaluation of Neurocognitive Function, Oxidative Damage, and Their Association With Treatment Outcomes in Methamphetamine and Cocaine Abusers 11/26/2013
CTN NIDA-CTN-0044 Web-delivery of Evidence-Based, Psychosocial Treatment for Substance Use Disorders 05/14/2014
CTN NIDA-CTN-0052 A Randomized Controlled Evaluation of Buspirone for Relapse-Prevention in Adults with Cocaine Dependence (BRAC) 05/14/2014
CTN NIDA-CTN-AWARE Project Aware: HIV Rapid Testing & Counseling in STD Clinics in the U.S. – an Adaptation of CTN-0032 07/03/2014
CTN NIDA-CTN-0030A3 Long-Term Follow-Up to CTN-0030 (A Two-Phase Randomized Controlled Clinical Trial of Buprenorphine/Naloxone Treatment Plus Individual Drug Counseling for Opioid Analgesic Dependence) 08/22/2014
CTN NIDA-CTN-0047 Screening, Motivational Assessment, Referral, and Treatment in Emergency Departments (SMART-ED) 09/02/2014
DPMC NIDA-CPU-0016 Double-Blind, Placebo-Controlled Assessment Of Potential Interactions Between Intravenous Methamphetamine And Osmotic-Release Methylphenidate (Oros-Mph) 12/04/2014
DPMC NIDA-CSP-1008A A Multicenter Efficacy/Safety Trial of Buprenorphine/Naloxone for the Treatment of Opiate Dependence 12/04/2014
DPMC NIDA-CSP-1008B A Multicenter Safety Trial of Buprenorphine/Naloxone for the Treatment of Opiate Dependence 12/04/2014
DPMC NIDA-CTO-0001 Phase 2, Double-Blind, Placebo-Controlled Trial Of Reserpine For The Treatment Of Cocaine Dependence 12/04/2014
DPMC NIDA-MDS-0007 Phase 2, Double-Blind, Placebo-Controlled Trial Of Bupropion For Methamphetamine Dependence 12/04/2014

Assessments Main Page

Source: https://datashare.nida.nih.gov/assessments

Here you will find a collection of assessments used on NIDA studies found on the Data Share website. There are two ways of locating assessments. First, there is the Complete Assessment List. Second, assessments may be searched either by category or by protocol.

Records for individual assessments contain a brief description of the assessment, which category the assessment is classified in, related assessments, if any, links to other protocols using the assessment, and possibly a link to more information about the assessment. All of the links to additional information, found in the green boxes, are from sites outside of the NIDA Data Share website. Most of this information is from the Alcohol and Drug Abuse Institute Library at the University of Washington.

By Assessment

Source: https://datashare.nida.nih.gov/assessments/assessment

Assessments may be compared using the categories listed below. To select a category, expand the category list by clicking on a link. Next, select the desired assessments by checking the check boxes next to the assessment. Finally, select whether or not all protocols should be included in the search or simply the protocols using the desired assessments. Once this is done, submit the form.

To view the results, scroll down the page. Here you will see a table with protocols that use the measure, indicated by check marks. Measures used across all of the selected studies will be highlighted in a pinkish box.

Display all protocols or only those used in the selected assessments:

Compare Assessments

By Protocol

Source: https://datashare.nida.nih.gov/assessments/protocol

Select the desired protocols by clicking the checkbox in front of the protocol. Selecting "Show All" will include measures used in all protocols. Selecting "Limit to those used in selected protocols" will limit the search to only the measures used in the selected protocols. Submit the form once this is done.

Display all assessments or only those used in the selected protocols:

 

Compare Protocols

Guidelines

Registration Agreement

Source: https://datashare.nida.nih.gov/guide...tion_agreement

Thank you for visiting the NIDA Data Share web site and reviewing our data sharing policy. Before downloading any data, you must first agree to the following terms and conditions (study documents can be viewed without registering). You will be prompted to complete the registration agreement once you attempt to access the data files.

The recipient of the data agrees:

  1. Not to use the received data, either alone or in conjunction with any other information, in any effort whatsoever to establish identities of any of the subjects from whom the data were obtained.
  2. To retain control over the received data, and not to transfer any portion of the received data, with or without charge, to any other entity or individual
  3. To notify the Recipient’s Institutional Review Board (IRB) operating under an Assurance approved by the Office of Human Research Protections (OHRP) as required by the Recipient's affiliated university, and in accordance with Department of Health and Human Services regulations at 45 CRF Part 46 of any new research projects based on the NIDA data. This requirement is university-specific and is not necessary for data uses such as teaching resources
  4. To acknowledge the NIDA database and the specific trials accessed in all oral and written presentations and publications resulting from analyses of the received data.NIDA data should be cited as follows: “The information reported here results from secondary analyses of data from clinical trials conducted by the National Institute on Drug Abuse (NIDA). Specifically, data from NIDA – XXXX-XXXX (actual protocol number and title) were included. NIDA databases and information are available at (http://datashare.nida.nih.gov).”
  5. To maintain security and privacy of the received data for as long as necessary per local and federal requirements.
  6. That the NIDA or its affiliates may contact you concerning publications or other issues regarding use of the data.

Role of the Sponsor: The National Institute on Drug Abuse (NIDA) has no role in the preparation, review, or approval of the manuscript.

Data Share Policy

Source: https://datashare.nida.nih.gov/guide...a_share_policy

The NIH expects and supports the timely release and sharing of final research data from NIH-supported studies for use by other researchers to expedite the translation of research results into knowledge, products and procedures to improve human health.

Data sets for CTN protocols will be available after (1) the primary paper has been accepted for publication, or (2) the data is locked for more than 18 months, whichever comes first.

In order to make the CTN data available to as wide an audience as possible, a Data Sharing link has been created on the CTN Homepage (link to be added). As studies are completed and their data become available, this site will be linked to that data.

The following will be posted per protocol:

  1. Data set (SAS)
  2. Data set (ASCII)
  3. Annotated Case Report Forms, Define file (aka data dictionary)
  4. Study protocol. The Investigators can provide an abbreviated protocol for sharing purposes, attached with the final study report
  5. Reference to study publication of primary outcome

(DPMC data share policy is under development.)

Frequently Asked Questions

Source: https://datashare.nida.nih.gov/faq

Do I need IRB approval to download data?

The Recipient’s Institutional Review Board (IRB) should be notified of any new research projects based on the NIDA data. This requirement is university-specific and is not necessary for data uses such as teaching resources. These data are good learning tools for new researchers and for those unfamiliar with clinical trials or SDTM data structures.

How do I download data?

  • Click on the "Data" tab at the top of the web page.
  • Click on the the desired protocol number from the first table column.
  • The protocol description along with a box on the right will appear, that box will contain the primary manuscript, CRFs, data dictionary and the data files.
  • Click on “Data Files” from the box, this will take you to the data share agreement. Complete the boxes at the bottom of the page including your name, position, affiliation, e-mail, and country of origin. Select the preferred data file format (SAS, ASCII, or both). Click “submit” to proceed with download.
  • The data files will display at the top of the page in the format you requested. You may then save the WinZip files to your computer.

Can I open the CSV data files using Excel?

The CSV data files are just comma delimited ASCII files that are in a format that you can open using any EXCEL version most of the time. However, for extremely large files (>65,536 records) you will need to use another method to view all data simultaneously such as the following:

  • Open all records at once in WordPad, NotePad, or EXCEL 2007
  • Import into an analysis software package such as SAS or SPSS
  • Open all records using a text file editor such as WordPad or NotePad and divide dataset into smaller files

Can I open/import SAS XPT files using SPSS?

SAS transport files can easily be imported into SPSS as follows:

  • Open SPSS and select File-> Open -> Data
  • Choose option "SAS Transport (*.xpt)"
  • Select desired datashare XPT file to open in SPSS

How do I download multiple data files?

You may submit a request for multiple data files to us by selecting the "Contact Us" link at the top of the page and completing the requested information. We will then contact you and arrange for a CD to be sent with the requested data files.

Contact Us

Source: https://datashare.nida.nih.gov/contact_us

Thank you for visiting our site and taking an interest in the project. Please feel free to contact us if you wish to receive more information.

Your full name including your credentials if you prefer.
Should be a properly formatted email address where you would like to be contacted.
 
Please provide any additional information that my help us assist with your comments/request.

NIDA-CPU-0016

Source: https://datashare.nida.nih.gov/protocol/nida-cpu-0016

CRF Level Data
Last Modified: Dec 04, 2014
Study Number: 
NIDA-CPU-0016
Investigator: 
Eugene Somoza, M.D. MY NOTE: All studies
Study Title: 
 Double-Blind, Placebo-Controlled Assessment Of Potential Interactions Between Intravenous Methamphetamine And Osmotic-Release Methylphenidate (Oros-Mph)
Short Description: 
 This is a human inpatient clinical pharmacology study to assess potential interactions between intravenous (i.v.) methamphetamine infusion and oral osmotic release methylphenidate (OROS-MPH).
Release Date: 
 12/04/2014
Study Description: 

The primary objective of this study is to determine the safety of the OROS-MPH concurrent with i.v. d-methamphetamine infusions of 15 mg and 30 mg. Safety outcome measures include cardiovascular responses [heart rate (HR), blood pressure (BP), and electrocardiograph (ECG) measurements], oral temperature, adverse events (AEs), and clinical laboratory analyses.

Data Download

Thank you for visiting the NIDA Datashare web site and reviewing our data sharing policy. Before entering the data site, you must first agree to the following terms and conditions:

The recipient of the data agrees:

  1. Not to use the received data, either alone or in conjunction with any other information, in any effort whatsoever to establish identities of any of the subjects from whom the data were obtained.

  2. To retain control over the received data, and not to transfer any portion of the received data, with or without charge, to any other entity or individual

  3. To notify the Recipient's Institutional Review Board (IRB) operating under an Assurance approved by the Office of Human Research Protections (OHRP) as required by the Recipient's affiliated university, and in accordance with Department of Health and Human Services regulations at 45 CRF Part 46 of any new research projects based on the CTN data. This requirement is university-specific and is not necessary for data uses such as teaching resources.

  4. To acknowledge the CTN database and the specific trials accessed in all oral and written presentations and publications resulting from analyses of the received data. CTN data should be cited as follows: “The information reported here results from secondary analyses of data from clinical trials conducted as part of the National Drug Abuse Treatment Clinical Trials Network (CTN) sponsored by National Institute on Drug Abuse (NIDA). Specifically, data from CTN-XXXX (actual protocol number and title) were included. CTN databases and information are available at http://datashare.nida.nih.gov

  5. To maintain security and privacy of the received data for as long as necessary per local and federal requirements.

  6. To inform the CCTN Data Manager when research paper(s) that include the use of CTN data, is (are) accepted for publication.

  7. That the CCTN or its affiliates may contact you concerning publications or other issues regarding use of the data.

  8. Complete the requested fields:

Drug Approvals and Databases

Source: http://www.fda.gov/Drugs/Information...gs/default.htm

FDA Acronyms & Abbreviations

Source: http://www.fda.gov/AboutFDA/FDAAcron...ns/default.htm

Search the FDA Acronyms and Abbreviations database
About This Database
The FDA Acronyms and Abbreviations database provides a quick reference to acronyms and abbreviations related to Food and Drug Administration (FDA) activities.

The emphasis is on scientific, regulatory, government agency, and computer application terms. The database includes some FDA organizational and program acronyms.  For more information about FDA's organization, please see our Web page "FDA Organization."

We have included some terms that are not strictly acronyms because of their relevance to FDA activities. Acronyms for journal titles do not appear in the database.

Additional Information

Acronyms & Abbreviations File Download MY NOTE: I downloaded this
Download a compressed file of the database
Suggest an FDA Acronym or Abbreviation Suggest terms for the FDA acronyms & abbreviations database

Acronyms & Abbreviations File Download

Source: http://www.fda.gov/AboutFDA/FDAAcron.../ucm070296.htm

Below you will find a compressed data file of the FDA Acronyms & Abbreviations database. All fields are separated by commas (CSV).  Its use is only recommended for those who wish to import this information into a database or spreadsheet. It will be updated quarterly. The data is one table that includes 3 fields:

  1. ID
  2. Acronym
  3. Definition

Drugs@FDA

Source: http://www.accessdata.fda.gov/script...er/drugsatfda/

Drugs@FDA Frequently Asked Questions

Source: http://www.fda.gov/Drugs/Information.../ucm075234.htm

1. What is the purpose of Drugs@FDA, and what are its main uses? 

Drugs@FDA allows you to search for official information about FDA approved innovator and generic drugs and therapeutic biological products.

The main uses of Drugs@FDA are:

  • finding labels for approved drug products
  • finding generic drug products for an innovator drug product
  • finding  therapeutically equivalent drug products for an innovator or generic drug product
  • finding consumer information for drugs approved from 1998 on
  • finding all drugs with a specific active ingredient
  • viewing the approval history of a drug

2. What drug products are in Drugs@FDA? 

Drugs@FDA contains prescription and over-the-counter human drugs and  therapeutic biologicals currently approved for sale in the United States.  Drugs@FDA includes discontinued drugs and "Chemical Type 6" approvals.

Drugs@FDA contains the following therapeutic biological products: 

  • monoclonal antibodies
  • cytokines, growth factors, enzymes, immunomodulators; and thrombolytics
  • proteins intended for therapeutic use that are extracted from animals or microorganisms, including recombinant versions of these products (except clotting factors)
  • other non-vaccine therapeutic immunotherapies

Not all therapeutic biological products are in Drugs@FDA.

Drugs@FDA contains most of the drug products approved since 1939.  The majority of labels, approval letters, reviews, and other information are available for drug products approved from 1998 to the present.

3. What drug products are not in Drugs@FDA?

Drugs@FDA does not include:

  • over-the-counter (OTC) products approved for marketing through a process other than submission of a New Drug Application or Biologic License Application
  • drugs sold outside the United States that are not approved for marketing in the U.S.
  • drugs not approved by the FDA
  • drugs under review at FDA for which no action (approved or not approved) has occurred yet
  • dietary supplements, which do not require FDA approval to be sold in the United States
  • biological products regulated by the Center for Biologics Evaluation and Research
  • animal drugs, which are regulated by the Center for Veterinary Medicine

4. Why doesn't Drugs@FDA include dietary supplements?

Dietary supplements do not require FDA approval to be sold in the United States.  FDA's Center for Food Safety and Applied Nutrition is responsible for the agency's oversight of these products.

5. How can I find out if a generic drug is available for an innovator drug?

  • Find the "Drug Details" page for your drug by following Instructions to Finding Health Information.
  • If a generic drug is available, you will see the link "Therapeutic Equivalents" in the middle of the "Drug Details" page. Click on this link to see the generic and other therapeutically equivalent drug products for your drug.
  • Be sure to read the definitions for Generic Drug and Therapeutic Equivalents.

6. What information is available for each drug product in Drugs@FDA?

The search results for all drug products include:

  • drug name
  • active ingredient
  • dosage form or route of administration
  • strength
  • marketing status (prescription, over-the-counter, or discontinued)
  • company that sponsored an application for approval
  • FDA action date
  • approval type (type of supplement type or other regulatory action)

Results for New Molecular Entities include:

Many, but not all drug products have links to:

  • current FDA approved labels
  • older labels
  • approval letters
  • reviews (scientific analyses of new drug applications that provide the basis for approval)
  • information for patients

7. How can I search Drugs@FDA?

You can search by:

  • drug name
  • active ingredient
  • drug name and FDA Action Date range
  • application number (NDA, ANDA, BLA)
  • action dates of approvals and supplements in one, two, or three month blocks
  • original and supplemental approvals by month

8. How do searches work in Drugs@FDA?

The drugs that are listed on the "Search Results" page are not always related in terms of their chemical makeup or the conditions they treat, and are not necessarily substitutable.  They appear together because their drug names or active ingredient names contain the words or parts of words you entered in the search box.  The text you searched for appears in bold letters in the search results.

Even if drug products have the same active ingredient, dosage form, and strength, it might not be safe to use one in place of the other.  You should always consult a health care professional to determine if one drug can be safely substituted for another, that is, if they are therapeutically equivalent.

How searches work:

  • When you enter a string of characters to search Drugs@FDA, you are searching for that string of characters in the exact order you typed them, anywhere in a drug name or an active ingredient name.
    • Example:
    • If you enter "proz" you will retrieve drug products that have that four-letter string somewhere in their drug names or active ingredient names:
      • CEFPROZIL   [from the "Active Ingredient" column]
      • OXAPROZIN POTASSIUM   [from the "Active Ingredient" column]
      • PROZAC   [from the "Drug Name" column]
      • PROZAC WEEKLY   [from the "Drug Name" column]

Tip:  Enter as much of the name as you know to focus your results.  For example, if you know you want to retrieve the records for Prozac, enter the entire word.

  • If you enter two or more words separated by a space, Drugs@FDA will look for records containing both of the words, whether they occur together or apart, in either a drug name or an active ingredient name.
    • Example:
    • If you enter "claritin pseudoephedrine" you will retrieve drug products that have either one of those words in either their drug names or active ingredient names:
      • CLARITIN-D  (LORATADINE;  PSEUDOEPHEDRINE SULFATE)
      • CLARITIN-D 24 HOUR  (LORATADINE; PSEUDOEPHEDRINE SULFATE)
  • You cannot combine and Application Number searches with Drug Name or Active Ingredient searches.  This search will not work: fluoxetine 018936.

9. How often do you update Drugs@FDA?

We make changes to the database every day, sometimes several times throughout the day.  When we are notified that a supplement has been approved, we wait 24 hours to add the information, with the exception of special approvals.

10. Where does the information in Drugs@FDA come from?

The information in Drugs@FDA comes from

11. How does Drugs@FDA compare with the Orange Book?

Drugs@FDA overlaps with the Orange Book in many aspects of content and retrieval capabilities, but it is not intended to replace the Orange Book. You can read about the origin and purpose of the Orange Book in the   Preface to the Annual Edition.

Content:

  • All of the drugs listed in the Orange Book appear in Drugs@FDA.
  • Drugs@FDA includes information not included in the Orange Book:
  • The Orange Book includes information not included in Drugs@FDA:
    • Patent and exclusivity information
  • The Orange Book is updated daily for new generic drug approvals and patent information and monthly for other information.
  • We update Drugs@FDA daily with information on new approvals and supplemental approvals, links to documents, and the latest Orange Book data.

Features:

  • Drugs@FDA provides features not available in the Orange Book, including:
    • tables of therapeutic equivalents grouped by product.
    • tables, grouped by product, showing over-the-counter drugs containing the same active ingredient
    • drug approval histories
    • links to documents and web pages related to the approval history, drug safety, and patient information
    • date-range searches
    • drug approval reports by month
  • The Orange Book provides features not available in Drugs@FDA , including:
    • search by applicant
    • search by patent
    • search by type: prescription (Rx), over-the-counter (OTC), and discontinued

12.  What do the Chemical Type and Review Classification codes stand for?

NDA Chemical Types

Number Meaning
1 New molecular entity (NME)
2 New active ingredient
3 New dosage form
4 New combination
5 New formulation or new manufacturer
6 New indication
7 Drug already marketed without an approved NDA
8 OTC (over-the-counter) switch
10 New indication submitted as distinct NDA - not consolidated

Review Classifications

Letter Meaning
P Priority review drug: A drug that appears to represent an advance over available therapy
S Standard review drug: A drug that appears to have therapeutic qualities similar to those of an already marketed drug
O Orphan drug - a product that treats a rare disease affecting fewer than 200,000 Americans

   

13. Can I get a copy of the Drugs@FDA database?

Yes. Please see the page "Drugs@FDA Data Files" for information about the database tables and a link to the compressed file for downloading. The file does not include the scripts (programming) we use to produce the online version of Drugs@FDA. We are providing this technical information for users who are familiar with working with databases or spreadsheets.

14. How can I get further assistance?

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