Project Management and General Utilities  


Successful FDA submissions require optimal project management skills as well as productive tools.  Generally all three basic constraints need to be planned across each of the three main topics (CDISC SAS Datasets, Tables, Lists and Graphs, and Validation): scope, schedule, and budget.  See also New to SAS Programming.

SOP: Program Index File  >>>  Variable Attribute File  >>>  Tables and Lists

General Macro Utility: Clinical Data Management: Building a Dynamic Application, Art Carpenter, Richard Smith


(Click on image below to start Pharmaceutical Industry mind map)









Industry Leaders / Tools

Data Collection – (CDM) RAVE, EDC tools

Data Transfer and Cleaning – (CDM) SAS, DataFlux

Data Tracking and Querying – (CDM) Jira, Microsoft Teams

Data Transformation to SDTMs/ADaMs – (Stats Prog) SAS, Formedix, MDR tools

Data Exploration - (Stats Prog, Stats) Spotfire

Data Analysis and Reporting – (Stats Prog) SAS, R Programming, Python

Table Development – (Stats Prog) R-Shiny

Statistical Team Workflow, KPIs and Collaboration Tools - (Stats Prog) BPS

SAS / CDISC Wiki / Mentoring – (CDM, Stats Prog)

Study Tools – (CDM, Stats Prog) Log and QC scans, Data Cutoff, Milestones

CDISC Compliance Tools – (Stats Prog) Pinnacle 21, Codelist Dictionaries, Define.xml, Review Guides, CRF Annotated


21 CFR Part 11 Sides    Center of Excellence Setup


GCP Refresher and GCP/GCDMP Trends in the CTN

How to keep the project on budget in the clinical trial study, Kevin Lee [Timelines for each task]


1. Standardizing Data Processing and e-Publishing for the Pharmaceutical Industry, Shawn Wang


2. Get your SAS in gear – Automate the Production of Analysis Datasets, Liz Taylor


3. Get your SAS in gear – Automate Appendix Numbers, Titles and Footnotes, Liz Taylor [Program Index]

4. Auto-Attributes: No More Typing of Variable Labels (and Other Attributes)!, Jonathan Squire [Metadata]

5. Developing, Managing, and Evaluating a Standard Macro System, Albert Mo

6. Using Metadata for Data Driven Programming, Brian Varney

7. Transforming Business Requirements into System Solutions, Yongcun Zhang

8. Supporting the Program-Analyze-Write-Review Process with a Development
Environment for Base SASâ and the Macro Language, Barry Cohen

9. Data Savant Consulting Macros

10. Names, Names, Names - Make Me a List, Ian Whitlock

11. Designing Clinical SAS Service Request Forms, Sunil Gupta

12. Utilizing Clinical SAS Report Templates, Sunil Gupta

13. Sending Emails in SAS to Facilitate Clinical Trial, Frank Fan

14. How to Write Standard Operating Procedures, Lori Hardwick

15. Ten Ways to Improve the Efficiency of Clinical Statistical Programming, Amos Shu

16. Rethink Training - Four reasons your FDA compliance training isn’t preventing violations — and how you can change that, Ellen Leinfuss


18. SQL SUBQUERIES: Usage in Clinical Programming, Pavan Vemuri

19. Statistical Table Specifications and Automatic Code Generation using XML, Alan Hopkins and Linda Collins 

20. Specifications for Derived Data (Or, Would You Build a House Without Prints?) Richard Weisman [Example]

21. A SAS Macro Application to Create Mock Tables in Statistical Analysis Plans for Phase I Clinical Studies, Yao Huang

22. A Simple Solution for Managing the Validation of SAS® Programs That Support Regulatory Submissions, Tony Chang and Dana Soloff

23. CDISC Electronic Submission, Kevin Lee

24. A Shout-out to Specification Review: Techniques for an efficient review of
Programming Specifications, Sajeet Pavate, Jhelum Naik

25. Managing bulk SAS job submissions with post execution analysis and notification, Bruce Kayton

26. SAS® Beyond Measure, Jim Baker

27. Searching for a Diamond in the Rough: Finding and Integrating SAS® Programming Talent, John Hotaling, Lynn DiFinizio

28. Proactive Management (Or Proactive Decisions), Johan Nordin

29. Challenges in Managing a Large (20+) SAS Programming Group, Paul A. LaBrec and Daniel Golder

30. Motivating Clinical SAS® Programmers, Daniel Boisvert, Andy Illidge

31. Experiences in Leading a Company-Wide First CDISC Filing from a Programming Perspective, Sho-Rong Lee

32. Organizing Deliverables for Clinical Trials – The Concept of Analyses and its Implementation in EXACT, Hansjörg Frenzel [Presentation]

33. ProjectTrackIt: Automate your project using SAS, Abhishek Bakshi

34. Every Study is Special! - Governing Data Standards, Chris Price, Elizabeth Nicol

35. Standards for the Management of Clinical Trial Data, why are they needed, what is needed ?, Isabelle ABOUSAHL-CHAUNU [QA Checklist]

36. Are you out of your mind? CDISC mapping using a Mind Mapping tool Johannes Ulander, Niels Both

37. Sponsor Oversight of CROs Data Management and Biostatistical Abilities, Lois Lynn

38. The Untapped Potential of the Protocol Representation Model, Frank Dilorio, Jeffrey Abolafia

39. An Introduction to SAS® Consulting From a Business Perspective, Robert Butler [estimate, scope of work]

40. Sounds Like a Good Idea, But What's the ROI? Justifying Your Project and Getting It Approved, John Bentley

41. A Lightweight HTML Codebook Generator for Clinical Trial Data, Lei Zhang

42. Implementing End-to-End Data Standards from a Metadata and Technology perspective [Presentation]

43. Automating CDISC deliverables through processing Metadata [Presentation]

44. The Chicken and Egg Dilemma: Why Metadata solutions have Struggled [Presentation]

45. Lead Programmer Needs Help: Dedicated Programming Project Manager to the Rescue! Gloria N. Boye, Aparna Poona, Bhavin Busa

46. Stakeholder Management: How to be an effective lead SAS® programmer, Aakar Shah

47. Graphing Made Easy for Project Management, Zhouming Sun

48. FDA review principles applied on CRO oversight, Sascha Ahrweiler, Ankur Mathur, Grace Ignacio

49. Clinical Timelines Visualized, Spencer Childress, Jeremy Wildfire, Ryan Bailey, Britt Sikora

50. A Regulatory Compliant Process for Developing SAS-Based Reports, Chuck Reap

51. The development of standards management using EntimICE-AZ, Shyamprasad Perisetla, Per-Arne Stahl

52. REACTing to data: The Use of Data Visualisation within Early Clinical Statistical Programming at AZ, Shyamprasad Perisetla, Suzanne Tautz

53. Delivering a quality CDISC compliant accelerated submission using an outsourced model, Mei Dey, Diane Peers

54. No Regrets: Hiring for the Long Term in Statistical Programming, Chris Moriak, Graham Wilson, Elizabeth Meeson

55. What Have I Done? Analysis Specification Document for Retrospective Database studies [Presentation]

56. A Similarities and Differences in Statistical Programming among CRO and Pharmaceutical Industries, Mark Matthews

57. Outsourcing CRO Oversite - GSK's journey over the last few years, Ryan Finch [Presentation]

58. Transition from “hands-on” statistical programmer to leader of a team of role based statistical programmers. Tools and tips to help you succeed, Rodrigo Ruiz

59. Improving the Relationship between Statisticians and Programmers in Clinical Trial Studies, Mai Ngo, Mary Grovesteen, and Vaughn Eason

60. Strategy to Evaluate the Quality of Clinical Data from CROs, Charley Wu, Rob Tarney

61. Avoiding Disaster: Manager’s Guide on How to Rescue a Failing Outsourced Project, Dilip Raghunathan

62. Customized Project Tracking with SAS and Jira Nancy Brucken

63. Distance Management: how to lead a team of SAS users who sit half a world away, Max Cherny

64. Best Practices in Managing a Global SAS Programming Team, Yi Zhang

65. Overcoming hurdles in clinical programming project management using Microsoft Teams, Cambre, Sofie; Joshi, Nirved; Tiwari, Miten; Wu, Yan; Xu, Qin

66. Integrating SAS and the R Language with Microsoft SharePoint, Prasoon Sangwan, Piyush Singh, Shiv Govind

67. Microsoft OneNote: A Treasure Box for Managers and Programmers, Jeff Xia, Mary Varughese

68. Project Metrics- a powerful tool that supports workload management and resource planning for Biostats & Programming department, Jian Huang, Rajan Vohra, Andy Chopra [Sharepoint]

69. A SAS Macro for Checking the Status of Table, Figure and Listing (TFL) Programming, Yuping Wu and Sayeed Nadim

70. The development of standards management using EntimICE-AZ

71. PhUSE CSS Webinar January 2016, Statistical Computing Environments (SCE) [Presentation]

72. Branding Yourself [Presentation]

73. Quality, Timely and Within Budget Analysis and Reporting – Yes, you can have all three! A process and tool to help achieve this goal, Wilminda Martin, Sharon Niedecken, Syamala Schoemperlen

74. Integrating Your Analytics In Database with SAS, Hadoop and the Teradata EDW, Bob Matsey

75. The Importance of Being Ernest – Risk Based Approach (RBA) [Presentation]




Agile Aliance Blog

1. When Software Development is Your Means Not Your End: Abstracting Agile Methodologies for End-User Development and Analytic Application, Troy Hughes

2. Toward Adoption of Agile Software Development in Clinical Trials, Troy Hughes

3. SAS in clinical trials – A relook at project management, tools and software engineering [Jira Presentation, Agile]

4. SAS Adapts Agile Process

5. Agile Data Science with R

6. Statistical Computing Environment Implementation – An Agile Approach Gary Cozzolino

7. Agile in Pharma Blog

8. Automated Test Framework for SAS Macros, Sven Prasse

9. Customized Project Tracking with SAS® and Jira, Nancy Brucken

10. Exploring DataOps in the Brave New World of Agile and Cloud Delivery, Shane Gibson

11. Agile Software Development: A gentle introduction

12. TOP 10 Best Agile Project Management Tools In 2021

13. Implementing Agile working in pharma

14. Benefits of Agile

15. How Agile helps non-technical teams get things done [Project Management]

16. 9 Key Benefits Of Agile Software Development

17. Agile at CDISC


OffShore and CRO Leadership and Management

Different Phases of Growth (Communication, Planning, Delivery and Issues)

< Client > < Engagement Manager > < CRO - staff, finance >

1. Resource planning to identify gaps in high workload and low staff.

2. Monitor monthly invoice against target levels and adjust as needed to maximize invoices.

3. Technical screening, interviewing and negotiations to identify A+ and A players to meet higher workloads.

4. Onboarding and tracking to build, guide, train and retain staff (> 90%, < 1 month to backfill) to get them engaged from the start.

5. Train on client SOPs, assign roles, responsibilities and SMART goals.

6. Monitor daily, weekly, monthly or quarterly as needed with different levels of client and CRO staff.

7. KPI metrics on timeliness (1 round), issues (< 3) and quality (100%) of deliverables.

8. Train and support on technical topics.  

Top 10 Tips for more effective management

 1. Technical training with hands-on activities for on-boarding and monthly, engage team to present code reviews 

 2. Mentor program to guide and answer questions

 3. IT support to address any system related issues

 4. Resource Planning and Management

 5. Communicate weekly conference calls

 6. Central project tracking sheet and issues log for better project management

 7. Follow and maintain process flow charts and task steps including - SDTM and ADaM specifications, create/qc SDTM, ADaM and TFLs

 8. All specifications should include the following answers: Who is the population?, What is being analyzed or derived?, When did the visit occur?, and How should the derivation be calculated?

 9. CC on all emails with client


1. How to Build an “Offshore” Team with “Onshore” Quality Lulu Swei, Margaret Li

2. Techniques for Managing Projects Outsourced to Offshore CRO Hong Qi, Margaret M. Coughlin

3. A Comparison of Two Commonly Used CRO Resourcing Models for SAS/Statistical Programmers, R. Mouly Satyavarapu [scope of work]

4. Empowering SAS® Programmers: The Role of the Manager, Carey Smoak

5. The 7 Habits of Highly Effective Programmers

6. Programmers are from Mars and Statisticians are from Venus [Presentation]

7. Building Effective Statistical Programming Teams for Clinical Trials, Dawn Edgerton

8. Developing Exploratory Programmers Based in India, Jan Stefanek

9. Clinical Trials Analysis & Reporting Performance Metrics, Ellen Asam, Donna Usavage

10. Building a Team of Remote SAS Programmers, Ramesh Ayyappath

11. Constructive Feedback: Statistical Programming Case Study [Presentation]

12. Monitoring Quality, Time and Costs of Clinical Trial Programming Projects using SAS®, Jagan Achi

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