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Cracking the Code: Estimate at Completion (EAC) of a Clinical Trial

Project management is a continuous loop of planning what to do, checking on progress, comparing progress to plan, taking corrective action if needed, and re-planning. The fundamental items to plan, monitor, and control are time, cost, and performance so that the project stays on schedule, does not exceed its budget, and meets its specifications.  Of course all of these activities are based on having an agreed upon Work Breakdown Structure (tasks/activities) on which to base the schedule and cost estimates.  During the planning phase of a project, the project manager with the assistance of the project team needs to define the process and procedures that will be used during the implementation phase to monitor and control the project’s performance.

Productivity in the pharmaceutical/biotech/medical device industry is going down. Some compounds have reached the billions expenditures cost without any guarantee that it will ever be approved or reach the market.  So how can we evaluate the performance of some of these clinical trials?

I will not go into details in the degree of project management activities managed and performed by a data manager since this can vary widely per company.  A good clinical data manager or manager of data management should be able to implement basic PM principles that will improve quality and timeliness of a clinical trial, regardless if the trial is fully outsourced (e.g. CRO performed most of the work).

You can find my article about the Role of Project Management in Clinical Data Management (2012) here for further reading.

So what is Estimate at Completion or EAC? or What is the project likely to cost?

There are several methods we could use to calculate EAC.

Let’s look at one formula. EAC =  AC (Actual Cost) + ETC (Estimate to Complete)  so what happens when you don’t know the ETC?

We could use the following formula to derive that value: ETC = (BAC – EV) / CPI =>>>>??? So what? More formulas? How do I get BAC or EV or CPI?

Let’s look at those in more details.

 BAC =>>>Budget at Completion (how much did you
budget for the total project?)
CPI =>>> Cost Performance Index (CPI): BCWP/ACWP

EV = Earned Value

Earned Value Analysis example for a phase 1 trial (*figures in the thousands / millions = fictitious  numbers)

The final clinical trial results includes 100 subjects. The estimated cost is $20 per subject.  That results in an estimated budget of $2000 (100 x 20). During the planning, the CRO indicated that would be able to enroll 5 subjects per week.  Therefore the estimated duration of the trial is 20 weeks (100 / 5)

EV blocks: From the project plan

Estimated Budget: $2000

Estimated Schedule: 20 weeks

Planned Value (PV): at the end of the trial is $2000

Variance between planned and actual at the end of the first week:

Based on the estimated scheduled, I should have 25 subjects enrolled. At $20 per subject, the planned value at the end of the week is $500 (25 x 20)

PV = $500

At the end of the first week, the CRO reports that he has enrolled 20 subjects  and the actual cost of that study is $450. With this information we can look at schedule and cost variance.

SV = EV – PV

SV = $400 – $500 = – 100 ($100 work of subject recruitment is behind schedule).

CV = EV – AC

CV = $400 – $450 = -50 ($50 work of the project is over budget)

*negative figures means bad.

Using early results to predict later results:

Schedule Performance Index (SPI)

SPI = EV/PV

SPI = 400/500 = .80

Cost Performance Index (CPI)

CPI = EV/AC

CPI = 400/450 = .89 –> over budget or expending more

These rations can be used to estimate performance of the project to completion based on the early actual experience.

Estimate to Completion (ETC)
ETC= (PV at completion) – EV)/CPI

ETC= (2000 – 400)/CPI

ETC = (1600/.89) =$ 1798 from end of week one (after 5 days) and it will take additional $1798 to complete the study

Estimate at Completion (EAC)

EAC = AC + ETC

EAC = 450 + 1798 = $2248

If nothing changes, based on the actual results at the end of the first week, the study is estimated  to cost $2248 (rather than the planned cost of $2000) and will take 20 percent longer.

The formulas assumes that the accumulative performance reflected in the CPI is likely to continue for the duration of the project.

You do not need to memorize all of these formulas. There are plenty of tools in the industry that does the computation for you. But if you do not have it available, you can use Excel, set-up your template and plug in the numbers.

Earned Value

 

 

 

 

 

 

 

As per PMI – PMBOK definition, Cost management “…includes the processes involved in estimating, budgeting, and controlling costs so that the project can be completed within the approved budget.”   A Guide to the Project Management Body of Knowledge (PMBOK® Guide).

We have shown you, that PM tools such as Earned Value  Analysis, can be applied to clinical trials or specific work break down (WBS) activities within the data management team.

Based on the above outcome of the project performance related to the schedule, the data manager should be able to determine if she should modify the current plan or revise the original plan.

It is a perfect tool for data managers and managers of data managers and could be part of your risk based processes.

If bringing efficiency, improving data quality and significantly reducing programming time after implementing CDISC standards is on your radar screen, I’d love to chat when it’s convenient. All the best.

Anayansi Van Der Berg has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical. SAS, CDASH/SDTM (CDISC standards implementation and mapping), SAS QC checks and clinical data reporting.

Source:

A Guide to the Project Management Body of Knowledge (PMBOK® Guide).

Notes from my PM class at Keller 2007-2009

Images – Google images

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Motto of the Month

Enjoy every moment as it is your last.  The simple things in life are the most important ones. Once you don’t see or have them any more, you realize, you had it good.

You don’t know what you got until it is gone…

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

FAIR USE
“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Motivation of the Month

In the absence of that which you-are-not, that which you-are, is not… With no cold we cannot know warmth; without the up we cannot know down, without “good” we cannot know “bad”. And yet, we make it all up. We decide what is “cold” and what is “warm”, what is “up” and what is “down”. We decided what is “good” and what is “bad”. The universe is a massive entity of objectives. We label them.

Data Management Plan – Coding and Reconciliation

All Adverse Events and Previous/Concomitant Medication should be coded and/or approved prior and during the trial.

Before adverse event terms can be reported or analyzed, they must be grouped based on their similarities. For example, headache, mild headache and acute head should all be counted as the same kind of event. This is done by matching (or coding) the reported adverse events against a large codelist of adverse events which is also known as dictionary or thesaurus.

Test cases and other documentation associated with the testing of auto-coding should be produced/documented.  This documentation is not part of the plan. It is a product of the design process and should be filed separately in the TMF system.

In the DMP. you should document the variables and the dictionary to be used.

For Concomitant Medications, WHO drug reference list is used.  Also document the version used and if applicable, the final version of the who drug (for trials running over 6 months).

For Adverse event, MedDRA dictionary is the choice of coding method. Document the version used.

Serious Adverse Event (SAE) Reconciliation:

Indicate SAE Reconciling Approach to be used to compare SAE database (e.g. Argus) to the Clinical study| database (e.g. EDC):

  • Indicate tools to be used
  • Location of SAE data
  • Planned timing
  • Planned frequency of SAE Reconciliation activities

What to look for during reconciliation:

  • There are matched cases but minor differences such as onset date
  • Case found in the CDMS but not in the SAE system
  • Case found in the SAE system but not in the CDM system

Methods for Reconciliation:

For electronic-automatic reconciliation between systems, there are some challenges you need to identify first such as which type of data is to be reconciled and then which fields to compare. Best practice is to reconciled those considered serious according to regulatory definitions.

For manual reconciliation, reports such as SAS listings extracted from both systems with study information, subject or investigator and other key data can be used to perform manual review.  A manual comparison of the events can then assure that they are both complete and comparable.

Central Coding Anayansi Gamboa
Central Coding

No matter which method you used for reconciliation, each type of data (eg, AE, MedHist, Conmed) should document which glossaries and version were used.

When data from the clinical trial database is entered into a drug safety database for coding, the data between the two systems should be reconciled to verify the data in both systems are

identical. The processes and frequency of reconciliation should be specified.

Source:

DIA -A Model Data Management Plan StandardOperating Procedure: Results From

the DIA Clinical Data Management Community, Committee on Clinical Data Management Plan

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“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, Medrio, IBM eCOS, OpenClinica Open Source and Oracle Clinical.

Data Management Plan – Study Specific Documents

Data Management personnel are responsible for creating, collecting, maintaining and/or retaining all essential study documents when contracted by the sponsor (e.g. biotech company, big pharma client).

It is important to keep electronic and paper records or hard-copies and specify retention records of these essential documents:

  • Final version including amendments of the clinical protocol
  • Final version of the CRF/eCRFs
  • Final version of the completion guidelines
  • All final approvals and written authorization (e.g. emails or note to files).
Study Specific Anayansi Gamboa
Study specific

-FAIR ;USE-
“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, Medrio, IBM eCOS, OpenClinica Open Source and Oracle Clinical.

Data Management Plan – Database Archive

Indicate how you intend to archive and share your data and why you have chosen that particular option.

The DMP should outline specific information regarding the organization’s procedures for archiving the electronic records.

Good practice for digital preservation requires that an organization address succession planning for digital assets.

Which criteria will you use to decide which data has to be archived? What should be included in the archive?

Type of data (raw, processed) and how easy it is to reproduce it. Also consider archiving audit trails as long as the records are (CRF Part 11, Section 11.10).

Does the archive have specific requirements concerning file formats, metadata etc.

It is recommended to use open source formats such as PDF-PDF/A, ODM-XML or ASCII type of files.

anayansigamboa

 

 

 

 

Who is responsible for the data after the project ends?

Sponsor, CRO, Vendor? All should be documented on the DMP. Once database is locked, within a reasonable time and after data submission to a regulatory agency, you want to archive your database for long term storage and recovery.

While most data submitted to regulatory agencies are available in SAS formats, there may be times when going back to the original data format may be required.

Even though the easiest way to make sure data is available after database lock is to archive this data in the built in structure as the current system. For example, for Medidata Rave studies, trials are built on on top of SQL server, hence, you should consider archiving the old studies in a compatible format of SQL Server, without any transformation or data manipulation = raw data.

Other formats for data archive can be considered are ODM XML, PDF-PDF/A or ASCII A-8. These are some options for long=term storage. FDA says in the guidance document for 21 CFR Part 11, ‘scope and application – section C.5″, “FDA does not intend to object inf you decide to archive required records in electronic format to nonelectronic media….As long as predicate rule requirements are fully satisfied and the content and meaning of the records are preserved and archived, you can delete the electronic version of the records”.

Archival Plan

For archiving data, this plan should list all the components of the orginal system that will be included in the archive and the formats being used for their storage.

The best practices for clinical data archiving in clinical research are no different from those for archiving any other kind of industry.

 

 

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“Copyright Disclaimer Under Section 107 of the Copyright Act 1976, allowance is made for “fair use” for purposes such as criticism, comment, news reporting, teaching, scholarship, and research. Fair use is a use permitted by copyright statute that might otherwise be infringing. Non-profit, educational or personal use tips the balance in favor of fair use.”

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source and Oracle Clinical.

At Last, at the Right Place, at the Right Time?

There’s something to be said for being in the right place at the right time. I, for once, I traveled the world and lived in many places. I can tell right away if it is going to work out. If I”m at the right place.

The last place I spent most of my time was the worse I ever seen and experienced but there was a lesson to be learned so for that, I have to be thankful for.

The pursue of happiness sometimes takes us to the wrong road. It is like getting lost without GPS and not knowing which way to go.

When you try hard enough for long enough you can’t help but end up achieving your goals.

It’s the most important reason why you should keep trying — because tomorrow might be the day where you find yourself standing at the right place at the right time.

You can’t change most of what goes on around you but you have control of your life. I learned that to be case. Know one can feel the satisfaction to wake up each morning and say “I did it my way” but yourself. Of course, there are third-parties controlling our life whether we want it or not. This is the system we live in.

 

 

 

 

 

 

 

 

 

 

 

Don’t get me wrong. I have made countless mistakes and my career almost suffered for those bad choices. I left a life of having it all, eg. brand new cars, houses, eating out in nice restaurants, traveling and staying in nice hotels to a dull, boring life with very little to show for. Where my only topic was about taxation, living in a boring town and political topics.

And then to top it off, I had just experienced a pretty major disappointment in the form of a deception – the most important person in my life deceived me and I was feeling pretty unimpressed and doubtful about myself, my decisions, my non-existent life plan and my need to get out of this town. To be totally honest, things had speedily declined from: I live in beautiful town and I’m awesome, to I live in horrible town and this sucks.

Then, something happened to totally and undoubtedly convince me that south of the border is indeed the right place and now is exactly the right time, in fact over the last month people around me have used that ‘right place, right time’ phrase to describe my circumstance and I agree. I am now 100% sure that I’m exactly where I should be right now.

Amazingly, I think I can be sure for once I am in the right place at the right time

My friend Osvaldo has also helped me to appreciate a few other life lessons. For example, he said to me that we have no control over the big plan. Now, don’t get me wrong, I’m not advocating sitting around and letting life just take you for a ride. I am big into making stuff happen, for pushing the envelope, for trying everything and finding out what’s right. But at the end of the day, the plan is already written, it’s up to you to listen to your instincts and look hard for the signs that you are on the right track; to live life doing the things you love.

Are you getting the most out of your life?

Anayansi Gamboa has an extensive background in clinical data management as well as experience with different EDC systems including Oracle InForm, InForm Architect, Central Designer, CIS, Clintrial, Medidata Rave, Central Coding, OpenClinica Open Source; Oracle Clinica and clinical programming using SAS.

No Disclaimer: There is no disclaimer in this article because the reader will learn that we are all responsible for our perception and interpretation of anything and everything we experience. I have no intention of disclaiming anything I write. – Anayansi Gamboa, DBA GAMBOA

Images: Copyright images from Google images

Mission Impossible?

We all know about the movie with Tom Cruise ‘Mission Impossible‘. I personally never liked it. It was just entertainment only. But these past few weeks I felt I was working on a mission impossible.  It is like this place didn’t want me to leave until a suffer one more time. What is one more struggle? This place, like a vampire, has sucked up all my money and energy. All of my blood. There is nothing left but my body, mind, and soul and it is trying to take that too.

I have to admit today I was doubting my own words. You can read my post on the law of attraction and success here. For several months, the law of attraction has worked. I attracted everything that I wanted in my career and life. But suddenly, I felt like I am walking through a desert with no end in sight. I felt like it’s windy and dusty and there’s no sign of water and I am walking with all me but getting nowhere.

Success is something you attract not something you pursue.

Law Of Attraction Success
Anayansi’s Mazda cx7
Anayansi’s Corvette
Anayansi’s Corvette
Ford Mustang
Law of Attraction affirmations
SYSDBA – Corvette License Plate
Mazda Miata
Anayansi in Germany
Anayansi’s Motorcycle

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

I am sorry. I have tried so hard to stay positive. Every day, I work on my positive affirmations but each time I read an email or sit around waiting, I got more upset and therefore, going backwards on the attend to reboot my career and bring success back into my life. That success I left behind in the United States. The land of dreams and opportunities.

Finally, I heard good news. My professional blue card is approved and I can start my new life and career away from this horse town. Away from this place and life that has drained everything out of me.

It’s time to pack up and say –‘doei doei‘ – ‘Willkommen zuhause‘.

Source:

https://www.linkedin.com/pulse/one-year-success-plan-anayansi-van-der-berg-mpm-pt

https://www.linkedin.com/pulse/personality-types-what-your-style-anayansi-van-der-berg-mpm-pt

Yvonne Koelemeijer

Using PROC UNIVARIATE to Validate Clinical Data

Using PROC UNIVARIATE to Validate Clinical Data

When your data isn’t clean, you need to locate the errors and validate them.  We can use SAS Procedures to determine whether or not the data is clean. Today, we will cover the PROC  UNIVARIATE procedure.

  • First step is to identify the errors in a raw data file. Usually, in our DMP, in the DVP/DVS section, we can identify what it is considered ‘clean’ or data errors.
    • Study your data
  • Then validate using PROC UNIVARIATE procedure.
  • Find extreme values

When you validate your data, you are looking for:

  • Missing values
  • Invalid values
  • Out-of-ranges values
  • Duplicate values

Previously, we used PROC FREQ to find missing/unique values. Today, we will use PROC UNIVARIATE which is useful for finding data outliers, which are data that falls outside expected values.

proc univariate data=labdata nextrobs=10;
var LBRESULT;
run;

Lab data result using Univariate

 

 

 

 

 

 

 

 

 

For validating data, you will be more interested in the last two tables from this report. The missing values table shows that the variable LBRESULT has 260 missing values. There are 457 observations. The extreme observations table can tell us the lowest and highest values (possible outliers) from our dataset. The nextrobs=10 specify the number of extreme observations to display on the report. To suppress it use nextrobs=0.

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