I still Cry – Ilse Delange

I Still Cry
I’m making flowers out of paper
While darkness takes the afternoon
I know that they won’t last forever
But real ones fade away to soon
I still cry sometimes when I remember you
I still cry sometimes when I hear your name
I said goodbye and I know you’re alright now
But when the leaves start falling down I still cry
It’s just that I recall September
It’s just that I still hear your song
It’s just I can’t seem to remember
Forever more those days are gone
I still cry sometimes when I remember you
I still cry sometimes when I hear your name
I said goodbye and I know you’re alright now
But when the leaves start falling down I still cry
I still cry sometimes when I remember you
I still cry sometimes when I hear your name
I said goodbye and I know you’re alright now
But when the leaves start falling down I still cry
But when the leaves start falling down I still cry
Source: LyricFind

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Clinical Trials – Computerized Systems

The Food and Drug Administration (FDA) established the Bioresearch Monitoring (BIMO) program of inspections and audits to monitor the conduct and reporting of clinical trials to ensure that data from these clinical trials meet the highest standards of quality and integrity and conform to FDA’s regulations.

Computerized systems used in clinical trials refer to the creation, modification, maintenance, archiving, retrieving or transmitting clinical data intended for submission to the Food and Drug Administration (FDA).

Key Definitions:

Audit Trail: a secure, computer-generated, time-stamped electronic record that allows reconstructions of the data course of events relating to the creation, modification, and deletion of an electronic record.

Certified Copy: it is a copy of the original information that has been verified, as an exact copy having all of the same attributes and information as the original. It must have a dated signature.

Computerized System: it is the computer hardware, software, and associated documents (i.e manuals) that create, modify, maintain, archive, retrieve, or transmit in digital form information related to the conduct of a clinical trial.

Electronic Case Report Form (e-CRF): designed to record information required by the clinical trial protocol to be reported to the sponsor on each trial subject.

Electronic Patient Diary: an electronic record into which a subject participating in a clinical trial directly entrees observations or directly responds to an evaluation checklist or questionnaire

Electronic Record: a combination of text, graphics, data, audio, pictorial, or any other information representation in digital form that is created, modified, maintained, archived, retrieved or distributed by a computer system.

Electronic Signature: a computer data compilation of any symbol or series of symbols, executed, adopted, or authorized by an individual to be legally binding equivalent of the individual’s handwritten signature.

Software Validation: verification and validation is the process of checking that a software system meets specifications and that it fulfills its intended purpose. For these guidelines, the design level validation is that portion of the software validation that takes place in parts of the software life cycle before the software is delivered to the end-user.

Source Documents: original documents and records including, but not limited to, hospital records, clinical and office charts, laboratory notes, memoranda, subjects’ diaries or evaluation checklists, pharmacy dispensing records, recorded data from automated instruments,copies or transcriptions certified after verification as being accurate and complete, microfiches,photographic negatives, microfilm or magnetic media, x-rays, subject files, and records kept at the pharmacy, at the laboratories, and at medico-technical departments involved in the clinical trial.

Principles:

Security measures should be in place to prevent unauthorized access to the data and to the computerized system.

1-Identify at which steps a computerized system will be used to create, modify, maintain, archive, retrieve, or transmit data.

2-Documentation should identify what software and, if known, what hardware is to be used in computerized systems that create, modify, maintain, archive, retrieve, or transmit data. This document should be retained as part of the study records.

3-Source documents should be retained to enable reconstruction and evaluation of the trial.

4-When original observations are entered directly into a computerized system, the electronic record is the source document.

5-The design of a computerized system should ensure that all applicable regulatory requirements for recordkeeping and record retention in clinical trials are met with the same degree of confidence as is provided with paper systems.

6-Clinical investigators should retain either the original or a certified copy of all source documents sent to a sponsor or contract research organization, including query resolution correspondence.

7-Any change to a record required to be maintained should not obscure the original information. The record should clearly indicate that a change was made and clearly provide a means to locate and read the prior information.

8-Change to the data are stored on electronic media will always require an audit trail, in accordance with 21 CRF 11,.10(e). It should include who made the changes, when, and why they were made.

9-The FDA may inspect all records that are intended to support submissions to the Agency, regardless of how they were created or maintained.

10-Data should be retrievable in such a fashion that all information regarding each individual subject in a study is attributable to that subject.

11-Computerized systems should be designed so that all requirements assigned to these systems in a study protocol are satisfied and to preclude errors in data creation, modification, maintenance, archiving, retrieval or transmission.

As we read in this blog about guidance for the industry around computerized systems revolts around data quality and data integrity. The users or people using the data from these systems should have confidence that the data are no less reliable than data in paper form.

In the next blog, we will cover audits and inspections, data entry into this computerized system, security and electronic signatures as a way of certifying the data.

Source:

CFR 11 and ICH

FDA.com

 

 

 

Becoming a Data Scientist {EDC Developer + Statistical Expert + Data Manager}

At an early age, I was drawn to computers. I did well in math; I love science and I started enjoying programming when my stepfather gave me a small computer to program games. This was my real experience with programming. I think the programming language was Basic. The computer had some built-in games and basic math problems in it but you could also play around with ‘Basic‘ codes and create your own.

Then I went to a technical school and into college where you take basic classes in information system /technology and took courses in telecommunication management.  Most of the courses were around IP, PBX and Network Administration.  As part of that curriculum, I took a basic programming course and VB.net. I really like that since it has a visual interface (drag and drop to create the interface) and when you click a button you create an event so I like the design aspect of it (I am known to be very creative) then I started to design for people (website design and development, small databases). A lot better than working in telecommunications. I thought VB was a great first language to learn. Later I took a Microsoft Access database development class and we learn database design (relational) and found out I was really good at that.

Before I graduated, I was already working for a well known pharmaceutical company as a database analyst within their data management and biometrics team. They really like what I did with their clinical operations data (investigator data – you know the one that now we need CTMS systems for nowadays). So this was a confirmation that ‘databases’ was my passion. I love designing it, managing and maintaining it.

During my early years in this industry, I spent a lot of time writing SQL codes and SAS programs.  We pulled the messy data (back in those years we used the Clintrial Oracle backend system) and very problem solving oriented. A business question was asked and we would go using either SQL or SAS and go into this messy database and figure it out the answer. I really enjoyed that.

In recent years, I take data from a {EDC} system then write scripts to summarize the data for reporting and put into a data warehouse and then I use a product called ‘IBM Cognos’, which points to the data warehouse to build those reports and worked with different users across different departments (a lot of different audiences for the data) with a lot of different interesting data in there. I have spent time using APIs to extract data via Web Services (usually in XML-ODM format) and generate useful reports in SAS or Excel XML.

People think that being a data analyst is just sitting around a computer screen and crunching data. A lot of it is design-oriented, people-oriented, and problem-solving. So when people ask a question, I get to dive into the data and figure it out the answer.

Next step is to get into predictive analytics and do more data mining and data forecasting.

Are you still excited about becoming a data scientist?

You can start by reading my blog about programming languages you should learn here!

Other tools and programming languages you should learn: Anaconda, R Programming, Python, Business Intelligence Software like Tableau, Big Data Analytics with Hadoop, create new representations of the data using HTML and CSS (for example when you use APIs, XML to extract data from third-party sources).

Anayansi, MPM, an EDC Developer Consultant and clinical programmer for the Pharmaceutical, Biotech, and Medical Device industry with more than 18 years of experience.

Available for short-term contracts or ad-hoc requests.  See my contact page for more details or contact me.

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Clinical Programmer Available for Consultancy projects.

Clinical Programmer Available for consultancy projects – Medidata Rave Certified.

Rate: Negotiable

Hours: part time or full time

Contracts: 1099 or Corp-2-corps only.

7 (Audio) Books You Should Read in 2018

Do you want to be successful? Looking for your life purpose? Are you feeling down? Unmotivated? Lost? Do you want a better career or business? The following books have helped me obtain the life I desire and guide me through difficult times.

My goals and desires are different than yours but I am sure you will benefit from these books. If anything, you will feel motivated again and eager to embark on a new life. Good luck and share your success stories.

  1. The Richest Man In Babylon –  Napoleon Hill

2.  The Strangest Secret by Earl Nightingale

3. Think And Grow Rich  –  Napoleon Hill

4. Change your life in 20 minutes – Earl Nightingale

5.  Use This For 30 days and Watch Your Prosperity Grow! – Catherine Ponder

6.  W. Clement Stone and Napoleon Hill – Success Through A Positive Mental Attitude

7. Ask and it is Given – Abraham Hicks

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Good Clinical Practice – The Bible

Good Clinical Practice (GCP) is an international ethical and scientific quality standard for
designing, conducting, recording and reporting trials that involve the participation of
human subjects. Compliance with this standard provides public assurance that the rights,
safety and well-being of trial subjects are protected, consistent with the principles that have
their origin in the Declaration of Helsinki, and that the clinical trial data are credible.

Below is the link to the most common terms used in clinical trials (for reference). Use it as your leisure, during work hours and day-to-day work as a clinical researcher.

Good Clinical Practice Bible – Terminologies

How to document the testing done on the edit checks?

Since the introduction of the Electronic Data Capture (EDC) in clinical trials where data is entered directly into the electronic system, it is estimated that the errors (e.g. transcription error) have been reduced by 70% [ Clinical Data Interchange Standards Consortium – Electronic Source Data Interchange 2005].

The Data Management Plan (DMP) defines the validation test to be performed to ensure data entered into the clinical database is complete, correct, allowable, valid and consistent.

Within the DMP, we find the Data Validation Plan. Some companies call it ‘DVS’ others ‘DVP’.  The Good practices for computerized systems in regulated GxP environments defines validation as a system that assures the formal assessment and reporting of quality and performance measures for all the life-cycle stages of software and system development, its implementation, qualification and acceptance, operation, modification, qualification, maintenance, and retirement.

As an {EDC} Developer or Clinical Programmer, you will be asked to:

  • Develop test scripts and execution logs for User Acceptance Testing (UAT).
  • Coordinate of UAT of eCRF build with clinical ops team members and data management and validating documents, included but not limited to: edit check document, issue logs, UAT summary report and preparation and testing of test cases.

Remember not every EDC system is alike. Some systems allow you to perform testing on the edit checks programmed; others allow you to enter test data on a separate instance than production (PROD).

Data Validation and UAT Module.png

For example, some EDC systems facilitate re-usability:

  1. There is a built-in test section for each study – where data can be entered and are stored completely separate from production data. This allows you to keep the test data for as long as needed to serve as proof of testing.
  2. The copy function allows for a library of existing checks (together with their associated CRF pages) to be copied into a new study. If there are no changes to the standard checks or pages then reference can be made back to the original set of test data in a standards study, thus reducing the study level overhead.
  3. The fact that many of the required checks (missing data, range checks, partial dates etc.) do not require the programming of an edit check at all. Each of these and many others are already there as part of the question definition itself and therefore do not need any additional testing or documentation for each study.

If you have not documented, you have not done it-FDA

The “ideal world” scenario would be to reduce the actual edit check testing by the system generating a more “human readable” format of the edit checks. The testers that way would not have to test each boundary conditions of the edit checks once the system is validated. All they would have to do is inspect the “human readable” edit checks vs the alerts and would also be easy for the clients to read and sign off.

You can leverage the EDC systems audit trail under certain conditions. First of all – the system you are testing with must be validated in itself. Some EDC products are only ‘validated’ once a study is built on top of them – they are effectively further developed as part of a study implementation process – in this situation, I would doubt you could safely use the audit trail.

Secondly, you need to come up with a mechanism whereby you can assure that each edit check has been specifically tested – traceability.

Finally, you need to secure the test evidence. The test data inside the EDC tool must be retained for as long as the archive as part of the evidence of testing.

The worst methods in my view are paper / screenshot based. They take too long, and are largely non-reusable. My past experience has been creating test cases using MS Word then performing each step as per test case and take a screenshot, where indicated. Then attached to the final documentation and validation summary. This obviously a manual and tedious process. Some companies create test cases using HPQC or similar tool. This is a bit more automated and traceable yet, it is still prone for errors. It is better than documenting using MS Word or Excel but it is still a manual process.

Re-usability is what it is all about, but, you need to ensure you have methods for assuring the test evidence produced for edit checks you are reusing is usable as part of the re-use exercise.

Edit Check Design, Development and Testing is the largest part of any typical EDC implementation. Applying methods to maximize quality and minimize time spent is one of the areas I have spent considerable time on over the last couple of years.

For additional tips on writing effective edit checks please go here -Effective edit checks eCRFs.

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn

Source images: provided courtesy of Google images.

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Case Study 4: A Full Data Management Solution

Working in a Collaborative Environment

The Scenario:

A phase II study was being managed by a CRO that had non-dedicated teams, escalating costs, with project timelines slipping on almost every deliverable.
RA eClinica Solution:

    • RA eClinica assumed responsibility for entire data management activities consisting of Data Management, Study Build / EDC Development, and Statistics and Programming.
    • RA eClinica preferred Data Management systems utilized with Sponsor’s Safety Surveillance system and Clinical Trial Management System, CTMS

Ra eClinica Results:

    • Study ongoing – All deadlines to date have been met or exceeded
    • Cost savings of approximately 35% in comparison to traditional CRO models
    • No turnover since study start

Anayansi Gamboa- Virtual DM Service from RA eClinica

RA eClinica is a established consultancy company for all essential aspects of statistics, clinical data management and EDC solutions. Our services are targeted to clients in the pharmaceutical and biotech sector, health insurers and medical devices.

The company is headquarter in Panama City and representation offices with business partners in the United States, India and the European Union. For discussion about our services and how you can benefit from our SMEs and cost-effective implementation CDISC SDTM clinical data click here.

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn

PM Hats – Six Thinking Hats in Project Management

Six Thinking Hats

Looking at a Decision From All Points of View

‘Six Thinking Hats’ is an important and powerful technique. It is used to look at decisions from a number of important perspectives. This forces you to move outside your habitual thinking style, and helps you to get a more rounded view of a situation.

This tool was created by Edward de Bono’s book ‘6 Thinking Hats‘.

Many successful people think from a very rational, positive viewpoint. This is part of the reason that they are successful. Often, though, they may fail to look at a problem from an emotional, intuitive, creative or negative viewpoint. This can mean that they underestimate resistance to plans, fail to make creative leaps and do not make essential contingency plans.

Similarly, pessimists may be excessively defensive, and more emotional people may fail to look at decisions calmly and rationally.

If you look at a problem with the ‘Six Thinking Hats’ technique, then you will solve it using all approaches. Your decisions and plans will mix ambition, skill in execution, public sensitivity, creativity and good contingency planning.

How to Use the Tool

You can use Six Thinking Hats in meetings or on your own. In meetings it has the benefit of blocking the confrontations that happen when people with different thinking styles discuss the same problem.

Each ‘Thinking Hat’ is a different style of thinking. These are explained below:

  • White Hat: neutral and objective, concerned with facts and figures
    With this thinking hat you focus on the data available. Look at the information you have, and see what you can learn from it. Look for gaps in your knowledge, and either try to fill them or take account of them.This is where you analyze past trends, and try to extrapolate from historical data.
  • Red Hat: the emotional view
    ‘Wearing’ the red hat, you look at problems using intuition, gut reaction, and emotion. Also try to think how other people will react emotionally. Try to understand the responses of people who do not fully know your reasoning.
  • Black Hat: careful and cautious, the “devil’s advocate” hat * 
    Using black hat thinking, look at all the bad points of the decision. Look at it cautiously and defensively. Try to see why it might not work. This is important because it highlights the weak points in a plan. It allows you to eliminate them, alter them, or prepare contingency plans to counter them.Black Hat thinking helps to make your plans ‘tougher’ and more resilient. It can also help you to spot fatal flaws and risks before you embark on a course of action. Black Hat thinking is one of the real benefits of this technique, as many successful people get so used to thinking positively that often they cannot see problems in advance. This leaves them under-prepared for difficulties.
  • Yellow Hat: sunny and positive 
    The yellow hat helps you to think positively. It is the optimistic viewpoint that helps you to see all the benefits of the decision and the value in it. Yellow Hat thinking helps you to keep going when everything looks gloomy and difficult.
  • Green Hat: associated with fertile growth, creativity, and new ideas
    The Green Hat stands for creativity. This is where you can develop creative solutions to a problem. It is a freewheeling way of thinking, in which there is little criticism of ideas. A whole range of creativity tools can help you here.
  • Blue Hat: cool, the color of the sky, above everything else-the organizing hat 
    The Blue Hat stands for process control. This is the hat worn by people chairing meetings. When running into difficulties because ideas are running dry, they may direct activity into Green Hat thinking. When contingency plans are needed, they will ask for Black Hat thinking, etc.

Exercise:

Here’s an exercise (inspired by Bono ideas) which will work very well with those who have been required to read Six Thinking Hats prior to getting together to brainstorm. Buy several of those delightful Dr. Seuss hats (at least one of each of the six different colors, more if needed) and keep the hats out of sight until everyone is seated. Review the agenda. Review what de Bono says about what each color represents. Then distribute the Dr. Seuss hats, making certain that someone is wearing a hat of each color. Proceed with the discussion, chaired by a person wearing a Blue or White hat. It is imperative that whoever wears a Black hat, for example, be consistently negative and argumentative whereas whoever wears a Yellow must be consistently positive and supportive. After about 15-20 minutes, have each person change to a different colored hat. Resume discussion.

Six Thinking Hats” is about improving communication and decision-making in groups.

Summary: Bono puts thinking into steps: 1. Information 2. Benefits 3.Critical thinking 4. Feelings 5. Creative thinking 6. Thinking about the thinking and creating and action plan for implementation.

How would you incorporate the ‘Six Thinking Hats’ in clinical data management?

Reference:

Six Thinking Hats by Edward de Bono, 1999

http://www.mindtools.com

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Data Management Plan in Clinical Trials

 

The preparation of the data management plan (DMP) is a simple, straightforward approach designed to promote and ensure comprehensive project planning.

The data management plan typically contains the following items. They are:

  1. Introduction/Purpose of the document
  2. Scope of application/Definitions
  3. Abbreviations
  4. Who/what/where/when
  5. Project Schedule/Major Project Milestones
  6. Updates of the DMP
  7. Appendix

The objective of this guidelines is to define the general content of the Data Management Plan (DMP) and the procedures for developing and maintaining this document.

The abbreviation section could include all acronyms used within a particular study for further clarification.

e.g. CRF = Case Report Form
TA = Therapeutic Area

The Who/What/Where/When section should describe the objective of the study specific data management plans for ABC study. This section provides detail information about the indications, the number of subjects planned for the study, countries participating in the clinical trial, monitoring guidelines (SDV) or partial SDV, if any CROs or 3rd party are involved in the study (e.g. IVRS, central labs), which database will be used to collect study information (e.g. Clintrial, Oracle Clinical, Medidata Rave or Inform EDC).

The Appendix provides a place to put supporting information, allowing the body of the DMP to be kept concise and at more summary levels. For example, you could document Database Access of team members, Self-evident correction plan, Data Entry plan if using Double-data entry systems or Paper-Based clinical trials systems.

Remember, this is a living document and must be updated throughout the course of the clinical trial.

If problems arise during the life of a project, our first hunch would be that the project was not properly planned.

Reference: Role of Project Management in Clinical Trials
Your comments and questions are valued and encouraged.
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.

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn

Disclaimer: The legal entity on this blog is registered as Doing Business As (DBA) – Trade Name – Fictitious Name – Assumed Name as “GAMBOA”.

Data Management: Queries in Clinical Trials

When an item or variable has an error or a query raised against it, it is said to have a “discrepancy” or “query”.

All EDC systems have a discrepancy management tool or also refer to “edit check” or “validation check” that is programmed using any known programming language (i.e. PL/SQL, C# sharp, SQL, Python, etc).

So what is a ‘query’? A query is an error generated when a validation check detects a problem with the data. Validation checks are run automatically whenever a page is saved “submitted” and can identify problems with a single variable, between two or more variables on the same eCRF page, or between variables on different pages. A variable can have multiple validation checks associated with it.

Errors can be resolved in several ways:

  • by correcting the error – entering a new value for example or when the datapoint is updated
  • by marking the variable as correct – some EDC systems required additional response or you can raise a further query if you are not satisfied with the response

Dealing with queries
Queries can be issued and/or answered by a number of people involved in the trial. Some of the common setups are: CDM, CRA or monitors, Site or coordinators.

Types of Queries

  • Auto-Queries or Systems checks
  • Manual Queries
  • Coding Queries
  • SDV related Queries generated during a Monitor visit
  • External Queries – for external loaded data in SAS format

EDC Systems and Discrepancy Output Examples

InForm

Note: All queries are associated to a single data item relevant to that query.

RAVE

Note: Users are only able to see / perform an action on a query based on their
role and the permissions via Core Config.

Timaeus

Note: Queries are highlighted by a red outline and a Warning icon.

OpenClinica

Note: Extensive interfaces for data query.

Query Metrics – It is important to measure the performance of your clinical trials.
Metrics are the same for all clinical studies but not all EDC systems are the same. Standardized metrics encourage performance improvement, effectiveness, and efficiency. Some common metrics are:

  • Outstanding Query
  • Query Answer Time
  • Average Time to Query Resolution
  • Number of closed discrepancies on all ongoing studies

Data management’s experience with data queries in clinical trials

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Trademarks: InForm is a trademark or registered trademark of Oracle Corporation. Rave is a trademark or registered trademark of Medidata. Timaeus is a trademark or registered trademark of Cmed Clinical Research.


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.

Role of Project Management and the Project Manager in Clinical Data Management

 

The Project Manager is responsible for the development, oversight of implementation, and communication of clinical research studies.

So what is a Project?

A project is a work effort with a definite beginning and end, an identifiable end result (deliverable), and usually has limits on resources, costs and/or schedule.

What is Project Management?

The application of knowledge, skills, tools, and techniques to project tasks in order to meet project requirements.

In order to be a successful project manager, you need to understand the “Tripple Constraint” and how they affect your project. Let’s look up the WBS-edit checks:

Note: I will refer a project = clinical study

Scope: What is in the contract? How many edit checks, SAS checks and manual checks are required in this study? What is the effort per edit check, SAS check and manual check?

The goal is to convert the idea of data management to that of statistical analysis – an analyzable database.

Time: What are the deliverables and timelines? What resources are needed?

Cost: What are the budget restrictions? Are there any risks associated with any changes?

Project Planning: During the planning of a clinical study, we identify the project scope, develop the project management plan and we identify and schedule the clinical study activities.

Some questions might arise during the project planning phase: how many sites/subjects and pages will be collected?Who will attend team meetings? what study fields will be code (i.e. Adverse Event term)?

Other important activities that the project manager and clinical team members will need to be involved:

Work Break Down (WBS) – it is the list of activities that will be performed during the course of a clinical study.

Resourcing – it is important to assign the right person to a particular task based on skills, education and experience.

ICH Guidelines ‘…all personnel involved in clinical trials must be qualified and properly trained to perform their respective tasks…’

Estimating Cost – look at historical data as well as good estimates from effort per unit and units using your WBS as references.

Scheduling and Budgeting – you will be able to build schedules and budgets that transform project constraints into project success after you successfully construct your Work Breakdown Structures (WBS) and network diagrams and estimate task durations.

Projects managers used techniques for employed to establish project. Project Manager can decide which activity can be delayed without affecting the duration of the projects. They help improving quality and reduce the risks and costs related with the projects.

A recent survey by the Project Management Institute provided 10 challenges affecting project managers. This research intended to identify key factors affecting project team performance:

  1. Changes to Project Scope (Scope Creep)
  2. Resources are Inadequate (Excluding Funding)
  3. Insufficient Time to Complete the Project
  4. Critical Requirements are Unspecified or Missing
  5. Inadequate Project Testing
  6. Critical Project Tasks are Delivered Late
  7. Key Team Members Lack Adequate Authority
  8. The Project Sponsor is Unavailable to Approve Strategic Decisions
  9. Insufficient Project Funding
  10. Key Team Members Lack Critical Skills

Another question to ask is what tools are available to help you get the job done?

  1. Resource allocation (and the software’s ability to easily display staff who were overallocated)
  2. Web-based/SaaS option
  3. Cost/Price of the system (big one!)
  4. Contractual terms we could enter into (i.e. 6 months, 12 months, month to month)
  5. Ability to demo the software and for how long
  6. What sort of customizations could be made to the software after purchase
  7. Types of customers the software has served
  8. Report types
  9. Ability to sync with accounting software and which ones, if so
  10. Timeline generation capabilities and import function with MS Project
  11. Ability to create template projects
  12. Ability to alert on early warning signs (i.e. budget overruns over 10%)

It is suggestted that you review each suggestion on project management tool very, very carefully to determine how it fits your processes.

Your organization’s processes are unique to your organization; no other organization anywhere has quite the same processes. So what may work for one organization may not necessarily work for you. Your organization developed its processes to suit your particular corporate culture, the particular collective character attributes of the employees (their experience, etc.), the type of projects that you execute and the particular types customers/clients that you have (especially the regular ones).

You now have to make sure that the tools you choose work for you and your particular processes. Do not change your processes again to suit whatever workflow (process) is dictated by the fancy tool that the fancy salesman sold to you; you are likely to find that the tool-dictated workflows do not work that well in your organization, with the result that the employees will give up following processes and/or give up using the tool, throwing everything into chaos again.

Be careful if you are looking at tools that offer to do a number of different functions or can be made to do any function you want it to do. They seldom do the job that you bought it for particularly well. For example, I have worked with a tool that was advertised as a combination issue tracking and defect/bug tracking tool. It was used as a defect tracking tool but it was very poor; it was tremendously difficult to make it prepare useful reports. A hand-written tool set up in a spreadsheet (e.g. Microsoft Excel) or database (e.g. Microsoft Access) would have worked better.

That said, there are tools out there that are specific to one particular function but do offer flexible workflows – they may be modified to match whatever processes your organization already follows.

If your organization has just started to organize the PM processes and PMO that would mean processes & other related areas are not explicitly defined. So there may be a huge risk trying to adopt an integrated and centralized project management system. It is more likely to offer you a very comprehensive, complex but expensive solution wherein your problem is still not defined completely. In such a case you are just not ready with the environment and process maturity that an integrated tool requires prior to implementation.

A more efficient approach should be iterative, incremental and adaptive in nature. That means you shall use simple, not so expensive tools with limited scope to begin with; they can be tools with basic functionalities of WBS, scheduling, traceability and custom datasheets. These tools should have capability to exchange data both ways with more commonly uses tools like MS Excel, MS Project, and Word etc. The processes are likely to mature over time and we will then know the real effectiveness of these basic tools in the context of company requirements. That may be the time to analyze and switch to more integrated solutions.

One important key to remember. The role of project management in clinical trials is evolving. There is a debate about who should be the ‘project manager’ for a particular clinical study. CRA or Clinical Data Manager or an independent project manager? Let’s review their roles within data management.

Clinical Research Associate (CRA): main function is to monitor clinical trials. He or she may work directly with the sponsor company of a clinical trial, as an independent freelancer or for a Contract Research Organization (CRO). A clinical research associate ensures compliance with the clinical trial protocol, checks clinical site activities, makes on-site visits, reviews Case Report Forms (CRFs) and communicates with clinical research investigators. A clinical research associate is usually required to possess an academic degree in Life Sciences and needs to have a good knowledge of Good clinical practice and local regulations. In the United States, the rules are codified in Title 21 of the Code of Federal Regulations. In the European Union these guidelines are part of EudraLex. In India he / she requires knowledge about schedule Y amendments in drug and cosmetic act 1945.

Clinical Data Manager (CDM): plays a key role in the setup and conduct of a clinical trial. The data collected during a clinical trial will form the basis of subsequent safety and efficacy analysis which in turn drive decision-making on product development in the pharmaceutical industry. The Clinical Data Manager will be involved in early discussions about data collection options and will then oversee development of data collection tools based on the clinical trial protocol. Once subject enrollment begins the Clinical Data Manager will ensure that data is collected, validated, complete and consistent. The Clinical Data Manager will liaise with other data providers (eg a central laboratory processing blood samples collected) and ensure that such data is transmitted securely and is consistent with other data collected in the clinical trial. At the completion of the clinical trial the Clinical Data Manager will ensure that all data expected to be captured has been accounted for and that all data management activities are complete. At this stage the data will be declared final (terminology varies but common descriptions are Database Lock and Database Freeze) and the Clinical Data Manager will transfer data for statistical analysis.

Clinical Data Management (CDMS) Tools: (we will review each of them on a separate discussion)

  • Standard Operating Procedures (SOPs)
  • The Data Management Plan (DMP)
  • Case Report Form Design (CRF)
  • Database Design and Build (DDB)
  • Validation Rules also known as edit checks
  • User Acceptance Testing (UAT)
  • Data Entry (DE)
  • Data Validation (DV)
  • Data Queries (DQ)
  • Central Laboratory Data (CLD)
  • Other External Data
  • Serious Adverse Event Reconciliation (SAE)
  • Patient Recorded Data (PRO)
  • Database finalization and Extraction
  • Metrics and Tracking – see BioClinica article on Metrics
  • Quality Control (QC)- see discussion on A QC Plan for A Quality Clinical Database

In conclusion, a key component of a successful clinical study is delivering the project rapidly and cost effectively. Project managers must balance resources, budget and schedule constraints, and ever-increasing sponsor expectations.

Source:

To hire me for services, you may contact me via Contact Me OR Join me on LinkedIn
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.

 

X EDC: The Next Generation of EDC?

RaveX is an EDC system that is powerful and easy to learn. Medidata has one of the best eLearning and training courses to get anyone up and running from the first time you use the system.

The study design setup still requires high technical skills including C# sharp for most complex data cleaning and study setup tasks.

Let’s discuss the new study hierarchy:

We already understand the relationship between the studies, sites, and subjects in Rave EDC.

At the navigation bar in RaveX EDC, we choose the study from the list of studies assigned to your role. At the second level, we can see the study dashboard. The dashboard contains information about the sites and subject enrollment.  From the sites, you can drill down to the subject level or subject related eCRFs.

Subject’s landing page:

  • Access eCRFs
  • Perform role-specific functions (e.g. SDV, DM data review, PI signature, enter data)

Understanding Status Icons in EDC:

On a form, when you click on an icon, the action is taken on that data point. Based on your roles and permissions, you could apply this action individually or to “Apply All”.

Common status icons:

When you select a subject, you arrive at the subject landing page. Some old features are the scheduled visit dates (a feel and look of the matrix in Rave Architect), the subject status and the status of their eCRFs and some additional information.

At the scheduled level (for Oracle InForm users, this is the Time and Event Scheduled with the traffic lights), you can open a folder and access a particular form residing on that folder.  You can then proceed with normal data entry.

There are several ways to access the same eCRF for another subject. Navigate to it by selecting a subject from the subject list.

Performing data cleaning and data review:

At the study level, select the RaveX study then select the study name you would like to perform a task.

On the screen, select ‘View Task Management’ link and then select the open queries link. At this level, you can select the particular subject and form a query that is opened on. For example, I noticed an open query on the informed consent form. To view it, select the query link on the screening informed consent row.

What modules are still available in this new design?

  • Rave Architect
  • Rave User Administration
  • Rave Site Administration
  • Rave Reporter
  • Rave Configuration
  • Rave PDF Generator
  • Rave Lab Administration
  • and more…

Overall, the EDC solution has been easy to use for database development, data entry, and data validation. The online, real-time validation feature is a plus as it does no longer requires the form to be saved for the checks to fire.

Have we lost any features to this new fancy design? Find out next.

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911 – Silence

Another year has passed and another year that the culprits of 911 are at large while the war on terror (aka the war on YOU) continues.

The only ones beneficiating from 911 war on terror are the same calling for more wars, more security at the airports (of course, they have the contracts for those machines causing cancers and the security agencies are all from the same group of people)

In order to keep the wars, they need more taxes.

He who has ears to hear, let him hear.

Follow the Money….before, during and after 911

A Conspiracy Theory that happened to be truth…

To Mossad from Dick Chenney – The Elephant in the room…

Methodical Deception

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O PAPAGAIO – Anne Simoni

I recently found a CD I bought years ago from a Brazilian friend. We used to hang out in the Philly area and finding this CD brought me good memories.

Anne has a lot of talent and a great voice. My favorite songs from the CD are: Longe de Mim, Unidos da Lavra, and Papagaio.

Foi bom lembrar os bons e velhos tempos. ..lembrando de você..

O PAPAGAIO GRITOU
QUANDO LIGUEI O ASPIRADOR
SÓ FALTOU ME PEDIR
DESLIGA ISSO, POR FAVOR

MAS NÃO PODE FALAR
ELE AINDA NÃO APRENDEU
VEIO LÁ DO BRASIL
PRA GAIOLA DO GRINGO ENFEITAR

ENQUANTO ASPIRO A SALA DO SOBRADO
EU FICO PENSANDO NO COITADO
FOI CAÇADO, VENDIDO, EXPORTADO
PRA VIVER ENGAIOLADO
E AINDA POR CIMA, VAI TER QUE APRENDER INGLÊS.

FALA, FALA, FALA PAPAGAIO
VOU TE ENSINAR O PORTUGUÊS
FALA, FALA, FALA PAPAGAIO
VOU TE ENSINAR A CONTAR ATÉ TRÊS

 

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Motto of the Month

‘When the debate is lost, slander becomes the tool of the loser.’ – Unknown.

Even though many websites attribute this quote to Socrates, it is confirmed he never said it. It is still a nice quote and I’m sharing it with you this month.

 

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How the Pharmaceutical Industry became into existence?

The Birth of the Pharmaceutical Industry can be traced back to 1850 – 1875 where the first “authentic” drug was developed by extracting agents from plants.

In those years, there were also developed the microbial theory of disease, medicines and homoeopathy patent and there heavy use of powerful purgatives and cathartics medicines.

By 1875, the Drug Development becomes a science and the first synthetic drug was introduced. By 1900, vaccines and antitoxins form the basis of the new pharmaceutical industry.

From 1900 to 1925, began what is now known as the pharmaceutical century. The U.S. Pure Food and Drugs Act was passed (known today as the FDA) and the development of hormonal and chemotherapy was introduced.

After 1925, it began what is known today as the Antibiotic and Regulatory Era. Vitamins, antimalarials, anticarcinogenic compounds and anti-infectives discoveries were made. The FDA gains independence as a regulatory agency and is given compliance responsibility.

From 1950 thru 1975, a new generation of the drug became apparent. Vaccines for polio became mandatory, oral contraceptives appears on the market and cardiovascular therapies.

Also, an amendment to the Federal Food Drug and Cosmetic Act of 1938 Act was signed by President Kennedy to ensure that consumers will not be the victims of unsafe and ineffective medications. Additional information about this Act can be read here: Kefauver-Harris Amendments

The Globalization of the Pharmaceuticals industry started from 1975 thru 2000. New drugs therapies, new antiviral drugs, and the development of new drugs by biotechnology companies were in global high demand.

By 2000, over 2.8 million people participated in over 50,000 clinical trials and more research and development funding was increased.

R&D Expenditures by Body System

R&D Expenditures

Cost (Billions) Body System
7.0 Central Nervous System
6.0 Cancer, endocrine and metabolic
4.5 Cardiovascular
3.5 Infectious Disease
2.5 Biological and vaccines
5.3 Other

Current Trends in the Industry since the late 2000s

Biotechnology Medicines
Drug Intervention Targets
Vaccines

 

Role of Generic Drugs
Generic drugs account for over 47% of prescription drugs in the market in which 43 major prescription drugs come off patent by 2005.

What does this mean for pharmaceutical drugs?
Between 40% – 60% of sales are lost to the generic brand within the two years of coming off patent.

Factors that will impact the R&D future:

  • There has been over 40 mergers and acquisitions since 1985
    • Sanofi and Synthelabo
    • Zeneca and Astra
    • Monsanto and Pharmacia
    • Roche and Genentech
  • Employment grew at a 3% rate per year

Total Drug Development Time (Years)

Summary:
On average, it takes at least ten years for a new medicine to complete the journey from initial discovery to the marketplace, with clinical trials alone taking six to seven years on average. The average cost to research and develop each successful drug is estimated to be $2.6 billion.

Pharmaceutical Regulation

In 1902, about 10 children die after receiving a vaccine shot. The BIOLOGICS CONTROL ACT was passed to ensure purity and safety of serums, vaccines and similar products used to prevent or treat diseases in humans.

In 1906, “The Great American Fraud” reveals patent medicines laced with addictive drugs, toxic additive and alcohol.

In 1912, Public outcry over the sales of “snake venom” and other wonder cures.  The SHERLEY AMEND was passed to prohibit labelling medicines with false therapeutic claims intended to defraud the purchaser.

In 1927, the government forms a separate law enforcement agency called the Food, Drug and Insecticide Agency.

In 1937, about 107 people, including many children die after drinking a syrup called Elixir of Sulfanilamide. Due to safety concerns, The Federal, Food, Drug and Cosmetic Act (1938) was passed as the first attempt to regulate cosmetics and medical devices.

In 1962, the sleeping pill “Thalidomide“, developed what is known today as Grunenthal Pharmaceutical in Germany, resulted in thousands of birth defects in Western Europe. The KEFAUVER-HARRIS Drug Amend was passed to ensure drug efficacy and greater drug safety.

In 1983, the ORPHAN DRUG Act was passed enabling the FDA to promote research and marketing of drugs needed for treatment of rare diseases. This year there as an outbreak of HIV / AIDS cases.

In 1988, The FOOD and DRUG ADMINISTRATION ACT were established as the FDA under the Department of Health and Human Services.

In 1992, the pharmaceutical industry complained that life-saving drugs were being reviewed too slowly by the FDA. The PRESCRIPTION DRUG USER FEE ACT (PDUFA) is made into law.

Source:

Image: Courtesy of Google image

FDA website

Private information for college researched in the 2000s.