Tag Archives: Clinical Data Analyst

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.

Fair Use Notice: Images/logos/graphics on this page contains some copyrighted material whose use has not been authorized by the copyright owners. We believe that this not-for-profit, educational, and/or criticism or commentary use on the Web constitutes a fair use of the copyrighted material (as provided for in section 107 of the US Copyright Law).

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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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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.

HTML Tips to Enhance Your eCRF

In some cases, the display of your OpenClinica eCRF may not be exactly what you had in mind. You may want to highlight key words or phrases, create a bullet point list, or insert a URL or image. Using HTML tags, you can make some simple manipulations to change the look and feel of your case report forms and make them more inviting for data entry.

Using HTML tags to enhance your eCRF

The HTML tags described in this document can be used in the following columns in the CRF Excel template:

  • Items Tab: LEFT_ITEM_TEXT
  • Items Tab: RIGHT_ITEM_TEXT
  • Items Tab: HEADER
  • Items Tab: SUBHEADER
  • Sections Tab: INSTRUCTIONS

What are HTML tags?

HTML, or Hyper Text Markup Language, is a markup language that is commonly used for web page development. HTML is written using “tags” that surround text or elements. These tags typically come in pairs, with a start tag and an end tag:

<start tag>Text to format</end tag>

To insert an HTML tag, simply surround the text you want to format with the desired tag. Below are the HTML tags that work in OpenClinica:

Table

You can download this HTML Tags Knowledge Article to help you to get started.

Inserting URLs and Images

HTML also allows you to insert a URL or Image into your CRF, which may be used to provide users with additional information or references.

Insert a URL

A URL may be inserted into a CRF in order to provide a link to further instructions or protocol information. To insert a URL into your CRF, use the following format:

Inserting images - using HTML tags to optimize your eCRF

Simply replace the areas highlighted in yellow with (a) your URL (inside the quotation marks) and (b) the hyperlinked text that you want to display to the user.

The following example will prompt the user to “Click Here!” and will open the OpenClinica website in a new browser tab:

<a href=”https://www.openclinica.com&#8221; target=”_blank”>Click Here!</a>

Inserting an image - using HTML tags to optimize your eCRF

Insert an Image

Similarly, HTML can be used to insert an image into your CRF. You might consider using an image to display a pain scale (or other reference image), or even to display your company’s logo.

Inserting an image - using HTML tags in OpenClinica

To insert an image into your CRF, use the following format:

<img src=”images/ImageName”>

Again, simply replace the highlighted text with your image name. You can use PNG, JPG, or GIF image extensions. You can control the height and width of the image using the following format:

<img src=”images/ImageName” width=“n” height=“n”>

The highlighted n corresponds to the desired width and height of the image in pixels.

The following example will insert an image (image1.png) with a width of 300 and a height of 150:

<img src=”images/image1.png” width=”300″ height=”150″>

You can download this Images & URLs Example CRF to help you practice.

The examples included in the above CRF Excel template will insert an image that already exists in the images directory of your OpenClinica application. To insert a custom image, community users will need to place the image in the following directory of the OpenClinica application:

\tomcat\webapps\OpenClinica\images

OpenClinica Enterprise customers can request an image be placed on the application server by reaching out to the OpenClinica Enterprise Support team via the Issue Tracker.

Have you used HTML in your CRFs? Let us know if you have any other suggestions or tips!


IMPORTANT NOTES:

 The RESPONSE_OPTIONS_TEXT field is not included in the list above, as HTML tags are currently not supported for response options.

 The QUESTION_NUMBER field will display the text properly, but has been known to cause issues when extracting data. Therefore, HTML should not be used in this column.

 

Source: This article was posted by OpenClinica.

Clinical Trials Terminology for SAS Programmers

Entry Level SAS Programmers

Statistical Programmer:requires him to program using the SAS language to analyze clinical data and produce reports for the FDA

Bioanalyst, Clinical Data Analyst, Statistical Programmer Analyst and SAS Programmer: same as Statistical programmer.

Biotechnology:companies which is a general term used to explain a technique of using living organisms within biological systems to develop micro-organisms for a particular purpose.

protocol:outlined all the procedures and contained detailed plans of the study.

controlled experiment: the clinical trial had patients grouped into different groups such as those in the placebo controlled group which had no active drug. This is how comparisons are made within the controlled clinical trial CFR Part 11:Code of Federal Regulations set by the FDA to regulate food, drug, biologics and device industries. The part 11 specifically deals with the creation and maintenance of electronic records.
Case Report Form or CRF:forms to collect information such as demographic and adverse events. Source Data or the information collected:which include important documents because they contain the core information required to reconstruct the essential capital of the study.
sponsor:company who is responsible for the management, financing and conduct of the entire trial. randomized: subjects that are randomly assigned to groups so that each subject has an equal chance to be assigned to the placebo control
baseline: subjects are assigned to their drug change from baseline:analyses that measure differences between baseline and current visit
placebo or sugar pill:is an inactive substance designed to look like the drug being tested. blinded:they do not know if the drug that they are taking contains the active ingredient.
open-label study:all was out in the open, the drug the subject is assigned to. Pharmacokinetics or PK:analysis of that study showed that with that dosing level, there were high levels of toxicity in the subject.
informed consent: described all the potential benefits and risks involved. TLGs: Tables, Listings and Graphs
trade name:drug name that is collected from the patient and recorded into the source data. For example: Tylenol generic name: refers to its chemical compound. For example: Acetaminophen.
WHO-DRUG: list all the drug names and how they matched to the generic drug names.This dictionary is managed by the World Health Organization MedDRA:This is short for Med (Medical), D (Dictionary), R (Regulatory), and A (Activities).
SAP: Statistical Analysis Plan ANOVA: analysis of variable
confidence interval:gives an estimated range of values being calculated from the sample of patient data that is currently in the study. null hypothesis:lack of difference between the groups in a report
pilot study:perform the same analysis upon an older. DIA: Drug Information Association
CBER: Center for Biologics Evaluation and Research (medical device) CDER: Center for Drug Evaluation and Research (drug)

Source:CDER Acronym List


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.