The FDA (Food and Drug Administration) has released the well known standard 21 CFR PART 11, which governs how affected systems should handle electronic records and signatures. The scope of this standard extends to all companies within the food, clinical or pharmaceutical industries.
The question is if a web-based training system (also called Learning Management System or LMS for short) is required to be compliant with Part 11 or not. There is no clear answer to this question however; just as it is the case with any type of system (be it web-based or not) it depends on two main factors:
- What the system is/will be used for.
- If the system’s output (electronic or paper) will be used as official records.
If the system is/will be used to train employees and the electronic records of this process will be the proof of completion, compliance with Part 11 is required.
On the other hand, if compliance is not required, it may still be a good idea to verify if the employed system would confirm with Part 11 or not. The standard itself was created for the purpose of information security and the general requirements of confidentiality, integrity and availability (also known as CIA) are represented in it. The same view is employed here as is in many standards regarding information security.
More information and resources on the subject can be found here:
As you probably know, there is a publicly available database wcich contains many information on majority of clinical trials – at least on trials with US-citizens – started in 1983.
In this post I try to show what information is stored in this database and how can you manage it with free statistical tools.
I give a detailed description on the ID-structure and give solutions for specific scientific questions.
The questions I try to answer with this small presentation:
- How to determine the number of “recruiting” sites, how to generate a list of cities with total number of recruiting facilities and how to plot the ‘Recruiting’ sites on a Google map.
The data can be downloaded from
With choosing pipe-delimited text files, you can easily read the content with any text-editor (I would recommend notepad++).
If you have some statistical background and especially you have access to SAS you can download SAS transport files as well.
After downloading a close to 2 GB zipped file, youl’ll get a set of 40 files.
One of the tools can be used for management of this files is R or its menu-driven version RStudio.
As it is stated on the webpage http://aact.ctti-clinicaltrials.org, you can easily read the downloaded files with the help of the code:
read.table(file = "id_information.txt", header = TRUE, sep = "|", na.strings = "", comment.char = "", quote = "\"", fill = FALSE, nrows = 200000)
The most important file is the Studies database ( open in new window ). You can find information – among others – on
last verification date
number of arms and groups.
The file contains data of more than 251 thousand studies (only the first 1000 can be found on our site).
Task 1: Answer the question how many open (overall status = ‘RECRUITING’) studies can be found tabulated by sites.
We have to lean on Facilities and Studies databases. The Facilities database – the 1st 1000 records – can be checked here.
To get the database containing both study and facility relevant data, you have to merge the two databases.
In R with the command
library(Hmisc) library(data.table) library(DT)studies <- read.table("DIR/studies.txt", header = TRUE, sep = "|", na.strings = "", comment.char = "", quote = "\"", fill = FALSE, nrows=5000) facilities <- read.table("DIR/facilities.txt", header = TRUE, sep = "|", na.strings = "", comment.char = "", quote = "\"", fill = FALSE, nrows=5000) sites <- merge(studies, facilities, by = "nct_id") my <- c("nct_id", "overall_status", "city", "state", "zip", "country", "name") sitesa <- sites[my] sitesa$city <- tolower(sitesa$city)
If you would like to have a table on sites with “recruting’ status, you can obtain a table like this:
with the commands:
datatable(setDT(sitesa_c_final)[, .N, by = .(overall_status,city)][order(-N)])
Or if you would like to demonstrate the status of the sites on a Google map? There is no problem, but I would recommend to change from RStudio to Knime.
If you would like to place the sites on a map you’ll need their exact coordinates. The good news is that this information is also available for free. You can download the necessary database from Maxmind site ( https://www.maxmind.com/en/free-world-cities-database ).
Addition of the coordinates to the database with cities can be done with the following code:
coords <- read.table("e:/_job/clinicaltrials.gov/worldcities/worldcitiespop.txt", header = TRUE, sep = ",", na.strings = "", comment.char = "", quote = "\"", fill = FALSE) sitesa_c <- merge(sitesa, coords, by.x = "city", by.y = "City") sitesa_c_final <- subset(sitesa_c, sitesa_c$overall_status == "Recruiting")
This sitesa_c_final table is given to KNIME, where the following actions should be done:
The outcome looks like this, where the shown sites (indicated by their names) indicate the sites with ‘Recruiting’ status.
OpenTrialsFDA works on making clinical trial data from the FDA (the US Food and Drug Administration) more easily accessible and searchable. Until now, this information has been hidden in the user-unfriendly Drug Approval Packages that the FDA publishes via its dataportal Drugs@FDA. These are often just images of pages, so you cannot even search for a text phrase in them. OpenTrialsFDA scrapes all the relevant data and documents from the FDA documents, runs Optical Character Recognition across all documents and links this information to other clinical trial data.
Explore the public beta version through a new user-friendly web interface at https://fda.opentrials.net.
Although it is piece of news from 2012, but it cannot be say enough, that FDA officially accepts submissions in R.
“The FDA does not endorse or require any particular software to be used for clinical trial submissions, and there are no regulations that restrict the use of open source software (including R) at the FDA. Nonetheless, any software (R included) used to prepare data analysis from clinical trials must comply with the various FDA regulations and guidances. The R Foundation helpfully provides a guidance document for the use of R in regulated clinical trial environments, which provides details of the specific FDA regulations and how R complies with them.”
The details can be found in here.