It's all About the Data and MetaData

Benefits of a CTMS in Drug Development

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The Information Technology revolution has simplified the process of managing and sharing large volumes of data.   This is especially true for the pharmaceutical industry that finds itself bogged down by bulk loads of data as it tries to meet the ever-stringent standards of the regulatory authorities. Pharmacovigilance systems and the Clinical Trials Management System (CTMS) help drug companies manage data from clinical trials efficiently, while saving them a great deal of time, money and other resources. Clinical trials usually involve a whole range of activities – right from study setup to recruitment of samples, finance management, investigator selection, monitoring, analyzing and collating data and results. This data-rich process is made a whole lot easier using a CTMS, as day-to-day data collection and collation is carried out in an organized fashion and the entire data can be retrieved, analyzed and transferred within minutes.  So, the company can save on time and money, which can be directed towards making better drugs.

Advantages of an effective Clinical Trials Management System:

1. Allows for integrated electronic data capture of all aspects of a clinical trial
2. Streamlines clinical trials making it easier to monitor, execute and manage clinical trials
3. Fast and accurate tracking and analysis of trial processes and results
4. Allows for easy access and transfer of data, anywhere across the globe
5. Provides automated safety-to-investigator report distribution
6. Saves drug companies money spent to record and maintain data during clinical trials
7. Gives drug companies the flexibility to manage information from clinical trials
8. In the race to get the next ‘wonder drug’ into the market and earn a few more billions, drug companies need to work faster and be more productive as time is of essence, when it comes to saving lives and beating competition.
9. Pharmacovigilance systems like CTMS help companies manage clinical trials efficiently and bring newer products into the market, a lot faster.

Software coding for a covariate adaptive randomization

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Here's a question we were asked regarding clinical trial coding that involved SAS programming.

Question? Can you code a software for covariate adaptive randomization? We are conducting a parallel double blind, placebo-controlled, 5-arm (1 control, 4 intervention) randomized study. We have a list of 225 subjects. For each subject we want the SAS program to put the subject in one of the five arms considering two covariates. The two covariates are: The Center where the patients are recruited (VA, UHS, and Center3), and the other is the Severity of Kidney Disease (Moderate, Severe). The random assignments using this method should prevent a skew of how the subjects get distributed in the arms (that is for example there should not be a large number of VA patients in one arm instead of being evenly distributed in all arms).

This can be done with covariate randomization models with normal distribution using Proc Lifetest, Proc GLM or Proc PHREG etc.

**Suppose there are 100 patients in 3 centers

  classified by sever 1 or 2.**;

data orig;

  do i=1 to 100;

    patNo=i;

      if i<33 then center=1;

      else if i>32 and i<65 then center=2;

      else center=3;

      if i<5 or (i>17 and i<22) or (i>77 and i<92) then sever=1;

      else sever=2;

      output;

  end;

  drop i;

run;

proc sort data=orig; by patNo;

**Randomly Assigning Subjects to Treatments we can use the PLAN procedureto design a completely randomized design to assign one of two  treatments to each patients.**;

**Permuted-block randomization**;

ods listing close;

proc plan seed=54321;

   factors patNo=100 cell=1;

   treatments trt=2 random;

   output out=rand;

run;

ods listing;

proc sort data=rand(drop=cell); by patNo;

data randomized; merge orig(in=a) rand(in=b); by patNo;

  if a;

run;

You can find good articles and further explanations at the SAS support website when typing 'randomization' in the search field. But basically PROC PLAN and PROC FATEX SAS procedures can do it all.

http://www.clinplus.com/report-landing-clinplus-report-tables-listings?utm_campaign=blog

Hope this was helpful! DZS Software Solutions

DZS/ClinPlus can also give you a hand producing the Statistical Analysis Tables of the trial results in the course of the trial. (Safety and Efficacy reports etc.).

A course in Data Management 101 from ClinPlus

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"We are a small emerging life sciences company, and we need to have a data management system that can handle paperCRF-based trials initially, with the ability to move to electronic data capture eventually, but we're not sure what's required in terms of additional staff, hardware and validation."

• Does ClinPlus software require specialized hardware?

Reason for asking:
Both minimum and recommended requirements should be obtained. The simpler the requirements the less costly the system.

DZS Answer:
The hardware requirements for the ClinPlus DM system are the same as SAS's. Generally, if you are able to run SAS then you will be able to support ClinPlus.

• Do we need to have programmers on staff to support your software?

Reason for asking:
Be sure to find out in what situations or phases of study setup where staff programmers are needed. Then inquire about what skill sets are required. The fewer the programmers and the less advanced they need to be, the more likely the software is better designed and easier to use and modify.

DZS Answer: 
Although programming is not required when designing data entry screens, ClinPlus does include "events" where custom code may be inserted.  This allows users to define data entry screens to work exactly as required for their unique application.  SAS SCL programming is used to support this feature (many examples can be found on our User Forum section under Support). 

 Also, Base SAS programming is required for writing edit check programs and any custom reports that are required. No DBAs are required to maintain system data.

• What kind of on-site support staff will we need with your software?

Reason for asking:
Onsite support includes IT support, DBAs, programmers, writers etc. You should also know what skill sets are required. The more support, the more demanding the skill sets requirements, the more expensive the system is to operate.

DZS Answer:
Typically the data managers administer the ClinPlus system. Because ClinPlus is purely SAS, there is little need for IT intervention other than hardware and data backup support. A SAS programmer or two may be needed primarily aiding in screen design and writing edit check programs.

• Will I receive upgrades and enhancements? How often? How much will they cost?

Reason for asking:
While you should expect to receive periodic upgrades and service releases, when those updates are too-frequent "patches", it may be an indication of software instability. Such instability can result in a validation nightmare. It is advisable that you inquire as to the release history of the system. The cost of upgrades should also be considered and added to the overall investment cost.

DZS Answer:
ClinPlus Data Management has been evolving for nearly 20 years with incremental updates including feature and performance enhancements and bug fixes. Incremental releases have averaged 1 per year. If serious problems are identified then a service release is provided immediately. This has occurred less than 10 times in the entire history of the software. DZS is dedicated to the continued development of the ClinPlus software to better serve our clients and to react to the ever-changing technologies and regulations.

• What aspects of the clinical trial process does ClinPlus software address?

Reason for asking:
Most clinical trials software programs are quite specific in their application. Be sure to determine exactly what applications are supplied as well as what other integrated modules are available. Although you many not recognize a current need for a specific capability, it is advisable that the software you choose be able to smoothly integrate with the full scope of clinical trials software requirements.

DZS Answer:
The ClinPlus Data Management product supports CRF tracking, data entry and data review with additional features that support EDC capabilities, import/export and a customizable report writer.   Also available are ClinPlus Coding that supports auto and manual coding of adverse events and drugs, ClinPlus CTMS for your clinical trial management needs and ClinPlus Report for the production of NDA quality tables and listings.
DZS Software Solutions provides the broadest suite of software available for clinical trial support.

• Is ClinPlus software fully validated?

Reason for asking:
If the software in not fully validated, neither is the data it will generate. Software validation is a key requirement of data submitted to the FDA.

DZS Answer:
DZS follows strict SOPs written to satisfy FDA and industry regulations and guidelines. No ClinPlus software is released until it has been fully validated.

• Are validation documents available to me?

Reason for asking:
You are urged to conduct a vendor audit before investing in any clinical trials software. If you are audited by a client or regulatory agency, your software vendor should be able to produce a well organized complete validation report with supporting documentation and assist you with the audit.

DZS Answer:
Yes. A copy of the validation summary may be requested and all supporting documentation will be made available to you during an audit. DZS personnel are also available to assist in an audit.

For more information regarding the implementation requirements of the ClinPlus Data Management System please go to:

Data Management for Clinical Studies 2010

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Found this informative blog post that nicely summarizes all the areas of concern for clinical data management moving into the year 2010.

The management of data at the clinical study level is the foundation of what will eventually become one of the many building blocks of your clinical submission to FDA. Considerations that must be processed and planned by regulation and guideline regarding FDA, EMEA, ICH, TGA, DEC, other, must be current in compliance and compatible and equivalent to pharmaceutical industry standards. Engage experts to manage your data - it is impossible to do otherwise and achieve the integrity of data and accuracy that is required by regulation. At the Clinical Study Level, there are steps in "handling" data, from CRF development to Database Lock to Database and Program Transfers at the end of the clinical study.

Here are important steps and points to consider, and without question, each step and/or action must be recorded, processed and managed by quality management data plans specific for the task - all of the following require "Standard Operating Procedures (SOPs)". On FDA Audit, for sure, these plans must be available for review by the agency. Each respective plan must include data handling versions specific for each task, as reviewed below.

1. CRF Development.
2. Database Setup - CDISC versions 2.0 and 3.1 are used by pharma at this writing and are compliant with regulatory standards and compatible with industry use and FDA review.
3. Data Validation.
4. Data Coding - The management of data for clinical signs and symptoms, AE coding using MedDRA Version 9.1 or previous versions. Treatment Coding using WHODRL Version 6.4 or previous versions. Pharmacovigilance database reconciliation. (See ClinPlus Coding Tool)
5. Quality Control Management Procedures for Interim Data Analysis (IA), Data Entry Audits, Data Review, Data Change, Database Lock and Data/ Program Transfer at the end of the Clinical Study. Data/Program Tranfers can be formatted in .sas., csv., txt., xml, other - the format must be agreed upon by the pharma, all CROs, FDA and WW agencies slated for submission.
6. Quality Control (QC) Plans to ensure accurate, compliant data. Expert QC teams work with raw data captured in the CRF, DCFs, listings, PPs, other source data documentation to ensure correct management and accuracy of data until the database is locked and the data is transferred to the sponsor or to the next step - the clinical submission team.
7. End of Clinical Study Data Management.
8. Data Tools - Clinical Data Management "Systems" that are used by the industry and compatible and compliant with FDA 21 CFR Part 11 Guidance. For example, "Capture System", Version 5.5, Editor "Clinsight".
9. Audit Trail Systems and SOPs to capture all data changes, database actions and data and procedural change and standard deviations.

Expert data management teams work onsite and offsite and integrate with the sponsor, the CROs, the monitors and clinical study site personnel, CRC, CRA, PIS, sub-PIs, from the first data point - and from CRF development to end of study transfer of data and programs. Monitor and Track Data. Develop Plans. Adhere to Plans. Record Changes. Manage Change. Lead the team and manage the plans.