Essay:

Essay details:

  • Subject area(s): Marketing
  • Price: Free download
  • Published on: 14th September 2019
  • File format: Text
  • Number of pages: 2

Text preview of this essay:

This page is a preview - download the full version of this essay above.

1.    Identification of 10 Concepts

1.1. The new rules/guidelines that support ICH concepts are making a major call for compliance with ICH requirements.

This concept is critical in strengthening and improving the existing regulations on compliance with ICH/GCP requirements.

1.2. An accurate case report form is the main intended and logical goal of a clinical trial.

This concept represents the protocol of the clinical trial, the CRF design, managing its production, monitoring the data collection and the auditing of the filled in CRF.

1.3. Remote data entry significantly reduces the chances of errors.

This concept entails entering data directly into a database eliminating the paper stage and reducing the chances of errors and availing up to date data.

1.4. The establishments of timelines result in identification of tasks and key milestones in clinical data management planning and implementation.

The concept provides the framework and timeframe on when/how various deliverables are to be delivered.

1.5. The data validation process ensures the completeness, integrity and consistency of the clinical trial data.

This concept ensures that data generated and processed is in compliance with ICH/GCP regulations and requirements.

1.6. Total quality management in clinical trials would markedly improve quality and accuracy.

The concept is essential due to the involvement of all staff from initial design to the end, quality control leading to less errors and quality data.

1.7. Data quality is an important measure of performance for the data management process in clinical trials.

The data quality as a measure of performance is a critical concept for it is the data that regulatory authorities critically evaluate to base their decisions.

1.8. The coding of data facilitates data management.

This concept enables the recording, storage, searching and retrieval, manipulation, tabulation, counting, summarization and analysis of data feasible and manageable.

1.9. The database systems designed to capture data from clinical trials laboratories should have an audit trail record of all entries built in.

This concept is critical in the production of authentic and credible laboratory data acceptable to regulatory authorities and the scientific world.

1.10. The validation of a computerized clinical system is a multifaceted process depended on many factors.

The level of validation of a clinical system determines the outcome of regulatory inspection. The validation depends on the software/system, development process, suitably trained and qualified personnel.

2. Critical Analysis of the Concepts.

2.1. The new rules/guidelines that support ICH concepts are making a major call for compliance with ICH requirements.

There are new rules and guidelines emanating from the US FDA and the European Commission covering protection of trial subjects, ethics committee options, conduct of a trial, labelling to notification of adverse events/reactions and electronic data submissions. These are very important submissions that would be part of ICH/GCP regulations to which sponsors and companies must comply.

The use of computers which has made data handling much doable is a major component of these rules/guidelines coming from the biologics and drugs division of the FDA. Overall the rules are meant to improve the execution of clinical trials.

2.2. An accurate case report [CRF] is the main intended and logical goal of a clinical trial.

All the data of patients/participants in a clinical trial are documented in the CRF including any adverse events. Obtaining an accurate CRF is the ultimate goal of every sponsor/investigator. Electronic CRFs are faster and efficient, security high and they are environmentally friendly due to the elimination of piles of paper.

The development of the CRF is essential in answering questions asked in the research protocol and to collect any adverse events data for safety reports. It must also promote accurate data entry and organise it in a way that facilitates data analysis.

2.3. Remote data entry [RDE] significantly reduces the chances of errors.

RDE means capturing data at the point of its generation. Generally the system provides a graphical user interface component for data entry, a validation part to check use data and a reporting tool for analysis. Compared to manual entries this system greatly reduces the chances of errors.

The advantages of RDE are improved data quality, speed, flexibility of access to data and automatic avoidance of simple errors {Rondel 2000}. The disadvantages would include cost in purchasing new hardware, training, communication etc .Electronic data entry /capture has been a welcome relief to clinical data management and clinical trials.

2.4. The establishments of timelines results I the identification of tasks and key milestones in clinical data management planning and implementation.

This concept emphasizes the importance of having time targets which then capacitates the identification of those milestones and tasks to be delivered. The availability of the final protocol and case report form would determine the finalization date or time frame for the project plans. The time for receipt of the first data depends on when the first patient completes the study. Most clinical trials miss their completion targets ,an area that needs correction.

Deliberate and proactive planning together with close communication will ensure accomplishment of quality and on time deliverables by the global clinical data management teams {Zia Haque 2010}.

2.5. The data validation process ensures the completeness, integrity and consistency of clinical trials data.

The data validation process is a series of documented tests of the data aiming to ensure the quality and integrity of the data. Data validation normally checks the originality, completeness, accuracy and consistency aspect of the data.

Validation is required because the FDA and other regulators evaluate the worth of the drug or device using it. Clinical data affect treatment decisions which affect patient health. The validation process begins with the planning, implementation and testing, followed by data entry and validation and ends with the database lock.

2.6. Total quality management in clinical trial would markedly improve quality and accuracy.

Total quality management in clinical research entails quality assurance and quality measures being carried out by all staff and starts from beginning to end. This would also involve training of individuals, payment of staff and all the other supporting tasks. This concept has been popularized by ISO 900 which is a series of quality management and assurance standards and guidelines for all industries.

It provides a framework for a quality system which can facilitate the handling of error free clinical data. This is achieved via training of personnel and exhaustive documentation of all the operating procedures to be followed by all.

2.7. Data quality is an important measure of performance for the data management process in clinical trials.

Regulatory authorities of clinical trials critically evaluate data from trials before making their approval or disapproval decisions. Therefore the data has to be of high quality.

High quality data is obtained by minimizing the number of errors and missing data and gathering maximum data for analysis {Krishnankutty et al 2012}. Hence to achieve this, best practices are adapted to ensure complete, reliable and correctly processed data.

2.8. The coding of data facilitates data management.

Data coding enables the recording, storage, searching and retrieval, manipulation, tabulation, counting, summarization and analysis of data feasible and manageable. Coding has three main phases namely abstraction, assignment and review.

There are several standardized medical coding dictionaries, however five are used namely COSTART, ICD9CM, MedDRA, WHOART and WHO-DDE. MedDRA {Medical Dictionary for Regulatory Activities} and WHO-DDE {World Health Organization Drug Dictionary Enhanced} are the most widely used.

2.9. The database systems designed to capture from clinical laboratories should have an audit trail record of all entries built in.

This concept facilitates the production of authentic and credible laboratory data acceptable to regulatory authorities and the scientific world. The building into the system of the creation of a complete record of all the entries and amendments is essential. The complete record {audit trail} indicates transparency, authenticity and completeness of the data.

2.10. The validation of a computerized clinical system is a multifaceted process depended on many factors.

Validation of computerized systems is defined as confirmation by examination and provision of objective evidence that computerized system specifications conform to user needs and intended uses {Rathore and Sofer page 314}.

Validation will confirm that the computerized system will do what it was intended to do and has been tested to prove that it functions properly. Various factors are considered in systems validation. These include the hardware, software, operating procedures, training of personnel and procedural controls.

3.0 IDENTIFYING CURRENT RESEARCH ACTIVITIES RELATED TO THE

     CONCEPTS/THEORIES

3.1. The new rules/guidelines that support ICH concepts are making a major call for compliance with ICH requirements.

Marie and Pierre Miossec {2006} picked up key points and compared the rules/guidelines for clinical trials in the United States and the European Union. They focussed on trial registrations, reporting of adverse events and risk management plans. They highlighted that most of these are now part of ICH rules and regulations.

The European Medicines Agency changed a guideline on potential high risk medicinal products to all investigational medicinal products after the TeGenero incident {Milton and Horvath 2009}. It was concluded that these guidelines were here to stay as part of European Medicines Agency/ICH guidelines were here to stay and that researchers should ensure the safety of clinical trial participants.

3.2. An accurate case report form is the main intended and logical goal of a clinical trial.

A dynamic case report form [CRF] which is protocol specific and customized, allows investigators to specify at design time the relevant parameters and web application software to read customization data [Richesson and Nadkarwi 2011]. This would facilitate obtaining quality data to achieve the objectives of the clinical trial.

The CRF should be very clear, simple, user friendly and concise. The CRF is the first step in translating protocol specific activities into data being generated [Krishnankutty et al 2012].

3.3. Remote Data Entry [RDE] significantly reduces the chances of errors.

Remote data entry significantly reduces the type of errors found in paper based CRF studies. These include out of range values and missing data. These can be detected and corrected earlier in the clinical trial with RDE because edit checks are automatic and visible at the time of entry [www.clinovo.com/blog/challenges and benefits of edc-adoption/].

Data collection across the internet offers a secure and reliable method to collect and process study data. RDE allows for remote data input from sa many sites as needed in as many locations as required {www.uclaisap.org/DMC/html/capture.html}. While it can be argued that there is no perfect data collection system,RDE across the internet is a fast, reliable, secure and cost effective method to capture data.

3.4. The establishment of timelines results in the identification of tasks and key milestones in clinical data management planning and implementation.

The establishment of timelines facilitates reviewing and measuring against standards created by the protocol and early correcting of any discrepancies is key to successful implementation [Thomas 2002].The setting of timelines and deliberate proactive planning together with close communication will ensure accomplishment of quality and on time deliverables [Zia Haque 2010].

A scope of work which clearly delineates who is responsible for what, and a detailed timeline of all activities that need to be completed at which phase of a project lifeline [Kamp 2009], helps to identify key milestones and tasks is required.

3.5. The data validation process ensures the completeness, integrity and consistency of the clinical trial data.

Aljawarneh et al [ 2010] reviewed the existing data validation approaches and weighed their strengths, weaknesses and limitations for the process to achieve completeness, integrity e and consistency. The semantic data validation was developed. Its based on semantic web technologies to prevent security vulnerabilities thus producing credible data.

The technology we use nowadays is also prone to sophisticated errors as illustrated by Machado et al [2014]. They showed that it is possible to store arbitrary data in the investigated cloud providers, bypassing the data validation process thus causing security, accounting and charging problems. They recommended the avoidance of the use of encoders that can be bypassed.

3.6. Total quality management in clinical trials markedly improves quality and accuracy.

Total quality management is whole package that takes cognisance of accuracy, assurance of subject safety, achieving the set objectives e t c [Kleppinger and Ball 2010]. It is important to have continual process improvements for all stages of performance to guarantee quality and accuracy. Total quality management from start to finish will produce high quality data strong enough to support conclusions and interpretations.

High level Lean and Six Sigma principles can be applied to clinical and translational research [Schweikhart and Dember 2009]. Total quality management in clinical trials by blending and adopting the Lean and Six Sigma principle will reduce waste, increase efficiency, quality and accuracy. There are vital goals in clinical trials.

3.7. Data quality is an important measure of performance for the data management process in clinical trials.

The quality of clinical trials largely depends on the data integrity and subject protection [Bhatt 2011]. Data quality is an important measure of performance for data management. Compliance to quality requirements results in scientically valid and ethically sound clinical trials. Without quality data, there are no meaningful

conclusions which can be made [Monsen and Van Horn 2007]. They concluded that any meaningful clinical trial conclusions can only be arrived at with credible and authentic data.

3.8. The coding of data facilitates data management.

Data coding is performed to categorize the medical terms used in reporting during clinical trials to facilitate analysis and review. Babre [2010] highlights the common problems faced in coding like spelling errors, use of abbreviations, multiple medical concepts coded together and adverse events recorded without the site. Once data coding faces problems, it results in complex and difficult data management.

According to Krishnankutty and Bellary [2012] the right data coding and classification of adverse events is crucial because incorrect coding may lead to masking of safety criteria related to the drug.

3.9. The database systems designed to capture data from clinical trials laboratories should have an audit trail record of all entries built in.

This concept is critical for it seeks to identify and prevent suspicious and fraudulent activities by the user collecting data into the database [Roratto and Dias 2014].

Data integrity is the foundation of regulatory compliance and audit trail reports confirm that procedures are being followed and the integrity of the data confirmed [Brandt 2014].

3.10. The validation of a computerized clinical system is a multifaceted process depended on many factors.

D’Incerti and Valsecchi [2004] concluded that the evolution of regulatory requirements coupled with the enhancement of technology has resulted in new approaches to computerized clinical system validation, mainly based on process analysis risk assessment. The documentation of user requirements and risk analysis of the automated process help define the scope of evidence indicating that the system is validated for its intended use.

The systems validation process encompasses the full developmental life cycle from initiation to development, testing and production to decommissioning. Process validation involves a series of activities taking place over the life cycle of the product and process ]Zbrozek et al 2013].

4. Application of concepts to real world.

4.0. The new rules/guidelines that support ICH concepts are applicable in my line of work in that similar rules and guidelines are applicable to ensure compliance and production conduct.

The case report form is equivalent to the laboratory reports in my line of work. The reports answer all the questions/requests made on the request form. The laboratory  

report is a logical ending of requests to answer diagnostic questions and progress of treatment.

The concept of remote data entry is widely used in my line of work. Laboratory results are transferred directly from machines to servers where practitioners can access the patient’s results via well protected modes of accessing the data. The laboratory results can also be sent to practitioners via email, fax or as hard copies, but making sure that confidentiality is maintained.

The establishments of timelines is a concept that we take seriously in my line of work in that every test requested has a time limit within which it must  be completed and results delivered. These timelines are important if patients are to benefit immediately. Each laboratory has time frames in which individual laboratory assays have to be completed. The validation of laboratory data is fundamental and is carried out via the use of quality control and assurance. All abnormal data is subjected to repeat analysis. Total quality management is an essential component in my line of work. This is achieved via well trained qualified registered scientists, well calibrated, validated and routinely serviced equipment and the use of appropriate reagents and application of quality control and assurance programmes.

The quality of data coming out from the laboratories is essential if it is going to be of any use. Wrong and inaccurate results mean wrong diagnosis and treatment. The coding of data is a concept applicable in my line of laboratory work. Various tests we perform are abbreviated and used in the machines, request forms and reports. Reagents are bar coded for identification by machine for appropriateness and checking of expiry dates.

The database systems designed to capture all recorded data are extensively used in laboratories. The analyzers and computers record all the data that is entered including changes and who made the changes. The computer systems we use in laboratories are validated to ascertain that they what they are supposed to do. Confidentiality is vital therefore access to the systems is safeguarded with passwords and electronic signatures.

5. Usefulness of Concept to the Current World

5.0. In the real world the new rules/guidelines that support ICH concepts are making a major call for compliance with rules and regulations. This is very applicable in clinical trials. In every industry and sphere of life new rules/guidelines are put in place to improve performance, quality and also to protect human life and the environment. Accurate case report forms come in different forms in different disciplines to achieve intended goals. They are equivalent to job cards/work sheets used in various industries to record everything being done. In the education and air travel industry records of every detail are kept and referred to when necessary.

Remote data entry is now extensively used in clinical trials and other types of research. Technology has taken over and remote data entry makes instant data checks in the hospitality industry when making bookings and orders. It is now used virtually in every sphere of life. The establishment of timelines is a universally accepted phenomena where targets, time limits and deadlines are common practice. In the real world this concept is applied in clinical trials and other research, education agriculture, travelling, hospitality etc.

The coding of data is used extensively in all industries, medical, agriculture, clinical trials and other research to enable the collection, recording and analysis of data. In the real world data validation is applied in clinical trials, academic research, the financial sphere and many other industries. After national censuses the collected data needs to be validated.

Total quality management is applied in all industries and spheres of life, hence the ISO 9000. It is an important tool used by management to achieve total quality of products and services. The database system designed to capture data from clinical trial laboratories is a concept applied widely by all laboratories. The system is used in many other disciplines where data integrity is a must. The validation of computerized clinical systems is used in the real world wherever computers are used. IT is vital that the computer systems perform according to intended purpose in education, medicine, finance, marketing etc.

Paste

...(download the rest of the essay above)

About this essay:

This essay was submitted to us by a student in order to help you with your studies.

If you use part of this page in your own work, you need to provide a citation, as follows:

Essay Sauce, . Available from:< https://www.essaysauce.com/essays/marketing/2015-10-27-1445952010.php > [Accessed 17.10.19].