Computational modelling of drug disposition lalitajoshi9
computational modelling of drug disposition is the integral part of computer aided drug design. different kinds of tools being used in the prediction of drug disposition in human body. This topic in the CADD explains the details about the drug disposition, active transporters and tools.
Role of computer in clinical developmentDivyaShukla61
computers have always played a crucial role in our daily lives, Here i have presented its role in Clinical development.Hope you understand easily from my presentaion.
Computational modelling of drug disposition lalitajoshi9
computational modelling of drug disposition is the integral part of computer aided drug design. different kinds of tools being used in the prediction of drug disposition in human body. This topic in the CADD explains the details about the drug disposition, active transporters and tools.
Role of computer in clinical developmentDivyaShukla61
computers have always played a crucial role in our daily lives, Here i have presented its role in Clinical development.Hope you understand easily from my presentaion.
MPH07 Computers in clinical development.pptxBhuminJain1
My topic is computers in clinical development. There are various ways pf collecting data like pure paper based system, electronic based system and communication.
In this presentation I have mentioned whatever the possible relevant content required for the title.
Citation Is done at the end of slide.
Content is up to date & true to my belief.
Thanks & Best Regards.
Anurag Pandey
B.Pharm (FACULTY OF PHARMACY, INVERTIS UNIVERSITY)
M.Pharm (INSTITUTE OF PHARMACY, NIRMA UNIVERSITY)
Email :- anurag.dmk05@gmail.com
Myself Omkar Tipugade , M- Pharm ,Sem - II, Department of pharmaceutics , from Shree Santkrupa College Of Pharmacy , ghogaon . Today I upload presentation on Active Transport like P-gp , BCPR, Nucleoside transporters etc .
Statistical modeling in pharmaceutical research and developmentPV. Viji
Statistical modeling in pharmaceutical research and development , Statistical Modeling , Descriptive Versus Mechanistic Modeling , Statistical Parameters Estimation , Confidence Regions , Non Linearity at the Optimum , Sensitivity Analysis , Optimal Design , Population Modeling
• In silico (literally alluding the mass use of silicon for semiconductor computer chips) is an expression used to performed on computer or via computer simulation
• In silico tools capable of identifying critical factors (i.e. drug physicochemical properties, dosage form factors) influencing drug in vivo performance, and predicting drug absorption based on the selected data set (s) of input factors.
Protein and Peptide drug delivery system are the Novel drug Delivery System. Proteins and peptides are the most abundant components of biological cells. They exist functioning such as enzymes, hormones, structural element and immunoglobulin. Proteins and peptides are therefore almost exclusively administered by the parenteral route. Although parenteral administration serves the purpose, it has several shortcomings. It encounters, many barriers affecting its stability, such as poor cellular membrane permeability at the GIT site, enzymatic degradation (various proteases), and first-pass hepatic metabolism.
T R I A L M O N I T O R I N GQuality Remote Monitoring .docxssuserf9c51d
T R I A L M O N I T O R I N G
Quality Remote Monitoring:
The Tools of the Game
Penelope Manasco, MD
Outlining those technologies best able to raise the
data and process quality of risk-based monitoring.
A
critical aspect of risk-based monitoring
(RBM) is rapid access to a site’s clinical
data. In 2013, industry median values from
2009-2012 Phase II and III clinical trials (see
Figure 1 on facing page) showed that the
median time from electronic case report (eCRF)
entry to data manager query opened was 59 to 89
days. This is even more extraordinary when one
considers that the median time from subject visit
to query close (all queries including automatically
generated queries) ranged from 30 to 36 days.'
These findings emphasize that direct data en
try, either into the electronic data capture (EDC)
or eSource systems, provides significant value in
overseeing study conduct quality. Mitchel et al.2
reported on their experience implementing direct
data entry (DDE) and RBM in a clinical trial of 18
investigative sites in the U.S. and Canada study
ing 180 research subjects. In that trial, 92% of the
data was entered within one day of the subject
visit and 98% within eight days. Data review was
also faster with 50% of the data reviewed within 13
hours of data entry. Source data verification (SDV)
was completed at the site for approximately 20%
of the data within the EDC. There were changes on
0.8% of the pages, with the majority in three areas:
concomitant medications, medical history, and
clinical laboratory results.
The evidence above, coupled with the find
ing that SDV was not an adequate approach to
ensure trial quality,5 illustrates the importance of
technology and process changes that should be
implemented to enhance remote trial oversight
as envisioned by the FDA,2 European Medicines
Agency (EMA),5 and International Conference on
Harmonization (1CH) guidance6 documents on
RBM and quality management. The following tech
nology solutions can provide significant benefits
to implementing RBM and remote trial manage
ment.
Technology solutions
EDC and eSource
Direct data entry can be accomplished though
web-based EDC solutions and tablets, it is imper
ative that sites have adequate Internet access to
use tablets for direct data entry. Sites benefit from
eliminating transcription of documents. Moni
tors and data managers also benefit from having
immediate access to the data. Questions that
document good clinical practice (GCP) compli
ance can be incorporated into the EDC or eSource.
These fields (e.g„ detailing timing for vital signs,
informed consent processes) enable monitors to
conduct source data review remotely. Many data
managers may not be familiar with the additional
questions the monitor will want to have docu
mented, so cross-functional input into the EDC
is needed during design. Tablet setup and testing
ensures tablets work as needed by the site. The
initiation visit should i ...
MPH07 Computers in clinical development.pptxBhuminJain1
My topic is computers in clinical development. There are various ways pf collecting data like pure paper based system, electronic based system and communication.
In this presentation I have mentioned whatever the possible relevant content required for the title.
Citation Is done at the end of slide.
Content is up to date & true to my belief.
Thanks & Best Regards.
Anurag Pandey
B.Pharm (FACULTY OF PHARMACY, INVERTIS UNIVERSITY)
M.Pharm (INSTITUTE OF PHARMACY, NIRMA UNIVERSITY)
Email :- anurag.dmk05@gmail.com
Myself Omkar Tipugade , M- Pharm ,Sem - II, Department of pharmaceutics , from Shree Santkrupa College Of Pharmacy , ghogaon . Today I upload presentation on Active Transport like P-gp , BCPR, Nucleoside transporters etc .
Statistical modeling in pharmaceutical research and developmentPV. Viji
Statistical modeling in pharmaceutical research and development , Statistical Modeling , Descriptive Versus Mechanistic Modeling , Statistical Parameters Estimation , Confidence Regions , Non Linearity at the Optimum , Sensitivity Analysis , Optimal Design , Population Modeling
• In silico (literally alluding the mass use of silicon for semiconductor computer chips) is an expression used to performed on computer or via computer simulation
• In silico tools capable of identifying critical factors (i.e. drug physicochemical properties, dosage form factors) influencing drug in vivo performance, and predicting drug absorption based on the selected data set (s) of input factors.
Protein and Peptide drug delivery system are the Novel drug Delivery System. Proteins and peptides are the most abundant components of biological cells. They exist functioning such as enzymes, hormones, structural element and immunoglobulin. Proteins and peptides are therefore almost exclusively administered by the parenteral route. Although parenteral administration serves the purpose, it has several shortcomings. It encounters, many barriers affecting its stability, such as poor cellular membrane permeability at the GIT site, enzymatic degradation (various proteases), and first-pass hepatic metabolism.
T R I A L M O N I T O R I N GQuality Remote Monitoring .docxssuserf9c51d
T R I A L M O N I T O R I N G
Quality Remote Monitoring:
The Tools of the Game
Penelope Manasco, MD
Outlining those technologies best able to raise the
data and process quality of risk-based monitoring.
A
critical aspect of risk-based monitoring
(RBM) is rapid access to a site’s clinical
data. In 2013, industry median values from
2009-2012 Phase II and III clinical trials (see
Figure 1 on facing page) showed that the
median time from electronic case report (eCRF)
entry to data manager query opened was 59 to 89
days. This is even more extraordinary when one
considers that the median time from subject visit
to query close (all queries including automatically
generated queries) ranged from 30 to 36 days.'
These findings emphasize that direct data en
try, either into the electronic data capture (EDC)
or eSource systems, provides significant value in
overseeing study conduct quality. Mitchel et al.2
reported on their experience implementing direct
data entry (DDE) and RBM in a clinical trial of 18
investigative sites in the U.S. and Canada study
ing 180 research subjects. In that trial, 92% of the
data was entered within one day of the subject
visit and 98% within eight days. Data review was
also faster with 50% of the data reviewed within 13
hours of data entry. Source data verification (SDV)
was completed at the site for approximately 20%
of the data within the EDC. There were changes on
0.8% of the pages, with the majority in three areas:
concomitant medications, medical history, and
clinical laboratory results.
The evidence above, coupled with the find
ing that SDV was not an adequate approach to
ensure trial quality,5 illustrates the importance of
technology and process changes that should be
implemented to enhance remote trial oversight
as envisioned by the FDA,2 European Medicines
Agency (EMA),5 and International Conference on
Harmonization (1CH) guidance6 documents on
RBM and quality management. The following tech
nology solutions can provide significant benefits
to implementing RBM and remote trial manage
ment.
Technology solutions
EDC and eSource
Direct data entry can be accomplished though
web-based EDC solutions and tablets, it is imper
ative that sites have adequate Internet access to
use tablets for direct data entry. Sites benefit from
eliminating transcription of documents. Moni
tors and data managers also benefit from having
immediate access to the data. Questions that
document good clinical practice (GCP) compli
ance can be incorporated into the EDC or eSource.
These fields (e.g„ detailing timing for vital signs,
informed consent processes) enable monitors to
conduct source data review remotely. Many data
managers may not be familiar with the additional
questions the monitor will want to have docu
mented, so cross-functional input into the EDC
is needed during design. Tablet setup and testing
ensures tablets work as needed by the site. The
initiation visit should i ...
Who needs fast data? - Journal for Clinical Studies KCR
How “no news” during the life of a trial is bad news, and what data management (among other things) can do to help when ensuring access to fast data? Get to know this and more about smart e-solutions in the newest article of Kaia Koppel, Associate Director, Biometrics & Clinical Trial Data Execution Systems at KCR, in the recent issue of Journal for Clinical Studies (p.40-21).
Dale W. Usner, Ph.D., President of SDC, co-authored the article "The Clinical Data Management Process," which was published in the November/December 2014 issue of Retina Today.
The article reviews the clinical data management (CDM) process in its entirety - from protocol review and CRF design through database lock. Describing the roles of various CDM team members and tips for efficient data management practices, "The Clinical Data Management Process" provides a comprehensive yet concise summary of this essential function in clinical trial research, specifically with respect to retina trials.
CDM is defined as the process of collection, cleaning, and management of subject data in compliance with regulatory standards.
A database must be accurate, secure, reliable and ready for analysis.
CDMS is the tool for clinical data management.
RESPONSIBILITES OF CDM
STUDY SET UP (15%) - this includes all the activities that are done before at the starting of the study.
STUDY CONDUCT (60%)- this starts once a subject enrollment begins or with first patient‘s first visit.
STUDY CLOSEOUT (25%) -the data is final and ready for statistical analysis.
CASE REPORT FORM
Types of CRF
PAPER CRF
e-CRF
Data entry is a process of entering or transferring data from case report form ( paper or image ) to clinical data management system (electronic storage ).
optical mark reading (OMR)
Data entry may be entirely manual or partly computerized using optical character recognition (OCR).
The three basic types of data entry system:
(a) Local data entry system - data entry is done on site
(b) Central data entry system - data entry is done at data management centre from the received CRFs;
(c) Web based data entry system - data entry is done through web (secure link) using internet connection.
DATA CLEANING
MANAGING ADR DATA
ADR data are collected from clinical trials and marketed products.
All ADR are reported to clinical data management system or safety system.
During clinical trials-ADR information is also received through CRF or EDC.
These information are stored in clinical data management database.
DATABASE LOCK PROCESS
Data manager – data is accurate and complete
Clinical project manager – site activities are complete
Medical monitor - data is medically accurate
Biostatistician - data is ready for evaluation and analysis.
Data manager asks for the database to be locked .
Done through the company’s IT department.
Once locked, no data can be changed.
Signed process for locking the database is placed in Trial Master File (TMF)
Data base closure (database lock): The database closure for the study is done to ensure no manipulation of study data during final analysis.
DATABASE LOCK/FREEZE is a TWO step process:-
The first step is often referred as SOFTLOCK or DATABASE FREEZE- occurs after all data cleaning, validation, and QC activities have been finalized.
The second step is called HARDLOCK or DATABASE LOCK –At this stage the database is handed over to statistics for data analysis.
DATA TRANSFER
Traditional Data Transfer
CRFs developed by sponsor and supplied to the site along with completion/instruction manual .
Use a black or blue ball point pen for permanency – and PRESS HARD.
At the time of a monitoring visit, CRFs are reviewed for adherence to
guidelines and verified against source documents by the Monitor.
During the monitoring visit, site staff make required corrections to CRFs
Verified/corrected CRFs are submitted to the sponsor, leaving a legible
copy of the CRF at the site.
Visit:www.acriindia.com
ACRI is a leading Clinical data management training Institute in Bangalore India.
ACRI creates a value add for every degree. Our PGDCRCDM course is approved by the Mysore University. Graduates and Post Graduates and even PhDs have trained with us and got enviable positions in the Clinical Research Industry. ACRI supplements University training with Industry based training, coupled with hands-on internships and projects based on real case studies. The ACRI brand gives the individual the confidence and expertise to join the ever-growing workforce both in the country and abroad.
6.COMPUTERS AS DATA ANALYSIS.pptxB.Pharm sem 2 Computer Applications in PharmacyVedika Narvekar
Computers as data analysis in Preclinical development:
Chromatographic dada analysis(CDS), Laboratory Information management
System (LIMS) and Text Information Management System(TIMS)
The impact of electronic data capture on clinical data managementClin Plus
electronic data capture (EDC)-based clinical trials offer operational and cost-effective approaches for ongoing data entry via the Internet for clinical sites; medical monitoring; monitoring by clinical research associates including initial review. Pharmaceutical, biotechnology, and medical device industry, as well as academia and the government, have all begun to adopt EDC as a new data management tool.
Some Of The New Technologies That We Are Working With Are.pptxRaptimResearch1
Raptim Research Private Limited (formerly known as Raptim Research Limited), is a global independent and internationally accredited Contract Research Organization (CRO), established in 2005 with state-of-the-art clinical research facilities in Mumbai and Gandhinagar (India).
We apply innovative tools and processes to our clinical development and support end-to-end services under the Clinical Research domain for all Global Pharmaceutical companies. With our experience and enhanced capabilities, we are in a unique position to assist our Sponsors with unparalleled support and provide them a single, global research network.
A crucial stage in clinical research is clinical data management CDM , which produces high quality, reliable, and statistically sound data from clinical trials. This results in a significantly shorter period of time between drug development and marketing. Team members of CDM are laboriously involved in all stages of clinical trials right from commencement to completion. They should be able to sustain the quality standards set by CDM processes by having sufficient process expertise. colorful procedures in CDM including Case Report Form CRF designing, CRF reflection, database designing, data entry, data confirmation, distinction operation, medical coding, data birth, and database locking are assessed for quality at regular intervals during a trial. In the present script, theres an increased demand to ameliorate the CDM norms to meet the nonsupervisory conditions and stay ahead of the competition by means of brisk commercialization of products. With the perpetration of nonsupervisory biddable data operation tools, the CDM platoon can meet these demands. also, its getting obligatory for companies to submit the data electronically. CDM professionals should meet applicable prospects and set norms for data quality and also have the drive to acclimatize to the fleetly changing technology. This composition highlights the processes involved and provides the anthology an overview of the tools and norms espoused as well as the places and liabilities in CDM. Syed Shahnawaz Quadri | Syeda Saniya Ifteqar | Syed Shafa Raoof "Data Management in Clinical Research" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-2 , April 2023, URL: https://www.ijtsrd.com.com/papers/ijtsrd55050.pdf Paper URL: https://www.ijtsrd.com.com/pharmacy/other/55050/data-management-in-clinical-research/syed-shahnawaz-quadri
A Pharma/CRO Partnership in the Design and Execution of Paperless Clinical Tr...Target Health, Inc.
DIA 2019 presentation by Dr. Jules Mitchel with Michelle Eli (Lilly) and Tom Haag (ex-Novartis) based on their experience with Lilly collaborating on Target Health's paperless clinical trial system.
Clinical Data management is one of the vital part of clinical research.
Clinical research is research on drugs,devices ,medicines that has to be adminstered for various diseases and illness,to check the efficacy and safety in human voluteers or patients.
It helps in determining dose and dosages of a particular drug or treatment regimen.CR also helps in label expansion of investigational drug. Furthermore it helps in checking any adverse event in post marketed drug which increases the potability of drug among population of various geographical regions.There are various guidelines and regulatory bodies from several parts of world . Each country has its own regulatory body both at state and central level,eg.CDSCO for India,TGA for Australia,USFDA for USA,MCC for South Africa ,UNCST for Uganda,EMEA for European Union,MHRA for UK.Thus CDM plays important role in maintaining accuracy,consistencies,validity reliabilty of available data.It also in decreasing redundancy of duplicate and inconsistent data.It is required to resolve issues pertaining to inaccuracy , signal detection in pharmacovigilance. CDM is completed in three steps set up,conduct ,close out.Database used i n cdm are DBMS ,MS -Access,OC-RDC.Data managers,operators,programmers,developers are include in the process.CDMS Clinical data management system ,clinical system validation.
EDC In Clinical Trials| Electronic Data Capture In Clinical Trialseclinicaltools
Unlock the transformative power of Electronic Data Capture (EDC) in clinical trials. EDC revolutionizes data management, ensuring real-time access, data accuracy, and streamlined processes. By replacing paper-based systems, it enhances efficiency, reduces errors, and expedites decision-making. Its adaptability facilitates various study designs, from traditional to decentralized trials. With features like remote monitoring and ePRO integration, EDC promotes patient-centricity. Embrace the future of clinical research, where EDC not only meets but exceeds the demands for precision, speed, and compliance, ultimately paving the way for more successful and patient-friendly trials.
Data Management and Analysis in Clinical Trialsijtsrd
Data management and analysis play a critical role in the successful conduct of clinical trials. Proper collection, validation, and handling of data are essential for ensuring the reliability and integrity of study findings. Data management involves the design and implementation of data capture tools, such as electronic case report forms eCRFs, to efficiently collect and store clinical data. Additionally, data analysis is a crucial step that involves applying statistical methods to extract meaningful insights from the collected data. This paper provides an overview of the key components of data management and analysis in clinical trials, highlighting the importance of adherence to data standards, ensuring data quality, and maintaining data security. Effective data management and analysis not only lead to robust study outcomes but also contribute to the overall advancement of medical knowledge and patient care. S. Reddemma | Chetana Menda | Manoj Kumar "Data Management and Analysis in Clinical Trials" Published in International Journal of Trend in Scientific Research and Development (ijtsrd), ISSN: 2456-6470, Volume-7 | Issue-4, August 2023, URL: https://www.ijtsrd.com/papers/ijtsrd59667.pdf Paper Url:https://www.ijtsrd.com/pharmacy/pharmacology-/59667/data-management-and-analysis-in-clinical-trials/s-reddemma
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Clinical data collection and management
1. Mohammad Asim
+919953194659
Page 1 of 5
Clinical data collection
When a clinical trial is being designed, it is important to plan how data will be collected and
captured during the trial. Data in a clinical trial are generated and collected by the investigator,
study staff and/or directly by patients {called Patient-Reported Outcomes (PROs)}
This can occur in the traditional way – on paper (such as Case Report Forms (CRFs), patient
diaries, or questionnaires); or in electronic ways – for instance in electronic CRFs (eCRFs), or by
using hand-held instruments such as mobile phones or tablets to collect data directly from patients
(ePROs). Another method of collecting data is called ‘direct data capture’ (DDC). In DDC, data
are directly generated by electronic devices and entered into the database.
Paper Case Report Forms (CRFs)
Paper CRFs are designed for handwritten data. They are cheap to produce and allow the creation
of direct copies and faxing. New technology such as optical character recognition (OCR) allows
computers to ‘read’ the data written by site staff and enter them automatically into a database.
Advantages:
Site staff can carry the CRF to wherever they need it
Site staff don’t need to worry about access to computers and passwords.
Relatively easy to amend if changes are required during the study
Disadvantages:
A large volume of paper to store
Space and correction limitations on the form itself
Incorrect data entries are not automatically flagged to the user as they may be on electronic
records
As data is later entered into a database, creates another opportunity for mistakes to be made.
Electronic Case Report Forms (eCRFs)
Electronic CRFs (eCRFS) are becoming more and more popular. However, they are much more
complicated to produce and need to adhere to strict regulations in Europe and the United States.
The computer programs or software must be validated, and every correction that is made to the
data entered must be traceable. They must ensure that only authorized persons have access to the
program and to the data. Data backups must occur regularly and automatically.
Using eCRFs in a study requires all investigator sites to have sufficient and reliable access to
computers and the internet. It also requires intensive training of the site staff using the eCRF, which
must often also be supported by a help-desk.
Regulatory requirements are in place that eCRFs must conform to:
In Europe: ICH GCP E-6, Section 5.5.3
2. Mohammad Asim
+919953194659
Page 2 of 5
In the US: FDA – 21CFR Part 11 and Guidance for Industry – Computerized Systems used
in Clinical Trials.
The validation of electronic systems is mandatory. A system must have an audit trail, meaning that
any change should be electronically recorded and traceable. It must be protected against
unauthorized access. It must be backed up regularly, meaning that data are regularly copied on a
different disk, server, or computer that can be accessed for the lifetime of the product.
Advantages
Data entry errors are directly detected
Range and edit checks minimize data entry errors and protocol violations
Data are available to sponsor immediately after entry at site
Faster query resolution is possible
Disadvantages
Benefit only seen in the long term
Technical problems may occur
Data protection issues may arise
Patient Reported Outcomes (PROs) and Electronic Captured PROs (ePROs)
The term Patient Reported Outcome (PRO) is used for all data that are directly provided by
patients. This includes all types of questionnaires and diaries. This can be recorded on paper or by
using electronic systems. Technical tools that can be used to receive these data in an efficient,
participant-friendly manner are rapidly evolving. If an electronic hand-held system such as a tablet
or text messaging (SMS) is used, the term ePRO is used. Typically, these electronic data are either
in the form of a daily diary at the patient’s home, or Quality of Life (QoL) questionnaires
administered during site visits.
Clinical data management (CDM)
CDM is the process of collection, cleaning, and management of subject data in compliance with
regulatory standards. The primary objective of CDM processes is to provide high-quality data by
keeping the number of errors and missing data as low as possible and gather maximum data for
analysis. To meet this objective, best practices are adopted to ensure that data are complete,
reliable, and processed correctly. This has been facilitated by the use of software applications that
maintain an audit trail and provide easy identification and resolution of data discrepancies.
Sophisticated innovations have enabled CDM to handle large trials and ensure the data quality
even in complex trials.
Many software tools are available for data management, and these are called Clinical Data
Management Systems (CDMS). In multicentric trials, a CDMS has become essential to handle the
huge amount of data. Most of the CDMS used in pharmaceutical companies are commercial, but
3. Mohammad Asim
+919953194659
Page 3 of 5
a few open source tools are available as well. Commonly used CDM tools are ORACLE
CLINICAL, CLINTRIAL, MACRO, RAVE, and eClinical Suite. In terms of functionality, these
software tools are more or less similar and there is no significant advantage of one system over the
other. These software tools are expensive and need sophisticated Information Technology
infrastructure to function. Additionally, some multinational pharmaceutical giants use custom-
made CDMS tools to suit their operational needs and procedures. Among the open source tools,
the most prominent ones are OpenClinica, openCDMS, TrialDB, and PhOSCo. These CDM
software are available free of cost and are as good as their commercial counterparts in terms of
functionality.
These CDM tools ensure the audit trail and help in the management of discrepancies. According
to the roles and responsibilities, multiple user IDs can be created with access limitation to data
entry, medical coding, database designing, or quality check. This ensures that each user can access
only the respective functionalities allotted to that user ID and cannot make any other change in the
database. For responsibilities where changes are permitted to be made in the data, the software will
record the change made, the user ID that made the change and the time and date of change, for
audit purposes (audit trail).
The CDM process, like a clinical trial, begins with the end in mind. This means that the whole
process is designed keeping the deliverable in view. As a clinical trial is designed to answer the
research question, the CDM process is designed to deliver an error-free, valid, and statistically
sound database. To meet this objective, the CDM process starts early, even before the finalization
of the study protocol.
Review and finalization of study documents
During this review, the CDM personnel will identify the data items to be collected and the
frequency of collection with respect to the visit schedule. A Case Report Form (CRF) is designed
by the CDM team, as this is the first step in translating the protocol-specific activities into data
being generated. The data fields should be clearly defined and be consistent throughout. The type
of data to be entered should be evident from the CRF. For example, if weight has to be captured
in two decimal places, the data entry field should have two data boxes placed after the decimal.
Similarly, the units in which measurements have to be made should also be mentioned next to the
data field. The CRF should be concise, self-explanatory, and user-friendly. Along with the CRF,
the filling instructions should also be provided to study investigators for error-free data acquisition.
Database designing
Databases are the clinical software applications, which are built to facilitate the CDM tasks to
carry out multiple studies. Generally, these tools have built-in compliance with regulatory
requirements and are easy to use. “System validation” is conducted to ensure data security, during
which system specifications, user requirements, and regulatory compliance are evaluated before
implementation. Study details like objectives, intervals, visits, investigators, sites, and patients are
defined in the database and CRF layouts are designed for data entry. These entry screens are tested
with dummy data before moving them to the real data capture.
4. Mohammad Asim
+919953194659
Page 4 of 5
Data collection
It is explained above.
CRF tracking
The entries made in the CRF will be monitored by the Clinical Research Associate (CRA) for
completeness and filled up CRFs are retrieved and handed over to the CDM team. The CDM team
will track the retrieved CRFs and maintain their record. CRFs are tracked for missing pages and
illegible data manually to assure that the data are not lost. In case of missing or illegible data, a
clarification is obtained from the investigator and the issue is resolved.
Data entry
Data entry takes place according to the guidelines prepared along with the data management plan
(DMP). This is applicable only in the case of paper CRF retrieved from the sites. Usually, double
data entry is performed wherein the data is entered by two operators separately. The second pass
entry (entry made by the second person) helps in verification and reconciliation by identifying the
transcription errors and discrepancies caused by illegible data. Moreover, double data entry helps
in getting a cleaner database compared to a single data entry. Earlier studies have shown that
double data entry ensures better consistency with paper CRF as denoted by a lesser error rate.
Data validation
Data validation is the process of testing the validity of data in accordance with the protocol
specifications. Edit check programs are written to identify the discrepancies in the entered data,
which are embedded in the database, to ensure data validity. These programs are written according
to the logic condition mentioned in the data validation plan (DVP). These edit check programs are
initially tested with dummy data containing discrepancies. Discrepancy is defined as a data point
that fails to pass a validation check. Discrepancy may be due to inconsistent data, missing data,
range checks, and deviations from the protocol. In e-CRF based studies, data validation process
will be run frequently for identifying discrepancies. These discrepancies will be resolved by
investigators after logging into the system.
Discrepancy management
This is also called query resolution. Discrepancy management includes reviewing discrepancies,
investigating the reason, and resolving them with documentary proof or declaring them as
irresolvable. Discrepancy management helps in cleaning the data and gathers enough evidence for
the deviations observed in data. Almost all CDMS have a discrepancy database where all
discrepancies will be recorded and stored with audit trail.
Medical coding
Medical coding helps in identifying and properly classifying the medical terminologies associated
with the clinical trial. For classification of events, medical dictionaries available online are used.
Technically, this activity needs the knowledge of medical terminology, understanding of disease
entities, drugs used, and a basic knowledge of the pathological processes involved. Functionally,
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it also requires knowledge about the structure of electronic medical dictionaries and the hierarchy
of classifications available in them. Adverse events occurring during the study, prior to and
concomitantly administered medications and pre-or co-existing illnesses are coded using the
available medical dictionaries. Commonly, Medical Dictionary for Regulatory Activities
(MedDRA) is used for the coding of adverse events as well as other illnesses and World Health
Organization–Drug Dictionary Enhanced (WHO-DDE) is used for coding the medications. These
dictionaries contain the respective classifications of adverse events and drugs in proper classes.
Database locking
After a proper quality check and assurance, the final data validation is run. If there are no
discrepancies, the SAS datasets are finalized in consultation with the statistician. All data
management activities should have been completed prior to database lock. To ensure this, a pre-
lock checklist is used and completion of all activities is confirmed. This is done as the database
cannot be changed in any manner after locking. Once the approval for locking is obtained from all
stakeholders, the database is locked and clean data is extracted for statistical analysis. Generally,
no modification in the database is possible. But in case of a critical issue or for other important
operational reasons, privileged users can modify the data even after the database is locked.