Have full fleged clinical trial data management systems which bring them a good amount of business and revenue.
CDM is a fundamental process which controls data accuracy of each trial besides helping the timelessness to be achieved.
It helps in linking clinical research co-ordinator = who monitor all the sites & collects the data.
it Links with biostatisticians = who analyze, interpret and report data in clinically meaningful way.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
Electronic Data Capture & Remote Data CaptureCRB Tech
CRB Tech is one of the best leading Software Development Company in Pune. We are offering Software Development Services as well as IT Training including Java, Dot Net, SEO and Clinical Research training in pune.
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.
Clinical data management (CDM) is a covered part in the clinical trial and most commonly used tools for the purpose of effectivity of clinical research
Clinical Data Management Plan_Katalyst HLSKatalyst HLS
Introduction to Data Management Plan in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Clinical Data Management (CDM) is a critical component of clinical research that involves the collection, cleaning, validation, and management of clinical trial data to ensure its accuracy, integrity, and compliance with regulatory requirements. The workflow of CDM typically consists of several key stages, each with specific activities and processes. Here is an overview of the typical workflow of CDM:
Study Startup:
Protocol Review: CDM teams begin by reviewing the clinical trial protocol to understand the study's objectives, endpoints, data collection requirements, and timelines.
Database Design: Based on the protocol, the team designs a data capture system or electronic data capture (EDC) system. This includes creating data entry forms, defining data validation checks, and setting up data dictionaries.
Data Collection:
Case Report Form (CRF) Design: CDM professionals design electronic or paper CRFs to collect data during the trial. CRFs capture specific data points required by the protocol.
Data Entry: Data is entered into the CRFs, either electronically by site personnel or through paper CRFs.
Data Validation: CDM teams implement validation checks to ensure data quality and consistency. Data validation checks may include range checks, consistency checks, and logic checks.
Query Management: Queries are generated when data discrepancies or inconsistencies are identified. CDM teams send queries to investigational sites for resolution.
Data Cleaning and Quality Control:
Data Cleaning: Data are cleaned to resolve discrepancies, discrepancies, and inconsistencies. This involves querying data discrepancies with clinical trial sites.
Data Review: CDM teams review data to ensure completeness and accuracy, and any outstanding queries are resolved.
Quality Control: Quality control processes are applied to verify the integrity and accuracy of data.
Database Lock:
Once the data are cleaned, reviewed, and validated, the database is locked, indicating that no further changes can be made to the data. Database lock is a critical step before data analysis begins.
Data Export and Analysis:
Data is exported from the database and provided to biostatisticians and researchers for statistical analysis. This analysis is conducted to determine the study's outcomes, efficacy, and safety profile.
Data listings, summaries, and tables are generated for regulatory submissions, reports, and publications.
Final Study Reporting:
After data analysis, CDM teams contribute to the preparation of final study reports, which provide a comprehensive overview of the trial's results, data quality, and regulatory compliance.
Archiving and Documentation:
Clinical trial data, documentation, and databases are archived to ensure their long-term availability for regulatory audits and future reference.
Regulatory Submission: CDM teams provide support for regulatory submissions.
An brief introduction to the clinical data management process is described in this slides. These slides provides you the information regarding the data evaluation in the clinical trials , edit checks and data review finally data locking,then the data is submitted to the concerned regulatory body.
Database Designing in Clinical Data ManagementClinosolIndia
When designing a Clinical Data Management (CDM) database, several key considerations should be taken into account to ensure efficient data capture, storage, and retrieval. Here are some important aspects to consider in CDM database design:
Define Study Requirements:
Understand the specific requirements of the study and the data to be collected. This includes variables, data types, formats, and any specific rules or calculations required for data validation and derivation. Consult with the study team and stakeholders to determine the necessary data elements.
Data Model Design:
Develop a data model that represents the structure and relationships of the data. Use standard data models, such as CDISC (Clinical Data Interchange Standards Consortium) standards, as a foundation. Define entities (e.g., patients, visits, assessments) and attributes (e.g., demographics, lab results) and establish relationships between them.
Data Dictionary:
Create a comprehensive data dictionary that provides a detailed description of each data element, including its name, definition, data type, length, format, allowable values, and any validation or derivation rules. The data dictionary serves as a reference for data entry and validation checks.
Database Schema:
Design the database schema based on the data model and data dictionary. Identify the tables, fields, and relationships needed to store the data. Determine primary and foreign keys to establish relationships between tables. Normalize the schema to reduce redundancy and improve data integrity.
Data Capture Forms:
Design user-friendly data capture forms to facilitate efficient and accurate data entry. Align the form layout with the data model and data dictionary. Include necessary data validation checks and provide clear instructions or prompts for data entry.
Data Validation and Quality Checks:
Incorporate data validation checks to ensure data accuracy and completeness. Implement range checks, format checks, consistency checks, and logic checks to identify and prevent data entry errors. Include data quality control processes to identify and resolve data discrepancies or anomalies.
Security and Access Controls:
Implement appropriate security measures to protect the confidentiality, integrity, and availability of the data. Define user roles and access levels to control data access and modification. Employ encryption, authentication, and audit trails to ensure data security and compliance with regulatory requirements.
Data Extraction and Reporting:
Consider the need for data extraction and reporting capabilities. Design mechanisms to extract data from the database for analysis or reporting purposes. Implement data export functionalities in commonly used formats, such as CSV or Excel, or integrate with reporting tools or systems.
Database design in the context of Clinical Data Management (CDM) is a crucial aspect of organizing and managing clinical trial data effectively and efficiently. A well-designed database ensures that data collected during a clinical trial is accurate, consistent, and accessible, facilitating data analysis, reporting, and regulatory submissions. Clinical Data Management involves various steps, including data collection, validation, cleaning, and reporting
clinical data management in clinical research, helpful for pharmacy, nursing, medical, health care providers, clinical research organization, PharmD, CROs, Clinical trial industry, human biomedical research.
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.
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.
Clinical data management (CDM) is a covered part in the clinical trial and most commonly used tools for the purpose of effectivity of clinical research
Clinical Data Management Plan_Katalyst HLSKatalyst HLS
Introduction to Data Management Plan in Clinical Data Management in Clinical Trials of Pharmaceuticals, Bio-Pharmaceuticals, Medical Devices, Cosmeceuticals and Foods.
Clinical Data Management (CDM) is a critical component of clinical research that involves the collection, cleaning, validation, and management of clinical trial data to ensure its accuracy, integrity, and compliance with regulatory requirements. The workflow of CDM typically consists of several key stages, each with specific activities and processes. Here is an overview of the typical workflow of CDM:
Study Startup:
Protocol Review: CDM teams begin by reviewing the clinical trial protocol to understand the study's objectives, endpoints, data collection requirements, and timelines.
Database Design: Based on the protocol, the team designs a data capture system or electronic data capture (EDC) system. This includes creating data entry forms, defining data validation checks, and setting up data dictionaries.
Data Collection:
Case Report Form (CRF) Design: CDM professionals design electronic or paper CRFs to collect data during the trial. CRFs capture specific data points required by the protocol.
Data Entry: Data is entered into the CRFs, either electronically by site personnel or through paper CRFs.
Data Validation: CDM teams implement validation checks to ensure data quality and consistency. Data validation checks may include range checks, consistency checks, and logic checks.
Query Management: Queries are generated when data discrepancies or inconsistencies are identified. CDM teams send queries to investigational sites for resolution.
Data Cleaning and Quality Control:
Data Cleaning: Data are cleaned to resolve discrepancies, discrepancies, and inconsistencies. This involves querying data discrepancies with clinical trial sites.
Data Review: CDM teams review data to ensure completeness and accuracy, and any outstanding queries are resolved.
Quality Control: Quality control processes are applied to verify the integrity and accuracy of data.
Database Lock:
Once the data are cleaned, reviewed, and validated, the database is locked, indicating that no further changes can be made to the data. Database lock is a critical step before data analysis begins.
Data Export and Analysis:
Data is exported from the database and provided to biostatisticians and researchers for statistical analysis. This analysis is conducted to determine the study's outcomes, efficacy, and safety profile.
Data listings, summaries, and tables are generated for regulatory submissions, reports, and publications.
Final Study Reporting:
After data analysis, CDM teams contribute to the preparation of final study reports, which provide a comprehensive overview of the trial's results, data quality, and regulatory compliance.
Archiving and Documentation:
Clinical trial data, documentation, and databases are archived to ensure their long-term availability for regulatory audits and future reference.
Regulatory Submission: CDM teams provide support for regulatory submissions.
An brief introduction to the clinical data management process is described in this slides. These slides provides you the information regarding the data evaluation in the clinical trials , edit checks and data review finally data locking,then the data is submitted to the concerned regulatory body.
Database Designing in Clinical Data ManagementClinosolIndia
When designing a Clinical Data Management (CDM) database, several key considerations should be taken into account to ensure efficient data capture, storage, and retrieval. Here are some important aspects to consider in CDM database design:
Define Study Requirements:
Understand the specific requirements of the study and the data to be collected. This includes variables, data types, formats, and any specific rules or calculations required for data validation and derivation. Consult with the study team and stakeholders to determine the necessary data elements.
Data Model Design:
Develop a data model that represents the structure and relationships of the data. Use standard data models, such as CDISC (Clinical Data Interchange Standards Consortium) standards, as a foundation. Define entities (e.g., patients, visits, assessments) and attributes (e.g., demographics, lab results) and establish relationships between them.
Data Dictionary:
Create a comprehensive data dictionary that provides a detailed description of each data element, including its name, definition, data type, length, format, allowable values, and any validation or derivation rules. The data dictionary serves as a reference for data entry and validation checks.
Database Schema:
Design the database schema based on the data model and data dictionary. Identify the tables, fields, and relationships needed to store the data. Determine primary and foreign keys to establish relationships between tables. Normalize the schema to reduce redundancy and improve data integrity.
Data Capture Forms:
Design user-friendly data capture forms to facilitate efficient and accurate data entry. Align the form layout with the data model and data dictionary. Include necessary data validation checks and provide clear instructions or prompts for data entry.
Data Validation and Quality Checks:
Incorporate data validation checks to ensure data accuracy and completeness. Implement range checks, format checks, consistency checks, and logic checks to identify and prevent data entry errors. Include data quality control processes to identify and resolve data discrepancies or anomalies.
Security and Access Controls:
Implement appropriate security measures to protect the confidentiality, integrity, and availability of the data. Define user roles and access levels to control data access and modification. Employ encryption, authentication, and audit trails to ensure data security and compliance with regulatory requirements.
Data Extraction and Reporting:
Consider the need for data extraction and reporting capabilities. Design mechanisms to extract data from the database for analysis or reporting purposes. Implement data export functionalities in commonly used formats, such as CSV or Excel, or integrate with reporting tools or systems.
Database design in the context of Clinical Data Management (CDM) is a crucial aspect of organizing and managing clinical trial data effectively and efficiently. A well-designed database ensures that data collected during a clinical trial is accurate, consistent, and accessible, facilitating data analysis, reporting, and regulatory submissions. Clinical Data Management involves various steps, including data collection, validation, cleaning, and reporting
clinical data management in clinical research, helpful for pharmacy, nursing, medical, health care providers, clinical research organization, PharmD, CROs, Clinical trial industry, human biomedical research.
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.
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.
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
Study start up activities in clinical data managementsoumyapottola
Study start-up (SSU) is so much more than a one-time document management exercise. It’s a global, strategic operation that can get new drugs approved faster – and it’s ripe for innovation – from Site Selection to Site Activation and Site Training.
Many SSU tech solutions deployed by sponsors don’t deliver the results promised because they add burden without benefits to clinical research sites. The result? Site staff simply avoid using them.
When that happens, document exchange and tracking falls back to paper, email and Excel formats – with CRAs holding the processes together. The tools that were supposed to solve a problem become part of the problem – and consume preThe implementation and conduct of a study can be a complex process that involves a
team from various disciplines and multiple steps that are dependent on one another. This
document offers guidance for navigating the study start-up processcious clinical trial budget.
A successful clinical study start-up is a crucial first step and an important factor for the overall success of the trial. For this reason, SCRO has experienced study start-up teams, offering customized services depending on your needs, whether it be fuWhile the definition varies across companies, study startup typically includes the process of identifying and qualifying sites, collecting essential documents at the study and site level, and submitting these documents for ethics approval. Successful study startup requires coordination between sites, sponsors, and contract research organizations (CROs) to achieve critical milestones in a compliant manner.ll-service or single activities.
How to achieve better time management in EDC start up
Clinical data management requires strict time management processes, especially in study start up within an electronic data capture (EDC) system. Three steps that clinical data management teams can take to outline the planning and executing of each task that needs to be considered are as follows:
Make a List: Create a daily or weekly task list and schedule when each task will be completed. This strategy will assist you in maintaining focus and staying organized.
Set realist goals: Be realistic about what you can finish in the amount of time you have. When setting unrealistic goals, failure is almost certain to follow.
Explore time-saving techniques: Examples of techniques that could help save time include grouping similar tasks together or using a timer to stay focused.
To help get started, here is a list of EDC considerations for Study Start-Up deadlines:
Protocol finalization and study enrollment
Split go-live considerations
eCRF Specification meetings (this will ensure proper collaboration and minimize any back-and-forth communication)
EDC add-on modules (which will be required and need validation?)
ePRO/eCOA used with licensed questionnaires.
IRB requirements for add-on modules (eConsent/ePRO)
Revelatory Trends in Clinical Research and Data ManagementSagar Ghotekar
Revelatory Trends in Clinical Research and Data Management
Clinical data management is a heart and important part of a clinical trials, the outcome to generate quality data and accounting of records to protect clinical trial participants data leads to highest quality and integrity of clinical trials.
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.
Everything related to CDM. Importance of CDM, Flow Activities in Clinical Trials, Data Management Plan, Database Designing, Data Management tools, Essential Characters of the database, Standard Global Dictionaries, Data Review and Validation, Query Generation, Database Lock, Technology in CDM, and Professionals of CDM.
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
Herbal drugs / herbal medicines include
herbs, herbal materials, herbal preparations and
finished herbal products, that contain as active ingredients, part of plants, or other plant materials, or combinations.
Herbal medicines comprise of therapies employing plant based products.
It is an integral part of Ayurveda and some indigenous medical systems.
Herbal drugs are becoming more popular in the modern world for their application to cure variety of diseases with less toxic effects and better therapeutic effects
OSI Reference Model - internationally standardised network architecture.
OSI = Open Systems Interconnection: deals with open systems, i.e.systems open for communications with other systems.
Specified in ISO 7498.
Model has 7 layers.
Supercomputers...are used to process very large amounts of information including processing information to predict hurricanes, satellite images and navigation, and process military war scenarios
Mainframes...are used by government and businesses to process very large amounts of information.
Mini-Computers...are similar to mainframes...they are used by business and government to process large amounts of information.
Personal Computers (PC
The first computers used vacuum tubes for circuitry and magnetic drums for memory.
They were often enormous and taking up entire room.
First generation computers relied on machine language.
They were very expensive to operate and in addition to using a great deal of electricity, generated a lot of heat, which was often the cause of malfunctions.
The UNIVAC and ENIAC computers are examples of first-generation computing devices.
Chromatography is an analytical method in which compounds are physically separated and measured.
The main purpose of chromatography is to separate and quantify the target sample.
The Chromatography technique used to separate a mixture of compounds in pharmaceutical sciences , analytical analytical Chemistry with the purpose of identifying, quantifying and purifying the individual components of the mixture.
The Hedgehog pathway was discovered in fruit fly (Drosophila) and is conserved in vertebrates (including humans)
The Hedgehog pathway is involved in cell growth and differentiation to control organ formation during embryonic development.
Hedgehog signalling regulates embryonic development, ensuring that tissues reach their correct size and location, maintaining tissue polarity and cellular content.
In the skin, the Hedgehog pathway is critical for regulating hair follicle and sebaceous gland development.
Germline mutations in components of the Hedgehog signalling pathway results in a number of developmental abnormalities.
Hedgehog signalling normally remains inactive in most adult tissues
Oxygen is highly reactive atom that is capable of becoming part
of potentially damaging molecule commonly called “free radical.”
Free radicals are capable of attacking cells of the body, causing
them to lose their structure and function.
Free radicals have been implicated in the pathogenesis of at
least 50 diseases.
Free radial formation is controlled naturally by various compounds
known as antioxidants.
It is when the ability of antioxidant is limited that this damage can
become cumulative and debilitating.
Following criteria should be considered while selecting an antioxidant.
It should be able to produce desire redox reaction.
It should be physiologically and chemically compatible.
It should be physiologically inert.
It should be non-toxic both in the reduced and oxidized forms.
It should be effective in low concentration.
It should provide prolonged stability to the formulation.
These are the substances which are added in the formulation along the therapeutic agent so as to impart specific qualities in the formulation.
These are have very little or no therapeutic value but are necessary in the manufacture of various dosage forms.
Purposes served by Additives:
Provide bulk to the formulation.
Facilitate drug absorption or solubility and other pharmacokinetic considerations.
Aid in handling of “API” during manufacturing .
Provide stability and prevent from denaturation etc
Exists without actions of humankind in the form of matter/energy which is available in the earth and get used by living thing.
Or exist as a separate entity such as fresh water, air and as well as a living organism such as a fish.
Or it may exist in an alternate form that must be processed to obtain the resource such as metal ores, petroleum, and most forms of energy.
Extraction is a process of separation or isolation of pharmaceutical active ingredients
from plant or animal drugs with the help of solvent.
On the basis of the physical nature of crude drug to be extracted i.e. liquid or solid ,the extraction process may be:
Liquid –Liquid Extraction Or
Solid –Liquid Extraction.
The solvent used for extraction is called as ‘Menstruum’ and the residue left after extracting desired constituents is called ‘Marc’.
Required Ideal Properties of Menstruum :
Should be inert and non –toxic
Should extract only the desirable constituent of the crude drug .
Should be cheap and easily available
Parkinson’s disease (PD) is the second most chronic, slowly progressive age associated
neurodegenerative disorder characterized by selective loss of dopaminergic neurons in the substantia nigra (SN) pars compacta, leads to deficiency or depletion dopamine (DA) in the striatum.
Idiopathic - (unknown cause)
Genetic - (clustering of early-onset pd in some families)
Drug induced (Anti-depressant, calcium channel blockers)
Toxins – (Environmental and Neurotoxins)
Head Trauma – (During accidental conditions)
Cerebral Anoxia
Histamine is an endogenous substance that is amine synthesized, stored and released by the various cells of the body: (a) Mast cells, which are abundant in the skin, GI, and the respiratory tract,
(b) Basophils in the blood, and (c) Some neurons in the CNS and peripheral NS.
It is an “Autocoid” that is secreted locally and regulate the activity of various near lying cells and neurons.
Huntington's disease is slowly progressive, rapidly growing hereditary brain disease that causes abnormal motor coordination, thinking, behavior and ultimately leads to dementia.
Its necessary to diagnosis earlier i.e. onset of movement disorder, particularly
with chorea and impaired voluntary movement.
Autosomal dominant inheritance with 2000 people are diagnosed each year.
No drug therapy is available
The worldwide prevalence of Huntington’s Disease is 5-10 cases per 10000 which affects men and women equally
SPECTROSCOPY is defined as the study of the interactions between radiations and matter as function of wavelength λ .
Interactions with particle radiation or a response of a material to an altering field
or varying frequency.
SPECTRUM : A plot of the response as a function of wavelength or more commonly frequency is referred to as spectrum.
SPECTROMETRY : It is measurement of these responses and an instrument which performs such measurements is a spectrophotometer or spectrograph, although
these terms are more limited in use to original field of optics from which the
concept sprang.
HPTLC is the improved method of TLC which utilizes the conventional technique of TLC in more optimized way.
It is also known as planar chromatography or Flat-bed chromatography.
Chromatography is a physical process of separation in which the components to be separated are distributed between 2 immiscible phases-a stationary phase which has a large surface area and mobile phase which is in constant motion through the stationary phase.
These are the organic products of natural or synthetic origin which are basic in
nature & contain one or more than one nitrogen atoms, normally of heterocyclic nature &
possess specific physiological actions on human or animal body, when used in small quantites.
The term is derived from the word ‘alkali-like’ & hence they resemble some of characters
of naturally occuring amines.
The term is derived from the word ‘alkali-like’ & hence they resemble some of
characters of naturally occuring amines.
A Ward round is a visit made by a medical practitioner, alone or with a team of health care professionals and medical students to hospital in-patients at their bedside to review and follow-up the progress in their health.
Usually at least one ward round is conducted
everyday to review the progress of each
patient outcome.
Pharmacist’s participating in medical ward
rounds promotes health care
Participation of the Pharmacists in ward
rounds in various practice settings helps to
provide rational drug use.
PHARMACOVIGILANCE
The World Health Organization (WHO) defines Pharmacovigilance as “the science and activities relating to the detection, assessment, understanding and prevention of adverse effects or any other drug-related problem.”
ADVERSE DRUG REACTION
According to WHO “ADR is a response to a drug which is noxious and unintended, and which occurs at doses normally used in man for the prophylaxis, diagnosis, or therapy of disease, or for the modifications of physiological function.”
Pyrogens include any substance capable of eliciting a febrile (or fever) response upon injection or infection
Endotoxin is a subset of pyrogens that are strictly of gram- negative bacterial origin; they occur (virtually) nowhere else in nature.
Lipopolysaccharide (LPS)is a part of endotoxin, or, endotoxin is the natural complex of LPS occurring in the outer layer of the bilayered gram-negative bacterial cell
The efficacy of antimicrobial preservation of a pharmaceutical preparation on its own or, if necessary, with the addition of a suitable preservative has to be ascertained during the development of the product.
The primary purpose of adding antimicrobial preservatives to dosage forms is to prevent adverse effects arising from contamination by micro-organisms that may be introduced inadvertently during or subsequent
to the manufacturing process.
However, antimicrobial agents should not be used solely to reduce the viable microbial count as a substitute for good manufacturing procedures.
There may be situations where a preservative system may have to be used to minimise proliferation of micro-organisms in preparations that are not required to be sterile.
Pulmonary Thromboembolism - etilogy, types, medical- Surgical and nursing man...VarunMahajani
Disruption of blood supply to lung alveoli due to blockage of one or more pulmonary blood vessels is called as Pulmonary thromboembolism. In this presentation we will discuss its causes, types and its management in depth.
Tom Selleck Health: A Comprehensive Look at the Iconic Actor’s Wellness Journeygreendigital
Tom Selleck, an enduring figure in Hollywood. has captivated audiences for decades with his rugged charm, iconic moustache. and memorable roles in television and film. From his breakout role as Thomas Magnum in Magnum P.I. to his current portrayal of Frank Reagan in Blue Bloods. Selleck's career has spanned over 50 years. But beyond his professional achievements. fans have often been curious about Tom Selleck Health. especially as he has aged in the public eye.
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Introduction
Many have been interested in Tom Selleck health. not only because of his enduring presence on screen but also because of the challenges. and lifestyle choices he has faced and made over the years. This article delves into the various aspects of Tom Selleck health. exploring his fitness regimen, diet, mental health. and the challenges he has encountered as he ages. We'll look at how he maintains his well-being. the health issues he has faced, and his approach to ageing .
Early Life and Career
Childhood and Athletic Beginnings
Tom Selleck was born on January 29, 1945, in Detroit, Michigan, and grew up in Sherman Oaks, California. From an early age, he was involved in sports, particularly basketball. which played a significant role in his physical development. His athletic pursuits continued into college. where he attended the University of Southern California (USC) on a basketball scholarship. This early involvement in sports laid a strong foundation for his physical health and disciplined lifestyle.
Transition to Acting
Selleck's transition from an athlete to an actor came with its physical demands. His first significant role in "Magnum P.I." required him to perform various stunts and maintain a fit appearance. This role, which he played from 1980 to 1988. necessitated a rigorous fitness routine to meet the show's demands. setting the stage for his long-term commitment to health and wellness.
Fitness Regimen
Workout Routine
Tom Selleck health and fitness regimen has evolved. adapting to his changing roles and age. During his "Magnum, P.I." days. Selleck's workouts were intense and focused on building and maintaining muscle mass. His routine included weightlifting, cardiovascular exercises. and specific training for the stunts he performed on the show.
Selleck adjusted his fitness routine as he aged to suit his body's needs. Today, his workouts focus on maintaining flexibility, strength, and cardiovascular health. He incorporates low-impact exercises such as swimming, walking, and light weightlifting. This balanced approach helps him stay fit without putting undue strain on his joints and muscles.
Importance of Flexibility and Mobility
In recent years, Selleck has emphasized the importance of flexibility and mobility in his fitness regimen. Understanding the natural decline in muscle mass and joint flexibility with age. he includes stretching and yoga in his routine. These practices help prevent injuries, improve posture, and maintain mobilit
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Flu Vaccine Alert in Bangalore Karnatakaaddon Scans
As flu season approaches, health officials in Bangalore, Karnataka, are urging residents to get their flu vaccinations. The seasonal flu, while common, can lead to severe health complications, particularly for vulnerable populations such as young children, the elderly, and those with underlying health conditions.
Dr. Vidisha Kumari, a leading epidemiologist in Bangalore, emphasizes the importance of getting vaccinated. "The flu vaccine is our best defense against the influenza virus. It not only protects individuals but also helps prevent the spread of the virus in our communities," he says.
This year, the flu season is expected to coincide with a potential increase in other respiratory illnesses. The Karnataka Health Department has launched an awareness campaign highlighting the significance of flu vaccinations. They have set up multiple vaccination centers across Bangalore, making it convenient for residents to receive their shots.
To encourage widespread vaccination, the government is also collaborating with local schools, workplaces, and community centers to facilitate vaccination drives. Special attention is being given to ensuring that the vaccine is accessible to all, including marginalized communities who may have limited access to healthcare.
Residents are reminded that the flu vaccine is safe and effective. Common side effects are mild and may include soreness at the injection site, mild fever, or muscle aches. These side effects are generally short-lived and far less severe than the flu itself.
Healthcare providers are also stressing the importance of continuing COVID-19 precautions. Wearing masks, practicing good hand hygiene, and maintaining social distancing are still crucial, especially in crowded places.
Protect yourself and your loved ones by getting vaccinated. Together, we can help keep Bangalore healthy and safe this flu season. For more information on vaccination centers and schedules, residents can visit the Karnataka Health Department’s official website or follow their social media pages.
Stay informed, stay safe, and get your flu shot today!
Title: Sense of Smell
Presenter: Dr. Faiza, Assistant Professor of Physiology
Qualifications:
MBBS (Best Graduate, AIMC Lahore)
FCPS Physiology
ICMT, CHPE, DHPE (STMU)
MPH (GC University, Faisalabad)
MBA (Virtual University of Pakistan)
Learning Objectives:
Describe the primary categories of smells and the concept of odor blindness.
Explain the structure and location of the olfactory membrane and mucosa, including the types and roles of cells involved in olfaction.
Describe the pathway and mechanisms of olfactory signal transmission from the olfactory receptors to the brain.
Illustrate the biochemical cascade triggered by odorant binding to olfactory receptors, including the role of G-proteins and second messengers in generating an action potential.
Identify different types of olfactory disorders such as anosmia, hyposmia, hyperosmia, and dysosmia, including their potential causes.
Key Topics:
Olfactory Genes:
3% of the human genome accounts for olfactory genes.
400 genes for odorant receptors.
Olfactory Membrane:
Located in the superior part of the nasal cavity.
Medially: Folds downward along the superior septum.
Laterally: Folds over the superior turbinate and upper surface of the middle turbinate.
Total surface area: 5-10 square centimeters.
Olfactory Mucosa:
Olfactory Cells: Bipolar nerve cells derived from the CNS (100 million), with 4-25 olfactory cilia per cell.
Sustentacular Cells: Produce mucus and maintain ionic and molecular environment.
Basal Cells: Replace worn-out olfactory cells with an average lifespan of 1-2 months.
Bowman’s Gland: Secretes mucus.
Stimulation of Olfactory Cells:
Odorant dissolves in mucus and attaches to receptors on olfactory cilia.
Involves a cascade effect through G-proteins and second messengers, leading to depolarization and action potential generation in the olfactory nerve.
Quality of a Good Odorant:
Small (3-20 Carbon atoms), volatile, water-soluble, and lipid-soluble.
Facilitated by odorant-binding proteins in mucus.
Membrane Potential and Action Potential:
Resting membrane potential: -55mV.
Action potential frequency in the olfactory nerve increases with odorant strength.
Adaptation Towards the Sense of Smell:
Rapid adaptation within the first second, with further slow adaptation.
Psychological adaptation greater than receptor adaptation, involving feedback inhibition from the central nervous system.
Primary Sensations of Smell:
Camphoraceous, Musky, Floral, Pepperminty, Ethereal, Pungent, Putrid.
Odor Detection Threshold:
Examples: Hydrogen sulfide (0.0005 ppm), Methyl-mercaptan (0.002 ppm).
Some toxic substances are odorless at lethal concentrations.
Characteristics of Smell:
Odor blindness for single substances due to lack of appropriate receptor protein.
Behavioral and emotional influences of smell.
Transmission of Olfactory Signals:
From olfactory cells to glomeruli in the olfactory bulb, involving lateral inhibition.
Primitive, less old, and new olfactory systems with different path
Ethanol (CH3CH2OH), or beverage alcohol, is a two-carbon alcohol
that is rapidly distributed in the body and brain. Ethanol alters many
neurochemical systems and has rewarding and addictive properties. It
is the oldest recreational drug and likely contributes to more morbidity,
mortality, and public health costs than all illicit drugs combined. The
5th edition of the Diagnostic and Statistical Manual of Mental Disorders
(DSM-5) integrates alcohol abuse and alcohol dependence into a single
disorder called alcohol use disorder (AUD), with mild, moderate,
and severe subclassifications (American Psychiatric Association, 2013).
In the DSM-5, all types of substance abuse and dependence have been
combined into a single substance use disorder (SUD) on a continuum
from mild to severe. A diagnosis of AUD requires that at least two of
the 11 DSM-5 behaviors be present within a 12-month period (mild
AUD: 2–3 criteria; moderate AUD: 4–5 criteria; severe AUD: 6–11 criteria).
The four main behavioral effects of AUD are impaired control over
drinking, negative social consequences, risky use, and altered physiological
effects (tolerance, withdrawal). This chapter presents an overview
of the prevalence and harmful consequences of AUD in the U.S.,
the systemic nature of the disease, neurocircuitry and stages of AUD,
comorbidities, fetal alcohol spectrum disorders, genetic risk factors, and
pharmacotherapies for AUD.
1. CLINICAL DATA MANGEMENT
(CDM)
SOURABH KOSEY
ASSOCIATE PROFESSOR
DEPT. OF PHARMACY PRACTICE
ISF COLLEGE OF PHARMACY
WEBSITE: - WWW.ISFCP.ORG
EMAIL: SOURABHKOSEY@GMAIL.COM
ISF College of Pharmacy, Moga
Ghal Kalan,nGT Road, Moga- 142001, Punjab, INDIA
Internal Quality Assurance Cell - (IQAC)
2. SOURCE DATA
• RECORDS
• ORIGINAL RECORDS OF CLINICAL FINDING
• OBSERVATIONS IN CLINCAL TRIALS
• RECONSRTUCTION AND EVALUATION OF THE TRIAL
• SOURCE DATA ARE CONTAINED IN SOURCE DOCUMENTS
•
2
3. 3
SOURCE DOCUMENTS
•ORIGINAL DOCUMENTS,DATA,RECORDS
•HOSPITAL RECORDS,CLINICAL & OFFICE CHARTS
•LABORATORY NOTES & FINDINGS,MEMORANDA
•SUBJECT’S DIARIES OR EVALUATION CHECKLISTS
•PHARMACY DISPENSING RECORDS
•RECORDED DATA FROM AUTOMATEDINSTRUMENTS
•COPIES OR TRANSCRIPTIONS CERTIFIED AFTER
•VERIFICATION AS BEING ACCURATE COPIES
4. 4
Source Document: The electronic record to used to keep together a
collection of eSource data items for capture, transmission, storage,
and/or display; and serving as a source document for a clinical
investigation.
Raw Data: Data as originally collected. Distinct from derived. Raw
Data includes original observations, measurements and activities
5. 5INTRODUCTION
•CRO’s
• DATA GENERATION & PRESENTATION
• ACCURACY OF TRAILS & REGULATORS
• INFORMATION TECHNOLOGY (IT)
• COMPUTERIZED SYSTEM (REMOVAL OF TRADITIONAL SYSTEM PAPER
WASTAGE )
• GROWTH & REQUIREMENTS OF GOOD DATA MANAGEMENT SYSTEMS
THAT COMPANIES WHICH ARE OTHERWISE IT-BASED
6. 6
• Have full fleged clinical trial data management systems which bring
them a good amount of business and revenue.
• CDM is a fundamental process which controls data accuracy of each
trial besides helping the timelessness to be achieved.
• It helps in linking clinical research co-ordinator = who monitor all the
sites & collects the data.
• it Links with biostatisticians = who analyze, interpret and report data in
clinically meaningful way.
7. 7
Good Clinical Data Management Practice
(GCDMP)
• The objective of GCDMP is to generate high quality database devoid of
errors and omissions
• ICH GUIDELINES.
• US FDA REGULATIONS.
DRUG AND DEVICE DEVELOPMENT PROCESS
The Society of Clinical Data Management (SCDM) has created a
comprehensive document- Good Clinical Data Management Practices
(GCDMP) (Version 4.0 is the most recently updated version published in
May 2007)- that provides guidance on accepted practices of Clinical Data
Management (CDM)
8. 8
SYSTEMIC APPROACH FOR CDM
INITIAL PLANNING
SPONSOR or INVSTIGATOR or CRO.
Standardized database management system.
CRF CASE RECORD FORMAT.
CRF as per database need, setting realistic dates for receipt, verification,
query resolution, corrections, Final editing and release of data and finally
resource mobilization
9. 9
• Preparing for Incoming Data Data management study
master file SOP’s should be established to ensure operational
documentation for computers.
• System reliability, Validation and accuracy.
• System security for hardware software and data from theft
and sabogate.
• Adequate access code and back up of the data.
• Indexes & Checklists for CRF’s Designing data entry screens
10. 10
• Establishing systems for tracking of CRF;s like Barcodes, deciding
which CRF copy to be working copy (usually second copy)
• Validating CRF and other data transfer procedures.
• Data Transfer may be on Paper or Electronic
11. 11INCOMING DATA
• Data received continuously and in a timely manner.
• Helps in data testing methodology, validates data base
management system (DBMS), helps in checking accuracy and
completeness of CRF.
• Timely clarification of errors and omissions with the investigators.
• It is also important to decide on unambiguous
Codes for subject identification that allow identification of all the
data of any subject.
12. 12INITIAL DATA REVIEW AND VERIFICATION
• DATA REVIEW COMMITTEE MEMBERS.
• MAINTAINING BLINDING DURING REVIEW AND ENTRY OF THE DATA.
• ERROR DETECTION IS AN IMPORTANT STEP TO BE DONE BEFORE AND DURING
DATA REVIEW AND VERIFICATION.
• THE VARIOUS ERRORS THAT ONE CAN EXPECT DURING THIS STAGE CAN
RANGE FROM MISSING DATA, FAULTY COMPLETION OF FORMS,QUESTIONABLE
VALUES (E.G. HEIGHT 20 FEETS), TREND TESTS TO GROSS PROTOCOL
VIOLATIONS
13. 13
• SUBSEQUENT ERRORS CAN ALSO BE DETECTED AT VARIOUS STAGES LIKE
DURING COMPUTER ENTRY, ERRONEOUS CODING OR INVESTIGATOR’S
CORRECTIONS NOT BEING TAKEN INTO ACCOUNT.
• DATA MONITORING COMMITTEE HELPS IN ASSESSING THE PROGRESS OF
TRIALS AT INTERVALS TO RECOMMEND WHETHER TO CONTINUE, MODIFY
OR STOP THE TRIALS.
• IT ALSO EVALUATES SAFETY DATA AND CRITICAL EFFICIACY END POINTS.
• THERE SHOULD BE WRITTEN OPERATION PROCEDURES AND
MAINTENANACE OF ALL MEETING RECORDS
14. 14DATA ENTRY, VERIFICATION AND VALIDATION
The Data entry person should be defined for the specific trial &
specified in a data management plan.
For transcription from paper CRF to electronic CRF different
procedures are used:
Double Data Entry form (one person)
Double Data Entry form (two persons)
Single entry with second look
Single data entry with reading aloud
Single data entry with source verification
15. Double data entry is not required by regulation by good
practice.
Data entry process should be chosen based on the skills
of the personnel, this will give good impact on to the
resources in the project and the reflected evaluation of
key variables.
Only authorized persons should be entitled to do entry
and corrections on the data entry screens.
Verification and Validation is done by Data Reviewers,
automated computer checks (an error message like
when a value is outside the acceptable norms) and
during audit
It has been that errors in entry is 1 % by good operator.
This Decreases to 0.1% by double entry of data by two
different operators.
15
16. CODING
FOR Adverse Events
COSTART (Coding Symbols for Thesaurus of Adverse
Reaction Terms)
WHO-ART (Adverse Reaction Terminology)
SNOMED (Systematized Nomenclature of Medicine)
MedDRA (Medical Dictionary for Regulatory Activities)
In House Codes
16
17. FOR concomitant diseases: international classification of
diseases version 10 (ICD-10)
FOR concomitant medications: WHO Drug Dictionary
Medical Term ----- Preferred term(s)----- Code
ERRORS IN CODING
Misunderstanding about medical terms, misinterpretation
of hand writing, defective translation, foreign Language
of CRF, wrong choice of preferred terms and difficulties in
transcoding.
This errors leads to inconsistencies in final
report, decreased credibility of report, delay in report
writing and represent evidence of negligence
17
18. To minimize errors only qualified and trained staffs should
be employed in the process the data entry operators
should insist on legible filling of CRFs.
It can also be minimized by keeping a log book of
difficult coding cases, doing translation-retranslation and
centralizing of the final coding
18
19. DATA QUERIES
Problems faced by data entry operators
Subject has to go back to investigator
Operators are failure to check the inclusion and exclusion criteria
Inconsistent Calendar Dates
Illegible entries
Unfamiliar Drugs Names
Text in unfamiliar Language
Entries in incorrect place at CRFs
Failure to specify indication for concomitant medication
Lack of reason for change in medication
Inconsistencies in physical examination at start and finish
Incomplete information on Adverse Events
Varying Units & Normal ranges in case of Laboratory Data.
19
20. Query Tracking and Resolution
A proper SOP has to be made in place of query tracking
and solving
Operator should draw a list of QUERIES
This List should be sent to investigators who verifies,
corrects, signs and corrects the dates the query
Three copies should be send to the same format then
To the data entry operator who operates the same
20
21. At the end a validation program is done and run to
follow the program and check the editing done.
Any change or correction must be readily spottable and
is called as AUDIT TRIAL.
This Trial may be given in the computers where
computers saves the date and time of correction, new
value along with old value and access code used to
make changes or on paper
21
22. DATA OUTPUT, REVIEW & FREEZING
As the data comes the manager and stastician finalizes
the data and queries are resolved.
Thereafter a final audit is performed, data is frozen and
sent to the statistician.
Goal of perfectly accurate database is usually
unrealistic.
It is preferable to set acceptable limits of error that do
not alter the validity of statistical analysis and results and
conclusions drawn from the study
22
23. ARCHIVING
Data mangers and statistician are responsible for
archiving the electronic database, associated computer
programs, Data monitoring conventions, audit trials and
final report.
They also maintain also all sponsor-specific essential
documents as per regulatory requirements.
23
24. REQUIREMENTS FOR ACQUIRING/
CAPTURING/ COPYING SOURCE DATA
In general data & documents containing source data must first be
specified in the trial protocol.
Source Data are the original data, the recordings and all information
regarding Clinical Investigations, Laboratory findings, anamnesis,
interviews, patient diaries and other sources.
The original documents have to be archived.
Copies have to be dated and signed by a responsible person
(Certified copies)
If the original data is stored electronically, a printout has to be made
or a list of dates and versions of stored documents signed/dated by
Principal Investigator.
24
25. In the case of eSource data, of course, this is not possible.
A copy of eSource data shall be accepted in place of eSource
data, if the copy hass been produced and verified against the
eSource data based on procedures defined in a SOP for
acquiring data duplication and verification.
Appropriate handling is also required for scanning source
documents.
The Scanning process has to be validated prior to
implementation in a trial to ensure the integrity of the generated
record
25
26. In the CRF is the source document (e.g., in psychiatric instruments
like psychometric scales ) this has to be defined in the protocol.
If work has been used as a transcription instrument (e.g., Transitional
documentation prior to electronic data entry), these are to be
considered as informal source data sheets and have to be filed and
quality checked appropriately.
In general, source data must be accessible and verifiable and the
quality of digitization must be carefully controlled using
appropriately defined SOPs.
26
27. pCRF to eCRF Transfer
In this scenario, clinical data are at first collected with a
pCRF.
Investigator has less time or has to move between
locations. (e.g. emergency ward, operation theatre)
In a remote data entry scenario, it is often not the
investigator, but special assistance personnel who enters
data from the pCRF into the eCRF.
This transcription step must be quality assured.
27
28. Type of personnel needed (i.e., for data entry, for data
review, etc.)
Criteria chosen to qualify them must be clearly defined.
For using eCRF, specific training programs for
investigators and assistance personnel must be included.
Appropriate quality control steps have to be
implemented and double data entry may be performed.
pCRF transfer as well as status (arrived, re-viewed, non-
correct, requested queries, correct, closed) must be
clearly tracked.
28
29. Personnel responsible for different phases of pCRF entry
must be tracked as well as all the changes.
Because the investigator’s signature is required, he is
responsible for the correct transcription of the data.
Appropriate workflow support should be implemented in
the Electronic Data Capture (EDC) system.
29
30. ESSENTIAL REQUIREMENTS
GOOD CDM SYSTEM
System evaluation and provider/vendor selection.
System installation, setup and configuration.
System configuration management (Configuration of
Audit Trial e.g. reson for change optional or not?).
System access and profile management.
30
31. Change Control
1. Risk Assessment of any change in the system.
2. Controlled processes of making changes to the system,
consisting of announcement, assessment and approval
of the change.
System Security
1. Password policy.
2. Firewall configuration.
3. Physical & Logical security, in particular also at the sites
(EDC).
4. System controls.
5. Network security for remote access.
31
32. Database and communication security
1. Encryption of data storage, data Transfer.
2. Electronic signature has to comply also with national
regulations [EDC].
Data protection
1. Handling of personally identifiable data (e.g., blinding of
additionally submitted identifying data; sites should
eliminate personal identifiers from source documents
prior to submission).
2. Specification of minimum subject identifiers.
3. Safeguarding that (future) use of data is in accordance
with informed consent.
32
33. 4 Regulation of access to electronic or paper based data
storage.
5 Particularly strict standards for genetic data.
6 Secure data handling procedures.
7 Use of pseudonyms/anonyms where appropriate.
8 Secure cross-border data transfer.
Data backup and recovery
Disaster system recovery
Database security
33
34. Data Archiving
1. Database specification.
2. Data files.
3. Audit Trial.
4. Clinical Data (open standards – vendor independent,
e.g., CSV, XML, PDF, ODM, from CDISC)
5. Archiving reports.
6. Scanned paper CRFs.
7. Content and Variable definitions (metadata).
34
35. 8 Report on data completeness at respondent and variable
level.
9 Secure Storage and access control.
Business continuity
Migration of data/meta-data (in case of system retirement)
System Validation.
Risk management.
1. All components of the system have to be judged according
to their risk to violate GCP.
2. GCP-compliance has to be guaranteed especially for high-
risk components.
3. Maintenance of GCP-compliance even after updates or
other changes to the system.
35
36. CONCLUSION
The importance of CDM can be realized from the fact a
lot of pure IT companies are involved in CDM activities
and this contributes a big share in their revenue. Some of
the advances in CDM are:
New hardware's like PCs, Electronic notebooks
Remote data entry.
Optical mark recognition like bar codes.
Optical character recognition like fingerprints.
Facsimile.
Smart cards for each patient.
Computer assisted new drug application [CANDA] by
FDA.
36
