WHO has recently issued draft document titled "Guidelines on Validation". These guidelines (i.e., the main text included in this working document) cover the general principles of validation and qualification.
These guidelines focus mainly on the overall concept of validation and are not intended to be prescriptive in specific validation requirements. This document serves as general guidance only and the principles may be considered useful in its application in the manufacture and control of starting materials and finished pharmaceutical products (FPPs), as well as other areas. Validation of specific processes and systems, for example, in sterile product manufacture, requires much more consideration and a detailed approach that is beyond the scope of this document. The general text in this document may be applicable to validation and qualification of premises, equipment, utilities, systems, processes, and procedures.
The draft on the specific topics, the appendices to this main text, will follow. The following is an overview on the appendices that are intended to complement the text of this working document:
Appendix 1: Validation of heating, ventilation and air-conditioning systems - will be replaced by cross reference to WHO Guidelines on GMP for HVAC systems for considerations in qualification of HVAC systems (update - working document QAS/15.639/Rev. 1)
Appendix 2: Validation of water systems for pharmaceutical use - will be replaced by cross-reference to WHO Guidelines on water for pharmaceutical use for consideration in qualification of water purification systems
Appendix 3: Cleaning validation - consensus to retain
Appendix 4: Analytical method validation - update in process
Appendix 5: Validation of computerized systems - update in process
Appendix 6: Qualification of systems and equipment - update in process
Appendix 7: Non-sterile process validation - update already published as Annex 3, WHO Technical Report Series, No. 992, 2015
Comments on this draft document are due by July 12, 2016.
A presentation on this guidance is given below:
Presentation on New WHO Guidance on Validations
Data integrity is a Fundamental in a pharmaceutical quality system. It ensures that medicines are of required quality. This presentation is based on MHRA Guidance and provides MHRA expectations. Guidance complements existing EU GMP relating to active substances and dosage forms. This guidance should be d in conjunction with national medicines legislation and the GMP standards published in Eudralex volume 4.
In Pharma and Biotech, Weightage of the Documentation is around 70 % because as per FDA "If you do not have Document, You dint have do it."
So Good Documentation Practice is of tremendous importance for the Industry to comply any regulation like FDA, GMP or ISO.
Data integrity, Pharmaceutical industry, Good Manufacturing Practice, GMP, Guidelines, Data management, DI and GMP Compliance, paper and electronic data, Archive and back up
www.3-14.com
Source Data expectations for the life sciences industry. Data integrity refers to the completeness, consistency, and accuracy of data. Complete, consistent, and accurate data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate.
WHO has recently issued draft document titled "Guidelines on Validation". These guidelines (i.e., the main text included in this working document) cover the general principles of validation and qualification.
These guidelines focus mainly on the overall concept of validation and are not intended to be prescriptive in specific validation requirements. This document serves as general guidance only and the principles may be considered useful in its application in the manufacture and control of starting materials and finished pharmaceutical products (FPPs), as well as other areas. Validation of specific processes and systems, for example, in sterile product manufacture, requires much more consideration and a detailed approach that is beyond the scope of this document. The general text in this document may be applicable to validation and qualification of premises, equipment, utilities, systems, processes, and procedures.
The draft on the specific topics, the appendices to this main text, will follow. The following is an overview on the appendices that are intended to complement the text of this working document:
Appendix 1: Validation of heating, ventilation and air-conditioning systems - will be replaced by cross reference to WHO Guidelines on GMP for HVAC systems for considerations in qualification of HVAC systems (update - working document QAS/15.639/Rev. 1)
Appendix 2: Validation of water systems for pharmaceutical use - will be replaced by cross-reference to WHO Guidelines on water for pharmaceutical use for consideration in qualification of water purification systems
Appendix 3: Cleaning validation - consensus to retain
Appendix 4: Analytical method validation - update in process
Appendix 5: Validation of computerized systems - update in process
Appendix 6: Qualification of systems and equipment - update in process
Appendix 7: Non-sterile process validation - update already published as Annex 3, WHO Technical Report Series, No. 992, 2015
Comments on this draft document are due by July 12, 2016.
A presentation on this guidance is given below:
Presentation on New WHO Guidance on Validations
Data integrity is a Fundamental in a pharmaceutical quality system. It ensures that medicines are of required quality. This presentation is based on MHRA Guidance and provides MHRA expectations. Guidance complements existing EU GMP relating to active substances and dosage forms. This guidance should be d in conjunction with national medicines legislation and the GMP standards published in Eudralex volume 4.
In Pharma and Biotech, Weightage of the Documentation is around 70 % because as per FDA "If you do not have Document, You dint have do it."
So Good Documentation Practice is of tremendous importance for the Industry to comply any regulation like FDA, GMP or ISO.
Data integrity, Pharmaceutical industry, Good Manufacturing Practice, GMP, Guidelines, Data management, DI and GMP Compliance, paper and electronic data, Archive and back up
www.3-14.com
Source Data expectations for the life sciences industry. Data integrity refers to the completeness, consistency, and accuracy of data. Complete, consistent, and accurate data should be attributable, legible, contemporaneously recorded, original or a true copy, and accurate.
This presentation contain introduction to Good Distribution Practices Guideline. and Legal GDP requirements put worldwide.
Good distribution practice (GDP) describes the minimum standards that a wholesale distributor must meet to ensure that the quality and integrity of medicines is maintained throughout the supply chain
Each participant in the distribution chain must agree by the relevant requirements in order to retain the original quality of pharmaceutical products.
Each activity in the distribution of pharmaceutical products shall be carried out according to the principles of Good Distribution Practices (GDP) as applicable.
The risks involved are likely to be of a nature comparable to those that are present in the industrial environment, such as mix-ups, adulteration, contamination, cross-contamination, and spurious.
The guideline addresses
Personnel
Quality System
Premises Warehousing and Storage
Documentation
Traceability
Complaints and Returns
Transportation
CCK Discussion Forum held at ICCBS, University of Karachi, attended by over hundred of registered experienced pharmaceutical professionals participants belonging from dozen of pharmaceutical manufacturing facilities
Qualification of Dissolution Test Apparatus and Validation of Utility System this presentation will help to enhance your knowledge in validation and qualification area.
Role of quality system and audits in pharmamaceuticalganpat420
Introduction
cGMP Regulations
Quality Assurance Function
Quality Systems Approach
Management Responsibilities
Resources
Manufacturing Operations
Evaluation Activities
Transitioning to Quality Systems Approach
Audit Checklist for Drug Industry
Presentation on data integrity in Pharmaceutical IndustrySathish Vemula
Presentation on data integrity in Pharmaceutical Industry
Contents:
- Definition & Basics
- Criteria for integrity of laboratory data
- Regulatory Requirements
- Barriers to Complete Data
- Possible data integrity problems
- Previous observations
- FDA Warning Letters – 2013
- FDA Warning Letters – 2014
- FDA 483’s related to data integrity
- EU – Non compliance Reports
- WHO - Notice of Concern
- Summary of Data Integrity issues
- Consequences- Rebuilding Trust
- Conclusion
This presentation contain introduction to Good Distribution Practices Guideline. and Legal GDP requirements put worldwide.
Good distribution practice (GDP) describes the minimum standards that a wholesale distributor must meet to ensure that the quality and integrity of medicines is maintained throughout the supply chain
Each participant in the distribution chain must agree by the relevant requirements in order to retain the original quality of pharmaceutical products.
Each activity in the distribution of pharmaceutical products shall be carried out according to the principles of Good Distribution Practices (GDP) as applicable.
The risks involved are likely to be of a nature comparable to those that are present in the industrial environment, such as mix-ups, adulteration, contamination, cross-contamination, and spurious.
The guideline addresses
Personnel
Quality System
Premises Warehousing and Storage
Documentation
Traceability
Complaints and Returns
Transportation
CCK Discussion Forum held at ICCBS, University of Karachi, attended by over hundred of registered experienced pharmaceutical professionals participants belonging from dozen of pharmaceutical manufacturing facilities
Qualification of Dissolution Test Apparatus and Validation of Utility System this presentation will help to enhance your knowledge in validation and qualification area.
Role of quality system and audits in pharmamaceuticalganpat420
Introduction
cGMP Regulations
Quality Assurance Function
Quality Systems Approach
Management Responsibilities
Resources
Manufacturing Operations
Evaluation Activities
Transitioning to Quality Systems Approach
Audit Checklist for Drug Industry
Presentation on data integrity in Pharmaceutical IndustrySathish Vemula
Presentation on data integrity in Pharmaceutical Industry
Contents:
- Definition & Basics
- Criteria for integrity of laboratory data
- Regulatory Requirements
- Barriers to Complete Data
- Possible data integrity problems
- Previous observations
- FDA Warning Letters – 2013
- FDA Warning Letters – 2014
- FDA 483’s related to data integrity
- EU – Non compliance Reports
- WHO - Notice of Concern
- Summary of Data Integrity issues
- Consequences- Rebuilding Trust
- Conclusion
This presentation highlights the reasons which lead to the withdrawal of the 2002 Guidance of the FDA and the current issue with Blend Uniformity and Content Uniformity Determinations.
Looking for expertise or support on Data Integrity? Contact us today.
Recently, the pharmaceutical industry has been challenged with the regulatory requirements to provide complete, consistent and accurate data, throughout all GMP regulated processes.
Moreover, during audits the regulatory bodies have observed a level of inconsistency in the application of the predicate rules in GMP processes. This has become a growing concern and has led to a set of new (draft) guidances from different market authorities.
Index:
Data Integrity – Why / What
Data life cycle
Core Data Integrity concepts & building blocks
Short & mid-term actions enabling a focused road to compliance
Pharmaceutical quality decisions are made by multidisciplinary teams (a range of maturity), at different times and in various organizations; understanding of the QbD paradigm and methodology is derived experientially -One Quality Voice is hard to achieve!
Legacy challenges, various ontological assumptions, and weak epistemology curtails knowledge sharing, delays consensus and keeps us trapped in a reactive mode (3rd Order)
The risk of irrational decision making needs to be accounted. ”Cut-paste” or “check-the-box” practices are reminders that we are not achieving an optimal integration or practicing systems thinking.
A reactive approach (3rd Order) to filling the noted gaps poses risk of continued erosion in the confidence the public should have in our assurance of pharmaceutical quality
We need a thoughtful, planned approach to filling these gaps –NIPTE should take on this challenge! Will it?
Data integrity is assuming greater importance in current Good Manufacturing Practices in FDA regulated industry with increased emphasis by other regulatory agencies like the EMA. Data integrity and security infractions are not only 21 Code of Federal Regulations (CFR) Part 11 issues but also severe CGMP violations. As FDA increases its focus on data integrity and reliability, inspectors are examining data based on multiple regulations and standards including CGMP, Good Laboratory Practices (GLP), Good Clinical Practices (GCP) and the Application Integrity Policy (AIP) in addition to FDA-recognized consensus standards.
This presentation discusses data integrity regulations and enforcement trends that have led to increased scrutiny of pharmaceutical laboratories by inspectors.
Provide recommendations and background information concerning computerised systems
Information will be of assistance to inspectors for training purposes and during the inspection
Where automated systems and electronic records are used in warehouses and similar establishments where GDP requirements are applicable, controls and disciplines outlined in this document, or a best practice alternatives are expected to be in place.
Vertically integrated companies (R&D, manufacturing and distribution) will already apply such controls and compliance measures.
International regulatory agencies have collaborated to produce this guidance.
Intended as a reference for regulated users, including their suppliers, in addition to regulatory inspectors and investigators.
Provides a logical explanation of the basic requirements for the implementation, validation and operation of computerised systems.
May be adapted to identify the criteria for a regulated user, or a regulatory agency, in an inspection of GxP computer systems.
National legislation should to be referred to when determining the extent to which the provisions laid down in this document may be applicable.
This presentation gives a summary of this guidance.
In March 2011, the EMA and FDA launched a pilot program that aims at a parallel assessment by both agencies of certain quality/CMC sections which are relevant to Quality by Design (QbD). This voluntary pilot program is open. This presentation gives a summary of the FDA and EMA expectation for QbD submissions based on the pilot programme.
FDA Process Validation Guidance (Guidance for Industry: Process Validation- General Principles and Practices, Jan. 2011) outlines process validation activities in three stages - Stage 1: Process Design, Stage 2: Process Qualification and Stage 3: Continued Process Verification. Completion of Stage 2 subsequent to Stage 1 is a major milestone in the Process Validation Lifecycle as it confirms the process design and demonstrates the expected consistent performance of the manufacturing process. Knowledge and information gained from the design stage through the process qualification stage is used to complete this assessment. Stage 2 demonstrates suitability for successful commercial distribution where the data indicates that the process meets the conditions established in the protocol. Continued Process Verification is initiated for the subsequent commercial batches. Stage 3 assures that the process remains in a state of control during commercial manufacture.
This presentation gives a practical approach to implement the stage 3 of the FDA Process Validation Guide.
Data Integrity in a GxP-regulated Environment - Pauwels Consulting AcademyPauwels Consulting
On Tuesday, December 6, 2016, our colleague Angelo Rossi, Senior Regulatory Compliance Consultant, gave an interesting presentation about “Data Integrity in a GxP-regulated Environment” at the Brussels Office of Pauwels Consulting in Diegem.
In his presentation, Angelo covered definitions and concepts of data integrity, the change in regulatory focus, lessons learned from recent FDA warning letters, importants highlights of regulations and guidelines. Angelo also presented a practical example of data integrity for a computerized system.
Please contact us at contact@pauwelsconsulting.com or +32 9 324 70 80 if you have any further questions regarding our consulting services in this area.
A primary mission of the Food and Drug Administration is to conduct comprehensive regulatory coverage of all aspects of production and distribution of drugs and drug products to assure that such products meet the 501(a)(2)(B) requirements of the Act. FDA has developed two basic strategies:
. 1) evaluating through factory inspections, including the collection and analysis of associated samples, the conditions and practices under which drugs and drug products are manufactured, packed, tested and held, and
. 2) monitoring the quality of drugs and drug products through surveillance activities such as sampling and analyzing products in distribution.
FDA compliance program “ Drug Manufacturing Inpsections” (7356.002) is designed to provide guidance for implementing the first strategy. Products from production and distribution facilities covered under this program are consistently of acceptable quality if the firm is operating in a state of control.
The inspectional guidance in this program is structured to provide for efficient use of resources devoted to routine surveillance coverage, recognizing that in-depth coverage of all systems and all processes is not feasible for all firms on a biennial basis. It also provides for follow-up compliance coverage as needed.
“Drug Regulations” has prepared a summary from the compliance programme and is given below in the presentation.
It is of key importance that the quality and the integrity of the medicinal products are maintained during the entire supply chain from the manufacturer to the patient. Today’s distribution network for medicinal products is increasingly complex and involves many players. The revised guidelines, published today, lay down appropriate tools to assist wholesale distributors in conducting their activities and to prevent falsified medicines from entering the legal supply chain.
The revised guidelines introduce the following changes:
the maintenance of a quality system setting out responsibilities, processes and risk management principles in relation to wholesale activities;
suitable documentation which prevents errors from spoken communication;
sufficient competent personnel to carry out all the tasks for which the wholesale distributor is responsible;
adequate premises, installations and equipment so as to ensure proper storage and distribution of medicinal products;
appropriate management of complaints, returns, suspected falsified medicinal products and recalls;
outsourced activities correctly defined to avoid misunderstandings;
rules for transport in particular to protect medicinal products against breakage, adulteration and theft, and to ensure that temperature conditions are maintained within acceptable limits during transport;
Specific rules for brokers (person involved in activities in relation to the sale or purchase of medicinal products)
Drug Regulations has prepared a presentation summarizing the new GDP requirements for Medicinal Products.
This presentation presents points to consider for building and using models in the regulated pharmaceutical industry and offers examples of how models can play a part in the Quality by Design (QbD) framework.
This presentation describes approaches for software validation used to automate laboratory research procedures, consolidate data collection and analysis and/or run sophisticated QC or manufacturing operations.
Several approaches to software validation exist and may be appropriate for a specific project.
The scope of any validation effort depends upon a number of factors
Size and complexity of the software,
Origin of the software (custom vs. off-the-shelf) and
Whether the functions are critical or non-critical in nature.
By effectively planning the process, validation time and resources can be reduced while meeting regulatory requirements.
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
Performance metrics are an essential element of the management review process.
Quality metrics may include elements such as customer satisfaction, supplier performance, manufacturing defects, complaints, cycle times and many other internal or external processes.
This presentation provides a framework for establishing right quality indicators for evaluating the performance of the quality system.
Regulatory Reporting in Pharmacovigilance: Compliance and Best PracticesClinosolIndia
Regulatory reporting in pharmacovigilance is a critical component of ensuring patient safety by promptly and accurately communicating adverse events and other safety-related information to regulatory authorities. Compliance with regulatory requirements is essential to maintain public health and trust in the pharmaceutical industry.
This presentation gives a overview of the new FDA draft guidance on Analytical Method Validation and compares it with the older version issued in the year 2000.
This presentation covers the manufacture and testing of all sterile drug products, including drugs that are sterilized by filtration or other means and aseptically processed, and drug products that are terminally sterilized. The type of products covered include sterile bulk drugs, ophthalmic drugs, otic dosage forms, small volume parenteral (SVS) products for small molecule and licensed biological
therapeutic drug products, large volume parenteral (LVP) products, and any other drug products required to be sterile or labeled as sterile. Center for Biologics Evaluation and Research (CBER) regulated products and veterinary drug products are excluded from coverage under this program.
The guidance information is tailored to sterile manufacturing operations and should be used in conjunction with the Compliance Program for Drug Manufacturing Inspections (CP 7356.002).
Similar to New PICS Guidance on Data Integrity and Management. (20)
Environmental Monitoring describes the microbiological testing under- taken in order to detect changing trends of microbial counts and micro- flora growth within cleanroom or controlled environments. The results obtained provide information about the physical construction of the room, the performance of the Heating, Ventilation, and Air-Conditioning (HVAC) system, personnel cleanliness, gowning practices, the equipment, and cleaning operations.
Over the past decade, environmental monitoring has become more sophisticated in moving from random sampling, using an imaginary grid over the room and testing in each grid, to the current focus on risk assessment and the use of risk assessment tools to determine the most appropriate methods for environmental monitoring.
This presentation gives current trends in the application of risk assessment to the practice of environmental monitoring.
This presentation is compiled from freely available resources like the websites of FDA, EMA ,WHO and research papers published by experts in this field like Sandle, T Reinmüller, B , Hyde, W,, Costello, E.K., Lauber, C. L., Hamady, M., Fierer, N., Gordon, J.I., Knight, R.
Paper published by T. Sandle on clean room contamination was referred extensively for this presentation. “Drug Regulations” is a non profit organization which provides free online resource to the Pharmaceutical Professional.
Visit http://www.drugregulations.org for latest information from the world of Pharmaceuticals.
This presentation gives an overview of : Validation of microbiological methods , Considering some of the limitations and
Key criteria that may be applicable for assessment.
Prix Galien International 2024 Forum ProgramLevi Shapiro
June 20, 2024, Prix Galien International and Jerusalem Ethics Forum in ROME. Detailed agenda including panels:
- ADVANCES IN CARDIOLOGY: A NEW PARADIGM IS COMING
- WOMEN’S HEALTH: FERTILITY PRESERVATION
- WHAT’S NEW IN THE TREATMENT OF INFECTIOUS,
ONCOLOGICAL AND INFLAMMATORY SKIN DISEASES?
- ARTIFICIAL INTELLIGENCE AND ETHICS
- GENE THERAPY
- BEYOND BORDERS: GLOBAL INITIATIVES FOR DEMOCRATIZING LIFE SCIENCE TECHNOLOGIES AND PROMOTING ACCESS TO HEALTHCARE
- ETHICAL CHALLENGES IN LIFE SCIENCES
- Prix Galien International Awards Ceremony
Title: Sense of Taste
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 structure and function of taste buds.
Describe the relationship between the taste threshold and taste index of common substances.
Explain the chemical basis and signal transduction of taste perception for each type of primary taste sensation.
Recognize different abnormalities of taste perception and their causes.
Key Topics:
Significance of Taste Sensation:
Differentiation between pleasant and harmful food
Influence on behavior
Selection of food based on metabolic needs
Receptors of Taste:
Taste buds on the tongue
Influence of sense of smell, texture of food, and pain stimulation (e.g., by pepper)
Primary and Secondary Taste Sensations:
Primary taste sensations: Sweet, Sour, Salty, Bitter, Umami
Chemical basis and signal transduction mechanisms for each taste
Taste Threshold and Index:
Taste threshold values for Sweet (sucrose), Salty (NaCl), Sour (HCl), and Bitter (Quinine)
Taste index relationship: Inversely proportional to taste threshold
Taste Blindness:
Inability to taste certain substances, particularly thiourea compounds
Example: Phenylthiocarbamide
Structure and Function of Taste Buds:
Composition: Epithelial cells, Sustentacular/Supporting cells, Taste cells, Basal cells
Features: Taste pores, Taste hairs/microvilli, and Taste nerve fibers
Location of Taste Buds:
Found in papillae of the tongue (Fungiform, Circumvallate, Foliate)
Also present on the palate, tonsillar pillars, epiglottis, and proximal esophagus
Mechanism of Taste Stimulation:
Interaction of taste substances with receptors on microvilli
Signal transduction pathways for Umami, Sweet, Bitter, Sour, and Salty tastes
Taste Sensitivity and Adaptation:
Decrease in sensitivity with age
Rapid adaptation of taste sensation
Role of Saliva in Taste:
Dissolution of tastants to reach receptors
Washing away the stimulus
Taste Preferences and Aversions:
Mechanisms behind taste preference and aversion
Influence of receptors and neural pathways
Impact of Sensory Nerve Damage:
Degeneration of taste buds if the sensory nerve fiber is cut
Abnormalities of Taste Detection:
Conditions: Ageusia, Hypogeusia, Dysgeusia (parageusia)
Causes: Nerve damage, neurological disorders, infections, poor oral hygiene, adverse drug effects, deficiencies, aging, tobacco use, altered neurotransmitter levels
Neurotransmitters and Taste Threshold:
Effects of serotonin (5-HT) and norepinephrine (NE) on taste sensitivity
Supertasters:
25% of the population with heightened sensitivity to taste, especially bitterness
Increased number of fungiform papillae
Recomendações da OMS sobre cuidados maternos e neonatais para uma experiência pós-natal positiva.
Em consonância com os ODS – Objetivos do Desenvolvimento Sustentável e a Estratégia Global para a Saúde das Mulheres, Crianças e Adolescentes, e aplicando uma abordagem baseada nos direitos humanos, os esforços de cuidados pós-natais devem expandir-se para além da cobertura e da simples sobrevivência, de modo a incluir cuidados de qualidade.
Estas diretrizes visam melhorar a qualidade dos cuidados pós-natais essenciais e de rotina prestados às mulheres e aos recém-nascidos, com o objetivo final de melhorar a saúde e o bem-estar materno e neonatal.
Uma “experiência pós-natal positiva” é um resultado importante para todas as mulheres que dão à luz e para os seus recém-nascidos, estabelecendo as bases para a melhoria da saúde e do bem-estar a curto e longo prazo. Uma experiência pós-natal positiva é definida como aquela em que as mulheres, pessoas que gestam, os recém-nascidos, os casais, os pais, os cuidadores e as famílias recebem informação consistente, garantia e apoio de profissionais de saúde motivados; e onde um sistema de saúde flexível e com recursos reconheça as necessidades das mulheres e dos bebês e respeite o seu contexto cultural.
Estas diretrizes consolidadas apresentam algumas recomendações novas e já bem fundamentadas sobre cuidados pós-natais de rotina para mulheres e neonatos que recebem cuidados no pós-parto em unidades de saúde ou na comunidade, independentemente dos recursos disponíveis.
É fornecido um conjunto abrangente de recomendações para cuidados durante o período puerperal, com ênfase nos cuidados essenciais que todas as mulheres e recém-nascidos devem receber, e com a devida atenção à qualidade dos cuidados; isto é, a entrega e a experiência do cuidado recebido. Estas diretrizes atualizam e ampliam as recomendações da OMS de 2014 sobre cuidados pós-natais da mãe e do recém-nascido e complementam as atuais diretrizes da OMS sobre a gestão de complicações pós-natais.
O estabelecimento da amamentação e o manejo das principais intercorrências é contemplada.
Recomendamos muito.
Vamos discutir essas recomendações no nosso curso de pós-graduação em Aleitamento no Instituto Ciclos.
Esta publicação só está disponível em inglês até o momento.
Prof. Marcus Renato de Carvalho
www.agostodourado.com
Acute scrotum is a general term referring to an emergency condition affecting the contents or the wall of the scrotum.
There are a number of conditions that present acutely, predominantly with pain and/or swelling
A careful and detailed history and examination, and in some cases, investigations allow differentiation between these diagnoses. A prompt diagnosis is essential as the patient may require urgent surgical intervention
Testicular torsion refers to twisting of the spermatic cord, causing ischaemia of the testicle.
Testicular torsion results from inadequate fixation of the testis to the tunica vaginalis producing ischemia from reduced arterial inflow and venous outflow obstruction.
The prevalence of testicular torsion in adult patients hospitalized with acute scrotal pain is approximately 25 to 50 percent
Knee anatomy and clinical tests 2024.pdfvimalpl1234
This includes all relevant anatomy and clinical tests compiled from standard textbooks, Campbell,netter etc..It is comprehensive and best suited for orthopaedicians and orthopaedic residents.
These lecture slides, by Dr Sidra Arshad, offer a quick overview of physiological basis of a normal electrocardiogram.
Learning objectives:
1. Define an electrocardiogram (ECG) and electrocardiography
2. Describe how dipoles generated by the heart produce the waveforms of the ECG
3. Describe the components of a normal electrocardiogram of a typical bipolar leads (limb II)
4. Differentiate between intervals and segments
5. Enlist some common indications for obtaining an ECG
Study Resources:
1. Chapter 11, Guyton and Hall Textbook of Medical Physiology, 14th edition
2. Chapter 9, Human Physiology - From Cells to Systems, Lauralee Sherwood, 9th edition
3. Chapter 29, Ganong’s Review of Medical Physiology, 26th edition
4. Electrocardiogram, StatPearls - https://www.ncbi.nlm.nih.gov/books/NBK549803/
5. ECG in Medical Practice by ABM Abdullah, 4th edition
6. ECG Basics, http://www.nataliescasebook.com/tag/e-c-g-basics
Lung Cancer: Artificial Intelligence, Synergetics, Complex System Analysis, S...Oleg Kshivets
RESULTS: Overall life span (LS) was 2252.1±1742.5 days and cumulative 5-year survival (5YS) reached 73.2%, 10 years – 64.8%, 20 years – 42.5%. 513 LCP lived more than 5 years (LS=3124.6±1525.6 days), 148 LCP – more than 10 years (LS=5054.4±1504.1 days).199 LCP died because of LC (LS=562.7±374.5 days). 5YS of LCP after bi/lobectomies was significantly superior in comparison with LCP after pneumonectomies (78.1% vs.63.7%, P=0.00001 by log-rank test). AT significantly improved 5YS (66.3% vs. 34.8%) (P=0.00000 by log-rank test) only for LCP with N1-2. Cox modeling displayed that 5YS of LCP significantly depended on: phase transition (PT) early-invasive LC in terms of synergetics, PT N0—N12, cell ratio factors (ratio between cancer cells- CC and blood cells subpopulations), G1-3, histology, glucose, AT, blood cell circuit, prothrombin index, heparin tolerance, recalcification time (P=0.000-0.038). Neural networks, genetic algorithm selection and bootstrap simulation revealed relationships between 5YS and PT early-invasive LC (rank=1), PT N0—N12 (rank=2), thrombocytes/CC (3), erythrocytes/CC (4), eosinophils/CC (5), healthy cells/CC (6), lymphocytes/CC (7), segmented neutrophils/CC (8), stick neutrophils/CC (9), monocytes/CC (10); leucocytes/CC (11). Correct prediction of 5YS was 100% by neural networks computing (area under ROC curve=1.0; error=0.0).
CONCLUSIONS: 5YS of LCP after radical procedures significantly depended on: 1) PT early-invasive cancer; 2) PT N0--N12; 3) cell ratio factors; 4) blood cell circuit; 5) biochemical factors; 6) hemostasis system; 7) AT; 8) LC characteristics; 9) LC cell dynamics; 10) surgery type: lobectomy/pneumonectomy; 11) anthropometric data. Optimal diagnosis and treatment strategies for LC are: 1) screening and early detection of LC; 2) availability of experienced thoracic surgeons because of complexity of radical procedures; 3) aggressive en block surgery and adequate lymph node dissection for completeness; 4) precise prediction; 5) adjuvant chemoimmunoradiotherapy for LCP with unfavorable prognosis.
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Couples presenting to the infertility clinic- Do they really have infertility...Sujoy Dasgupta
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NVBDCP.pptx Nation vector borne disease control programSapna Thakur
NVBDCP was launched in 2003-2004 . Vector-Borne Disease: Disease that results from an infection transmitted to humans and other animals by blood-feeding arthropods, such as mosquitoes, ticks, and fleas. Examples of vector-borne diseases include Dengue fever, West Nile Virus, Lyme disease, and malaria.
New Drug Discovery and Development .....NEHA GUPTA
The "New Drug Discovery and Development" process involves the identification, design, testing, and manufacturing of novel pharmaceutical compounds with the aim of introducing new and improved treatments for various medical conditions. This comprehensive endeavor encompasses various stages, including target identification, preclinical studies, clinical trials, regulatory approval, and post-market surveillance. It involves multidisciplinary collaboration among scientists, researchers, clinicians, regulatory experts, and pharmaceutical companies to bring innovative therapies to market and address unmet medical needs.
Evaluation of antidepressant activity of clitoris ternatea in animals
New PICS Guidance on Data Integrity and Management.
1. This presentation is compiled by “ Drug Regulations”
a non profit organization which provides free online
resource to the Pharmaceutical Professional.
Visit http://www.drugregulations.org for latest
information from the world of Pharmaceuticals.
8/23/2016 1
2. This presentation is compiled from freely available
resource like the website of PIC/S, specifically the
PIC/S draft guidance titled
“GOOD PRACTICES FOR DATA MANAGEMENT AND
INTEGRITY IN REGULATED GMP/GDP ENVIRONMENTS”
“Drug Regulations” is a non profit organization which
provides free online resource to the Pharmaceutical
Professional.
Visit http://www.drugregulations.org for latest
information from the world of Pharmaceuticals.
8/23/2016 2
Drug Regulations : Online
Resource for Latest Information
3. This presentation is based on
PIC/S guidance titled
◦ “GOOD PRACTICES FOR DATA
MANAGEMENT AND INTEGRITY IN
REGULATED GMP/GDP ENVIRONMENTS”
This is a Draft document for comment
8/23/2016 3Drug Regulations : Online Resource for Latest Information
4. PIC/S Participating Authorities regularly undertake inspections of
manufacturers and distributors of API and medicinal products
This is done in order to determine the level of compliance with
GMP/GDP principles.
These inspections are commonly performed on-site
However they may also be performed through the remote or off-site
evaluation of documentary evidence
Of course these have the limitations of remote review of data and
these should be considered in such evaluations.
8/23/2016 4Drug Regulations : Online Resource for Latest Information
5. The effectiveness of these inspection processes is
determined by the veracity of the evidence provided to
the inspector
This ultimately depends on the integrity of the
underlying data.
Data integrity is critical to the inspection process
Inspectors need to fully rely on the accuracy and
completeness of evidence and records presented to
them to arrive at conclusions about GMP compliance.
8/23/2016 5Drug Regulations : Online Resource for Latest Information
6. Good data management practices influence the
integrity of all data generated and recorded
These practices should ensure that data is
accurate, complete and reliable.
The main focus of the PIC/S document is in relation
to data integrity expectations,
These principles should also be considered in the
wider context of good data management.
8/23/2016 6Drug Regulations : Online Resource for Latest Information
7. Data Integrity is
◦ Defined as “the extent to which all data are
complete, consistent and accurate, throughout
the data lifecycle”
◦ Fundamental in a pharmaceutical quality system,
which ensures that medicines are of the required
quality.
8/23/2016 7Drug Regulations : Online Resource for Latest Information
8. Poor data integrity practices and vulnerabilities
undermine the quality of records and evidence.
This may ultimately undermine the quality of
medicinal products.
Data integrity applies to all elements of the Quality
Management System
These principles apply equally to data generated by
electronic and paper-based systems.
8/23/2016 8Drug Regulations : Online Resource for Latest Information
9. The responsibility for good practices regarding
data management and integrity lies with the
manufacturer or distributor.
They have a duty
◦ To assess their data management systems for potential
vulnerabilities
◦ To take steps to design and implement good data
governance practices
8/23/2016 9Drug Regulations : Online Resource for Latest Information
10. Provide guidance for inspectorates in the interpretation of
GMP/GDP requirements
Provide consolidated, illustrative guidance on risk-based
control strategies
Facilitate the effective implementation of data integrity
elements into the routine planning and conduct of GMP/GDP
inspections;
Provide a tool to harmonize GMP/GDP inspections
Ensure the quality of inspections with regards to data
integrity expectations.
8/23/2016 10Drug Regulations : Online Resource for Latest Information
11. PICS guidance will enable the inspector to evaluate data
management and integrity
This guide does not impose additional regulatory burden
However it does provide guidance on the interpretation of
existing PIC/S GMP/GDP requirements
The principles of data integrity apply equally to both manual
and computerised systems
They should not place any restraint upon the development or
adoption of new concepts or technologies.
8/23/2016 11Drug Regulations : Online Resource for Latest Information
12. In accordance with ICH Q10 principles, this guide should
facilitate the adoption of innovative technologies through
continual improvement.
This version of the guidance is intended to provide a basic
overview of key principles regarding data management and
integrity.
The PIC/S Data Integrity Working Group will periodically
update, amend and review this guidance
8/23/2016 12Drug Regulations : Online Resource for Latest Information
13. PICS guidance has been written to apply to both
on-site and remote (desktop) inspections
Applies to sites performing manufacturing (GMP)
and distribution (GDP) activities.
The guide should be considered as a non-
exhaustive list of areas to be considered during
inspection.
8/23/2016 13Drug Regulations : Online Resource for Latest Information
14. These principles have applications for other areas
of the regulated pharmaceutical and healthcare
industry.
This guide is not intended to provide specific
guidance for “for-cause” inspections
When significant data integrity vulnerabilities have
been detected forensic expertise may be required.
8/23/2016 14Drug Regulations : Online Resource for Latest Information
15. What is data governance?
◦ Data governance is the sum total of arrangements which
provide assurance of data integrity.
◦ These arrangements ensure that data, generated, recorded,
processed, retained, retrieved and used will ensure a
complete, consistent and accurate record throughout the
data lifecycle.
◦ This irrespective of the process, format or technology
8/23/2016 15Drug Regulations : Online Resource for Latest Information
16. Data lifecycle
◦ Refers to
How data is generated, processed, reported, checked, used for
decision-making,
Stored and finally discarded at the end of the retention period.
8/23/2016 16Drug Regulations : Online Resource for Latest Information
17. Data relating to a product or process may cross various
boundaries within the lifecycle.
This may include
◦ Data transfer between manual and IT systems
◦ Between different organizational boundaries;
◦ Both internal
(e.g. between production, QC and QA) and
◦ External
(e.g. between service providers or contract givers and acceptors).
8/23/2016 17Drug Regulations : Online Resource for Latest Information
18. Data governance systems
Data governance systems should be integral to the
pharmaceutical quality system described in PIC/S
GMP/GDP.
8/23/2016 18Drug Regulations : Online Resource for Latest Information
19. It should address
◦ Data ownership throughout the lifecycle, and
◦ Consider the design, operation and monitoring of processes / systems in
order to comply with the principles of data integrity,
◦ This should include control over intentional and unintentional changes to,
and deletion of information.
◦ The data governance system should ensure controls over data lifecycle
◦ These should be commensurate with the principles of quality risk
management.
8/23/2016 19Drug Regulations : Online Resource for Latest Information
20. Organizational
Procedures,
◦ e.g. instructions for completion of records and retention of completed paper records;
Training of staff and documented authorisation for data generation and
approval;
Data governance system design, considering how data is generated recorded,
processed retained and used, and risks or vulnerabilities are controlled
effectively;
Routine data verification;
Periodic surveillance,
◦ e.g. self-inspection processes seek to verify the effectiveness of the data governance policy.
8/23/2016 20Drug Regulations : Online Resource for Latest Information
21. Technical
◦ Computerised system control,
◦ Automation
8/23/2016 21Drug Regulations : Online Resource for Latest Information
22. An effective data governance system will demonstrate
Management’s understanding and commitment to effective
data governance
The approach may be a combination of
◦ appropriate organizational culture and behaviors and
◦ an understanding of data criticality, data risk and data lifecycle.
There should also be evidence of communication of
expectations to personnel at all levels within the organization
8/23/2016 22Drug Regulations : Online Resource for Latest Information
23. Risk management approach to data governance
◦ Senior management is responsible for the implementation of systems and
procedures
◦ This should minimize the potential risk to data integrity, and for
identifying the residual risk, using the principles of ICH Q9.
◦ Contract Givers should perform a similar review as part of their vendor
assurance programme.
◦ The effort and resource assigned to data governance
Should be commensurate with the risk to product quality,
Should also be balanced with other quality resource demands.
8/23/2016 23Drug Regulations : Online Resource for Latest Information
24. Risk management approach to data governance
◦ Manufacturers and analytical laboratories should design and operate a
system, which provides an acceptable state of control
◦ This should be based on the data integrity risk, and which is fully
documented with supporting rationale.
◦ Where long term measures are identified in order to achieve the
desired state of control, interim measures should be implemented
◦ These measures should mitigate risk, and should be monitored for
effectiveness.
◦ Residual data integrity risk should be communicated to senior
management, and kept under review.
8/23/2016 24Drug Regulations : Online Resource for Latest Information
25. Risk management approach to data governance
◦ Reverting from automated / computerised to paper-
based systems will not remove the need for data
governance.
◦ Such retrograde approaches are likely to increase
administrative burden and data risk
◦ This will also prevent the continuous improvement
initiatives.
8/23/2016 25Drug Regulations : Online Resource for Latest Information
26. Risk management approach to data governance
◦ Not all data or processing steps have the same importance to product quality
and patient safety.
◦ Risk management should be utilized to determine the importance of each
data/processing step.
◦ An effective risk management approach to data governance will consider:
Data criticality (impact to decision making and product quality) and
Data risk
(opportunity for data alteration and deletion, Likelihood of detection / visibility of
changes by the manufacturer’s routine review processes).
◦ From this information, risk proportionate control measures can be
implemented.
8/23/2016 26Drug Regulations : Online Resource for Latest Information
27. Risk management approach to data governance
Data criticality
◦ The decision that data influences may differ in
importance,
◦ The impact of the data to a decision may also vary.
◦ Points to consider regarding data criticality include:
8/23/2016 27Drug Regulations : Online Resource for Latest Information
28. Risk management approach to data governance
Which decision does the data influence?
◦ For example:
When making a batch release decision, data which
determines compliance with critical quality attributes is of
greater importance than warehouse cleaning records.
8/23/2016 28Drug Regulations : Online Resource for Latest Information
29. Risk management approach to data governance
What is the impact of the data to product
quality or safety?
◦ For example:
◦ For an oral tablet, active substance assay data is of
generally greater impact to product quality and safety
than tablet friability data.
8/23/2016 29Drug Regulations : Online Resource for Latest Information
30. Data risk
Data risk assessment should consider
◦ The vulnerability of data to involuntary or deliberate alteration,
falsification, deletion, loss or re-creation, and
◦ The likelihood of detection of such actions.
◦ Consideration should also be given to ensuring complete data
recovery in the event of a disaster.
◦ Control measures which prevent unauthorized activity, and increase
visibility / detectability can be used as risk mitigating actions.
8/23/2016 30Drug Regulations : Online Resource for Latest Information
31. Data risk
Examples of factors which can increase risk of data integrity
failure include
◦ Complex, inconsistent processes with open ended and subjective
outcomes.
◦ Simple tasks which are consistent, well defined and objective lead to
reduced risk.
8/23/2016 31Drug Regulations : Online Resource for Latest Information
32. Data risk
Risk assessments should
◦ Focus on a business process (e.g. production, QC),
◦ Evaluate data flows and the methods of generating data
◦ They should not just consider IT system functionality or
complexity.
8/23/2016 32Drug Regulations : Online Resource for Latest Information
33. Data risk
Factors to consider include
◦ Process complexity;
◦ Methods of generating, storing and retiring data and their ability
to ensure data accuracy, legibility, indelibility;
◦ Process consistency and degree of automation / human
interaction;
◦ Subjectivity of outcome / result
(i.e. is the process open-ended or well defined?); and
8/23/2016 33Drug Regulations : Online Resource for Latest Information
34. Data risk
Factors to consider include
◦ The outcome of a comparison between
electronic system data and manually recorded
events could be indicative for malpractices
(e.g. apparent discrepancies between analytical
reports and raw-data acquisition times).
8/23/2016 34Drug Regulations : Online Resource for Latest Information
35. Data risk
◦ For computerised systems, manual interfaces with IT
systems should be considered in the risk assessment
process.
◦ Computerised system validation in isolation may not
result in low data integrity risk,
◦ This is especially when the user is able to influence
the reporting of data from the validated system.
8/23/2016 35Drug Regulations : Online Resource for Latest Information
36. Data risk
◦ Critical thinking skills should be used by inspectors to determine
whether control and review procedures effectively achieve their
desired outcomes.
◦ An indicator of data governance maturity is an organizational
understanding and acceptance of residual risk, which prioritizes
actions.
◦ An organization which believes that there is ‘no risk’ of data integrity
failure is unlikely to have made an adequate assessment of inherent
risks .
8/23/2016 36Drug Regulations : Online Resource for Latest Information
37. Data risk
◦ The approach to assessment of data lifecycle,
criticality and risk should therefore be examined
in detail.
◦ This may indicate potential failure modes which
can be investigated during an inspection.
8/23/2016 37Drug Regulations : Online Resource for Latest Information
38. Data governance system review
◦ The effectiveness of data integrity control
measures should be assessed periodically
◦ This could be part of self-inspection (internal
audit) or other periodic review processes.
◦ This should ensure that controls over the data
lifecycle are operating as intended.
8/23/2016 38Drug Regulations : Online Resource for Latest Information
39. Data governance system review
◦ Self-inspection activities should be extended to a
wider review of control measures, including:
◦ A check of continued personnel understanding of
data integrity should be performed.
8/23/2016 39Drug Regulations : Online Resource for Latest Information
40. Data governance system review
◦ In situations where routine computerised system data is
reviewed by a validated ‘exception report’, a risk-based
sample of computerised system logs / audit trails to ensure
that information of relevance to GMP activity is reported as
expected
8/23/2016 40Drug Regulations : Online Resource for Latest Information
41. It may not be appropriate or possible to report an
inspection citation relating to organizational behavior.
An understanding of how behavior influences the
incentive to amend, delete or falsify data and the
effectiveness of procedural controls designed to ensure
data integrity, can provide the inspector with useful
indicators of risk which can be investigated further.
8/23/2016 41Drug Regulations : Online Resource for Latest Information
42. Inspectors would be sensitive to the influence of
culture on organizational behavior.
They would apply the principles described in this
section of the guidance in an appropriate way.
8/23/2016 42Drug Regulations : Online Resource for Latest Information
43. An effective ‘quality culture’ and data governance may be
different in its implementation from one location to another.
Depending on culture, an organisation’s control measures
may be:
◦ ‘open’
(where hierarchy can be challenged by subordinates, and full reporting of a
systemic or individual failure is a business expectation)
◦ ‘closed’
(where reporting failure or challenging a hierarchy is culturally more difficult)
8/23/2016 43Drug Regulations : Online Resource for Latest Information
44. Good data governance in ‘open’ cultures may be
facilitated by employee empowerment to identify
and report issues through the quality system.
In ‘closed’ cultures, a greater emphasis on
oversight and secondary review may be required .
The availability of anonymous escalation to senior
management may also be of greater importance in
this situation.
8/23/2016 44Drug Regulations : Online Resource for Latest Information
45. The extent of Management’s knowledge and
understanding of data integrity can influence the
organisation’s success of data integrity
management.
Management must know their legal and moral
obligation to prevent data integrity lapses from
occurring and to detect them, if they should occur.
8/23/2016 45Drug Regulations : Online Resource for Latest Information
46. Lapses in data integrity are not limited to fraud or
falsification, they can be unintentional and still pose risk.
Any potential for compromising the reliability of data is a risk
that should be identified and understood
Then appropriate controls should be put in place.
Direct controls usually take the form of written policies and
procedures,
Indirect influences on employee behaviour should be
understood and addressed as well.
◦ (such as incentives for productivity in excess of process capability)
8/23/2016 46Drug Regulations : Online Resource for Latest Information
47. Data integrity breaches can occur at any
time
Management needs to be
◦ Vigilant in detecting issues
◦ Understand reasons behind lapses
◦ Willing to investigate the issue and implement corrective
and preventative actions.
8/23/2016 47Drug Regulations : Online Resource for Latest Information
48. There are consequences of data integrity lapses
that affect various stakeholders
◦ (patients, regulators, customers)
They can directly impact patient safety
They can also undermining confidence in the
organisation and its products.
Employee awareness and understanding of these
consequences can be helpful in fostering an
environment in which quality is a priority.
8/23/2016 48Drug Regulations : Online Resource for Latest Information
49. Management should
◦ Establish controls to prevent, detect and correct data
integrity breaches,
◦ Verify those controls are performing as intended to assure
data integrity.
◦ To achieve success with data integrity, Management should
address the following: ( See next slides)
8/23/2016 49Drug Regulations : Online Resource for Latest Information
50. A Code of Values & Ethics should reflect
Management’s philosophy on quality
This should be achieved through policies that are
aligned to the quality culture.
They should develop an environment of trust,
All should be responsible and accountable for
ensuring patient safety and product quality.
8/23/2016 50Drug Regulations : Online Resource for Latest Information
51. The company’s general ethics and integrity standards
need to be established
It should be known to each employee
These expectations should be communicated frequently
and consistently.
Management should make personnel aware of the
Importance of their role in ensuring data integrity and
The implication of their activities to assuring product
quality and protecting patient safety.
8/23/2016 51Drug Regulations : Online Resource for Latest Information
52. Code of Conduct policies should clearly define the
expectation of ethical behaviour, such as honesty.
This should be communicated to and be well
understood by all personnel.
The communication should not be limited only to
knowing the requirements
It should also address why they were established and
the consequences of failing to fulfill the requirements.
8/23/2016 52Drug Regulations : Online Resource for Latest Information
53. Unwanted behaviours, such as deliberate data
falsification, unauthorised changes, destruction of
data, or other conduct that compromises data
integrity should be addressed promptly.
Disciplinary action may be taken, when warranted.
Similarly, conforming behaviors should be
recognized appropriately.
8/23/2016 53Drug Regulations : Online Resource for Latest Information
54. There should be a confidential escalation program
This should be supported by the company policy
and procedures
The program should encourage personnel to bring
instances of possible breaches to the attention of
management without consequence.
8/23/2016 54Drug Regulations : Online Resource for Latest Information
55. Management should aim to create a work environment (ie.
quality culture) that is
Transparent and open,
One in which personnel are encouraged to freely
communicate failures and mistakes, including potential data
reliability issues,
This should enable implementation of corrective and
preventative actions .
Organizational reporting structure should permit the
information flow between personnel at all levels.
8/23/2016 55Drug Regulations : Online Resource for Latest Information
56. It is the collection of values, beliefs, thinking, and
behaviours demonstrated consistently by
management, team leaders, quality personnel and
all personnel that contribute to creating a quality
culture to assure data integrity.
8/23/2016 56Drug Regulations : Online Resource for Latest Information
57. Management can foster quality culture:
◦ Ensure awareness and understanding of expectations
(eg. Code of Ethics and Code of Conduct);
◦ Lead by example,
management should demonstrate the behaviours they expect to see ;
◦ Ensure accountability for actions and decisions;
◦ Stay continuously and actively involved;
◦ Set realistic expectations, consider the limitations that place pressures
on employees;
◦ Allocate resources to meet expectations;
Implement fair and just consequences and rewards; and
Be aware of regulatory trends to apply lessons learned to your organisation.
8/23/2016 57Drug Regulations : Online Resource for Latest Information
58. The application of modern quality risk management principles
and good data management practices to the current
pharmaceutical quality management system serves to
modernize the System
8/23/2016 58Drug Regulations : Online Resource for Latest Information
59. The company’s Quality Management System should be able to
prevent, detect and correct weaknesses in the system or their
processes that may lead to data integrity lapses.
The company should know their data life cycle and integrate
the appropriate controls and procedures such that the data
generated will be valid, complete and reliable.
8/23/2016 59Drug Regulations : Online Resource for Latest Information
60. Specifically, such control and procedural changes may be in
the following areas:
◦ Risk assessment and management,
◦ Investigation programs,
◦ Data review practices
◦ Computer software validation,
◦ Vendor/contractor management ,
◦ Training program to include company’s data integrity policy and data
integrity SOPs ,
◦ Self-inspection program to include data integrity, and
◦ Quality metrics and reporting to senior management.
8/23/2016 60Drug Regulations : Online Resource for Latest Information
61. The head of the Quality unit should have direct access to the
highest level of management
She/He should be able to directly communicate risks so that
senior management is aware and can allocate resources to
address any issues.
Management can have an independent expert periodically
verify the effectiveness of their systems and controls.
8/23/2016 61Drug Regulations : Online Resource for Latest Information
62. Management should allocate appropriate resources to
support and sustain good data integrity management
The workload and pressures on those responsible for data
generation and record keeping should not increase the
likelihood of errors or the opportunity to deliberately
compromise data integrity.
8/23/2016 62Drug Regulations : Online Resource for Latest Information
63. There should be sufficient number of personnel for
◦ Quality and management oversight
◦ IT support,
◦ Conduct of investigations, and
◦ Management of training program
This should be commensurate with the operations of the
organization.
8/23/2016 63Drug Regulations : Online Resource for Latest Information
64. There should be provisions to purchase equipment, software
and hardware that are appropriate for their needs, based on
the criticality of the data in question.
Personnel must be qualified and trained for their specific
duties, with appropriate segregation of duties, including the
importance of good documentation practices.
8/23/2016 64Drug Regulations : Online Resource for Latest Information
65. There should be evidence of the effectiveness of training on
critical procedures, such as electronic data review.
The concept of data integrity applies to all functional
departments that play a role in GMP, including areas such as
IT and engineering.
8/23/2016 65Drug Regulations : Online Resource for Latest Information
66. Data integrity should be familiar to all,
Data integrity experts from various levels (SMEs, supervisors,
team leaders) may be called upon to work together
This could be to conduct/support investigations, identify
system gaps and drive implementation of improvements.
Introduction of new roles in an organization relating to data
integrity such as a data custodian or Chief Compliance Officer
might be considered.
8/23/2016 66Drug Regulations : Online Resource for Latest Information
67. In the event that data integrity lapses are found, they should
be handled as any deviation.
It is important to determine the extent of the problem
Also important to determine its root cause, then correcting
the issue to its full extent and implement preventative
measures.
This may include the use of a third party which may involve a
gap assessment to identify weaknesses in the system.
8/23/2016 67Drug Regulations : Online Resource for Latest Information
68. When considering the impact on product, any conclusions
drawn should be supported by sound scientific evidence.
Corrective actions may include product recall, client
notification and reporting to regulatory authorities.
8/23/2016 68Drug Regulations : Online Resource for Latest Information
69. The Pharmaceutical Quality Management System (QMS) should
be implemented throughout the different stages of the life
cycle
Use science and risk-based approaches.
Document decision and actions.
Decision-making should be well informed.
Information should be reliable.
8/23/2016 69Drug Regulations : Online Resource for Latest Information
70. Good Documentation Practices (GDocPs) are key to
ensuring data integrity,
It is a fundamental part of a well designed PMS.
8/23/2016 70Drug Regulations : Online Resource for Latest Information
71. The application of GDocPs may vary depending on the
medium used to record the data
◦ (ie. physical vs. electronic records),
However the principles are applicable to both.
Some key concepts of GDocPs are summarised by the
acronym ALCOA:
◦ Attributable,
◦ Legible,
◦ Contemporaneous,
◦ Original,
◦ Accurate.
8/23/2016 71Drug Regulations : Online Resource for Latest Information
72. To this list can be added the following:
◦ Complete,
◦ Consisitent,
◦ Enduring and
◦ Available (ALCOA+5).
Together, these expectations ensure that events are properly
documented and the data can be used to support informed
decisions.
8/23/2016 72Drug Regulations : Online Resource for Latest Information
77. Structure of quality management system (QMS) and control of
blank forms/templates/records
The effective management of paper-based documents is a
key element of GMP/GDP.
Accordingly the documentation system should be designed to
meet GMP/GDP requirements
It should ensure that documents and records are effectively
controlled to maintain their integrity.
8/23/2016 77Drug Regulations : Online Resource for Latest Information
78. Paper records must be controlled and must remain
◦ Attributable,
◦ Legible,
◦ Indelible/durable,
◦ Contemporaneous,
◦ Original and
◦ Accurate
(ALCOA) throughout the data lifecycle.
8/23/2016 78Drug Regulations : Online Resource for Latest Information
79. Procedures outlining good documentation practices and
arrangements for document control should be available
within the QMS.
These procedures should specify:
◦ How master documents and procedures are created, reviewed
and approved for use;
◦ Generation , distribution and control of templates used to
record data (master , logs, etc.);
◦ Retrieval and disaster recovery processes regarding records.
8/23/2016 79Drug Regulations : Online Resource for Latest Information
80. These procedures should:
◦ Specify the process for generation of working copies of
documents for routine use,
◦ Have specific emphasis on ensuring copies of documents, e.g.
SOPs and blank forms are issued and reconciled for use in a
controlled and traceable manner.
◦ Provide guidance for the completion of paper based
documents, specifying how individual operators are identified,
data entry formats and amendments to documents are
recorded.
8/23/2016 80Drug Regulations : Online Resource for Latest Information
81. These procedures should specify:
◦ How completed documents are routinely reviewed for
accuracy, authenticity and completeness;
◦ Processes for the filing, retrieval, retention, archival and
disposal of records.
◦ How data integrity is maintained throughout the lifecycle of
the data.
8/23/2016 81Drug Regulations : Online Resource for Latest Information
82. Generation, distribution and control of template records
Why is managing and controlling master records necessary?
◦ Managing and controlling master records is necessary to ensure that the
risk of someone inappropriately using and/or falsifying a record ‘by
ordinary means’ is reduced to an acceptable level.
◦ The following expectations should be implemented using a quality risk
management approach, considering the risk and criticality of data
recorded
8/23/2016 82Drug Regulations : Online Resource for Latest Information
89. An index of all the template records should be maintained by
QA organisation.
This index should mention for each type of template record at
least the following information:
◦ Title,
◦ Reference number including version number,
◦ Location
(e.g., documentation data base, effective date, next review date, etc.
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90. Use and control of records within production areas
◦ Records should be appropriately controlled in the production areas by
designated persons or processes.
◦ These controls should be carried out to minimize the risk of damage or
loss of the records and ensure data integrity.
◦ Where necessary, measures must be taken to protect records from being
soiled (e.g. getting wet or stained by materials, etc).
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91. Filling out records
The items listed in the table below should be controlled to
assure that a record is properly filled out.
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103. Paper records generated by very simple electronic systems,
e.g. balances, pH meters or simple processing equipment
which do not store data provide limited opportunity to
influence the presentation of data by (re-)processing,
changing of electronic date/time stamps.
In these circumstances, the original record should be signed
and dated by the person generating the record and the
original should be attached to batch processing records.
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104. Copies of original paper records are generally very useful for
communication purposes,
◦ e.g. between companies operating at different locations.
◦ (e.g. analytical summary reports, validation reports etc.)
These records must be controlled during their life cycle to
ensure that the data received from another site (sister
company, contractor etc.) are maintained as “true copies”
It could be used as a “summary report” where the
requirements of a “true copy” are not met (e.g. summary of
complex analytical data).
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105. It is conceivable for raw data generated by electronic means
to be retained in an acceptable paper or pdf format, where it
can be justified that a static record maintains the integrity of
the original data.
However, the data retention process must be shown to
include verified copies of all
◦ Raw data
◦ Metadata
◦ Relevant audit trail and result files
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106. Software / system configuration settings specific to each
analytical run, and all data processing runs (including
methods and audit trails) necessary for reconstruction of a
given raw data set.
It would also require a documented means to verify that the
printed records were an accurate representation.
This approach is likely to be onerous in its administration to
enable a GMP compliant record.
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107. Many electronic records are important to retain in their
dynamic (electronic) format, to enable interaction with the
data.
Data must be retained in a dynamic form where this is critical
to its integrity or later verification. This should be justified
based on risk.
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108. At the receiving site, these records (true copies) may either be
managed in a paper or electronic format (e.g., PDF)
However they should be controlled according to an approved
QA procedure.
Ensure that documents are appropriately authenticated as
“true copies”
This can be done either through the use of handwritten or
digital signatures.
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112. A quality agreement should be in place to address
the responsibilities for the generation and transfer
of “true copies” and data integrity controls.
The system for the issuance and control of “true
copies” should be audited by the contract giver and
receiver to ensure the process is robust and meets
data integrity principles.
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113. The remote review of data within summary reports is a
common necessity;
The limitations of remote data review must be fully
understood to enable adequate control of data integrity.
Summary reports of data are often supplied between
physically remote manufacturing sites, Market
Authorization Holders and other interested parties.
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114. Critical supporting data and metadata is often not included in
summary reports and therefore original data cannot be
reviewed.
It is therefore essential that summary reports are viewed as
but one element of the process for the transfer of data
Interested parties and inspectorates should not place sole
reliance on summary report data.
Prior to acceptance of summary data, an evaluation of the
supplier’s quality system and compliance with data integrity
principles should be established.
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115. This can be done through on-site inspection when
considered important in the context of quality risk
management.
The inspection should ensure the veracity of data
generated by the company.
This should also include a review of the
mechanisms used to generate and distribute
summary data and reports.
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116. The retention period of each type of records should (at a
minimum) meet those periods specified by GMP/GDP
requirements.
Consideration should be given to other local or national
legislation that may stipulate longer storage periods.
The records can be retained internally or by using an outside
storage service subject to quality agreements.
A risk assessment should be available to demonstrate
retention systems/facilities/services are suitable and that the
residual risks are understood.
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119. A documented process for the disposal of records should be
in place to ensure that the correct original records are
disposed of.
This should be done after the defined retention period.
The system should ensure that current records are not
destroyed by accident.
Similarly it should be ensured that historical records do not
inadvertently make their way back into the current record
stream
◦ (eg. Historical records confused/mixed with existing records.)
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120. A record/register should be available to demonstrate appropriate and
timely destruction of retired records.
Measures should be in place to reduce the risk of deleting the wrong
documents.
The access rights allowing deletion of records should be limited to few
persons.
In case of printouts which are not permanent (e.g. thermo transfer
paper) a verified (‘true’) copy may retained,
In such cases it is possible to discard the non- permanent original
Paper records may be replaced by Scans provided that the principles of
‘true copy’ are addressed
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121. Structure of the QMS and control of computerised systems
Companies use a large variety of computerised systems.
These range from the simple standalone to large integrated and
complex systems.
Many have an impact on the quality of products manufactured.
It is the responsibility of each regulated entity to fully evaluate and
control all computerised systems
The responsibility also includes their management in accordance
with GMP and GDP requirements.
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122. Structure of the QMS and control of computerised systems
Organizations should be fully aware of the nature and extent of
computerised systems utilized
Assessments should be in place that describe each system, its
intended use and function,
Assessment about any data integrity risks or vulnerabilities should
also be documented.
Particular emphasis should be placed on determining the criticality
of computerised systems and any associated data, in respect of
product quality.
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123. Structure of the QMS and control of computerised systems
All computerised systems with potential for impact on product
quality should be effectively managed under a mature quality
management system
The system should be designed to ensure that systems are protected
from acts of accidental or deliberate manipulation, modification or
any other activity that may impact on data integrity.
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124. Structure of the QMS and control of computerised systems
For example, data integrity of an analytical method with
computerised interface is affected by
Sample preparation,
Entry of sample weights into the computerised system,
Use of the computerised system to generate data, and
Processing / recording of the final result using that data.
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125. Structure of the QMS and control of computerised systems
The guidance in this document is intended to provide specific
considerations for data integrity in the context of computerised
systems.
Further guidance regarding good practices for computerised
systems may be found in the PIC/S Good Practices for Computerised
Systems in Regulated “GxP” Environments (PI 011).
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126. Qualification and validation of computerised systems
The qualification and validation of computerised systems should be
performed in accordance with the relevant GMP/GDP guidelines;
The tables in next slide provide clarification regarding specific
expectations for ensuring good data governance practices for
computerised systems.
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156. General supply chain considerations
Data integrity plays a key part in ensuring the security and integrity
of supply chains.
Data governance measures by a contract giver may be significantly
weakened by unreliable or falsified data or materials provided by
supply chain partners.
This principle applies to all outsourced activities, including suppliers
of raw materials or contract manufacture / analytical services.
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157. Initial and periodic re-qualification of supply chain partners and
outsourced activities should include consideration of data integrity
risks and appropriate control measures.
It is important for an organization to understand
◦ The data integrity limitations of information obtained from the supply chain and
◦ The challenges of remote supervision.
This will help to focus resources towards data integrity verification
and supervision using a qualiity risk management approach.
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158. Routine document verification
The supply chain relies upon the use of documentation and data
passed from one organisation to another.
It is often not practical for the contract giver to review all raw data
relating to reported results.
Emphasis should be placed upon robust supplier and contractor
qualification, using the principles of quality risk management.
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159. Strategies for assessing data integrity in the supply chain
Companies should conduct regular risk reviews of supply chains and
outsourced activity that evaluate the extent of data integrity controls
required.
Information considered during risk reviews may include:
The outcome of site audits, with focus on data governance measures
Review of data submitted in routine reports, for example:
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161. Quality agreements should be in place between manufacturers and
suppliers/contract manufacturing organisations (CMOs)
There should be specific provisions for ensuring data integrity
across the supply chain.
This may be achieved by setting out expectations for data
governance, and transparent error/deviation reporting
There should also be a requirement to notify the contract giver of
any data integrity failures identified at the contract acceptor site.
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162. Audits of CMO’s should include a verification of data integrity
Audits and routine surveillance should include adequate verification
of the source electronic data and metadata by the Quality Unit of the
contract giver
A quality risk management approach should be used.
This may be achieved by measures such as: ( See subsequent slides)
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164. Contract givers may work with the contract acceptor to
ensure that all client- confidential information is encoded to
de-identify clients.
This would facilitate review of source electronic data and
metadata at the contract giver’s site, without breaking
confidentiality obligations to other clients.
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165. By reviewing a larger data set, this enables a more
robust assessment of the contract givers data
governance measures.
It also permits a search for indicators of data
integrity failure, such as repeated data sets or data
which does not demonstrate the expected
variability.
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166. Care should be taken to ensure the authenticity
and accuracy of supplied documentation.
The difference in data integrity and traceability
risks between ‘true copy’ and ‘summary report’
data should be considered when making contractor
and supply chain qualification decisions.
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167. Deficiency references
The integrity of data is fundamental to good
manufacturing practice.
The requirements for good data management are
embedded in the current PIC/S Guides to GMP/GDP
for Medicinal products.
The table in next slide provides a reference point
highlighting some of these existing requirements.
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169. This guidance is intended to aid consistency in
reporting and classification of data integrity
deficiencies,
It is not intended to affect the inspecting
authority’s ability to act according to national legal
frameworks.
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170. Deficiencies relating to data integrity failure may
have varying impact to product quality.
Prevalence of the failure may also vary between the
action of a single employee to an endemic failure
throughout the inspected organization.
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171. “A critical deficiency is a practice or process that has
produced, or leads to a significant risk of producing
either a product which is harmful to the human or
veterinary patient or a product which could result in a
harmful residue in a food producing animal.
A critical deficiency also occurs when it is observed that
the manufacturer has engaged in fraud,
misrepresentation or falsification of products or data”.
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172. Notwithstanding the “critical” classification of
deficiencies relating to fraud, misrepresentation or
falsification, it is understood that data integrity
deficiencies can also relate to:
◦ Data integrity failure resulting from bad practice,
◦ Opportunity for failure (without evidence of actual failure)
due to absence of the required data control measures.
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173. In these cases, it may be appropriate to assign
classification of deficiencies by taking into account the
following
◦ (indicative list only):
Impact to product with risk to patient health:
◦ Critical deficiency:
Product failing to meet specification at release or within shelf life.
Reporting of a ‘desired’ result rather than an actual out of
specification result when reporting of QC tests, critical product or
process parameters.
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174. Impact to product with no risk to patient health:
◦ Major deficiency:
Data being miss-reported, e.g. original results ‘in
specification’, but altered to give a more favourable trend.
Reporting of a ‘desired’ result rather than an actual out of
specification result when reporting of data which does not
relate to QC tests, critical product or process parameters.
Failures arising from poorly designed data capture systems
(e.g. using scraps of paper to record info for later
transcription).
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175. No impact to product; evidence of widespread failure:
◦ Major deficiency:
Bad practices and poorly designed systems which may result
in opportunities for data integrity issues or loss of traceability
across a number of functional areas (QA, production, QC etc).
Each in its own right has no direct impact to product quality.
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176. No impact to product; limited evidence of failure:
◦ Other deficiency:
Bad practice or poorly designed system which result in
opportunities for data integrity issues or loss of traceability in
a discrete area.
Limited failure in an otherwise acceptable system.
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177. It is important to build an overall picture of the adequacy of
the key elements to make a robust assessment as to whether
there is a company-wide failure, or a deficiency of limited
scope/ impact.
Data governance process,
Design of systems to facilitate compliant data recording,
Use and verification of audit trails and IT user access etc.
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178. Individual circumstances (exacerbating / mitigating
factors) may also affect final classification or
regulatory action.
Further guidance on the classification of
deficiencies and intra-authority reporting of
compliance issues will be available in the PIC/S
guidance on the classification of deficiencies, once
it has been published.
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179. Responding to Significant Data Integrity issues
◦ Consideration should be primarily given to resolving the
immediate issues identified and assessing the risks
associated with the data integrity issues.
◦ The response by the company in question should outline
the actions taken. Responses should include:
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180. A comprehensive investigation into the extent of the
inaccuracies in data records and reporting, to include:
◦ A detailed investigation protocol and methodology;
◦ A summary of all laboratories, manufacturing operations, and
◦ Systems to be covered by the assessment; and
◦ A justification for any part of the operation that the regulated
user proposes to exclude;
◦ Interviews of current and former employees to identify the
nature, scope, and root cause of data inaccuracies.
◦ These interviews may be conducted by a qualified third party;
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181. A comprehensive investigation into the extent of the
inaccuracies in data records and reporting, to include:
◦ An assessment of the extent of data integrity deficiencies at the
facility.
◦ Identify omissions, alterations, deletions, record destruction, non-
contemporaneous record completion, and other deficiencies;
◦ Determination of the scope and extent and timeframe for the incident,
with justification for the time-boundaries applied;
◦ Data, products, processes and specific batches implicated in any
investigations;
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182. A comprehensive investigation into the extent of
the inaccuracies in data records and reporting, to
include:
◦ A description of all parts of the operations in which data
integrity lapses occur, additional consideration should be
given to global corrective actions for multinational
companies or those that operate across multiple differing
sites;
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183. A comprehensive investigation into the extent of
the inaccuracies in data records and reporting, to
include:
◦ A comprehensive retrospective evaluation of the nature of
the testing and manufacturing data integrity deficiencies,
and the potential root cause(s).
◦ The services of a qualified third-party consultant with
specific expertise in the areas where potential breaches
were identified may be necessary;
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184. A comprehensive investigation into the extent of the
inaccuracies in data records and reporting, to include:
A risk assessment of the potential effects of the observed
failures on the quality of the drugs involved.
The assessment should include
◦ Analyses of the risks to patients caused by the release of drugs affected by a lapse
of data integrity,
◦ Risks posed by ongoing operations, and
◦ Any impact on the veracity of data submitted to regulatory agencies, including data
related to product registration dossiers;
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185. Corrective and preventative actions taken to address the data
integrity vulnerabilities and timeframe for implementation,
and including:
◦ Interim measures describing the actions to protect patients and to ensure
the quality of the medicinal products, such as
◦ Notifying customers,
◦ Recalling product,
◦ Conducting additional testing,
◦ Adding lots to the stability program to assure stability,
◦ Drug application actions, and enhanced complaint monitoring.
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186. Long-term measures describing any remediation efforts and
enhancements to
Procedures,
Processes,
Methods,
Controls, systems,
Management oversight, and
Human resources
◦ (e.g., training, staffing improvements) designed to ensure the data
integrity.
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187. Whenever possible, inspectorates should meet with
senior representatives from the implicated companies
To convey the nature of the deficiencies identified and
Seek written confirmation that the company commits to full
disclosure of issues and their prompt resolution.
A management strategy should be submitted to the
regulatory authority that includes the details of the
global corrective action and preventive action plan.
The strategy should include : ( See Subsequent Slides)
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188. The strategy should include :
◦ A detailed corrective action plan that describes how the
regulated user intends to ensure the reliability and
completeness of all of the data generated, including
analytical data, manufacturing records, and all data
submitted to the Competent Authority.
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189. The strategy should include :
◦ A comprehensive description of the root causes of data
integrity lapses, including evidence that the scope and
depth of the current action plan is commensurate with the
findings of the investigation and risk assessment.
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190. The strategy should include :
◦ This must indicate if individuals responsible for data
integrity lapses remain able to influence GMP/GDP-related
or drug application data.
◦ Inspectorates should implement policies for the
management of significant data integrity issues identified
at inspection in order to manage and contain risks
associated with the data integrity breach.
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191. Indicators of improvement
An on-site inspection is required to verify the
effectiveness of actions taken to address data integrity
issues. Some indicators of improvement are:
◦ Evidence of a thorough and open evaluation of the identified
issue and timely implementation of effective corrective and
preventative actions;
◦ Evidence of open communication of issues with clients and
other regulators.
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192. Indicators of improvement
◦ Transparent communication should be maintained
throughout the investigation and remediation stages.
◦ Regulators should be aware that further data integrity
failures may be reported as a result of the detailed
investigation.
◦ Any additional reaction to these notifications should be
proportionate to public health risks, to encourage
continued reporting;
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193. Indicators of improvement
◦ Evidence of communication of data integrity expectations
across the organisation, incorporating processes for open
reporting of potential issues and opportunities for
improvement without repercussions;
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194. Indicators of improvement
◦ The regulated user should ensure that an appropriate
evaluation of the vulnerability of any sophisticated
electronic systems to data manipulation takes place to
ensure that follow-up actions have fully resolved all the
violations, third party expertise may be required;
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195. Indicators of improvement
◦ Implementation of data integrity policies in line
with the principles of this guide;
◦ Implementation of routine data verification
practices.
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196. Archive
◦ Long term, permanent retention of completed data and
relevant metadata in its final form for the purposes of
reconstruction of the process or activity.
Audit Trail
◦ GMP/GDP audit trails are metadata that are a record of
GMP/GDP critical information (for example the change or
deletion of GMP/GDP relevant data), which permit the
reconstruction of GMP/GDP activities.
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197. Back-up
◦ A copy of current (editable) data, metadata and system
configuration settings (e.g. variable settings which relate to
an analytical run) maintained for the purpose of disaster
recovery.
Data
◦ Facts, figures and statistics collected together for reference
or analysis.
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198. Data Governance
◦ The sum total of arrangements to ensure that data,
irrespective of the format in which it is generated, is
recorded, processed, retained and used to ensure a
complete, consistent and accurate record throughout the
data lifecycle.
Data Integrity
◦ The extent to which all data are complete, consistent and
accurate throughout the data lifecycle.
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199. Flat file
◦ A ‘flat file’ is an individual record which may not carry any
additional metadata with it, other than that which is
included in the file itself.
Meta-data
◦ Data that describe the attributes of other data, and provide
context and meaning.
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200. This presentation is compiled from freely available
resource like the website of PIC/S, specifically the
PIC/S draft guidance titled
“GOOD PRACTICES FOR DATA MANAGEMENT AND
INTEGRITY IN REGULATED GMP/GDP ENVIRONMENTS”
“Drug Regulations” is a non profit organization which
provides free online resource to the Pharmaceutical
Professional.
Visit http://www.drugregulations.org for latest
information from the world of Pharmaceuticals.
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