Monday, 21 May 2018

CLINICAL TRIAL & 13 Principles of ICH GCP

In Clinical Trials to achieve Quality readiness one needs to understand the Principles of Good Clinical Practices. GCP has been well defined in EU Directive 2001/20/EC, under Clause 2 of Article 1, which discusses about scientific quality requirements for designing and conducting clinical trials.

The data obtained from Clinical trials should be credible as well Clinical trials should protect the rights, safety and wellbeing participating subjects as per National Research Act and Belmont Report, to ensure the authenticity of data and protection of human subjects The International Conference on Harmonisation of Technical Requirements for Registration of Pharmaceuticals for Human Use (ICH) created Good Clinical Practices in the year 1996, which eventually became mandatory to be followed in the year 2004 for conducting trials on all Investigational Medicinal Products (IMP).

Principles of GCP are summarized as follows

1.Clinical Trials should be conducted as per Declaration of Helsinki, which provides ethical guidelines on human experimentation.
2.Before the initiation of clinical trial, the risks for subject and society should be weighed against its anticipated benefits. 
3.The safety and rights of the participating subjects should considered with utmost importance over the benefits of trial. 
4.Clinical information and non-clinical information on the investigational medical product should be adequate to support the trial.
5.Specifics of clinical trials should be well defined and explained in Protocol
6.Protocol should be approved by Institutional review board (IRB)/independent ethics committee (IEC), following which clinical trial should be conducted in compliance with Protocol. 
7.During the trial, qualified physician would be responsible for the well the being of the subject 
8.The staff conducting the trail should be qualified in education, training and experience to perform task allocated to them.
9.Prior to the clinical trial signed informed consent should be obtained from the subject
10.To allow accurate reporting, interpretation and verification of clinical trial data, measures to and record and maintain the data should be sought out.
11.The records identifying the confidentiality of subject should be protected in respect to privacy and confidentiality regulations.
12.The Investigational medicinal product in Clinical Trials should be manufactured as per Good manufacturing practices (GMP) and should be used in accordance to the protocol. 
13.Quality systems should be maintained to ensure quality in Clinical Trials.

Reference: GCP 13 Principles
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Wednesday, 16 May 2018

Clinical Research- opening new doors to Duchenne muscular dystrophy

Duchenne muscular dystrophy (DMD) is a muscular dystrophy characterized by severe muscle weakness due breaking of skeletal muscles. DMD mostly occurs in boys at around age of 4. The aetiology of DMD is said to be attributed to the mutation of a gene called dystrophin located at locus Xp21 or on Chromosome X. Dystrophin is responsible for connecting the cytoskeleton of each muscle, without dystrophin, excess calcium would enter into the cell and cause the cell to burst.
It was not too long before Erin realized that her two year old son Oliver Lambright was diagnosed with Duchenne muscular dystrophy, a generic disorder which occurs in one in 3000 boys. She looked at every possible treatment on the internet, only to realize that there was no cure, till she found Dr. Jean Mah, who was an Associate Professor at Cumming school of Medicine in the Department of Paediatrics, she told her family that there is ongoing clinical trial on DMD at the University of Calgary in Alberta, Canada in which around 100 patients with DMD from all over the world participated in the trial.

Clinical trials are essentials as it paves way for new line of treatment drugs. Before a drug is dispensed in a clinic,It has to undergo clinical trial. At the University of Calgary there are around 563 active trials.

Reference: UToday, University of Calgary
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Wednesday, 25 April 2018

Social media analytics ‘The WEB RADR trials’

Web RADR (Recognising Adverse Drug Reactions) is platform which provides technological solutions for robust pharmacovigilance. Web RADR has its key contributions in Governance and policy, Social media and Analytics.

Web RADR is led by the European Medical Agency to provide its recommendation on developing mobile based application and use of social media for monitoring adverse drug reactions. Web- RADR goes in consultation with bodies like Eudravigilance- Expert Working Group (EV- EWG), Patient’s and Consumer Working Party (PCWP).

Key stakeholders in this project include Novartis Pharma, Janssen Pharmaceutica, Sanofi-Aventis, UCB and Amgen
Web RADR along with Epidemico (An organization with the capability to analyse and visualize data, comprising of public health leaders, software experts and data scientist) is now working its way to provide access to social media content by visualization using technology by Epidemico in detecting signals. Analysis of social media content through Big Data Analytics would be applied in forecasting problems with marketed medicinal products, it would enable the regulators to understand nature of safety signals and all of the content screening would be done on data which would be publically available, without violating data protection act adding further to this where social networking users would also have the provision to opt out of data collection.

Through a recent it was determined that in 2016, Facebook has highest number of threads with 2.2 Billion post, Twitter following with around 318 millions tweets and You tube with 1.5 billion videos.
Alongside with screening digital content from social media, Web RADR in collaboration with World Health Organization’s, Uppsala Monitoring Centre would be developing analytical tool, which would help in extraction of relevant and quality data from social media for  screening and would also focus on case triaging and linkage of duplicate reports.
Another initiative led by Web-RADR is designing android/ IOS based apps with key functions to report ADR and provide alerts. The apps would be linked with various regulatory agencies and would provide tailored alerts to the users about safety issues and warnings. The app would also facilitate anonymous ADR submissions using customized reporting forms. Web-RADR would be making the app soon available in different languages and additional products would be added in the product list for easy recognition of suspect.

In UK almost 4000+ users have used Yellow Card app with 400+ safety reports being sent to MHRA

Web- RADR , together with University Medical Centre Groningen and University College London would analysing barriers for patient and healthcare professionals to use mobile application for reporting ADR, studies through conjoint analysis where different versions of app are tested on different levels of health, literacy and usability on focussed population groups of patients adolescents, orphan disease populations and elderly patients have been undertaken by the University.
Web-RADR would also be conducting Scientific Impact Evaluation, together with University of Liverpool to determine whether mobile based application and social media content screening would be a value addition to Pharmacovigilance as output of these activities would impact policy recommendations.

·         WEB-RADR, Work Packages (url: )
·         EPIDEMICO (url: )

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Monday, 2 April 2018

MHRA’s Black Triangle Report

In United Kingdom, there are certain drugs in which although they were granted marketing approval by the Medicines and healthcare product regulatory agency (MHRA), they need to be closely monitored, since limited information were available about these drugs.

One of the key reasons attributed to this may be, less subjects being enrolled in the clinical trials, short therapy duration etc.…thus, in order to identify rare adverse reactions, effect of the drug in different populations or effect of the drug under different co-morbidities, such drugs are tagged with an inverted black triangle () on their package insert, to ensure that these drugs are intensively monitored.

The Commission on Human Medicines (CHM) and MHRA encourages expedited reporting within 15 calendar days of all such drugs with an inverted black triangle symbol if, found to have caused serious or non-serious adverse drug reaction.

You may find the black triangle drugs at the Electronic Medicines Compendium, British National Formulary, Nurse Prescribers’ Formulary etc.… A black triangle symbol may be assigned to any new active drug / vaccine or even a Biosimilar (Biosimilar are similar biological therapeutic products). Black triangle is not restricted to only drugs, it may also include new route of administration, new drug delivery systems or even new patient population.

Black triangle drugs are reviewed every 2 years by the MHRA and monitoring black triangles reports helps in identifying benefit risk profile of drug and unrecognized adverse effects.


·         List of medicines under additional monitoring, European Medical Agency (url: )
·         EMC ( )

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Thursday, 29 March 2018

European Medical Agency to increase fees upto 1.7 %

There would be an increase in fees upto 1.7 % from April 1st 2018 as mentioned in the notification of Commission Regulation (EU) No 2018/471 (amending Council Regulation (EC) No 297/95), the fees however would be implemented for all activities carried out by the agency except pharmacovigilance. Apart from Pharmacovigilance the agency has also exempted fees ofMicro Small or Medium Sized Enterprise, Orphan Medicinal Products, Medicinal Products for Paediatric Use, Advanced Therapy Medicinal Productsetc… Detailed information on has been provided on an explanatory note.

The agency every year revises its fees as per the statistical data from EUROSTAT (European Union’s statistical office), the current revision is made in accordance with the inflation rate for 2017.

1.       Explanatory note on general fees payable to the European Medicines Agency
2.       COMMISSION REGULATION (EU) 2018/471 of 21 March 2018
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Friday, 9 March 2018

Artificial Intelligence Seeing through the lens of Pharmacovigilance

Pharmacovigilance as we know is a science with a set of pre defined functions to collect, analyse, monitor adverse event reports in understanding the safety profile of drug.
The set pre defined functions would include case processing through data entry of adverse event forms into safety database, medical review, aggregate reporting, signal detection, risk evaluation and mitigation strategies.

With patients awareness and regulatory compliance we may have seen a surge of adverse event data over last few years , resulting in the urgent need for the application of automation. Pharmacovigilance is the only discipline where in which timelines and quality data are evaluated on a benchmark of 100 % and a compromise in these two parameters are considered to be a zero tolerance.
Automation of above pre defined function is possible through machine learning, which is an integral components of Artificial Intelligence.

What is Artificial Intelligence ?       
Artificial intelligence may be called as an ability of a computer system to perform task that require human intelligence such as cognition through visual acuity, voice recognition, language translation leading to decision execution of a certain function.
Machine learning is based on reinforced data, where in which when an algorithm is executed to accomplish a specific task.

If it accomplishes the algorithm ends and the entire procedure in auto stored in the program, which means next time one does not need to manually execute the program, it would be auto executed in order to accomplish the task, if presented with the exact same variables as that of the earlier scenario.
In the second case if the task is not accomplished then too the procedure would be stored in the program and next time when the program is auto executed it would not take the same path thus minimizing error.

This process self-learning through experience is called machine learning For example imagine a scenario where in which you have you have received an email from a patient who has experienced nausea, followed by headache and bleeding from nose on Lisinopril, the patient also mentions that he has a history renal impairment and also that he was a chain smoker for which he took Varenicline to quit smoking.

An algorithm created on the principle of machine learning would have the capability to auto recognises and identify the suspect drug from concomitant therapy, adverse event from medical history and not only this through robotic process automation it may integrate the email with safety database, which means not only it identifies the suspect drug and the adverse event, it now also does the auto data entry, prepares auto case narrative and auto sends letters to the patient or physician for further follow up  from the safety database.

This is ‘Artificial Intelligence’, a capability attained through self-learning to process thousands of data within seconds.With automation employees engaged in manual data entry would be upskilled in the execution of AI process.

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Thursday, 8 March 2018

PvPI to include vector borne disease as part Pharmacovigilance for Public health

Pharmacovigilance programme of India (PvPI), soon to include diseases caused in tropical climate, vector borne diseases like malaria and dengue, tuberculosis and HIV- AIDS as part the Pharmacovigilance for public health. The programme would be soon incorporated by all South East Asian Regulatory Network (SEARN) member countries.

When carrying out pharmacovigilance activities for the above targeted diseases, a common questionnaire has been developed by the  WHO for SEARN countries.

The PvPI would now have an added responsibility of updating adverse drug reaction database on Vigiflow based on the reports received from other SEARN centres.
This indeed shows a remarkable progress of our country- INDIA in translating pharmacovigilance for better patient safety.

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