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Apr 3rd, 2023

DF mSafety AI Version 4.0 Released! Explore the new features. 

We are thrilled to announce a new release of DF mSafety AI, the most advanced […]

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Feb 8th, 2023

Safety Signal Management:  How AI is Driving the Future

The life sciences industry is constantly evolving and seeking new ways to improve the safety […]

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Jan 18th, 2023

Leveraging Data Digitalization Technology for Effective IDMP Compliance 

Understanding IDMP  IDMP, or Identification of Medicinal Products, is a set of five standards (ISO […]

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Dec 7th, 2022

Maximizing The Benefits Of Data Digitalization In Life Sciences

Digital transformation in life sciences organizations involves implementing new technology and digital systems to improve […]

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Sep 27th, 2022

Opportunities for Digitalization in Pharma & Life Sciences 

Digital technologies are rapidly changing the DNA of the life sciences & healthcare sectors leading […]

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Aug 17th, 2022

AI in Pharmacovigilance: Need, Opportunities and Challenges 

Pharmacovigilance is the practice of protecting public health by detecting, assessing, and managing potential adverse […]

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May 9th, 2022

Automation of Literature Monitoring for pharmacovigilance

Introduction:  The drug development process for hit-to-lead molecules relies inevitably on the knowledge of adequate […]

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Apr 5th, 2022

Use of Artificial Intelligence and Machine Learning for Safety Signal Management  

The Drug Safety and Clinical Data Quality Act is a U.S. law that is meant to provide the FDA with more authority to regulate and enforce drug safety for consumers, as well as monitor clinical trials. The Act was enacted in 2012 and is currently enforced under the FDA’s Center for Drug Evaluation and Research (CDER).

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Mar 3rd, 2022

The Changing Landscape of Pharmacovigilance Technologies

Modern technology solutions for Pharmacovigilance are required to solve the emerging needs in the area  […]

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Jan 31st, 2022

An integrated approach to pharmacovigilance

The pharmaceutical market is highly regulated, and any misstep can lead to product recall that […]

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Nov 18th, 2021

AI for Drug Safety Case Processing

The Drug Safety and Clinical Data Quality Act is a U.S. law that is meant to provide the FDA with more authority to regulate and enforce drug safety for consumers, as well as monitor clinical trials. The Act was enacted in 2012 and is currently enforced under the FDA’s Center for Drug Evaluation and Research (CDER).

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Nov 18th, 2021

AI-assisted Literature Monitoring and Review

It is estimated that top pharma companies and research institutions commission around 20 literature review projects each on an average per year. Regulatory agencies expecting a Literature Review section in key regulatory documents such as Safety Aggregate Reports, Clinical Evaluation Reports (CERs) for devices etc. Literature survey findings are used to strengthen the regulatory submissions for drugs, biologics and medical device authorizations. US FDA guidance requires literature surveys as sources of information on safety, efficacy and ‘other known uses’ information.

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Nov 18th, 2021

Understanding Literature Monitoring in Pharmacovigilance – The importance, challenges and role AI can play 

The term ‘literature monitoring’ refers to the process by which adverse events or new drug efficacy data are detected in published sources. Literature review can be defined as a systematic examination of different studies about a given subject to come up with an overview of the entire topic. Literature monitoring is important to ensure that the medical professionals are aware of the latest research findings. Pharmacovigilance specialists monitor medical literature for adverse events, side effects, and new drug effectiveness.

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