The RxView Blog

Written by Wassim Aldairy, Head of Pharmacovigilance and Clinical Safety @ Cerevel Therapeutics

When implementing a pharmacovigilance system at Cerevel it was very important to us to document and track all actions related to drug safety. As a clinical stage company, those requirements included tracking signals from non-clinical sources, any safety related clinical datasets such as vital signs, lab values, and safety scales, and of course traditional clinical sources such adverse event data.

We've heard a lot about the 'new normal' lately.  The world we knew at the beginning of 2020 is very different from the world that we are now cautiously reopening. Here in Massachusetts, the final phase of reopening is even called "The New Normal".

Everyone I speak to has an opinion on how we should deal with this new normal.

I have trouble just dealing with it: 

On April 7th, Advera Health Analytics moderated a roundtable discussion with drug safety industry experts to discuss the challenges in pharmacovigilance caused by the COVID-19 crisis.

July 11, 2029 Wednesday - 9:01 AM. The Tech-Com Human Resistance succeeds in destroying Skynet's defensive grid located in Colorado, USA. The Skynet mainframe is breached by Resistance soldiers, and Skynet is deactivated, finally ending the War of the Machines and returning domain of planet Earth to humankind.

Perhaps, because I grew up on Terminator movies, the year 2020 feels like the future to me. It was 2029 when Skynet collapsed and here we are only nine short years away! Using Terminator math, the case processing AI is already turning on the human pharmacovigilantes and throwing the world of drug safety into a fight for its very existence!

Luckily for all of us, the War of the PV Machines is the stuff of science fiction.  However, the conflict, or more specifically the friction that exists within pharmacovigilance is at the top of our minds here at Advera Health.

#5: How to Replicate a Clinical Meta-Analysis Study in Evidex

Overview: 

Traditionally, safety related meta-analyses have been costly, taken significant time to produce and can often miss relevant studies. Further, there has been no efficient way to test the outcome of those studies prior to initiation. This has led to a lot of unnecessarily wasted resources. 

Luckily, Advera Health with the help of machine learning, artificial intelligence, and data science is solving this problem for drug safety, epidemiology, and medical affairs departments of all sizes. 

Thanks to everyone on the great feedback we have received on this blog series focused on pharmacovigilance best practices for clinical and early post-approval biopharma companies. We've discussed discussed the importance of understanding reporting and submission to FDA, taking control of your pharmacovigilance software and creating a shared services model with your CRO.

Last week's blog post discussed the importance of taking control of your pharmacovigilance software. This week we discuss Best Practice #3: Using software to create a shared services model with your CRO.

Last week's blog post discussed the importance of understanding what adverse events are reportable to FDA and how they are submitted. This week we discuss Best Practice #2: Take control of your software. 

Last week's blog post introduced our new pharmacovigilance "best practices" series that we have put forward for clinical and early stage biopharma companies. This week we discuss Best Practice #1: Understand what is reportable and know how reports are submitted to FDA. 

The idea of selecting, implementing, and deploying pharmacovigilance software is overwhelming for smaller companies. At larger pharma companies, teams of people, vendors, and consultants are dedicated to  implement the software and keep it running. Smaller clinical and early post-approval stage biopharma companies have to make do with significantly fewer resources and they are understandably quick to look for outside help.