Future of pharmacovigilance in next 5 years?

Future of pharmacovigilance in next 5 years?

Pharmacovigilance is the process of monitoring and documenting drug development right from conception to implementation and beyond. As the name somewhat indicates the sphere of pharmacovigilance relates to data collection, analysis and prevention of adverse effects of drugs. It may be pertinent to note that despite best efforts adverse drug reactions (ADRs) are the cause of death of patients in some cases globally. The aim of pharmacovigilance is to ensure that these ADRs are prevented and limited to the absolute minimum in the best interests of patient wellbeing. To this effect pharmacovigilance analyses various aspects of drug safety and associate risk of ADRs by in-depth analysis right from phases 1 to 3 of clinical trials to ascertain whether drugs are safe or there could be risk of patient adverse reactions.

While pharmacovigilance as a process is not new, the methods generally employed for the same leave a lot of scope for improvement. Some of the methods are decades old and are still being employed despite a dire need for upgradation and development. The proof of this lies in the fact that there are still many cases of adverse drug reactions leading to patient hospitalization and even regrettable death, some of which could have been avoidable. All of these factors point to gaps and lapses in the process of pharmacovigilance that need to be tackled.

It is heartening to note that there have been many technological developments over the past few years that would aid in more scientific and accurate pharmacovigilance going forward. In the past the focus of pharmacovigilance has been on data collation and documentation rather than proper data analysis and prediction of ADRs. The use of latest analytics technologies and AI (Artificial Intelligence) hold a lot of promise in advancing pharmacovigilance. For instance AI can use data from various documentation formats be it rudimentary or non structured to more structured formats to arrive at inferences that are beneficial from the pharmacovigilance perspective. This can also be used in tandem with robotic process automation, automation of signal and validation the aim being more sophisticated data processing and accuracy in inferences leading to better drugs that have fewer chances of causing ADRs in patients.

Advances in pharmacovigilance also imply the use of pharmacovigilance techniques to more traditional forms of medicine so that these are compliant with global standards and protocols leading to greater drug safety. There are certain requirements in the EU for instance that need to be complied with while applying for drug usage approvals based on latest pharmacovigilance methods and processes. These are developments that are aimed towards making drug availability more broad based and not limited to just contemporary or new drugs. To this end governments around the globe are also evolving more advanced standards of pharmacovigilance to ensure that drug companies are compliant thereby mitigating drug related risks.

Effective pharmacovigilance methods mean development of more effective means of pharmacovigilance training in modes that are more sophisticated and evolved as compared to earlier. This is possible only through by updating pharmacovigilance methods and availing latest and most up to date pharmacovigilance course. This necessitates updated methods and data analysis modes that are in tune with the times and the latest technological developments in this arena. Such training also incorporates elements of artificial intelligence, big data and analytics that are an important and inalienable part of pharmacovigilance of the future. These courses are available both in online and offline modes, but need to be assessed properly for relevance before these are availed of.