Despite use of big data for identification and investigation of medicine-adverse event associations that happen over a longer period of time which could be missed by spontaneous reporting, the international guidelines on sharing of big data analytics between countries with respect to pharmacovigilance is yet to be developed.

With an aim to facilitate international collaboration on use of big data in pharmacovigilance, the International Coalition of Medicines Regulatory Authorities’ (ICMRA) pharmacovigilance working group’s “big data” sub-group has released a policy paper examining the opportunities and challenges for big data and analytics, within the context of pharmacovigilance. Ministry of health and family welfare, government of India is also member of ICMRA.

The sub-group, including experts from the European Medicines Agency, Health Canada and the UK’s Medicines and Healthcare products Regulatory Agency (UK MHRA), has held a series of meetings to develop the policy paper and an inventory of big data initiatives in pharmacovigilance, both of which have been endorsed by ICMRA.

While each member acknowledged benefits of big data in post-market surveillance, a number of challenges were highlighted, particularly with the integration and utilization of big data into the current pharmacovigilance framework. The common challenges identified include: privacy & legal considerations for sharing of data between countries; building domestic and international partnerships to access data sources that are not held by the regulator; building internal capacity to leverage new data sources, including both IT infrastructure and the expertise to use it effectively; building infrastructure and common data models to support datasets and develop innovative methods to link together different data sources; resources required to develop, evaluate and use data may be substantial and will involve multi-disciplinary teams.

The members agreed to share experiences and knowledge in utilizing big data for regulatory purpose which would help them identify common challenges for regulatory harmonisation and collaboration on use of big data in pharmacovigilance.

The utilisation of big data in pharmacovigilance complements traditional spontaneous reporting systems, by allowing an epidemiological approach to determining the incidence of adverse events in the population. It has greater potential for the investigation of signals across different sub-populations and to control for confounders, said Krishna Bahadursingh MBBS, FRCS, MBA, LLB, head of corporate and product strategy, RxLogix.

Said Bahadursingh “There is no guidelines, technical standards, protocols for managing and analysing big data sets in pharmacovigilance across various regulatory jurisdictions of the world.”

He emphasised on critical need for establishment of international best practices for utilizing real-world data sources such as EHRs, EMRs and AHD together with traditional spontaneous reporting data.

Ensuring that aggregated data from available data sources are both consistent and comparable is an important  prerequisite. Critical evaluation of the impact of innovative data sources and techniques, and whether these should uniquely complement or replace existing approaches, or are redundant, adding little or no value to current pharmacovigilance practice, he said.

As of now a global platform capable of capturing large amounts of data from multiple sources and storing in a common data model does not currently exist. Various coding and standardisation in currently existing datasets would not allow immediate and systematic use of available ‘raw’ big data.

Big data refers to a collection of structured (spontaneous reporting, electronic health records (EHRs), electronic medical records (EMRs), administrative health data (AHD), registries), and unstructured data (social media like Twitter, Facebook, patient forums, clinical narratives within EMRs).

Spontaneous reporting systems are inalienable components of pharmacovigilance, but on their own can never offer a complete picture of patient safety information because the number of reports received cannot be used as a basis for determining the incidence of a reaction as neither the total number of reactions occurring in the population nor the number of patients exposed to a health product is known. In addition, the structured and unstructured data collected “often have limited patient information including medical histories, concomitant treatment(s), pre-existing conditions, time to onset, etc.” and there “is under-reporting of adverse reactions with both voluntary and mandatory surveillance systems, and reporting rates may vary widely for drugs as well as for jurisdictions.”