OBJECTIVES:This study is aimed at assessing applications of new technologies like Machine learning (ML), Natural Language Processing (NLP), Artificial intelligence (AI) and Blockchain for leveraging RWE.

METHODS: Literature review was conducted in PubMed, Embase, and grey literature using keywords: Real world data/ evidence, electronic health record, claims data, Natural Language Processing, Machine learning, Artificial intelligence and Blockchain. All articles in English were included without any timeline restrictions.

RESULTS: Literature review found 170 relevant references out of which 87 were included. NLP can automate data mining from unstructured electronic health records and claims for identification of patient and real‐time adverse events. ML algorithms can assess patterns in big data through predictive analytics to identify unmet needs, intervention risks and predict outcomes like mortality to aid personalized care for heart failure patients. Risk assessment models and deep learning. AI algorithms can identify predictors of hospital admission; predict events like diabetic retinopathy and adverse event cases from Real World Data (RWD). FDA plans to incorporates RWE in regulatory decisions and post market monitoring safety (via Sentinel project) to provide reliable, high-quality safety information to patients and providers faster. Implementation issues such as lack of interoperability still persist alongside privacy and trust concerns. Blockchain, a decentralized distributed ledger can enable secure streamlining, storing and sharing RWD among stakeholders. RWE driven smart contracts implemented by blockchain can facilitate risk sharing agreements among insurers, providers, patients, manufacturers among others.

CONCLUSIONS: It is still early days for widespread use of advanced analytics in the domain of RWE with pilots like FDA’s Sentinel initiative leading the way. Potentially AI along with Blockchain enabled RWE can predict and incentivize right health outcomes in health system while mitigating concerns of data security. Further research is needed to gather evidence regarding future applications of ML, NLP, AI and Blockchain in leveraging RWE.