TriNetX: Using real-world data to improve clinical research 

Pfizer has announced that it will join the TriNetX network, which will offer access to clinical data from a diverse range of healthcare organisations.

TriNetx is a global health research hub that connects pharmaceutical companies, healthcare organisations and CROs to improve trial design, optimise patient recruitment, conduct research and potentially enable new treatments to reach the market faster.

Using TriNetX’s cloud-based platform, researchers can analyse patient populations and carry out ‘what-if’ analyses in real-time. Members are given summated views, but each data point in the TriNetX network is directly linked to healthcare organisations, which are able to identify patients. This enables researchers to set up virtual patient categorisation for potential recruitment into a clinical trial.

“Pfizer joined TriNetX to harness real world data for clinical trial optimisation, with the goal of accelerating our ability to bring new therapies to market,” explains Dr Mohanish Anand, Pfizer’s head of study optimisation. “Pfizer will use the real-time access to clinical, genomic and oncology data to design clinical trial protocols with greater efficiency.”

TriNetX will help Pfizer to find patients with rare diseases who can be difficult to track down by other means, and to identify sites with patients who meet inclusion and exclusion criteria.

“Our members are liberating data that is trapped within disparate databases all around the world and through our platform we’re able to provide researchers with access to rich, longitudinal and harmonized data,” says Gadi Lachman, CEO at TriNetX. “Pfizer has selected us as a digital partner to help in its strategic initiative to leverage real world data across its organisation, from drug development to outcomes and healthcare research.”

TriNetx made a keynote presentation at the International Society for Pharmacoeconomics and Outcomes Research (ISPOR) 2018 annual meeting, held this week in Maryland, US. The company was keen to herald RWD as an established method for evaluating safety and comparative effectiveness and also entered into a dialogue about other emerging methods.

“Our research shows that answers to very essential scientific questions can be found in real-world data, if you have the right data source, network and methods,” says Manfred Stapff, chief medical officer at TriNetX.

Increasingly, RWD is being relied upon by the pharma industry, but challenges and limitations can complicate its use. There may be inconsistencies and gaps in data depending on the methodologies and tools used to collect it. Variations in the quality of clinical practice across global regions and health systems may also make the data less statistically reliable than RCTs and more difficult to interpret and analyse.

“There’s a lot of mixed data available so companies must meet the challenge of how to access and utilise the right kind of information to get insights that are useful,” observes Bansal. “Many of the systems on the market right now do not have adequate tools to analyse RWD effectively.”

Issues around global data sharing are also key.

“There are a lot of additional local requirements,” he continues. “Take Germany and China for example – you cannot take patient data out of those countries, so how do they optimise their efforts based on containing it within those regions?”

The cost of maintaining RWD is also a factor, with many professional and patient groups reliant on government funding, including the UK’s National Health Service. Linked to this is the fundamental issue of the security and anonymity of data.

“We are talking about accessing the data of millions of patients, the EHR and diagnostic data of entire countries,” continues Bansal. “It is essential to make sure all concerned have the technology and expertise to protect that data and ensure there’s no security breach.”

So what does the future hold for RWD? Bansal predicts that in five to ten years’ time, RWD and RWE will have completely transformed the industry: “The potential is huge. We will have safer drugs because RWD tells us so much more about how drugs interact with patients in the real world, and the insurance companies like this approach of data-driven decision making for drug approval.”

It will also optimise drug discovery, he says: “Because you can find out and better predict what kind of compounds are working for patients in different environments and understand the related treatment outcome by using RWD. We will see a scenario where end-to-end reliability on data from clinical trials will decline and use of real-world data will go up. RWD and RWE will become essential for drug approval.”