DIA 2019: Genetics, big data, AI, and separating the hope from hype

By Melissa Fassbender

- Last updated on GMT

(Image: Getty/grapestock)
(Image: Getty/grapestock)

Related tags DIA AI Big data Artificial intelligence Wearables Clinical trials Drug development

New this year to the discussion at DIA is the conversation around data ownership, as the industry continues to face a deluge of information from more sources than ever.

Attendees at this year’s DIA Annual Meeting will join in on the “ongoing revolution”​ in health care. One that is being transformed by genetics, big data, artificial intelligence (AI) and myriad new innovations, said Sudip Parikh (SP​), senior vice president and managing director of DIA Americas.

Ahead of the conference, which takes place next week in San Diego, CA, Outsourcing-Pharma (OSP​) caught up with Parikh to discuss some of the key changes, challenges, and opportunities in the industry.

OSP: What are some of the new themes this year?

SP:​ Data is central to DIA2019 – It’s uses in drug development and regulation, ensuring its quality, and enabling analysis of it using artificial intelligence and machine learning. As important – and a topic we will cover in the very first DIAmond session – is who owns the data being used and should the people and patients giving that data receive any compensation for providing it.

The trends around AI and blockchain will be covered extensively—and set to address the potential impact of these technologies across health care. Aside from being a buzzworthy topic, AI is extremely powerful in providing better patient recruitment and better signal detection.

At DIA2019, we will work hard to drive the dialogue that separates the hope from the hype. One specific set of sessions will discuss a study DIA led looking at AI use throughout the drug development continuum​. The study identified the areas where AI is most mature and investment is being made. 

OSP: And how are these indicative of the evolving industry?

SP: ​We are facing a deluge of data – from electronic health records, claims data, fitness trackers, and other mobile technologies. Everyone – industry, regulators, patients – hopes these real world data hold the key to better and safer therapies getting in the hands of patients more quickly.

Many argue that AI may be the solution to the challenges of turning real world data into real world evidence for regulatory purposes—and for good reason, but it is not a panacea. We have to examine where these technologies might be valuable and where there are better solutions.

More than anything, AI is a sign that the industry is open to new ideas and disruption. One of the things that is evident at DIA2019 is that these technologies are drawing inspiration from the patient experience, which is fantastic.

OSP: What are some of the conversations that are continuing? And how have these discussions progressed from previous years?

SP: ​Patient engagement in the drug development and regulatory process remains a focus of the ecosystem and DIA2019 will cover this area from every perspective. Patients have been a key attendee group at DIA for almost twenty years. They’ve been integral to the content – leading and participating in panels and dialogs for almost as long.

From trial recruitment and retention to endpoint development and patient access – DIA2019 will drive conversations that enable the ecosystem to measure the right things to make patients’ lives better. 

Another reoccurring topic is how to turn real world data and evidence into regulatory approval data. The potential is extraordinary, but the challenges are many.

OSP: Since last year’s meeting, what has been one of the most significant changes in the industry?

SP: ​The conversation around data ownership. We have reached a place where legislation is being introduced and companies are interested in understanding how data ownership truly works. Pharmaceutical companies spend billions yearly on data.

The story of Henrietta Lacks must not be repeated in digital form.

Henrietta’s cells, known to scientists today as HeLa cells, became one of the most important tools in medicine, vital for developing the polio vaccine, cloning and gene mapping.

Only years later did her family learn that cells derived from her tissue was used in this way – and she nor they received benefit or recognition. Health care data may be the digital form of Henrietta’s tissue and a shift is happening in the perception of data ownership. We will see where it leads.

Read more: Taking a better path: Fair trade data ‘is better data … there’s no question about it’

The first DIAmond session at the conference will feature a conversation around health data ownership. Who owns health care data and who should benefit from its use to discover new – and valuable – therapies? Harlan Krumholz from Yale University, Doug Peddicord from the Association of Clinical Research Organizations, Deven McGraw from Ciitizen, and Donna Cryer from the People-Centered Research Foundation. Craig Lipset, who recently led Clinical Innovation at Pfizer, will moderate.

OSP: The challenges?

SP: ​Data is being used differently across a variety of industries – not just health care. This is driving a growing demand for data scientists. However, we are now finding ourselves with a shortage of people available to help interpret this data. In the future, we’ll need to rethink how we build teams amidst a shortage of data scientist.

The industry continues to be challenged by regulatory and operational barriers hindering value-based care. Tying payments to actual outcomes versus fee-for-service payments presents an opportunity to have health care providers offer the best care for the lowest cost.

Related news

Show more

Related products

show more

Saama accelerates data review processes

Saama accelerates data review processes

Content provided by Saama | 25-Mar-2024 | Infographic

In this new infographic, learn how Saama accelerates data review processes. Only Saama has AI/ML models trained for life sciences on over 300 million data...

More Data, More Insights, More Progress

More Data, More Insights, More Progress

Content provided by Saama | 04-Mar-2024 | Case Study

The sponsor’s clinical development team needed a flexible solution to quickly visualize patient and site data in a single location

Using Define-XML to build more efficient studies

Using Define-XML to build more efficient studies

Content provided by Formedix | 14-Nov-2023 | White Paper

It is commonly thought that Define-XML is simply a dataset descriptor: a way to document what datasets look like, including the names and labels of datasets...

Related suppliers

Follow us

Products

View more

Webinars