Today, thanks in part to the Covid-19 pandemic, the pharma industry is accelerating its artificial intelligence usage to speeds that could result in a quicker path to therapies for various diseases. In fact, a new report from GlobalData suggests AI will be the emerging technology that will “have the greatest impact on the pharmaceutical industry in 2021.”
Back in 2018, we wrote about the potential impact of artificial intelligence on the pharma industry. At the time, a survey released by the Pistoia Alliance suggested the widespread integration of AI technology had yet to be realized, with less than half (44%) of survey participants experimenting with AI-based solutions. The two primary limitations of the time were the lack of in-house expertise and lack of access to quality data to develop domain-specific AI solutions.
Connecting Data Sources to Improve Discoverability
In a recent article from The Guardian, Karen Taylor, director of the Centre for Health Solutions at accounting and consultancy group Deloitte, said Covid-19 vaccines and potential treatments were aided by AI, because “it allows you to cross-reference a lot of published literature with other data within seconds.”
In our white paper Data Integration and the R&D Organization, we discuss how data is the lifeline between R&D and breakthrough innovations.
This sounds simple enough, but people, processes, and technology often hinder data from being readily available and interoperable. AI technology is important, but algorithms won’t work effectively if the data isn’t there in the first place.
Information silos are common within pharma organizations, because each department typically collects its own needed set of data, using purpose-built systems. For instance, regulatory affairs teams organize published literature to support patent submissions and regulatory filings, while market intelligence teams collect materials like market research reports, competitive intel, and meeting notes. Meanwhile, pharmacovigilance and drug safety teams are monitoring literature, social media, and news reports for adverse events, and medical affairs teams are collaborating on materials that span the entire drug development lifecycle. While all this information is interconnected in one way or another, if content is housed in a set of disjointed, incompatible internal and external repositories, none of these departments have insight into the information they’re missing.
The result? Lost ROI and delayed discoveries. When employees must consult multiple sources to find all the data they need — it results in wasted time and money. More than 8 in 10 workers worldwide are forced to reacquire or recreate lost documents previously in their company’s possession, according to the 2019 Global Intelligent Information Management (IIM) Benchmark report.
Covid-19’s Impact on Artificial Intelligence
In the case of the Covid-19, wasting time to develop an effective vaccine would have had major implications effecting nearly every industry and aspect of life. Taylor says as a result, the pandemic acted as a “tipping point” for the widespread adoption of AI across the pharma industry.
Now, the world’s largest drug makers are committing to AI projects that have the potential to improve clinical trials, personalized medicine, and drug discovery. In the Guardian article, GSK’s Chief Scientific Officer Hal Barron says the use of AI technologies could “at least double the success rate [of developing new drugs] to 20 percent.”
The ROI of Better Data Integration
Integrating data can help free the flow of information and analytics across an organization. But this can be exacerbated by the fact that all this data can reside on a diverse array of private or public cloud-based and on-premise systems. Many organizations even store recent data separately from historical data, further complicating integration efforts. Sometimes data silos are years in the making, so it takes time and a solid strategy to deconstruct them.
But when the result could equate to billions of dollars saved on drug development, it’s a worthwhile investment.