The global human toll of COVID-19’s – nearly 2.5 million deaths from 112 million cases as of late February – has devastated families and communities, strained health systems and left political and business leaders, as well as other decision makers, grasping for solutions around prevention, treatment and vaccination.
As much as any other sector, pharma has dramatically transformed itself in response to the pandemic upending expectations about how quickly certain treatments can be brought to market. The painstaking steps of developing drugs and vaccines – a process that typically takes 10 years – has shrunk to less than a year.
A key reason we in the U.S. have a number of viable COVID-19 vaccines, and three to four therapeutics, comes from the application of data agility, insights and artificial intelligence (AI). China had made the gene sequence of the virus available to key national health authorities within days, a process that would have taken months a decade ago. Computing power and AI uncovered vaccine and drug targets quickly, condensing from years to months the preclinical development of a human-trial-ready product.
In KPMG’s survey of 100 life sciences business leaders, we found agreement on AI’s capabilities to solve major industry problems, including pandemic-related challenges. As we continue to navigate the pandemic, 94 percent expressed confidence in AI’s ability to track COVID-19 cases. Additionally, life sciences business leaders are confident in AI’s ability help with vaccine development (90 percent) and vaccine distribution (90 percent).
In some ways, AI’s accelerating importance is only possible because of a change in mindset at drug makers, who have rapidly evolved their thinking – seeing AI as an opportunity to change their drug development value chains, improve efficiency and better engage patients. Our findings also indicate that in the next two years, life sciences business leaders are planning to focus their AI investments in discovering new revenue opportunities (46 percent) and reducing administrative costs (45 percent). Interestingly, our research found 81 percent of life sciences business leaders said they wished their business would more aggressively adopt AI technology. Behind all the benefits of AI, however, life sciences organizations still need data scientists, researchers and clinicians to put context around the data, interpreting it to make meaningful decisions – as well as digital technologists to connect the enterprise to these new capabilities. But challenges may still remain, as life sciences business leaders (73 percent) say their company struggles to select the best AI technologies. Additionally, 51 percent of life sciences business leaders indicate threats to security and privacy is the top ethical concern when it comes to AI technology.
The data that is gathered through the business not only should be treated as an asset but also as ‘connective tissue’ for collaborative decision making at speed. As we saw with the rapid development of COVID-19 vaccines and treatment, life sciences companies met society’s demands quickly for treatments and cures with unprecedented speed. The question now is whether they can use the same approach to meet other pressing medial needs.
To interview Justin Hoss, please contact Melanie Batley.
The KPMG study, Thriving in an AI World, is an evolution of a study KPMG originally released in early 2020. The findings are based on feedback from a range of 950 full-time business decision makers and/or IT decision makers* with at least a moderate amount of AI knowledge and at companies with over $1 billion in revenue**, across seven industries (150 respondents+ per industry): technology, financial services, industrial manufacturing, healthcare, life sciences, retail, and government. The online survey was fielded between January 3rd, 2021 and January 16th, 2021. The margin of error (MOE) for the total sample at the 95 percent confidence level is +/- 3.2 percentage points.
*Only government respondents included IT decision makers.
**Healthcare and life sciences respondents were from companies with over $100 million in revenue. +Healthcare and life sciences respondents only had 100 respondents per industry.