At last month’s AI Summit, which took place in the U.K. during London’s Tech Week, Google, Indegene, and Microsoft came together in a joint panel moderated by Pfizer to discuss “How AI is transforming clinical and commercial operations in life sciences.”
The panel covered a number of Artificial Intelligence (AI) use cases for real world data (RWD) in commercial and patient empowerment, and for the optimization of clinical trial operations. Discussions also focused on present as well as future advances in the patient journey, inclusive of examples of preventive medicine that will likely shape the future state of medicine.
The innovations highlighted included the Moorfields Eye Hospital and DeepMind project where machine learning has been applied to 1 million anonymous eye scans to help identify early signs of eye conditions that humans might miss in the diagnosis process. DeepMind, acquired by Google in 2014, published the project in late 2018.
Considering that 98 percent of vision loss resulting from diabetes is preventable through early detection, and that in the U.K. alone, 2 million people live with vision loss, a more intelligent and reliable diagnostic solution needed to be discovered.
Microsoft highlighted its project with NHS Glasgow and Clyde where tracking of patient data from various sources, such as chronic obstructive pulmonary disease (COPD) symptom diaries, and activity monitors allow the NHS to predict flare-ups in order to help reduce patient intake at hospital emergency centers and treat patients with COPD in earlier stages of the disease.
Indegene’s AI use case focused on the R&D, clinical, and medical business sides of life sciences, looking at how AI can help biopharma companies reuse content by auto-creating and updating medical documents. The AI use case highlighted the incubation initiative with Pfizer, to create an integrated content model of interrelated clinical, regulatory, safety, and medical documents, leveraging Indegene’s Intelligent Content Platform to systematically and holistically determine what content or documents could be auto-generated and what content could be meaningfully reused.
“These types of efficiencies are critically important in generating high-quality clinical documents to support approval of our medicines, so that we can fulfill our purpose of bringing new breakthroughs that change patients’ lives more quickly than ever before,” says Dr. Sian Ratcliffe, head of medical writing at Pfizer, and the panel moderator at the AI Summit.