TECHNOLOGY AND DATA MANAGEMENT N
ot only is the pharmaceutical industry starting to take notice of
companies have also started to future- proof their approaches in order to keep First, some background: one feature of the
ecosystem is the Thematic Scorecard, which evaluates companies on how equipped they are in a certain theme, such as AI, over the next two to three years. This is based on their AI activity and investment. Companies can garner a score between 1 and 5, with the score of 5 denoting a high AI commitment from the company. The score covers the use of AI for faster drug discovery and repurposing, enhanced clinical trial design, and smarter supply chains, among other uses. Of the pharma companies monitored, those with a score of 5 are AstraZeneca, Bayer, Bristol Myers Squibb, GSK, Johnson & Johnson (J&J), Novartis and Takeda Pharmaceutical. pharma companies investing in AI in clinical trials. One is AstraZeneca working with Singapore-based Oncoshot regarding the latter’s AI-driven patient-to-trial matching technology. ConcertAI, meanwhile, has several collaborations with big pharma, such as one announced in 2021 with Janssen aims to support trial designs, broaden new sites, and strengthen trial diversity. (J&J is the parent company of Janssen.)
AI in clinical trial patient matching While there has been increasing interest in AI in the pharma space, there are still untapped opportunities around using AI in clinical with name recognition, such as DeepMind
“There has been increasing interest in AI in pharma. One of the clearer uses is applying the tech to match patients to a clinical trial”
38 | Outsourcing in Clinical Trials Handbook
driven more by molecule optimisation, drug repurposing or drug discovery than by AI use in clinical development, says Lucas Glass, vice president of IQVIA’s Analytics Center of Excellence.
One of the clearer uses of AI in clinical trials is applying the technology to match patients to a clinical trial. Glass says there sites sifting through their patient database to match patients with a given trial. The second is patients themselves looking for clinical trials that are best suited to them. a relatively robust speed of development because the funding mechanisms in that space are clear, Glass explains. As for the second paradigm, in the US for
example,
ClinicalTrials.gov can help patients friendly, he says. A way to move the needle, he suggests, could be to have a bedside technology that alerts clinicians to patients of theirs who may be eligible for ongoing trials. Yet the development of such an approach impact clinicians’ daily workflows, he notes. “I imagine it as a bit more of a passive thing, so it’s not like slamming it in the doctor’s face, but an alert on the side [of the screen] they can click on and see and explore.” Clinicians are likely to engage as they are used to doing their due diligence to explore all possible therapeutic options for their patients, he adds.
Page 1 |
Page 2 |
Page 3 |
Page 4 |
Page 5 |
Page 6 |
Page 7 |
Page 8 |
Page 9 |
Page 10 |
Page 11 |
Page 12 |
Page 13 |
Page 14 |
Page 15 |
Page 16 |
Page 17 |
Page 18 |
Page 19 |
Page 20 |
Page 21 |
Page 22 |
Page 23 |
Page 24 |
Page 25 |
Page 26 |
Page 27 |
Page 28 |
Page 29 |
Page 30 |
Page 31 |
Page 32 |
Page 33 |
Page 34 |
Page 35 |
Page 36 |
Page 37 |
Page 38 |
Page 39 |
Page 40 |
Page 41 |
Page 42 |
Page 43 |
Page 44 |
Page 45 |
Page 46 |
Page 47 |
Page 48 |
Page 49 |
Page 50 |
Page 51 |
Page 52 |
Page 53 |
Page 54 |
Page 55 |
Page 56 |
Page 57 |
Page 58 |
Page 59 |
Page 60 |
Page 61 |
Page 62 |
Page 63 |
Page 64 |
Page 65 |
Page 66 |
Page 67 |
Page 68 |
Page 69 |
Page 70 |
Page 71 |
Page 72 |
Page 73 |
Page 74 |
Page 75 |
Page 76 |
Page 77 |
Page 78 |
Page 79 |
Page 80 |
Page 81 |
Page 82 |
Page 83 |
Page 84 |
Page 85 |
Page 86 |
Page 87 |
Page 88 |
Page 89 |
Page 90 |
Page 91 |
Page 92 |
Page 93 |
Page 94 |
Page 95 |
Page 96 |
Page 97 |
Page 98 |
Page 99 |
Page 100
