Clinical supplies & logistics
Generative AI and machine learning can help pharma companies quickly abandon unproductive trials, thereby cutting losses while also avoiding wasted resources.
to improve how you decide when to ship the right amount of investigational drug and comparator to the correct clinical trials sites at the right time, so that drug is available for patients, but not sitting idle at a site that is not recruiting well.”
“A lot of these therapies are usually last-resort for patients – especially in cancer. And if we can get it to them, there’s hope to elongate their lives, which has a huge meaning behind it.”
Salman Shah
It goes without saying, meanwhile, that big data and the like can also ensure pharma conveners choose the most efficient (and ultimately the cheapest) supplier for the job, even as technology can lower trial costs in other ways too. From generative AI to machine learning, Shah explains that automation can help pharma companies “fail fast” – quickly abandoning trials that aren’t bringing results, cutting their losses and not ploughing resources into pointless ventures. Considering the median start-up time for oncology trials is 33 weeks, that’s sure to make the accountants happy, particularly when AI can also pinpoint exactly the sort of subject conveners should recruit.
Tech trouble $1.3bn
The predicted size of the global comparator drug sourcing market by 2031.
Growth Market Reports 24
All the same, technology probably isn’t a panacea. Think about it like this: if ones-and-zeros can quickly tell pharma staff who to approach, there’s no guarantee that subjects will actually agree to undergo tests. With that in mind, no wonder some industry experts are pushing to pay people better, especially when remuneration remains so inconsistent. That’s echoed by other common sense tactics, for example, liaising with several comparator suppliers at once, ensuring that there’ll always be drugs to spare if the vagaries of global supply chains cause problems elsewhere.
And if that makes sense from a statistical perspective – industry wisdom suggests that companies should aim for ‘overage’ of 40–50% – Shah speaks to the broader benefits of keeping different parties happy. “I think,” he says, “we need – as a continuum of the entities, or the players, or the stakeholders involved – to have better relationships between them, which will allow us to be much faster and improve that trust process.” Fair enough: with 58% of pharma suppliers lacking proper visibility into their supply chains, there’s clearly room to bring people round the table. Not that relationship management is the only potential stumbling block here. Let’s return, to give one example, to the question of technology. It obviously has a lot to offer financially – but digitalisation inevitably dovetails with privacy worries too. “There is still a lot of concern around data privacy and security around use of patient data in clinical research,” Anderson says, noting that patients may not be willing to share their information. From there, the Deloitte expert continues, is the need to abide by privacy rules, no easy task when regulations vary across borders and the trials are under way in literally hundreds of countries. Once again, that arguably hints at the human aspect of clinical trials, with conveners under increasing pressure to reassure patients that their data will be used ethically. There’s rising evidence, in fact, that some of the world’s biggest pharma companies are moving in just that direction. At J&J, for instance, staff explicitly commit to ensuring data integrity, while Pfizer emphasises it’ll return trial data to patients a year after the trial ends. Between that and the digital wizardry, Anderson is optimistic about getting costs down over the years ahead – at least once the technology fully matures. Especially as more conveners pull data directly from medical records of patients, Anderson adds the underlying costs could decline “significantly” in future. Given how important keeping prices down is to patients and pharma firms alike, you have to hope she’s right. ●
Clinical Trials Insight /
www.worldpharmaceuticals.net
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