The proper use of medicines could save the US healthcare system $213 billion annually, according to Joseph Jimenez, CEO of Novartis, in an article for the World Economic Forum. He goes on to say that, based on research, US healthcare costs could be reduced by 25% if health systems and policy makers could stop treatments that aren't working.
Or maybe stop them in trials? Products with marketing approval are only part of the problem of course. Surely we need to start at the beginning? Let's focus on clinical trials. The 'gold standard' is being challenged, fundamentally at the level of data and how it is captured and when. But increasingly also on how decisions are made based on a changing relationship with that data.
Real World Evidence, or patient level data captured outside clinical control, is only one challenge to the RCT gold standard. The rise of Adaptive clinical trials is another sign that the drug industry is responding to cost pressures and looking at ways to improve on what was previously considered optimal.
Real World Evidence has already been demonstrating an impact on development costs, by identifying unmet needs or subpopulations responding well to therapeutics. But with increasing pressure to make more from less change needed to happen. When even relatively new therapeutic areas like IO are already hotly contested and with diminishing returns in saturated markets, we already knew the days of the blockbuster were behind us. The RCT model, well suited to the blockbuster and its immense financial returns, needed to evolve to a model more suited to speciality indications.
The Adaptive trial brings a new level of agility to the trial sequence, although the protocol must still be approved in advance. In the adaptive model, patient biometric data can be collected and utilized to make scheduled adjustments to the trial design. By capturing real-time patient data for analysis, treatment aims, dosage etc can be varied to telescope in on the patient group which respond to treatment, or treatments which have an optimal outcome for the patient group.
Like Real World Data and Evidence synthesis, Adaptive trials have advantages over the gold standard RCT model. Trial timelines can be shorter, and patient recruitment - a real pain point - is reduced.
Perhaps the biggest winner is the patient group. Treatments or doses which don't work can be dropped from the trial based on interim data. Patients are exposed to more effective treatments quickly, rather than having to wait until the end of a lengthy RCT.
Of course, having the right data in a format which is quickly understandable and sufficient to make decisions from has it's own challenges. Technology, people, cultural shift to adopt to an adaptive model and accepting that confidence based on interim results might have to trump certainty with more data.
Adaptive trials could make a big impact on costs, but it needs more adaptive thinking to make them happen. Say 25% more.
Written by Kevin A'Court - Head of Healthcare and Life Sciences Practice at Consulting Point