LBA108 is a very important study. It looked at real world evidence to look at how inclusion criteria and exclusion criteria are needing to change. We exclude far too many patients from clinical trial participation and over the last twenty years we’ve seen the number of inclusion and exclusion criteria for enrolling into clinical trial grow rapidly. LBA108 shows us that it’s possible by modifying inclusion criteria that we can make clinical trials available to a larger percentage of the population but, of course, there are going to be risks.

As we allow more patients with worse renal function, patients who have brain metastases and other significant comorbidities into clinical trials we’re going to find that we’re enrolling a population that’s going to be slightly sicker. So when we do that we’re going to find that the rates of adverse events and serious adverse events are likely going to increase because we know that sicker patients have more adverse events. It’s going to be particularly important if the findings from LBA108 are instituted throughout the oncology community that we have some way of objectively stratifying patients according to illness. There are many ways of doing it – we can do it with comorbidity indexes we can do it with a global understanding of other illnesses but we can also do it using digital tools and technology that allow us to quantify performance status in ways that are objective, to better stratify the patient populations and really understand whether toxicities associated with new drugs being tested in clinical trials are reflections of the actual toxicity of the drug or whether they’re simply reflections of the comorbidities that the patients have. Teasing out the difference between drug-related and disease-related toxicities that occur on studies is going to need to be a major effort of the pharma industry over the next ten years.

We’ve instituted a clinical trial at USC, the Precision Performance Status study, where we’re looking at all of our patients enrolling in early stage clinical trials and using digital tools like 3D cameras as well as wearable devices in order to objectively quantify performance status.