Thanks. Pleasure to be here. So I'm going to talk a little bit about something you probably are not familiar with and perhaps don't expect to be hearing from the FDA. But this is about whether we can use clinical data to inform and identify the potential new value of existing HDTs. As a disclaimer, you know, this presentation reflects my views as a presenter and not necessarily the agency's. So CureID is a website and mobile app that was developed by FDA in collaboration with NCATS at NIH and was designed to capture treatment experiences of clinicians and patients for diseases where we just don't have good treatment options. The goal was for it to provide a tool for surveillance of efficacy data when repurposed drugs are used for areas of unmet need. And we have a number of therapeutic areas of interest but focus primarily on infectious diseases and in critical care illnesses in relation to that. But also expanding into rare diseases and special populations. So why is such a platform needed? The reality is that new drugs are not being developed for many infectious diseases or critical care illnesses where there may be a limited commercial incentive for researching existing drugs for other uses that might address a public health need but would not necessarily be profitable. Real-world data on drug repurposing, including host-directed therapies for infectious diseases and critical care conditions is also not captured systematically. And therefore, how and what we can learn from past experience is often limited by these facts. So Cure provides an opportunity for clinicians to have a mechanism to rapidly share their treatment experiences with the global clinical community. It collects the data in a manner that enables it to be immediately aggregated and systematically collected. And the platform can capture the use of HTT's for infectious diseases and other critical care illnesses, both through manual data entry but now increasingly through EHR automated extraction. And in partnership with SCCM, we're currently doing this for COVID and hope to now be applying it to sepsis and other conditions in the near future. Thank you. The types of data in Cure include clinician reports, patient reports, and clinical data extracted electronically from electronic health records. So the potential to use Cure for host-directed therapies is that all three sources of data could be used and have been used to collect real-world data on HTT repurposing in infectious diseases. And in particular, the COVID treatment data from electronic health records illuminates the opportunity to evaluate this clinical data for host-directed therapies and this could be done for other conditions in the future. I encourage everyone to download the mobile app. You just go to CureSpace ID in the app or Play Store. It's a freely accessible and open platform for data sharing. And, you know, clinicians can access all of this information. I'm going to skip through a couple of these things. Just as a note, so the sort of example of the case report form we historically collected included this type of information. And then through the expansion to automated EHR extraction, which was supported by HHS, we're able to really greatly expand the quantity of and to some extent quality of data collected to now include longitudinal information. For example, on vital signs and laboratory values, calculating comorbidity indexes, inclusion of social determinants, clinical complications, oxygen support, WHO ordinal scale scores and outcomes including death, discharge and dialysis. The way that the EHR data is collected is through leveraging the SCCM virus registry, which spanned out of the COVID pandemic and enables sites to participate by mapping their data into a common data model and then contributing it to the virus registry and ultimately to NCATS QID. And I just note this because all of this information, the large data set is made available for researchers through both SCCM and Edo at Oxford. So anyone who is interested in this information can have access to it through a research proposal and then also through the QID platform. So the objective of the QID initiative is to enable the clinical research and regulatory communities to identify signals of potentially safe and effective treatments, including HTT's from amongst the armamentarium of existing drugs approved by FDA and other stringent regulatory authorities. These signals, we hope, will enable generation of clinical hypotheses and may accelerate the identification and further development of effective treatments. This is not meant to be a substitute for large and adequate randomized controlled trials, but is meant to generate hypotheses that may help to expedite the process of studying and make the trials that we do more strategic. I also just want to note that there is a public-private partnership supporting this initiative that was convened by the Critical Path Institute in June of 2020. And they have been essential to establishing the EHR automated extraction effort, as well as trying to assess how this data could be used to inform ongoing and future platform trials. So I'll just skip through some of these. The highlights, I guess, are that we have currently 28 sites participating in the electronic health record extraction. Eight of those sites have now transferred their data to SCCM representing over 100,000 cases. And the data is slowly making its way through the process to get all the way to NCATS and QRID. But this represents an incredible opportunity for progress and the opportunity to expand to future areas beyond COVID as well, such as sepsis and hopefully meningitis. And as was obviously noted in many of the earlier examples, you know, we have history can tell us some things about the potential of host-directed therapies, looking at COVID data. Certainly the primary types of HGTs that were included in the QRID information are steroids and immunomodulators. And I think it's important, again, to emphasize that the value of this information is collection of real-world data and using that to inform adequate, large, and well-controlled RCTs. And the examples that we have of the recovery trial, as well as, you know, ACT-2, Covariate Barrier, and other trials demonstrate the potential to leverage this information going from case reports, you know, initially identifying things like tocilizumab as potentially interesting products to study to the large pragmatic trials that we have seen being a mechanism for really verifying and validating whether the treatments are effective or not. So in future, we hope to expand our EHR extraction work in collaboration with the SCCM Discovery Network, particularly on sepsis, ARDS, and others. We're developing a larger network of sites that have deployed the EHR extraction tool and may be interested in participating in future randomized controlled trials. And we're examining whether the EHR extraction tool that was developed could also be used to conduct randomized controlled trials itself by embedding those trials within clinical practice. Hopefully reducing the cost and burden of participating in trials to participating clinicians.

CureID

drug repurposing

real-world data

infectious diseases

clinical trials