In this article we shall discuss about ORCATECH or a technical house for clinical research. It’s an R&D centre formed while combining with the neurology and biomedical engineering departments at Oregon Health and Science University.
Judith Kornfeld and her group developed a system for clinical research based on remote sensing and computing whereby data is collected without any obstruction and continuously. ORCATECH installs sensors in patient homes, rather than outfitting patients with wearable devices, to monitor patient activity.
Here is what Judith had to share with a leading magazine.
About ORCATECH’s technology.
ORCATECH technology was developed to allow the patient’s daily life be the source of data to measure health changes and meaningful outcomes in clinical research.
In essence, the approach to data collection in clinical trials has not changed since such trials were first conducted over 250 years ago, while medical technologies for treatment and drug development have advanced incredibly.
Moreover, this approach to clinical trials requires a smaller sample size per clinical trial by an order of magnitude, and the ability to detect change and response to therapy is much faster because of the density and the plurality of the data.
What are the types of data you’re collecting?
The main types of data are the movement around the house, walking speed, leaving and entering the house, sleep measurements, computer usage, balance, weight, medication, socialization and more.
This is an open platform and can use any sensor that collects data that is of interest to the questions asked in a clinical trial.
Is this dense data ?
Yes, because it’s consistent and usually collected 24/7.
There’s a potential for too much data, right? What are the data considerations then?
This is a very important question. There is never really “too much data,” it’s all about making sense of this gold mine. In a way, that’s the secret sauce of ORCATECH. It’s the algorithms developed here that take all this data and interpret it into essential clinical information.
These are digital biomarkers?
Exactly. These are digital biomarkers that can be obtained in a very accurate manner that reflect the patient’s parameters of real life. We measure what you want to improve. With medical treatments you want to improve patient’s lives. We are able to measure those parameters.
Digital biomarkers are a new concept. What are some of the considerations for adopting these within the pharma industry?
One has to think about compliance. If you’re wanna use a device, you need to consider how it’s actually being used, how accurate it is and how it reflects what you’re trying to measure?
Here emphasis is on multi-source data to get a real and true picture. It is also ensure before collection of the data how patients will interact with the sensors. Focus groups are conducted to see how patients might use it and how it relates to real life.
The whole idea is to collect something that is ecologically valid, and the patient is doing something in a manner they would do daily. It is important to not use a single device and follow one data stream that is isolated from fact.
Emphasis is being less dependent on patient compliance, such that data is whole and accurate. In our system, the only part we rely on subject compliance for is a weekly email questionnaire. This helps us get information that we could otherwise not get, and it puts the data we collect in context.
How there is drug development evolving with technology like this?
There are many compounds out there, but very few get approved. The clinical trial process is very costly, tenacious and not very efficient. Things have to be changed.
There is an effort to lower costs of healthcare, and therefore the cost of R&D for treatments must be reduced, both pharma and medical devices.
It’s not just a matter of using a device in a periodic manner without context. The whole design of the clinical research has to change.
What will trials look like if everything goes well?
They will get conducted very differently than now. The emphasis of the protocols would be to collect consistent and objective data, less reliant on sporadic and often inaccurate reporting of patient, or clinician’s periodic observations sometimes not correlated to real-life testing. The whole process will be more accurate and true, and that’s where hope is things will go.
New technology can actually reduce costs?
New technologies might reduce costs in several ways, but this need to be measured by the cost of technology, the cost of installation and the increased efficiency of the process.
But the real cost benefit happens in the long term, because less sample size and short clinical trials are where the costs savings will be most prominent.
Time in a clinical trial is very expensive, so if you can shorten the time to detect changes or reach an endpoint, you might reduce the cost effectively.
What are the concerns about this type of technology?
Security and privacy; though none of the data collected identifies a person. No cameras or facial recognition, and all the sensor data collected in the home is separated from the identity of the subject.
We conclude the discussion here. Hope you liked it and let us know what else could be the advantages of technology in the field of clinical research trials.
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