The clinical trial of the future
Caution: A really long post, but worth reading.
The industry is approaching a new age of trials that are
streamlined, connected and more engaged with the patient – but only if pharma
can embrace the changes
With patent cliffs approach and development
costs reach record highs, pharma companies need to evolve their R&D efforts
to ensure the core of their business keeps pace with the changes. Many firms
are already looking at clinical trials in new ways, but as ever with R&D,
it's going to be a slow process.
"Clinical
trials are getting more complex and increasing amounts of data are being
collected," says Steve Cutler, chief operating officer of clinical research
organisation ICON. "We
need better approaches and we need to apply our current systems and technology
better in order to meet the challenges posed by this – such as increasing
numbers of patient subgroups, difficulties in finding those patients, and
trials in rare diseases and orphan drugs becoming more common."
Kevin Julian, managing director of Accenture –
who recently published a report on Digital's transformative power across
R&D – identifies three main technology categories that could change
clinical trials: cloud, analytics and mobile. "When we double-click on that, under 'cloud' there is more than hosting,
there's using tech as a means to seamlessly integrate and collaborate with
external partners, which we are finding is a significant trend in R&D,"
he says. "Under 'mobile', wearables
are the most obvious example, as well as smart devices and social media for
patient enrolment and investigator interactions."
The
digital patient
Of all these technologies, wearables elicit
the most excitement from the industry at the moment.
"Historically
in clinical trials, we have collected more or less subjective data through
diaries, paper, etc. or by getting patients to come into the clinic and do a
test," says Tarek Sherif, CEO of clinical trial software specialists
Medidata. "These
supposedly measure the efficacy of a treatment, but you are taking a snapshot
in time and you're asking someone to remember a particular day, so there are
many factors that come into it.
Now,
with patient instrumentation, you can get a very objective set of patient data
that is more encompassing of your real-world experience. If you're wearing a
Fitbit and you're taking a treatment that makes you less tired, you can see
what someone's mobility is like, you can see how many steps they took a day
before the trial and during it, you can see how someone sleeps. In the next five
years this field is going to expand rapidly. A lot of people are doing
electronic clinical trials but very few are doing wearable trials, even though
that's the fastest growing part of our business."
Cutler says that the biggest impact of
wearables is unlikely to be the kind of data being collected, but rather the
amount of data. "Typically you might
only collect data from a patient once or twice a month, but when you think
about wearables you can potentially collect that data from patients on a much
more frequent and regular basis. For some data, such as blood pressure or heart
rate, you can do even it continuously.
"We're
struggling a little bit with what to do with all that data. How much do we
need, and the impact on the number of patients required in a trial given the
amount of information you get from each one. We need to look at what we
collect, how we analyse it, what endpoints we should collect and whether the
additional data is worth the effort and expense. But wearables remain a huge
opportunity to more efficiently collect key data that can establish safety and
efficacy."
Wearables are just the tip of the iceberg,
though – digital technologies are changing almost every part of the clinical
trial process, including:
• Patient recruitment – "We can use digital technologies and
wearables to go directly to patients with opportunities for participating in
trials," says Cutler. "Five
percent of patients is probably the higher end of the range for participation
in trials. I'd like to see that get to 20 percent within my lifetime, and I
think we have the opportunity and the potential to get there."
Accenture's Julian adds: "Another
exciting development is the ability to bring specific patient profiles into the
recruitment process – not just connecting patients to trials that they might be
interested in but digitally prescreening patients for the inclusion-exclusion
criteria on a trial and learning early on if a patient is a candidate, or
perhaps in a particular population seeing whether there are even enough
patients that meet the criteria. It's better to know ahead of time than work it
out later by trial and error."
• Electronic health records – As
digitisation becomes the norm electronic health records are going to become
more and more important to the clinical trial process. "We're seeing opportunities to be where the
right patients are," says Cutler. ICON has partnered with IBM Watson
and the Electronic Health Records for Clinical Research (EHR4CR) project, among
others, to facilitate this. "Often
you go to 100 sites to do a trial and you might find that 20 percent of those
sites don't ever recruit. So there's already inefficiency there. As we have
greater access to the electronic medical records within those sites, we can see
if they really do have the right patients available for our trial."
• Cloud and collaboration – Julian
says he is seeing a trend of more academic and inter-company collaboration.
"Pre-competitive collaboration
consortiums like TransCelerate are something that they would not have dreamed
of doing a few years ago. Creating a single industry pool of data that other
companies can access would never have happened without digital technology,
particularly the cloud. There are several consortia looking to improve the
speed of collaborations by aggregating data from disparate sources to develop
research hypotheses, and we're getting a lot of favourable reaction to that."
Better
software
With this much digital data flying around,
it's important that clinical trial management and data analytics software keep
pace. If they do, Julian says they may even provide opportunities to remove
many of the inefficiencies that can plague R&D.
"With
better analytics we are going to be able to make much better decisions about
whether the product is performing the way the company wants it to earlier on in
the process," he says, "and perhaps make adjustments to the way the
trial is being conducted to react to those findings. Historically you would not
have known that until months after the trial was locked. It is a fundamentally
transformative potential."
Medidata's Sherif believes that making sure
these cloud-based platforms are automated, integrated and standardised will be
key – and that many current systems limit how complex clinical trials can get.
"The manual data protocols are very
brittle and error-prone," he says, "so having a platform where you can integrate it all very well brings
more efficiency and allows a more complicated trial to happen. Once you are
working in multiple geographies and have multiple arms to the trial, or even
multiple sponsors contributing their drugs to a trial, the logistics get out of
hand for traditional systems." He adds that some systems "can configure in days or weeks what some
organisations take three to five months to programme".
This also applies to the logistics of how
researchers manage monitoring reports, site payments and other more mundane
processes. "It isn't as sexy as how you manage the data itself," says
Sherif, "but the reality is that one of the biggest contributors to site
satisfaction is whether they get paid on time. When you're dealing with global
trials and the different tax situation in each geography, that gets very
complex and at the moment it's very manual, mostly being done on spreadsheets.
But if you automate it using one system, you know when a site has done
something and when to trigger a payment, and it happens automatically and
accurately."
Remote
trials
Remote clinical trials may be one way in
which many of these ideas come together in the near future. Technology and
consulting company eClinicalHealth recently experimented with this model in the
VERKKO
remote online phase IV clinical trial for diabetes.
The objectives of VERKKO, developed in
collaboration with Sanofi, Langland and Mendor, were to study the use of an
online clinical trial platform integrated with Mendor's 3G-enabled wireless
blood glucose meter in a completely remote setting.
Sixty patients – all recruited through
Facebook – participated in the study, which had no site visits. Patients
self-registered their interest in eClinicalHealth's cloud-based trial system
Clinpal, after which the coordinating study site reviewed their application.
Those selected reviewed patient information and signed the informed consent
form electronically. Study materials were delivered directly to patients who
then connected the smart, wireless glucose meter with their personal Clinpal
account.
"The
problem that diabetes companies have is that it's difficult to understand how
diabetes and its treatments behave in different populations," says
eClinicalHealth's patient-centric clinical trial solutions expert Kai Langel,
explaining the reasoning behind the trial. "To be able to measure that you need to look at lots of people in lots
of countries, which can become very expensive and cumbersome. However, if you
can do it remotely, it could be practicable to start trials in many countries,
make it easier for patients to take part, keep costs down and be able to do it
in a more efficient way.
"It
does not require any lab tests other than patients measuring their own blood
glucose at home. They were doing normal finger prick tests using a smart
glucose meter with a smartcard in it, which not only captures the data but
automatically sends it straight away. It also reminds the patient to do the
test at the right time, which was a really important part of improving
compliance."
To measure whether this model was actually
feasible and successful the company looked at a number of factors.
"We
wanted to know how much time patients would spend in order to take part in the
study," says Langel. "At the end, they completed a satisfaction
survey, which asked how much time they spent on the trial. We looked at how
happy they were with the materials they were provided, how they found using the
meter, and how satisfied they were with study participation – which had very
high ratings, 4.62 out of five.
"We also measured site efficiency, asking
them how much more efficient our trial was to a sister non-remote trial, and
they reported that ours was 66 percent more efficient, which means that our
trial only required one third of the effort that the other trial took.
"The
platform performed very well and we were able to track the patients throughout.
We were able to track how long it took from the first contact with the patient
to them becoming involved, how long it took them to complete their glucose
profile, and we could see where the bottlenecks were. Patients reported that
the platform helped them across the study. The lowest scores were about the
digital materials we provided – we basically took the informed consent
materials and converted them into electronic format but we didn't create any
videos or graphics, so they felt it wasn't very friendly, although it still got
good ratings and is easily improved.
"The
average age of those that completed the study was 59, so there were some
individuals who had some generic technology problems. For example, they had to
find the activation email and click a link, and we learned that the patient
didn't always click on the link as soon as they received the email and
sometimes it had expired by the time they did click it. We just had to send
another, but some of the participants were not used to doing email every
day."
Langel says that the trial has shown him that
this model can definitely have wider applications. "You can take these individual modules – such as online recruitment,
electronic informed consent, supporting patients remotely, offering patients a
dashboard that they can look at to see what's going on and what to do next –
and apply them to traditional trials to make them more patient-centric and
improve the data. Also, patient feedback after study participation is very easy
to implement, and we learned so much by doing this in our study that I really
hope more companies will implement that mechanism."
He adds that many companies have already
shown interest in trying out this model. "I hope more will because the technology is not an obstacle, the
regulatory acceptance is not an obstacle, so it's more to do with internal
change management within these companies in order to change the way they
think."
Pharma resistance
However, Cutler believes that mindset changes
within pharma companies may be slow to arrive. "There's an element of conservatism that always overlays innovation in a
clinical trial setting," he says. "Most of our customers are relatively conservative in the way they
approach new things. Their business model is working pretty well and there's an
element of 'if it ain't broke don't fix it'.
"When
I think about the future I also look back to the past. When I got into the
industry we were starting to talk about electronic data capture and it's
probably taken 15 to 20 years for that to become a standard part of trials.
We're dealing with human subjects, and there's always a requirement – and I
think it's an important requirement – to validate the systems and make sure
what you're doing is in place and proven before you roll it out.
Nevertheless, Cutler is still optimistic for
the future: "The pharma industry is
under significant pressure at the moment, so they do recognise that improving
and getting better is an important part of what they need. There are a number
of people who are very open to these changes and see the opportunity. There's
enough momentum in the industry to move this forward, albeit probably not at
the pace we'd like to see."
Accenture's report gives a more concrete
picture of how pharma is responding to new developments in clinical trials,
showing that 55 percent of companies surveyed had adopted digital as a key
strategy in R&D, and 42 percent were exploring it.
"I
would like to see a higher adoption rate but it seems like people are at least
on the journey, and it's a good start," says Julian. "Some of the things I would have expected to
rise high on the list of digital adoption examples such as wearables or social
media, are still relatively low adoption and low potential in the eyes of heads
of R&D. We are on a learning curve, identifying digital as a key driver of
the outcomes-based R&D approach that R&D executives are driving to, and
there are certainly opportunities for educating the industry on the greater
potential that's out there."
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