For me, an important aspect of the presentation was the successful implementation of Health 2.0 strategies. This is an area that I’m seeing more discussion and development in and am keen to see its applications expanding the future. The increasing movement of patients interacting with the internet is leading to higher volumes of e-patients (empowered patients) becoming more able to apply information to enhance self-management and illness understanding.

Whilst remote trials such as the one Dr Orri presented are giving us new e-trial methodologies, it also shows us how IT developments can truly benefit patients and scientific aims. Currently we have lots of disparate information sources on the net which are poorly co-ordinated.  Now is the time to truly embrace Health 2.0 so we can enhance the application of professional uses of social media channels for the benefit of better informed and managed patients.

We should be aiming to get to a place where patients can use modern technology easily to better understand and self-manage their illnesses. A place where they and can find clinical trials to potentially participate in and in turn give better real-life information on how illnesses are being treated. By using the net as a strong and safe platform for patient empowerment, knowledge and communication, then significant eHealth strides will have been made.

There’s still a long way to go with this, particularly with regulation and security of personal data over the net, but we’re now moving in the right direction and I’m feeling positive about the road ahead.

And yet…. it was fantastic.

The atmosphere was like a carnival, with music, laughter and all types of group events along the way in the 80 pubs we passed and on the countless corners we negotiated. I can’t remember a day full of such positive happy vibes in all my 49 (and three quarters) years.

The day started early after a poor sleep in a noisy hotel in Holborn and got worse with the dreaded tube but when we finally got to Greenwich Park the frustration of the journey melted away leaving just plain nerves and a series of logistical problems – when to use the loo, when to strip off our warm clothes and pack them on the lorry, ready to meet us at the finish, when to drink, when to eat, when to go to the start …..

Then we just …got going – it was incredibly well organised and ultra efficient. Within moments we found ourselves in the queue waiting to start with a manic DJ screaming out excited messages at full pelt for about 45 minutes, 22 minutes waiting to start and 23 minutes walking up to the actual start line – then at 10.08 we were off!

The kids had all joined us the evening before and had arranged to cheer us on at Tower Bridge, just before the half way mark, and again at the other side of the Bridge for when we next went past at 23 miles. We went with the flow, averaging about a 10 minute mile for the first half, shouted and cheered on by name (we had carefully ironed our name transfers onto our vests in preparation for just this form of encouragement) by an endless stream of supporters by the side of the route. They were happy (it was between 10.30 and 12.00 and most had a drink in their hand – clearly not the first of the day by the time we ran past), it was sunny and we all jigged along to the music and drums played by the side of the road. Amazingly we spotted our own kids and managed to soak them a bit with our water bottles, then ran on (it was a race after all, no time for idle chatter).

Once past the halfway mark I started to tire – we slowed to around 11-12 minute miles and the aches and pains started to settle in for the long haul. By 15 miles we were thinking about walking a bit but managed to keep going to the 18 mile marker – our longest distance without a walk ever. This left a third of the distance to go, but fatigue was starting to bite. We stopped, stretched, ate more of the gel packs and drank more of the energy drink, but we (of course) continued to slow down.

Our training over the last 6 or 7 months had taken us through 7 runs at half marathon length or longer, 3 at 18 to 19 miles long, which we had generally run in about 3 hours, but as I went past these distances on the day we were slower (the crowds of runners make faster running unlikely when you are at the back) and in more pain. By the time we got back to the kids at 23 miles I was in my own universe – watching Elaine to make sure we were together and thinking about my quads, which were burning up and starting to spasm – stopping was agony as they immediately seized up, but things improved when I then stretched them out.

Elaine was brilliant, talking me in for the last 3 miles to keep my mind off my legs! The supporters were not shouting loudly enough any more, the music was gone, the sun had gone behind the clouds and I was VERY grumpy! Seeing Big Ben helped, and then the 800m marker on Birdcage Walk meant we were almost there – but we only had 8 minutes left to beat 5 hours – by now I was probably doing a 16 minute mile – and so there was no let up.

At the 26 mile marker we had 385 yards to go and finally I felt it was really almost over. Elaine lifted her arms all the way down the final stretch, but I could not even do that. She (deservedly) crossed the line 4 seconds in front of me and we hugged and hobbled into the finishing process to surrender our time tags and pick up our goody bags.

When I got the medal I really felt I deserved it!

After that the day blurred into wandering around in the rain trying to find the kids, the tube to the car, eating half a pizza (sorting out the car window which had been smashed so some thug could steal my ancient computer and credit cards!), driving home and getting in a bath.

It’s been a bit of a blur since as well, but I am now recovered, getting back into the swing of family life and work and planning the next one. Already signed up with the kids into a half in Birmingham in October ……….

When the going gets tough…

An interesting set of publications on trial workload throw some light on the matter. If you measure trial workload by the number of assessments the staff have to undertake, a recent report shows that  between 2000 and 2003 the workload was on average 28.9 units (defined as tasks in the protocol for the site staff or patient), whereas between 2004 and 2007 this increased to 44.6 units. It also showed that the annual workload had not increased that much, implying the extra work is due to prolongation of therapy periods. This is a growth of 54%.

Another analysis of complexity – using a complex algorithm assessing visits, types of efficacy and safety assessments and amount of data collected – demonstrate a growth in complexity of trials between 2007 and 2009 of 11%.

On top of this of course, the MRN data shows that resources are low in almost half of all sites we use (see last blog).

Finally we can see early signs of a reversal in the steady year on year reduction in patient numbers per NDA from 2001 (5,144 patients per NDA) to 2008 (2,175 patients per NDA), which climbed in 2009 to 3,714 patients per NDA, back to 2004 levels.

The overall conclusion is hard to escape. Trials are getting more complex, longer and more arduous for the site staff and need more patients. Meanwhile sites are becoming poorly resourced and are dropping out of research at a prodigious rate. This is backed up by some overall FDA stats which show that between the periods of 2000-2003 and 2004-2007 recruitment on trials slowed by 21% and retention reduced by 30%. These numbers are ignored at our peril.

The tough get going….

So what do we do? Well, given that copying is the sincerest form of flattery, we could take a leaf out of the books of the top 10 pharma companies (in terms of R&D speed) who report a concerted effort to:

- Reduce protocol complexity

- Introduce innovative recruitment and retention methodologies

- Improve site management.

Protocol complexity is a viable target as reports show that 15% to 30% of trial data is unused in analysis. This is estimated to cost $20 to $35 million per drug to collect. Regulators need to think twice about asking for longer and longer therapy periods and harder to conduct efficacy assessments. In fact the top 10 companies are already estimated (by Tufts) to be saving $30 million per drug compared to those lower down the league table, and to be able to earn $1.1 billion more revenue per product. This is because they are investing in new techniques and ideas as well as analysing exactly what they do to see if it is worth doing!

Needless to say we at the MRN will want to encourage the use of innovative recruitment and retention techniques. The use of Home Trial Support and Site Support is targeted directly at these issues, recruiting faster and allowing reduced costs and increased revenue overall.

Virtual studies and patient access not fettered by gate-keepers in sites are also a positive step to reducing these issues, allowing us to run studies with far fewer unproductive sites and unnecessary costs (see blog of Nov 15th 2011).

There is a lot to play for. Although drug costs are now estimated at $1 billion to get a drug to market, this includes the costs of all those who don’t make it. Tufts estimates this to be 75% of the costs, implying the actual cost of a drug program is averaging at $250 million. If we can save $30 million (12%) from eliminating unused clinical data, $20 to $30 (8% to 12%) million from copying the top 10 R&D companies and eliminating the 33% of unproductive sites in trials (perhaps another 10% of costs?) we have the potential to reduce R&D costs by a third.

A few risks to save that sort of money must be worth it – or will we keep making the same old safe mistakes?

How big is the problem?

MRN research shows that 33% of sites recruit one patient or less and indicators tell us this is getting worse. Some reports quote this figure as high as 50%.

Why is this? What is going on?

Reviewing published stats about trials we might conclude the cause is a continuing increase in the complexity and workload trials place on sites as well as the background bureaucracy that has always kept trials limited to a small percentage of interested investigators.

A second part of our survey uncovered the view that on average 47% of sites are inadequately resourced. Clearly the increasing complexity of trials is leaving sites chronically under-resourced and unable to recruit to their potential.

Some solutions may try to address the fundamental issues, fixing the problems; others may be to adjust to a new reality. TUFTS report that the top 10 phama companies (in terms of speed of R&D) are doing both – reducing protocol complexity, implementing new recruitment and retention strategies to help sites and improving site management.

MRN survey

Over the past nine months we asked over 80 people in the industry to answer two simple questions:

In your experience:

a) What is the percentage of sites who recruit one patient or less?

b) What percentage of sites in your trials are poorly resourced?

Answers were as follows:

To Question A

On average 33% of sites fail to recruit more than one patient. This is far worse than a site that recruits none, as the monitoring commitment kicks in and significant extra resources need to be spent to keep the site fully compliant.

To give a feel for the range, 70% of respondents reported a figure of at least 20%, and 30% reported a figure of greater than 40%.

To Question B

Respondents felt there were insufficient resources to meet their study commitments in 47% of sites.  Again to give a feel for the range, 88% of respondents felt at least 20% of sites were inadequately resourced, 58% thought more than 40% of sites were under-resourced, and 35% of respondents thought more than 60% of sites were under resourced. This is clearly a large problem.

I went out looking for related data published elsewhere, and whilst this is not scientifically rigorous, there is some interesting collateral data out there that supports and adds to the overall impression:

• 27% of US sites and 19% of Rest of World sites fail to recruit ANY patients – reported in the Parexel 2011 year book.

• 75% of sites fail to meet minimum recruitment targets.

• The issue is worst in the USA, which is now averaging 4.6 patients per site in a protocol against 7.1 elsewhere.

This is an expensive problem. Sites are variously reported as costing $25k to set up and $1,200 to $2,500 per month to maintain. Taking an ‘average’ study, say 30 sites, with 10 visits a year running for two years this adds up to a waste of $250k set up costs and $200k to $500k maintenance costs.  It contributes to the staggering 90% of trials who report extensions to deadlines, reducing the speed of R&D and therefore reducing revenue returned from the product once on the market.

Costs are exacerbated by a lack of many actually experienced investigators. In the USA (where we have published data) the FDA reports having 26,000 sites signed up to trials at any given time. They also have 14,000 new sites added per year, because a huge 85% are signed up for one trial only and 50% of signed up sites don’t sign up again.

Something has to change.  At this rate our ability to run clinical trials will become significantly compromised.  Trials in the east will take up the slack.  Market prep in the west will suffer.  The warning signs are easily visible and accelerating.

We need to innovate our way out of this problem – sooner rather than later.  If we don’t, ignoring the problem will just make it worse.

It was a very well-attended event thanks to our pre-dinner speaker, Professor Trevor Jones. He gave us so much food for thought on the challenges facing the clinical trials sector (not to mention the broader pharmaceutical world) that some of us struggled to digest the excellent meal that followed.

Professor Jones opened his speech (I’ll ignore the one liner he delivered with regards the recent rugby score) with his view on the conversations taking place within board rooms across the land: “is it gloom or doom we face?”

He continued on the theme highlighting the pressures/challenges the sector needs to conquer which he summarised as follows:

- As we know, the global markets are slowing down, and value-based drug pricing has now being implemented across the EU with the exception of the UK, which Professor Jones argued is a spiral of decline as driving down prices and the associated profits will only drive down the sums available within the industry for R&D.

- Blockbuster drug patent expiry last year alone equated to $10 billion dollars.

- He believed that, certainly within the biotech space, the “runway of cash” organisations hold will be no greater than a six month reserve, so the pressure is constantly on for the next round of investment.

- All of the above driving a market place of consolidation for survival.

The topic then turned to what was seen as the next big opportunity – China – which purely from a population headcount alone looks exciting. However in the Professor’s view, the Chinese are looking for price cuts and are looking to locally create more local generic drugs/products which he warned often aren’t as powerful a medicine as the brand names.

However Professor Jones didn’t just deliver a doom and gloom set of messages; he countered them with the following observations and advice for the audience to consider:

- Organisations need to really drill down and focus on their key areas of expertise and that they should avoid areas of diversification.

- Organisations need to look to outsource non-core competences.

- With the “days of the blockbusters” gone consideration needs to be given to lower revenue drugs/products which are often found in areas of specialism.

- Organisations need to rethink their approach to market; sales people are now being replaced by the marketing people as the key drivers of sales as consumers select products through marcomms.

- Within the marcomms space the growth of social media (Facebook, Twitter, YouTube etc) needs some strong consideration as it’s a powerful, cost effective tool to utilise but the freedom it gives the individuals within an organisation to voice opinion is potentially damaging to corporate reputation.

- With patients having 24/7 access to the web, perhaps the traditional route of visiting a doctor or pharmacist is becoming obsolete. This is due to the rise of online direct communication between patients, prescribers and drug providers all becoming a viable alternative.

- Partnerships and collaborative working methods to aid bringing better drugs/products to market faster is surely the way forward, Professor Jones suggested.

Like I said earlier, it’s food for thought indeed. I’d be delighted to hear your views in the comment section below.

Guest speaker at the event was Dr Miguel Orri from Pfizer who gave an informative presentation on Virtual Clinical Trials: Science Fiction or Reality highlighting Pfizer’s development of remote trials.

The presentation sparked debate about how close the industry is to carrying out widespread virtual trials and led inevitably to a discussion on the value of sites.

Virtual trials
With virtual clinical trials, patients can self-select online, be screened remotely and have their drugs shipped to them. Plus, they can complete ediaries – online or via a mobile app – to report their progress to the Principal Investigator.

This increased use of technology is bringing rise to the epatient and creating a new pharmaceutical industry term dubbed ‘health 2.0’. The internet and mobile phone technology is becoming available to an ever wider audience and users are becoming more savvy; searching online for health information has made them sophisticated social media users.

This is a much debated topic and opens up opportunities for sponsors to promote their trials and drive patient recruitment online. However there is still significant reticence about how it can be effectively incorporated into clinical trials, specifically the management of safety, the hard to define ‘opinion’ of the physician and of course we shouldn’t forget the overall benefit of human interaction. 

Although totally virtual trials raise these issues as it represents an extreme, there is clearly a place for all these approaches in most clinical trials when mixed in with the more traditional approaches. In a similar way to how Formula One cars pave the way for new motoring technology in every day cars, virtual trials are assessing the technology of future clinical trials which will be used in less ‘virtual’ and trial environments to great effect. All of these models promote the patient-centric trial, which has to be the way forward to encourage patients into trials, whether totally virtual or not.

Decentralised sites?
Why do patients in a clinical trial always have to see the same physician?  For most routine assessments, this would not be necessary. Clinical trials becoming part of the GP treatment paradigm would create an ideal patient-centric model; one that incorporates regular healthcare with support, the promotion of relevant clinical trials and management of the patients throughout the trial. It would speed up the recruitment process and reduce costs on the sponsor as it would be more targeted.

Alternatively, one could imagine a patient being seen by a specific expert occasionally through a trial and then by a local specialist physician or a nurse for others. If they were a long distance from the specific expert this would significantly reduce the impact of the trial not the patient’s life, making them more likely to consent to participate.

What’s next?
As clinical trials become more intelligent we could see innovations in the methods assessment. We already have smart phones that take diagnostic pictures of patients, measure sleep patterns, assess diet, take a pulse and more. Couple that with tablets that provide feedback when they have been swallowed and devices that transmit biological data from within the patient and you have a lot more assessments made with much less physician time.

The conduct of virtual trials is an innovative idea and there is no doubt it would open up clinical trials to a much wider audience, and reduce costs; something that is an issue for even the biggest pharma companies over recent years.

So maybe virtual trials are the way forward – at least occasionally? Certainly the balance of technological intervention to speed up the process and reduce cost, together with the human interaction providing the support and reassurance seems to be an excellent mix, and may represent the happy medium between the current approach and a fully-health 2.0 model?

Given that the editorial’s main conclusions are actually completely unsupported by the papers, such a claim cannot be left unchallenged as it could lead to astronomical costs and be a retrograde step for science.

The BMJ has been in the vanguard of a campaign to force publication in journals of all trial data, and the editorial uses the data in the papers to promote this agenda. On first read the editorial is unsettling, but when I looked at what the papers actually say and how the conclusions are drawn, I was forced to conclude otherwise. The science in the papers is simply descriptive, with no assessment of impact of their findings, yet the editorial builds an assessment of their impact which it claims they support but which is in fact unfounded and untested. So called ‘opinion pieces’ can do this, but editorials are meant to be more discerning, balanced and objective, which makes this piece misleading.

So how can I justify this position? Firstly, five of the articles focus solely on metrics not interpretation, three just measure how much data is missing and how long it takes for publication of results, whilst the remaining two deal with the number of published papers that fail to recognise publication bias of publication bias in meta-analysis and the numb of articles missed in mata-analysis papers due to poor indexing of trial publications in Medline.  The final article assesses the quality of journal publications and registry reports compared to study reports sent to government regulatory agencies.  From them we can conclude:

1. Meta-analysees ‘summary estimates’ change when previously unpublished data is added.  Efficacy increases in 46%, decreases in 46% and remains the same in the remainder. Sadly the way this was done tells us nothing about how important those changes were, as even a 1% change was counted either as an increase or decrease in efficacy (safety data was not examined).  All we can actually conclude then is that, since the number which increased and decreased in efficacy was the same, there is no evidence of a slight of hand by the industry concealing data it does not want published.  The most worrying data is the range of impact, from 1% to 56% decrease in efficacy and from 2% to 166% increase in efficacy.  There are nine drugs and 24 meta-analysees involved, so we don’t know the overall effect on any one drug, whether for the same drug some go up and some go down, whether the overall impact would change the labelling or treatment algorithms in common use today.  In short, no knowledge is added, only a few numbers that I’m afraid are almost meaningless as shown.

2. Data is published slowly. Only 8% of NIH trials are published one year after the trial finishes, climbing to 68% over 80 months.  Looking at all sponsors, the one year figure rises to 22% with the industry doing the best at 40%.  No longer term data is available, so we do not know what percentage the industry achieves after that.  The only conclusion we can draw is that academic trials sponsored by the NIH publish slowly and 32% of them never publish.  We have no idea how the industry performs except that at one year, which is fast in publication of final results; they outperform academics by a factor of five.

3. Meta-analysis studies fail to recognise publication bias and fail to find many trials that are published, as they are not looking at those not indexed as randomized controlled clinical trials in medline. These are purely methodological studies. Interestingly they are not actually about unpublished data, but about data that is missed by the academics doing the research.

4. The best quality of science is found in study reports, not publications or registry reports.  Not much to conclude from this except it is supportive of the regulatory process and validates the way the science done by the industry and how the regulators control it.  It also makes the drive to publish everything in journals seem a retrograde quality step.

The editorial is breath taking in its ability to leap to conclusions from studies that do not support them in any way. In short, it implies that regulators are doing a poor job in ensuring data is published, claiming most doctors would be shocked to see the regulators were allowing this to happen, that the industry is still to blame for the lack of data and that patients are being harmed and health resources misapplied on the basis of poor data. Not one of these assertions is even addressed in the papers in the journal.  In fact safety data is explicitly NOT included in the mata-analysis report, and is of course managed through the pharmacovigilence system, which is vastly wider than scanning publications and is not even mentioned in the papers or editorial.  As for health resources, no consideration is even made of how resources are allocated by any of the papers.

The whole editorial rests on the fact that the authors believe unpublished data will lead to these things – there is not one shred of evidence to support it in the actual papers themselves.  This belief is itself worthy of examination, as it leads to the conclusion of the editorial – a call for a comprehensive database of ALL patient data with ALL protocols and ALL publications for anyone to investigate as they see fit. This in turn is based on their repeatedly stated position that data sets must be ‘complete’ to be valuable. This flies in the face of post-modern science philosophy and is at odds with the whole basic premise of the science we practice.  Why?  Because it assumes two of the bedrocks of modern biological science are wrong, the use of sampling (rather than completeness) and the use of controls in experiments (which is weak or missing in mata-analysees).

1. SAMPLING. Our science is based on making probabilistic conclusions on the basis of samples that reflect the whole overall population. The concept of a complete data set is and should be irrelevant, not to mention impossible. Not only can we never know about all data that is not available but exists, but a data set complete at one moment will be incomplete the next as new data is created. The important thing here is NOT completeness, but representativeness of the samples taken to answer a specific question in an experiment.  These studies had no question to asses except ‘how many?’

2. Controls allow direct comparison of groups within a study with different therapies because we can assume all groups are treated the same, and therefore the unknown variables should not affect the results. The editorial is implying that in fact Meta-analysees are the best way of adding to knowledge. This is manifestly not the case as they are poorly controlled, making them very hard to interpret with any accuracy.  They cannot claim to have all groups treated the same and secondly because the patient groups are by definition different (if we ruled out all the ones that were different we would be back to a small number of exactly the same studies – ie back to sampling).

For this reason the editorial claims we need an “everything database”, but in fact this would be a huge retrograde step as we can see that it  will never be complete anyway, will be constantly used for relatively poor analytical techniques such as meta analyses and would cost an astronomical amount of time and money. It is in fact the last thing we ought to do.

“Fredrick, the time has come,” his doctor told him last week, “to consider a new approach.  We have identified a promising new drug that could help you, it’s currently in clinical trials and we think you should consider taking part.” “Crickey!” Fred thought; this was a bit of a shock! 

After accepting the seriousness of his situation, he decided to give it a go. He wanted to get the best therapy and knew that because his family were overweight they might benefit too. However, Christmas was a particularly busy time of year for him in the office and if he participated in the trial he would have to be seen by a nurse every few days for his infusion. “Well” said his doctors, “we have a home-based service for this trial if you would like it?  A nurse can come and see you at home or at work to give the infusion.” “Really?” He said “Well that is brilliant, I’ll do it!”

Janice was at home.  It was Christmas in a couple of days but instead of getting ready for the festivities she was still working on her trials. She really cared about her patients and this great new idea of seeing patients in trials at home was proving really popular with them.  She picked up the phone to arrange her next visits. She called Frederick first as he was a nice old duck and needed to see her every few days for his trial, including tomorrow, Christmas Eve.  “Where are you going to be tomorrow?” she asked, “At home with the family?”  There was a short pause and then he replied, “Actually….I am at work.  I know it’s an inconvenience, but can you make a special trip here for me?  I am really busy at the moment?” Once Janice had ensured it was a safe enough environment to do the infusion, she agreed to come and asked for the address.  Frederick, sounding quite relieved, said he would send a parcel round that would have all the details in it.

Early the next day a courier appeared with a parcel for Janice.  He was a small thin man, bundled up tight with a big hat pulled down over his ears to keep out the biting cold. As he gave her the package he gave a big smile and told her not to open it until midnight.

Janice had forgotten all about the parcel until late that night. “Oh no!” she flew into a brief panic, “I am not ready for Fred tomorrow!” She rushed to the package and tried to open it.  It resisted at first, but after a few minutes the parcel started to yield to her efforts, just as the clock started to chime for midnight.  Inside she found a box with Christmas decorations on it. As she opened the catch, out popped a Santa jack in the box carrying a card. It read

Dear Janice,

This may seem rather odd, but to get to where I work you need to follow some very precise instructions.  A small (probably cold) person will arrive shortly to pick you up and bring you to me.  Get all your stuff ready, as he will be with you soon.

Yours, Mr F. X. Mas
CEO, North Pole industries

At that moment, Janice began to hear some noises through the window – she could barely make out a jingling of bells, gradually becoming louder…. Curiously she opened the door to see the amazing sight of a large sled pulled by reindeer landing on her front lawn, driven by that same little man who delivered her package that morning.  He whipped of his hat, revealing pointy ears, and explained that he would take her to the North Pole to see Mr Mas, who was in fact Santa Claus. 

Bemused, but totally entranced with the scene, Janice found herself scooping up her things, wrapping up in a warm scarf, hat and gloves, and trotting out to the sled where the little driver sat blowing steam clouds into the cold air.

Off they went, shooting straight into the sky!  The view was amazing! Fantastic! Exhilarating! Far too quickly, they arrived.  “It’s all magic”, said the elf. “Santa can stop time as he has a lot to do in one day.” The elf led her to the top floor of a magical building, into a large “power office” with ‘Mr. F. X. Mas etched in gold on the door.  “Janice, welcome!” boomed Frederick from behind the desk, “just in time!”

As Janice worked, setting up Frederick for the infusion, the office was humming.  Large scrolls of good and bad children were examined, broken toy making machines were discussed and reindeer grievances were heard. Janice was mesmerised, but kept on with the infusion until it was all done. 

“Oh no!” Jane exclaimed. They had to get the blood samples to the hospital in Cricklewood!  “No problem” said Frederick, “delivering parcels is what we do!” A few minutes later an elf zoomed into the office with a large box, full of special north pole snow, into which the samples were placed to freeze them, and after all the documents were filled the box was whisked off into the back of the sleigh.  The next morning a lab tech in Cricklewood was rather bemused to see one of his sample boxes wrapped in fantastic Christmas paper!

Janice gathered up her things and asked how she was getting home.  “With me, of course!” cried Frederick. He took her back down to the sled, now loaded high with presents and off they went.  Janice had the time of her life, visiting all the children of the world, watching Frederick disappear down chimneys and returning with pockets stuffed full of mince pies. Then, far too soon, they were back at Cricklewood.  Santa let her down beside her house and thanked her deeply for putting herself out on Christmas Eve for a sick old man.  He handed her a beautiful box then climbed back into his sleigh.

Janice looked at the box in her hand and took out the card, which said:

Dear Janice. 

Thank you for taking the time to see me on Christmas Eve. This gift will always give you the time you need for your busy life.

Yours

Frederick Xavier Mas

Inside was a beautiful gold watch for her nursing uniform, with a note saying it never went wrong.  She pinned it to her uniform, and years later still wore it, as indeed it always told perfect time.

Why focus on patient motivators?
There seems to be fairly universal agreement that recruitment and retention of patients is a major – and often THE major – challenge to study timelines. Most of our solutions have focused on increasing patient numbers going into the top of the recruitment funnel, but these are looking increasingly expensive and still may not work if you don’t have the resources available downstream to handle the extra patient numbers – most of whom will not finally enter the study (see our Hierarchy of Need model elsewhere on the blog). 

Focusing on patient motivators works further down the recruitment funnel, converting those who don’t consent into those that do, thus making more of the patients already identified at great expense. For simple studies this can double recruitment rates, for complex studies the effect can be much greater.

What are patient motivators?
Our understanding of patient motivators is becoming more sophisticated as we gather real data rather than opinion. Since 2001 there have been a few (but only a few) surveys, from Centerwatch (2005, 2007, 2009), Harris (2001, 2004), Cutting Edge (2010) and a variety of scientific publications.  These all seem to show much the same thing:

• 75% of people cite altruism, those patients hoping to improve medical advances in order to help themselves and those whose loved ones may later suffer from the same condition, and access to better medicines for their condition as their key motivators.

• These reasons are closely followed by access to higher quality medical care (in around 50% of cases) and access to free medicines and financial reward (in around 35% of cases). 

• Recommendation from a physician or family member is reported around 10% of the time. 

Interestingly the Harris survey in 2004 also noted that simply knowledge and information about the trials existence had become a key reason for taking part, growing to 41% from 28% in the 2001 results.

• Let’s not forget demotivators. Recently I have seen more reports about concerns patients have with trials. Just as important as positive motivators, these negative factors drive patients to not take part or to drop out of trials once enrolled. 

The top concerns are the risk of side effects, risky or invasive procedures and non-flexible hours of visits. The next set of concerns, reported less often (no actual metrics in the source, so I can’t quote percentages etc) were the risk of getting the placebo, the lack of access to the site by public transport and the high number of visits. 

Reported elsewhere I have also seen concerns of distrust (being a guinea pig I assume) and lack of information about the study against which to make an informed decision. 

Once patients are enrolled the causes of drop-out are driven first and foremost by side effects; accounting for around a third of cases usually. The next commonest reasons were all lumped together being of roughly equal impact and were changing medical circumstances, ineffective treatment, personal issues and issues with site staff.

What can we do?
Once we filter out things we can’t do much about, such as side effects etc. we are left with some important but manageable issues to confront – predominantly those of study design, logistics and site operation.

Study logistics
• Cover costs
• Provide more information

Study design
• Reduce risky or invasive procedures
• Reduce number of visits

Site operation
• Increase flexibility of visit hours
• Ease of transport to sites
• Site staff training

Although we are mostly familiar with compensating patients for costs, this still only happened in around 50% of trials, excluding phase I.  Similarly we know staff training at site is important, but do we train them in the right things – such as treating patients correctly?  Otherwise most of our tools don’t address many of these issues at all.

Conclusion
We need to start considering patients as key participants in the trial. Perhaps “customer” is the wrong word, but they have many things in common with customers and will respond to being treated well; having efforts made to meet their requirements, motivating them to take part and remove the negative incentives.

It is time to start asking them what they want and putting their needs higher up our priority list.

Patients are fully in charge of their own medical care and are the final arbiters of whether they would like to participate in a clinical trial or not. Therefore, those who are cared for day-to-day by medical professionals, who are not interested in research, are disadvantaged. In such a situation both the patients sitting one side of the gate keeper and the study sponsors on the other side both want to take part, but the gate keeper is unable or unwilling to get them together.

As we look at the development of the research process in the UK and in many western countries today, we can see that regular health provision services are designed to keep hold of the patients in each site, treating them as assets they own. They can then charge for access and their time in running the trial. This introduces bureaucracy, delays and expense where none is really required.  Although a traditional approach, I see this as a risky strategy for the future, given that the tools are available today to break down these barriers.  It is quite possible, right now, to truly liberate the clinical trials environment from the traditional medical practice straitjacket imposed by such gate keeping behaviours.

One rheumatologist or cardiologist (or any other specialist) should be as good as any other at looking after the patients within the confines of a trial, so why not put all of the patients under the care of a dedicated team of physicians and nurses whose only job is to run clinical trials in a given therapeutic area. Such a team would perform the trial to a much higher standard as they can undergo intensive training and become very expert in their field – that of research. 

Imagine – no more investigators who are not really interested, none who don’t really have the time, or don’t have enough staff?  GCP would be adhered to, data would be provided fast and clean and the patients would be happy and well cared for. 

How would it work?
Medical staffing – If we assume a medic can see a patient for 2 hours for 5 visits a year in a typical trial (the nurse seeing them the rest of the time), then 1 physician can see up to 150 patients and still have 25% their week free to do the associated paperwork and anything else they want to do.

In the present model, if the average site sees 5 patients per trial, then a physician in our new model can run 30 such trials at once. Support them with say 3 or 4 research nurses and the team would be able to manage the rest of the visit demand for those trials.

Patient visits – The patients can be seen in the home by travelling staff – mostly by nurses, but medics and any other type of healthcare professional as well. The cost of one-to-one assessments would easily be paid for by the faster recruitment and hence shorter studies, due to the increased access to a much larger patient population – filling the recruitment funnel at the top. It would reduce trial impact on the patient’s life; increasing the percentage of patients getting through the various stages of the funnel and entering randomisation at the bottom. Site costs would drop dramatically as non-performing sites would be eliminated. 

What about equipment for the trial? – Patients would be no further away from fixed site activities than they are now – they can go down the road to get an X ray or MRI – and those centres can be fully trained as required for each protocol.

Drug administration and sample collection? – Complex drugs that have to be managed within a cold-chain and given IV, or through other more complex routes than simply oral, are already administered regularly in the home. You can already take blood samples at home, where they can be spun, separated and otherwise treated prior to being placed onto dry ice if freezing is required, with specialist couriers collecting them to whisk them straight to a central laboratory.

Complex diagnosis – We routinely send complex digital MRI or X rays around the globe to experts for review. Data analysis is in fact improved as variance drops because fewer investigators are needed. A lot of equipment is already portable and can be used with basic training in the home – from ECGs through to EEG, ultrasound, dialysis etc.

What are the down sides? – Immediate arguments put forward to promote the site-based system tend to be that patient’s receive continuity of care if they undergo research at the hands of their usual physicians.  But how true is this?  Many patients in trials are seeing multiple physicians anyway – their general practitioners as well as a several specialists – it does not seem beyond us to keep that whole team in the loop, so the incremental impact of adding another trial specialist to the team is quite limited.

It is worth bearing in mind that clinical trials are not about day-to-day care; they are about taking a very specific sub-group of patients with a clear cut diagnosis at a well-defined part of their disease life cycle and in a particular part of the treatment algorithm, and exposing them to new medications to determine their effect. Day–to-day care is usually fairly straightforward once in that environment, and the control over what happens to patients within the protocol is strict and highly documented, so communication about what they have experienced should be fairly simple.

The patient safety argument has also limited relevance. The patient is receiving one-to-one care throughout the trial from the same team, in their own home, including medics, nurses and other specialists – the same type of people who would see them as out-patients in the hospital or GP clinic. They are getting the same care almost exactly, just in a different setting.

How would you find the patients? – Disintermediation takes place when technology is able to remove steps requiring interaction with a person from a process. Today to get cash you no longer talk to a bank teller, you go to an ATM. Similarly for trials, the internet brings access to trials to a massive patient population directly – no gate keeper required. Patients have to know where to look, but we already have websites boasting huge numbers of patients who are interested in trials – and some very specialised sites who have access to large numbers of patients with rare diseases.  Searching for health information is one of the top activities on the internet – the interest and activity is clearly already there to hugely boost recruitment.

There is no question that it would be medically, logistically and technically possible for a trial to be run completely outside the traditional site. It would significantly improve data quality, trial speed and possibly even reduce overall cost. Less than 6% of investigators take part in trials today in western countries. The restriction on the patient population is significant; implying disintermediation for trials would have a profound, even seismic impact on recruitment in trials today. It is time we tried it.