a few more thoughts...
I appreciate the frustration as well as the indignation about the slowness of progress. I know firsthand how hard it is to try to view the big picture and have a sense for things moving. Science is complex and biology is hard. I have a couple of parts of this thread where I want to weigh-in:
We have novel therapies (beyond the dopamine system) in trials today! I repeat. We have novel therapies beyond dopamine right now in trials. This is reason for excitement.
For disease modification there will be 3 trials in trophic factors (promising proteins being delivered via various strategies to various regions of the brain) ongoing or starting this summer. We have our first trial in alpha synuclein finally in trials. This is good news and more novel targets in the pre-clinical pipeline and are getting close based on our increasing knowledge of Parkinson’s (such as LRRK2 strategies).
We also have a number of very promising trials with novel approaches to treat dyskinesias. The most recent success announced with the Addex trial which (if they can find an investment partner) should be moving to phase III by the end of the year.
All science is high risk. Rather than thinking of "good and bad" science, I find it more useful to think of "interesting" science vs "relevant" science. MJFF focuses aggressively on funding the high-risk science that is relevant for drug development. Many of the exciting strategies now in the clinic (for disease modification and/or dyskinesias) are programs we have been funding since our earliest days when we put smaller dollars out on higher-risk/earlier stage ideas. We continue to make those critical bets and at the same time, now some of those first bets have been stewarded all the way to the clinical testing stage (which has been the motivation behind our growing call for trial participants).
More exciting studies mean more volunteers needed—plain, but not so simple. Patients aren't learning about trials from their physicians. Fox trial finder is a tool that actually relies on self-reported information (patient data) to find smart suggestions on suitable trials. We see it not only as a tool to support recruitment but as a first step into the field to prepare for the bigger undertaking of collecting significant patient-reported data (the idea mentioned in the thread). Our fantasy (and 23andMe's--we are exploring this together) is to pair genetic data with additional clinical, imaging, biological and self-reported data. This goes far beyond what has been done to date but builds on works done in a couple of current efforts.
All these platforms, PPMI, 23andMe, and Fox Trials Finder, in addition to their respective primary goals, are teaching us and confirming what to collect, refining collection standards, establishing data sharing models, and testing patient willingness to engage. One of the things that keeps me up at night is the observation that despite an intention to help, ultimately few patients take action. Inertia and apathy (as part of the disease) present real challenges. Given the extraordinary investments here, no one can afford to set up a system with ambitious collection, sharing and mining expectations only to get a small numbers of participants.
Consider these numbers: 23andMe (spit in a test tube for genetic SNP's – a relatively low friction call to action) has found ~6000 of the desired 10,000 study participants with 2 years of investment in outreach. Note the test is free and not location sensitive. Fox Trial finder isn't a study but does request the expression of "interest" in the form of registration to capture basic patient data for trial matching. Again, minimal impediments to action and conveniently web-based. We have ~4000 registrants since June 2011 with broad media and community outreach. We hope to get to 10,000 registrants this year but really need to get multiples of that to have the desired impact of speeding recruitment. Breast cancer got over 300,000 such volunteers.
PPMI is an example that represents the other extreme. Data collected here is extensive and selective and participants need to be sourced from specific locations. Plus the subjects needed (newly diagnosed but not yet on medications) are particularly hard to find. Elaborate systems have been put in place for training, sample storage and data sharing for this study. The investment in recruiting the needed 600 subjects has been significant and one year into it we are just at the half-way mark for enrollment. I share these details to provide some context around the challenges in “getting all the pwp” to actually engage in these activities. Plus, PPMI is designed to optimize the learnings from this data as soon as possible. Researchers around the world can access the data in real time and start making discoveries. Already, the data has been downloaded over 15K times by researchers from all over the world.
I mention these platforms for a couple of reasons…they represent new ways in which folks from outside the traditional research enterprise are problem-solving around getting information from patients. These new approaches in themselves are high-risk translational investments but are newly feasible as today there are new ways to leverage technology advancements to better support science. These are meaningful new tools at our disposal that can reshape the promise of science and shift the equations of possibilities. These changes are complex and, at least I’d like to believe, come in the context of pretty significant change that has been underway in the last decade. To compliment this, we could use some continued help in reaching more patients with a message to encourage engagement—there are some aspects of this where only the patient can make the difference…we have a long way to go on all fronts but if everyone does their best to do their part (whatever that may be), I believe we can get better treatments delivered.
PS..if one only looks at the cost of administering a test (such as a collecting DNA samples) it doesn’t provide a full view of what is needed to capitalize on the information. While sobering, it is important to view putting all the pieces in place to get useful outcomes. Who will establish the protocols, who will build the infrastructure for collection, who will orchestrate sharing, who will manage questions, who will protect data, who will build networks to find patients, who will pay to analyze data? This list goes on and on taking me back to my first statement science is complex.