Neurosciences – Need is Growing, but not Investments: Part #3
Private Capital in the Neurosciences… is Overdue
Private Capital in the Neurosciences… is Overdue
Managing the growing prevalence of neurologic diseases requires better prevention techniques and better therapeutics in any form, e.g. drugs, nutraceuticals, electric stim, light therapy, or neuro-modulation. One of our biggest obstacles is the inability to objectively monitor brain function with high sensitivity and specificity.
There are solutions to this problem, but acceptance requires capital and management. It does befuddle me that investors willingly place $100+ million bets on a new neurologic drug when successful FDA approvals are so based on a clinical assessment that remains subjective.
The recent tempest around the FDA’s approval of Biogen and Eisai’s Alzheimer’s drug, Aduhelm, is a great example. Alzheimer’s diagnosis is a process of elimination and essentially subjective. Again, we do not understand the disease and its natural history well, and for neurologic conditions there aren’t effective animal models from which to test and learn. The state of the art assumes that beta-amyloid plaques (Aß) are highly correlated to Alzheimer’s. We use the new radiotracer, C-11 PIB, to structurally observe levels of Aß with MRIs. Aduhelm decreases Aß plaques, but we don’t yet understand the precise role Aß plays in Alzheimer’s. All Alzheimer’s patients seem to have Aß plaques, but all Aß plaques are not associated with Alzheimer’s. So, while Aduhelm may measurably help with Aß plaques, it does not necessarily help Alzheimer’s. Demand in the neurosciences for such a drug, even a loosely efficacious drug, is huge. Think of the possibilities if we could do more!
As Peter Drucker, management guru, told us, “If you can’t measure it, you can’t improve it.”
Structural observations can be highly specific, but are often not sufficiently sensitive. We must be able to both detect a disease early for effective treatment and to measure a drug’s effect with greater specificity and sensitivity. Measuring a drug’s effectiveness with high sensitivity and, appropriate specificity, will: 1) accelerate identification of study design errors for more timely study adaptations, e.g., pivots in chemistry, dosing, study designs, or new delivery mechanisms; 2) cut losses in failing studies; 3) provide objective data increasing FDA approval odds and timelines; 4) enable accelerated go to market strategies; and or 5) shorten investment cycles. Being able to de-risk costly clinical trials with such a data set enhances net present values and is, simply, financially prudent.
Integrating objective diagnostics/ neuro-functional measurements into FDA drug studies to improve the odds of success are not new. In 2008/2009 the ARMY’s Combat Casualty Care (JP6) team, led by COL (ret) Dallas Hack, now a brain health consultant (Dallas Hack), recognized the problems associated with the absence of a practical, objective set of metrics for measuring brain health. In this case the target was concussion/ TBI. JP6 invested heavily (~$400 million) in technologies to objectively diagnose TBI. In 2014, Col. Hack’s team established the first TED (Traumatic Brain Injury Endpoints Development) Consortium to facilitate collaboration between the DoD, FDA, academia, and private enterprise. Its main theme; “if the FDA has not cleared an objective measurement tool for brain health or a diagnostic for TBI, then how can the FDA efficiently and accurately evaluate the effectiveness of a drug for concussion in order to approve it?” The JP6 team understood the challenges of getting new or re-indicated drugs approved for TBI through the FDA without cleared, objective, measurement tools.
The DoD funded (continues to fund) scores of clinical studies using multiple technologies on hundreds of subjects. One such study was Neuro Kinetics’ 408 subject trial run at San Diego Naval and Madigan Army hospitals. This study generated what I believe remains the most statistically sensitive and specific dataset on concussion (mTBI) subjects to date. [Note: DoD funding accelerated Neuro Kinetics’ development of its compact head mounted virtual reality-based testing system with embedded eye-tracking that executed an extensive set of oculomotor, vestibular, reaction time and cognition (OVRT-C) tests. The device, originally named I-PAS™, is now called DX100, post Neuro Kinetics’ merger with Neurolign Technologies, Inc.].
When these investments did not result in a clear, “official” winner for objective diagnostics, the DoD withdrew its funding commitment. Missed in the DoD’s conclusion was what we had learned. These investments pushed the limits of known, accepted science. EEG is a widely used and accepted, if not very sensitive and specific, tool. It was logical for EEG companies to receive a large portion of the DoD largess and push the limits of electrode technology to read our brains. They tried many paths including adding novel AI/ machine learning algorithms to solve noise-to-signal ratio problems.
How our brains function and adapt is, still, simply, a wonder, and the complex electrical signals of our brains are difficult to capture. While these investments in some of our brightest minds advanced EEG technologies too many of the noise to signal problems remain to successfully detect a mild TBI. Some have secured clearances to detect hematomas, useful for stroke detection.
As one should expect, the shortfall in the EEG efforts forced scientists and professionals to open their minds to possible, different solutions. Technologies such as doppler, near infrared spectroscopy, and eye-tracking, to name a few, began to get more attention.
And, just as these “alternative” technologies were getting more attention, DoD investments stopped. Private capital had looked to the DoD as the domain experts, validating and de-risking promising technologies. When the DoD left, so did private capital. The resulting void left small, innovative companies, some on the cusp of successful commercialization, starving for capital.
So why isn’t private capital picking up the mantle? My last post outlining the unmet need has gotten nearly 3,000 views, and some great comments. This suggests that many of us agree that the lack of neuro-measurement tools that are practical and objective with high sensitivity is an important and significant unmet need.
Market size does not appear to be the issue. When presenting to potential neuro-investors, I never had pushback on the size of the concussion market. It was accepted as being a billion-dollar market. Include use cases from brain health triage or concussion triage at the field side or urgent care; to therapeutics and rehabilitation; to drug studies; to specialty markets, e.g. neurologists, ophthalmologists, functional (chiropractic) neurology, and the potential market multiplies to many billions. Given that most investors are attracted to billion-dollar markets this does not appear to be the cause of the inhibition to invest.
Understanding the many sub-segments of this market is a challenge. Here one has to match technologies and data sets to use cases such as triage vs. drug discovery. The triage market needs a quick, cost effective, objective field-side test with a subset of objective metrics that are sufficiently sensitive to determine whether or not a brain is healthy. I do not think specificity, i.e., “is it a concussion or MS?” is critical here, as it would up the cost and bulk of a device. For the right product(s) a billion-dollar market seems viable.
The drug discovery market, on the other hand, needs a tool that is not only sensitive, but that can be specific to, for example, measuring the functionality of the various parts of the brain, e.g., distinguish between frontal lobe, corpus callosum, or basal ganglia. There are about 1,800 neurologic clinical trials underway in the US right now, representing a market of say $.25 to .5 billion. One would expect the market for the neurologic specialists such as neuro-ophthalmologists, functional neurologists (aka neurologic chiropractors), neurologists or neurosurgeons to have a similar set of technical requirements representing another market in the billions. Add other potential markets for variations of these same technologies, e.g., physical therapy rehabilitation and ophthalmics, and we add a few more billion to market size. Again, market size does not appear to be the deterrent.
Having immersed myself in this field for 20 years, it is a daunting challenge to grasp the complex Venn diagram of: 1) point(s) of care, 2) appropriate use case(s) and 3) technology platform(s). Some technologies have narrow applications, while some address more complex use cases. Given this, it is unlikely that there is a silver bullet, or single technology platform that meets the needs of all the potential market segments.
The brain is a magically complex organ and one issue could simply be that we have a subcurrent of cultural or intellectual disbelief that anything could profess to accurately and sensitively measure our brains.
In general, medical devices are a complex, highly regulated business. Devices can be highly profitable, but it is hard steady work. Simply having a great technology, is not at all like having a great drug. Doctors don’t usually prescribe a daily dose of device. In the device business one sells and manufactures each device one day at a time.
Another issue is the low entry barrier for many of the technologies in this space. Core components for all of these technologies exist. EEG has been in clinical use for decades. Doppler, near infrared, eye-tracking, and cognitive apps are all existing platforms. Any research lab can purchase, say, an Oculus VR system, add off the shelf eye-tracking cameras, and have a device. When universities announce a new development by one of their researchers, investors pull back trying to understand how this alters the competitive landscape. Such “off-the shelf” devices usually lack the necessary sensitivity required to measure the brain. The barrier to entry resides in patent portfolios, which requires investors to be able to evaluate the technologies, their intellectual property protection and how they fit to a given use case.
Lastly, even with good technology, and a strong patent portfolio, these small companies are often led by technical innovators focused on their technology, and lacking necessary strategic, financial and marketing experience.
To summarize:
1) Society still needs a set of accepted, practical devices that produce objective neuro-metrics with cost, sensitivity and specificity and form function matched with the appropriate use case(s) and point(s) of care.
2) Neuro-pharma needs objective neuro-measurement technologies for successful drug development.
3) Solutions exist, but capital is required.
It is the opinion of some that we are at a nascent stage in the business of neuroscience and brain health. It was not until the early 2000’s that computer processing speeds allowed us to mimic the processing power of our brains. Since then digital technologies have transformed most everything, with neuroscience the next to be transformed (Actually in process now, just needs capital!). Those who invest wisely now in the existing rough-cut diamonds of these emerging technologies will do very, very well.
As one attempts to understand these markets, there are few who have sweated, learned, and know them as well as I do. If I can help, please let me know.
My email: jhschroeder2@rzacquisition.com, my website: https://rzacquisition.com/, my phone #: 412-427-0998
JHS July 22, 2021
In science we trust, unless, it seems, it is neuroscience…