Utilizing scientific breakthroughs to identify and treate mental health and wellness more precisely and effectively.
Mental health continues to plague a huge portion of the population with varying levels of effectiveness. We have seen digital health come in to treat this (Compound was an early investor in Talkspace) and pharma perhaps overtreat this. With the FDA approval of Aducanumab was a large signal for further development for therapeutics and technologies to manage and treat mental health. We believe a variety of companies and platforms will be built on the thesis and research advancing to better and more precisely understand this component of healthcare.
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The FDA approval of Aducanumab was a large signal for further development for therapeutics and technologies to manage and treat mental health. Unfortunately, our understanding of diseases of the mind falls far behind diseases of the rest of the body. Brain related disorders are something that everyone will eventually succumb to, and represents a market opportunity as large as any other. However, the field has been defined by therapeutic failure, and only recently been accepted into mainstream conciousness as an aspect of our health worthy of being monitored and treated.
Therapeutics for mental health range from more wellness based approaches to more pharmacologic approaches. Current pharmacologic interventions are blunt, have variable and poorly characterized side effect profiles, and can be ineffective for some patient subgroups. Wellness based approaches to mental health are effective but poorly controlled and dependent on patient activities and resources. Deciding when to resort to pharmacological intervention for mental health management is a central question in a patient's care journey, and one that is often made with little to no data to help patients and their providers make decisions with conviction.
An important aspect of mental health is that we are often acutely aware of what troubles us, and many times far more than a neurologist ever will be. Yet providers should theoretically be aware of the most cutting edge research and provide decision making value to their patients. At this juncture, there is a disappointing lack of biomarker datapoints for clinicians and their patients to use to bridge their communication gap.
The diversity of the human experience is at the core of our inability to successfully segment, diagnose, and treat mental health disorders. Unlike diseases like cancer where tissue can be biopsied and studied in great detail for molecular characteristics, the study of brain disorders has had to rely on tissue from dead donors, animal models, and non-invasive imaging. Compounding this issue is the fact that the brain is systems and network based. The molecular characterization of single neurons might not be as useful in stark contrast to other biological disciplines, where -omics revolutions have dramatically accelerated progress.
This isn't to say that -omics based characterization of brain related cells won't be useful. Similar to how the molecular pathways of cancer were elucidated, there are molecular pathways of neurological conditions. Large scale genetic studies have identified risk variants for diseases like APOE4 for Alzheimer's which can even underlie the basis for gene therapy. But it's unique that the system that keeps cognition functional is dependent on connections and neuronal activity. How we treat and see mental disorders is by addressing cell death or blocking/activating receptors that very bluntly activate or diminish the activity of cells. There are far fewer targeted agents that act on specific intracellular pathways.
Given the lack of biological understanding of neurological conditions, it isn't a surprise that molecular biomarkers have been scarce and hard to come by. Even with molecular biomarkers, they may be downstream products of molecular damage, making therapeutic development difficult. Understanding the 'atomic unit of disease' from a mechanistic standpoint is clearly the most promising path towards real, actionable, and predictable biomarkers. Until then, biomarkers for mental disorders will likely be driven by secondary measurements based on patient physical or social activity. Longitudinal brain imaging may prove useful but at this stage is far too expensive to be clinically useful.
Importantly, there are no north stars yet. Randomized control trials or other robust statistical evidence will be the only way to truly gauge the success of new biomarkers. Here, the strategy is to either get measurements from as many people as possible, or to track select individuals and get as many longitudinal measurements as possible. Some of the more interesting data being collected are smartphone usage based biomarkers and physical markers like gait and voice. Survey based collection methods are used and may appeal to a subset of patients as well. At the end of the day, patient data is what is valuable. Products that build in mental health data collection tools into existing care packages will be useful for accelerating discovery. However, at this point, standalone biomarker discovery tools and service companies don't seem investible at the seed stage. It remains hard to gain conviction on why a specific marker may be more valuable than another without robust statistical evidence and if that exists, the company likely already outgrows its status as a seed stage company. For many consumers, by the time they turn to mental health services, it may be too late and biomarkers don't have actionable value. Cultural shifts towards continuous mental and physical health monitoring and renewed fervor in brain research may represent future catalysts.