What If Training the Brain, Not Medicating the Body, Is the Future of Medicine?

Globally, the pharma industry invests over $200 billion annually in developing molecules that act on the body. Meanwhile, a very sophisticated and much less expensive drug delivery system remains largely untapped as a therapeutic mechanism itself: the human nervous system. 

What if we could unlock this delivery system to replace or enhance drug-based interventions?

The technology already exists that would allow us to close the loop between physiological dysfunction and neural adaptation in real time. The question is not if, but how, rapidly this capability will reshape therapeutic paradigms and the economics that sustain them.

Measurement leads to mastery

Consider chronic cough, a condition affecting up to 10% of adults and costing the U.S. healthcare system alone over $100 billion a year in diagnostic procedures, specialist visits, pharmaceutical interventions, and lost productivity. Traditional approaches target the cough reflex with centrally acting suppressants or treat presumed underlying inflammation. But chronic cough, in many cases, represents a “learned” hypersensitivity; a neural circuit is misfiring and has become dysfunctionally reinforced.

We now have technology that can detect cough continuously and objectively, providing granular data that was previously accessible only in controlled clinical settings over short periods of time. This has facilitated the design of a biofeedback loop that can rewire the misfiring circuits.

This AI-driven feedback loop is linked to continuous cough monitoring on ubiquitous devices (phones, smartwatches), enabling patients to implement proven cough suppression techniques that reduce cough frequency and, over time, normalize the urge to cough itself. Patients observe their cough declining in a matter of days or a couple of weeks, as they apply the techniques. The brain then performs its magic trick, carving and reinforcing a neural pathway, which instead of telling the body to cough when there’s no obstruction or pathogen, tells the body that no cough is needed. Practicing at first when there’s no or little urge to cough enables easier implementation in real-world situations where troublesome cough triggers are present, reinforcing this new pathway and paving the way to cough freedom. This is neuroplasticity at work, guided by machine learning and validated by continuous objective measurement.

Technological convergence

Three technologies have converged to enable this shift.

1. Continuous passive monitoring – Wearable sensors, ambient acoustics, and smartphone-based measurement now capture physiological signals with clinical-grade accuracy outside healthcare settings in real time. The prior constraint was data availability, but  the new challenge is data interpretation.
2. Real-time machine learning inference – Efficient algorithms and data computing allow pattern recognition to occur right on personal devices, like smartwatches and phones, with millisecond latency. The feedback loop no longer requires connectivity or additional infrastructure. Cough suppression lessons are communicated in direct response to coughing, shortening the delivery timeline of behavioral therapy. 
3. Neuroscience-validated interventions – Decades of research in neuroplasticity, interoception, and the neurobiology of learning have identified specific mechanisms to modulate autonomic and semi-voluntary processes through awareness and attention. These are not relaxation techniques. These are targeted clinical interventions designed to exploit known neural architecture. Previously, these interventions had an accessibility problem. In the case of cough, there are under 200 experts in the US who practice cough suppression therapy. Digitalizing these clinically validated techniques allows us to scale and democratize them. 

This flexibility with digital therapeutics moves parts of care from the exam room into a patient’s routine, where habits form and life happens. When software can deliver the right therapeutic experience, at the right dose, with the right feedback loop, care becomes more personal and more continuous.

Economic disruption 

Traditionally, the pharma business model depended on recurring revenue from chronic conditions. A patient who requires daily medication for decades represents a high lifetime value. A patient who achieves durable symptom control through neural retraining after a month of digital intervention does not.

This presents both a threat to the status quo and an opportunity for a new generation of business models. The threat is obvious: effective digital therapeutics could erode markets for symptomatic treatments for conditions in which neural dysregulation is a causal factor. Chronic pain, mental health, certain gastrointestinal disorders, insomnia, and a subset of respiratory conditions appear vulnerable.

The opportunity is more interesting. First-line digital neuroplastic modulation will reduce the population requiring pharmaceutical intervention, but those who do progress to medication would represent truly refractory cases, potentially justifying premium pricing for advanced therapeutics. 

More significantly, pharma companies that develop expertise in combination therapies, deploying both digital and molecular treatments, could address conditions currently considered intractable in ways that will increase outcomes and return on investment. Digital companions for pills can help improve dosage, regimen, and response to side effects. Continuous engagement with patients will increase compliance, adherence and retention.  

For payers and healthcare systems, digital therapeutics offer marginal costs approaching zero once developed, no manufacturing complexity, no supply chain vulnerability, and no adverse event profile resembling traditional pharmaceuticals. A single algorithm can serve millions of patients simultaneously. Once a digital therapeutic has demonstrated effectiveness, it scales the same way Candy Crush does, with minimal friction from the patient side. 

A new infrastructure

In order to effectively implement these digital therapies, we must rethink our existing procedures in reimbursement and our clinical approaches to intervention and prescription of therapeutics. Reimbursement frameworks built around procedure codes and pharmaceutical dispensing do not currently accommodate software-based interventions naturally. Clinical workflows designed around episodic interventions will have to adapt to continuous monitoring and iterative refinement. Physicians trained to prescribe molecules will adapt to learn to prescribe behavior change protocols augmented by AI, using real-time data in their clinical evaluation and decision-making. 

Fortunately, frameworks such as the German digital therapeutics reimbursement framework (DiGA) and the UK’s NICE evidence standards for digital health technologies already demonstrate viable pathways. As the evidence accumulates, adoption will follow, first in systems with strong cost-containment incentives, then more broadly.

Health system plasticity

The promise of brain-based therapeutics does not eliminate the need for molecular medicine, as  not all conditions will yield to neuroplastic modulation. Structural pathology, infectious disease, acute trauma, genetic disorders, and conditions where neural circuits don’t play a primary role will continue to require traditional pharmacological or surgical intervention. 

But the boundary of what constitutes a trainable neural dysfunction versus an irreversible biological deficit is not fixed. It shifts with our understanding of neuroplasticity’s extent and our technical capability to guide that mechanism precisely. Conditions currently considered purely biological may reveal previously unrecognized neural components amenable to retraining. 

Additionally, the promise of combination therapy implementing both molecule and digital treatments, carries significant potential. The most sophisticated future treatments will one day combine both a biological intervention to create a therapeutic window paired with a digital intervention to train the brain. The molecule provides the opportunity; the algorithm provides the permanence.

Pharmaceutical companies that quickly move towards building capabilities, internally or through partnerships, will grow or retain their competitive positioning. Healthcare systems will have to figure out how to restructure incentives to favor durable outcomes over recurring interventions. For clinicians, the question is how to smoothly integrate continuous digital feedback into diagnostic and therapeutic workflows.

The most powerful drug, it turns out, may not be a drug at all. It may be the way our nervous system is primed to absorb new information, enabling the brain to do what it evolved to do: learn, adapt, and heal.

Photo: Khanisorn Chaokla, Getty Images

This post appears through the MedCity Influencers program. Anyone can publish their perspective on business and innovation in healthcare on MedCity News through MedCity Influencers. Click here to find out how.