| Treatments for yesterday’s smoker
The dominant cessation therapies — nicotine replacement, prescription medications, behavioral counseling — were developed in an era when nicotine use was relatively uniform. A patient smoked a fairly predictable number of cigarettes per day, at fairly predictable times, with a fairly predictable dose curve. Treatments were designed around that pattern: fixed daily doses, slow and steady delivery, standardized behavioral protocols. That patient is increasingly rare. Today’s nicotine user often moves between cigarettes, e-cigarettes, pouches, and other products, sometimes within a single day. Consumption tends to be more frequent, more situational, and closer to continuous, with doses absorbed throughout the day rather than organized around the rituals of a pack of cigarettes. Modest, inconsistent wins
The response from much of the field has been to add things on top. A companion app. A telehealth coaching layer. Digital reminders stapled to a decades-old pharmacological regimen. The evidence on these additions is mixed. Some studies show meaningful gains when apps are paired with pharmacotherapy; others show no difference at all. What’s consistent is that the wins tend to be modest, inconsistent across populations, and heavily dependent on engagement that most users don’t sustain. Patients open the app for a few weeks. Whether they quit is another question. The problem is that the underlying therapy has no way to act on what the digital layer observes. If an app flags that a patient tends to relapse on weekday afternoons, the nicotine patch on their arm can’t do anything about it. The treatment and the data sit in separate systems, with a clinician, if one is even in the loop, as the only connection between them. What could work?
A treatment regimen designed for how nicotine is used now would look different from the start. It would deliver nicotine in higher doses and at faster onset. It would capture patterns of use, timing, frequency, context, all as part of the therapy itself, not as an add-on. It would adjust delivery based on those patterns rather than running on a fixed schedule. It would give clinicians real-time information about when a patient is struggling and when tapering is working, rather than relying on self-report at a follow-up visit weeks later. There’s a difference between tools that track behavior and tools that act on it. Most of what’s reached the market does the first. The category has yet to produce much of the second. — By MedCity Influencer Mario Danek |
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