In the debate on methods of clinical validation of DTx, one possible approach is to consider software as the 'active ingredient' and the user interface as the 'excipient' to be adapted to the socio-cultural context of patients

In a study just published in The Lancet Regional Health-Europe, a team of Finnish researchers has shown that a smartphone application is three times more effective than using written material in reducing the likelihood of a smoker kicking the habit.
To prove the validity of this solution, the authors conducted a randomized controlled trial on 200 smokers stratified by age, gender and years of smoking, in a 1:1 ratio between experimental arm and standard of care: essentially the gold standard of clinical validation.

However, the need to apply this type of clinical approach to digital therapies is an idea that is not yet universally accepted.

What kind of validation?

Although not all digital health technologies necessarily need clinical trials, digital therapies (DTx), which by definition deliver therapeutic interventions to treat a medical disorder or disease, require medical evidence and real-world results to be validated. However, some authors urge to consider 'digital medicines' with a different approach.

For instance, in 2018, an editorial published by The Lancet itself evoked a kind of 'digital exceptionalism', according to which digital medicine should be considered differently from standard medicine and can afford significantly facilitated pathways.

Digital products inherently collect a large amount of data in real time and other methods of evaluation might be more suitable for this field.

The Lancet

An anomaly not limited to this field: in surgery, the 'difficulty of conducting randomized trials, also due to the strong influence of individual ability' has long been described, which led to the creation of the IDEAL recommendations, a specific tool for evaluating surgical innovations .

"It is evident," the editorial concluded, "the need for similar standards, not only for safety and data utilisation, but also for clinical effectiveness and cost-efficiency of digital medicine.

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