Derma Pitch Competition

The objective is to meet the main challenges facing the medical treatment of psoriasis, and enable faster and more efficient diagnosis and treatment management that would be mutually beneficial for patients and dermatologists.

How could we apply digital tools/resources to help patients take accountability for their dermatology care?

Actual situation

Psoriasis is a complex autoimmune disease caused by a systemic inflammation that affects skin among many other body organs. This has led to the coinage of the term psoriatic disease. [1] 

Some of the most frequent disorders related to psoriatic disease are psoriatic arthritis, dyslipidemia, hepatic alterations, and depression. [2] Specifically, up to 40% of patients suffer from psoriatic arthritis [3], and up to 30-50% of them –  from hepatic alterations. [4] [5]

The burden of psoriatic disease can greatly affect patients’ wellbeing. In fact, up to 40% of psoriatic patients state that their disease moderately or highly affects their quality of life. [6]  

The poor adherence to treatment is also one of the major problems among patients with this disease; which could be related to a lack of knowledge about the expansion rate of psoriasis that could be valuable to know for improving self-management.  

Spreading patients’ knowledge and awareness about the complexity and progression of psoriatic disease may be a key to improve their satisfaction with the care [7] received.   

Desired situation

Novartis is looking for a patient-centered scalable solution that would help to optimize patient care, allowing both patients and dermatologists to capture relevant clinical information and key events, as well as to track progress of the disease. 

For example, a potential solution could be capable of sending medication reminders, informing of the healthy habits that help improve patient outcomes, or providing personalized recommendations based on the detected symptoms.

We will highly value the solutions that can be integrated into the applications already used by patients, as well as the solutions that apply Artificial Intelligence to recognize images and prediagnose the disease.

Initial nominations
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