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  • Writer's pictureAbhi

EPP Companion Project Updates

Updated: Nov 1, 2019

Project Background:

Imagine feeling pain on being exposed to Light. Imagine how that would effect your daily life and way of being. Thats what people who have the rare disease Erythropoietic protoporphyria (EPP) go through. Read more about a direct experience about an 11 year old girl from the US and about the journey of our project guide and collaborator Rocco who has lived life long with the disease.

Patients with the genetic rare disease Erythropoietic protoporphyria (EPP) do not have a mechanism to correlate the level of pain and symptoms they suffer when exposed to various light spectrum. While a therapy exists to help them manage the disease, its access remains limited, and the day-to-day living of most patients is guided more by their own sixth sense than any guidelines.

Project Aim: Create a mobile app paired with a light sensor.

We want to enable the patients to start reporting the level of pain they experience, capturing associated light information, area of pain and activities at time of episode. The app also supports a Quality of Life (QoL) questionnaire. The aim is to create a toolset that captures enough data over the longer run to support further medical research and support therapy access discussions (which is an ongoing challenge for the patient community, read more here).

Timeline of development:

When we heard the patient experience at a conference where Rocco was presenting, and also the day to day challenges, we were extremely motivated to help. That initial encounter led to a great collaboration with Rocco - who is not only an EPP Patient, but a drug researcher, a leading patient advocate, president of the Swiss association for porphyria and the International Porphyria Patient Network. Together, we embarked on a journey of discovery and development (video of the start of our journey).

A full timeline till date:

Technical Information:

The mobile app is protoyped using invision, programmed in react.js, the database used is SQLite. We are working to make the data available via a project on Open Humans

The light measuring device comprises three sensors; the AS72651, the AS72652, and the AS72653 from AMS and can detect the light from 410nm to 940nm. In addition, 18 individual light frequencies can be measured with precision down to 28.6 nW/cm2 and accuracy of +/-12%.

The git repo (private as yet) is

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