How to improve early diagnostics with the application of digital biomarkers?

Digital biomarkers (DB) are objective, quantifiable, physiological and behavioral clinically-relevant information. On one hand, DB could be seen as consumer-generated physiological and behavioral measures collected through connected digital tools (mainly wearables and apps). On the other hand, DB could be considered as broader meaning such as new ways of capturing data that before was not possible.

DB can be collected massively and cost-effectively. Besides patient monitoring, people living with a condition may only see a physician once or twice a year and may not entirely remember how they have felt on a specific day. DB help to provide more comprehensive picture continuously.

DB could significantly help in bringing healthcare from a reactive towards a more preventive approach. The characteristics of DB also holds promising potential for value-based patient-centered healthcare. Longitudinal and individual-level data collection provides the granularity and time context necessary to understand, prevent, detect, and manage disease.

How to improve early diagnostics with the application of digital biomarkers?

Digital biomarkers (DB) are objective, quantifiable, physiological and behavioural, clinically relevant information. While often seen as consumer-generated physiological and behavioural measures collected through connected digital tools (mainly wearables and apps), DB could be considered in a broader context – such as new ways of capturing data that before was not possible. The use and evaluation of DB is growing rapidly with the benefits potentially three-fold. From the patients’ point of view, DB could unlock hidden information able to track and accurately measure any changes and lead to ways to slow, or even prevent, disease progression. For physicians, DB could fine-tune personalised treatment by continuously monitoring DB (even in real-time). From a scientific perspective, DB holds the promise of opening new paths to a better understanding of the progression and the management of diseases.

How to improve early diagnostics with the application of digital biomarkers?

Patients living with a condition may only see a medical professional once or twice a year and are not necessarily be able to recount their health or pin point their feelings on a particular day. DB provides the means to collect information cost-efficiently and en masse, helping to give a comprehensive picture of a longer period of time. What’s more, the characteristics of DB have great potential for value-based, patient-centred healthcare. Longitudinal and individual-level data collection provides the granularity and time context necessary to understand, prevent, detect, and manage disease. To date, only large cohort studies have been able to collect granular and longitudinal information, but at a high operational cost. DB are increasingly proving their value in several areas in the medical field; such as chronic pain management, cognitive function assessment, and neurodegenerative disorders. For example, the use of DB for neurodegenerative disorders aims to overcome the limitation of the sparse collection of subjective data to inform drug development and the design of phase III trials in the presence of unreliable, physiological biomarkers. The data generated by mobile phone and wearable/implantable devices are independent from raters and virtually free from intra- and inter-rater variability. For instance, motor assessments of finger tapping have been used in clinical trials in Parkinson’s disease and gait assessments have been used in clinical trials in Huntington’s disease.

Dinosis

The idea

Early detector of lung infections through immune system self-monitoring.

The team

The Wild Card 2019 BioDTek team is a merger of the original BioDTek project, started in 2010, and Pextract, which formed after a meeting between Eduard and Enrique at the inside design health Barcelona programme in 2017. Both BioDTek and Pextract have experience in the lung health space.

  • Francisco Aloa Salazar
  • Eduard Guerrero
  • Edilberto Ojeda
  • Enrique Hernandez Jimenez
  • Erika Paola Plata

BioDTek

The idea

Eye tracking method for early autism diagnosis in infants.

The team

Dinosis was formed in 2019 following the Wild Card hackathon.

  • Miguel Amador
  • Jane Bourginand
  • Andreu Oliver

Phi

The idea

Biomonitoring stickers for physiological data acquisition, such as heart and brain signals, muscular activities and body temperature.

The team

Pedro and Mahmoud first began working together on a biomonitoring project at the University of Coimbra in Portugal in 2014. They have been honing their technology since then. 

  • Pedro Alhais Lopes
  • Mahmoud Tavaloki

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