Modelling and Control of Non-invasive Vagus Nerve Stimulation for autoimmune diseases (VaNeSA)

Autoimmune disease is characterized by the failure of an organism to tolerate its own cells and tissues, resulting in an aberrant immune response by lymphocytes and/or antibodies.

VaNeSA – Modelling and Control of Non-invasive Vagus Nerve Stimulation for autoimmune disease (2021-2024).  Reference: PID2020-117171RA-I00. Funded by MICINN.117.370 €. P.I. Ivan Contreras

SUMMARY:

Autoimmune disease is characterized by the failure of an organism to tolerate its own cells and tissues, resulting in an aberrant immune response by lymphocytes and/or antibodies. This leads to pathological changes and dysfunction of the tissue that is the target of the self-directed immune response. Autoimmune diseases can be systemic or can affect specific organs or body systems including the endocrine, gastro-intestinal and liver, rheumatological, and neurological systems. Patients with autoimmune diseases such as type 1 diabetes (T1D) and systemic lupus erythematosus (SLE) have been found to suffer from dysautonomia, which manifests as an imbalance in activity/reactivity of the sympathetic and parasympathetic divisions of the autonomic nervous system (ANS). This autonomic imbalance is related to an increased risk of developing cardiovascular disease, which is a major cause of morbidity and mortality in patients with T1D and SLE.

To restore balance to the ANS, improve patient outcomes and improve patients quality of life, non-invasive vagus nerve stimulation (nVNS) has been proposed.  Further investigation of the nVNS parameters is required to enable appropriate administration to patients with autoimmune diseases such as T1D and SLE. As the ultimate goal, a Mobile-based nVNS platform will be developed with analysis and prediction tools to personalize nVNS administration thus, optimizing the desired therapeutic outcomes.

This project aims to:

1) Collect data via an exploratory study

2) Analyze clinical markers to distinguish useful biomarkers of disease and physiological signals for our purposes

3) Create computational models to understand how these clinical markers change dynamically with the delivery of nVNS for a deepened
understanding of the characteristic responses

4) Predict each subject responses to nVNS for improved treatment outcomes

5) Optimize nVNS waveform parameters for the personalized treatment of autoimmune disease

6) Develop a decision support system for patients

7) Bundle the developed tools into a mobile-based nVNS platform, and finally

8) Clinically validate the developed nVNS platform. 

PID2020-117171RA-I00 Founded by MCIN/ AEI/10.13039/501100011033

TEAM:

MICELAB:

Research leads:

  • Iván Contreras Fernández-Dávila
  • Inés Ferrer Mallorqui
 Research Team:

  • Charrisse Mary Ramkissoon
  • Aleix Beneyto Tantiña
  • Alvis Cabrera Tejera
  • Amina Sundas

FUNDACIÓN MÚTUA DE TERRASA DRBS, F.P.C.:

  • Ignasi Rodríguez-Pintó

FUNDACIÓ PRIVADA CLÍNIC PER A LA RECERCA BIOMÈDICA:

  • Judith Navarro Otano
  • Roberto Ríos Garcés

IMPERIAL COLLEGE LONDON

  • Pau Herrero Viñas
  • Pantelis Georgiou
  • Amparo Güemes González

JOHNS HOPKINS UNIVERSITY

  • Ralph Etienne-Cummings

RESEARCH OUTCOMES:

  • Identification of physiological signals, clinical biomarkers and outcomes of disease to determine most effective measures for the personalization of nVNS in T1D and SLE.
  • New analysis and prediction tools exploiting biomarkers of disease and physiological measures for improved nVNS therapies.
  • A clinically evaluated mobile-based nVNS platform with automatic data collection from wearables, manual data input for biomarkers, automated model updates, and a decision support system.
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