top of page
Our projects

Our projects

Xions projects include a comprehensive entourage of health informatics projects that broadly include immune monitoring, neoantigen vaccine program, and digital medicine.

Neoantigen  vaccine_edited.jpg

Neoantigen vaccine program

This project aims to develop personalized neoantigen vaccines to train cancer patients’ immune systems to recognize and kill cancer cells. The vaccine will be designed according to the individual patient’s tumor mutation profile. For this, the individual’s genome sequence data will be used to predict the neo-epitope. The peptides predicted to be effective will be administered to the patient as neoantigen vaccine therapy. Students who excel well in the research program will get an opportunity to work on this project with a team of skilled scientists.

Immune monitoring

In spite of scientific improvement and the development of newer treatment methods, survival rates for many types of malignant primary brain tumors remain low. Adult malignant gliomas are the most common, aggressive, and deadly primary brain cancers. Some of these treatments are currently being tested in clinics, while others are in different stages of clinical testing. In order to improve survival and quality of life for patients with glioma, it is important to bring newer treatments to the clinic. A successful student who has impressed our scientific team will be inducted to work on the project.

Immune  monitoring
Digital  medicine

Digital medicine

The data generated from wearable sensor devices such as Fitbit can be valuable to make predictions about a person’s health. This data can also be used to detect health anomalies which can make timely life-saving interventions possible. The primary function of wearable devices such as Fitbit is to track a person’s heart rate and activity, as other variables such as the number of steps taken, calories, and elevation. Even though data generated by wearable devices can be useful in monitoring the health of a person and offering suggestions for changes in daily habits that can improve health, the data can also be applied clinically. In this project, wearable device data from patients with disease conditions will be analyzed by deep learning algorithms to detect anomalies. This project will also explore the correlation of this data with clinical data.

Students who have demonstrated exceptional skills in the research program work will have the opportunity to work with one of the best teams on this project.


Bhimar logo.png
bottom of page