GLP1 and muscle loss: A computer simulation using publicly available data

Glucagon-like peptides are hormones that control stomach emptying and recently, they have been used to treat obesity and control diabetes. But there have been some studies that have shown that GLP-1 and GIP drugs also cause significant muscle loss (It is estimated that up to 40% of the weight lost with these medications come from lean mass).

The goal of this research is to investigate whether data about a person before and during GLP1 treatment can be used to predict how much lean body mass they may lose and what we can do to prevent it.

What did I do last year?

Last year I generated pseudo-random data for patient data(the patient data was not fully random since there were ranges to stats).In the model, I used a python environment and NumPy, Pandas, and Matplotlib to complete mathematical functions.

 I created 100 digital patients. With these patients, I assigned each an ID, Age weight, height, muscle mass, fat mass, protein Intake, BMI, Gender, activity level and other characteristics that contribute to muscle loss. 

The feedback I received after the final presentation was that the data was too linear, biological systems do not show a clear trend, and it is almost like I reverse-engineered the result.

This year’s plan

This year I plan to use real existing data from a clinical database and  I then will use a simple machine learning model to identify certain characteristics and help predict lean-mass decline .