CHANGING THE FUTURE OF THE DRUG TESTING INDUSTRY
CHANGING THE FUTURE OF THE PHARMACEUTICAL TRIAL INDUSTRY...
Replacing cell diffusion with machine learning algorithms for more accurate and personalized drug testing
Our Mission Statement:
To see how emerging machine learning technology can change the drug testing industry by evaluating drugs on how they interact with the proteins of the phospholipid bilayer rather than considering circumstantial diffusion through the bilayer.
How It Works
The proteins that are actually responsible for drug transport, instead of what we thought was diffusion, can be detected using a sequence of an individual's genome to determine exactly how their cells will react to said drug. By deducing the makeup of the proteome in the cell membrane, we can know how much of the drug will be transported into the cell
Our Revolutionary
Machine Learning Approach
Developed in Julia and designed for a future with a larger computing capacity, our SVM is up and running and can be used now on a set of Iris flowers. The accelerating research on the proteome will be used to make a protein and gene dataframe for the SVM in the future.
The Impact
Idea So Far...
25+
Uses
5
95.8%
Accuracy So Far
1
0
Need for human or animal testing
Solution
Dr. Douglas Kell
Khali Alfar
IMOGEN CARS
IDI SOFTWARE
Jeff Bezanson
Tonya Bongolan
TRI-NEX
Our Team
Our team is committed to making a difference.
We believe that drug testing can do so much better than it is now and are looking to fabricate a future where big pharma has no excuse but to strive for success. Drug testing has been profiting for too long off of people's suffering. It's time that we faced the scientific reality of the industry's problems and took them head on with the best that our emerging technology can offer.
