This site uses cookies.
Learn more.

×

This website uses cookies. Some of the cookies we use are essential for parts of the website to operate while others offer you a better browsing experience. You give us your permission to use cookies, by continuing to use our website after you have received the cookie notification. To find out more about cookies on this website and how to change your cookie settings, see our Privacy policy and Terms of Use.

Can a Computer Scientist Cure His Son?

Published August 12, 2019

Can a Computer Scientist Cure His Son?
Matthew Might, PhD

Matthew Might, PhD

By Robert Birchard, NYAS Staff

Matthew Might, Director, Hugh Kaul Precision Medicine Institute at the University of Alabama at Birmingham is a computer scientist by training, but now works in the field of drug repositioning. His research is dedicated to finding new therapeutic purposes for already existing drugs. Recently he sat down to discuss his work.

How would you describe your work?

As a researcher I’m focused directly on scaling up the process of drug repositioning for specific rare and medically complex patients. I’m investing heavily in the creation of bioinformatics infrastructure that allows us to repurpose drugs and implement a workflow that can guide patients through the identification of a therapy.

What brought you to the field of drug repositioning? 

My shift from computer science to medicine was motivated entirely by my son Bertrand. He is the first discovered case of an ultra-rare genetic disorder known as NGLY1 deficiency. The lack of any available treatments inspired me to look for existing medications that could be repurposed to treat his disease. Over time I was able to use a variety of techniques to find three different compounds with some therapeutic potential for his disorder.


“I wouldn’t have done this without the personal motivator, but I think this is not just the right time to have more computer science in biology. It’s the right time to have more computer scientists in biology.”

— Matthew Might, PhD

How difficult was transitioning from computer science to medicine?

The transition was gradual. Initially, I learned about genetics, and then I began reading about glycobiology, which is an interesting way to learn biology. After learning enough glycobiology and about metabolism, I made some predictions about what Bertrand might be deficient in. That led to the discovery of the first natural product that serves as a therapy for his disorder.

Six years was the total time it took to go from computer science to having enough biology to make a reasonable therapy prediction. I wouldn’t have done this without the personal motivator, but I think this is not just the right time to have more computer science in biology. It’s the right time to have more computer scientists in biology.

When looking for drug repositioning candidates do you identify a disease or treatment first?

We start with the disease. When a patient comes in with a rare monogenic disease, we ask four questions about the gene: ’Is the gene overactive? Is it underactive? Is activity absent? Or has its activity become toxic?’ These answers tell us what direction to go.

The two most common directions are genes that have a gain of function or partial loss of function. We’re going to be manipulating the gene that has a variant. The tools we've developed are capable of answering questions like, ‘Given a gene, how do I modulate its activity up or down through any mechanism whatsoever?’ A lot of what we do is harvesting data sets that enable us to answer that specific question better.

What’s the biggest challenge in identifying drugs to be repositioned?

From a bioinformatics perspective the challenge we face is that only a small fraction of genetic targets have a candidate drug known to hit them. This isn’t a limitation of the drugs, it’s a limitation of our knowledge about them. If I could have the NIH fund one experiment, it would take all approved drugs and do an exhaustive transcription against many cell lines. That would show the impact of every drug on every cell type, on every gene. If we had that database, we could do much more drug repurposing.

How do you get these treatments to patients?

Once we've found a target, we will do whatever we can computationally to find a compound that might modulate the target. If we get lucky and we hit it computationally, we will end up generating a research report. We do this when we find an approved compound, or a natural product that's already available.

The report is a factual summary of the information we’ve discovered about the compound and includes research papers that back this up. We turn that report over to the patient’s treating physician. At that point, it's up to the treating physician to decide what to do.

Want to learn more about drug repositioning? Register to attend Advances in Drug Repositioning.