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Faces of HPC: Zoe Cournia

Dr Zoe Cournia was the first recipient of the PRACE Ada Lovelace Award in 2016. Having come into computing via a Chemistry degree, Zoe is passionate about communicating science, and in particular that science is for everyone (and that it isn’t as hard as it might at first appear!).

Introduction

Zoe Cournia’s work focuses on ‘precision medicine’ using HPC to facilitate drug discovery, taking advantage of computational simulation to reduce the cost of designing new medicines. In particular, her team helps to target very specific cancer types to treat patients more effectively.

Biography

Tell us a bit about yourself.

I have always been fascinated by how the world around us works. Everything around us, what we hear, see, smell, taste, and touch involves chemical reactions and chemicals found in our body. When I learned in primary school that scientists named chemists can explain these reactions and can even make drugs, I decided to become a Chemist. Later on while in the University of Athens, I was excited by technological advances in computer science, and thus I decided to combine my two passions and become a “computational chemist”, a scientific field where everything from chemical reactions to drugs, food, materials, cosmetics, electronics, and proteins is being simulated. Thus. I enrolled in PhD studies in computational chemistry at the University of Heidelberg. During my Ph.D. studies I realized that I wanted to use my expertise to help develop products that have the potential to save millions of lives worldwide. It was in 2005, when I discovered a field called computational drug design. A professor at Yale University, who is a pioneer in this field, accepted me in his lab for further training (postdoctoral studies). So, I went to his lab for three years to specialize in this area. Later on, I came back to Athens to become a faculty member at the Biomedical Research Foundation of the Academy of Athens (BRFAA) in designing new anti-cancer drugs.

Many people believe that science is incomprehensible and there is a huge disconnect between the research community and the general public. That is why it is important to give the example that research and science is accessible to all and there is a real need for scientists to communicate their scientific work to people more effectively. So my hobby is science outreach! I aim at promoting public awareness (and understanding) of science and at making informal contributions to science education. I participate in a highschool program, where we open our labs for students from around Greece for several days a year and speak to them about science. I maintain the blog “Life is Chemistry”, which explains in simple words how Chemistry is connected with our everyday life and I am the Editor Elect of the Chemistry in Cancer Research Group Newsletter of the American Association for Cancer Research. I also organize or give talks with scientific themes for the general public such as “Café Scientifique” http://bit.ly/2urgTYc .

I co-organize the yearly Athens Science Festival (http://www.athens-science-festival.gr) as part of the Science Communitation (‘SciCo) non-profit organization. The Athens Science Festival has over 30,000 visitors per year, connecting the Sciences with everyday life and highlighting their role, presenting the high quality scientific research done in Greece, discussing and seeking answers to complex and controversial scientific issues, inspiring and creating new standards in the field of Science and encouraging young people to think of a career close to science. But most importantly, the Athens Science Festival has managed to show young and old that science is not only knowledge but also entertainment.

Through these actions I hope that I can convince young people that science is not hard ! And that through a career in science can make a difference in improving people's quality of life !

Finally, because myself and many consumers are increasingly worried about the safety of food & cosmetics products, yet we cannot decode the complex ingredient chemical names, I have helped develop a mobile app that informs you on potential hazards of food ingredients.

Users photograph ingredients label  & our app informs whether the cosmetic or food products are potentially unsafe according to European Commission & National Institutes of Health data.  

With Ingredio, we have transformed publicly available information into meaningful, fast, and easy-access information for consumers.

What is your current job?

I am now an independent researcher working in the Biomedical Research Foundation of the Academy of Athens, where I run a molecular modeling and drug design lab. In my lab we design anti-cancer candidate drugs inside the computer and predict their interactions with proteins that cause cancer. For decades, drug discovery was being made with the experimental screening of large libraries of chemicals against a biological target (for example a protein) responsible for a disease. With the advent of computational chemistry, we are now able to design drugs tailored for the protein in question by investigating the detailed underlying molecular and atomic interactions involved in drug-protein interactions. Computer-aided drug discovery has recently had important successes: new candidate drugs have been predicted and the success rate of candidate drugs discovered has been significantly greater than with traditional experimental screening. In other words, using the computer makes the drug discovery process much cheaper and more efficient than solely performing experiments.

We are entering the era of “precision medicine”, which means that disease treatment and prevention takes into account individual variability in genes, environment, and lifestyle for each person.

In our lab we work on designing new drugs against specific cancerous mutations that target specific cancer subtypes. Each patient may display a different cancer subtype. For example, we now know that there are over 200 different breast cancer subtypes that may occur due to different mutations in our genes that are expressed in proteins in our body, or due to protein overexpression or due to changes in the signalling pathways in our body. New cancer therapies, therefore, target the specific type of cancer that the patient has; this goes beyond the traditional chemotherapy approach because these therapies focus on the specific therapeutic target  special to each person, which is usually a malfunctioning protein. If we block this particular protein with a chemical molecule-drug then we can stop the progression of cancer. So we work to develop drugs specifically for each type, which is diagnosed after biopsy, and not generally such as chemotherapy.

How do supercomputers help us in this process? They help us by reducing the time and cost of conducting an experiment in the lab after everything is done electronically! In particular, we examine the structure and dynamics of mutant proteins within supercomputers, and based on the data we design candidate drugs that we anticipate to block the cancerous protein. We then go through experiments on cancer cells only for the chemical molecules that passed the "test" on the computer, and then on preclinical studies in mice.

We are currently working on two mutations of PIK3CA protein found in 30% of breast cancer patients and 15% of patients with colon cancer. Our goal is to block the mutant but not the normal forms of PIK3CA with drugs, so that tumors can be treated without toxic side effects for healthy tissues. So we developed some of these drug candidates through computer, and then, following experimental evaluations using cell cultures, we co-operated with BRFAA researchers in preliminary preclinical studies in mice with breast tumors that had encouraging positive results.

Also, in collaboration with researchers at the Biomedical Research Foundation of the Academy of Athens (BRFAA), we are also working on designing candidate drugs against Myc oncoprotein, which is overexpressed in 30% of human tumors and is considered by many to be "Key Protein" for the treatment of various cancers. Researchers at the BRFAA led by Dr. Argyris Eustratiadis created animal models of pancreatic cancer, and Dr. Dimitris Stellas examined candidate drugs against the Myc protein. Candidate drugs were also evaluated pharmacologically by Dr. Konstantinos Tamvakopoulos in studies that showed that they remained in the bloodstream for a long time to be able to act. Following drug administration, moribund experimental animals survived for at least three months without drug toxicity, and a spectacular reduction in tumors was observed by the administration of candidate drugs against Myc. Tumor reduction was certified by Dr. Konstantinos Anagnostopoulos, who performed PET scans to control the course of disease progression in the animal. These preclinical investigations are expected to be completed shortly, and based on the positive results we had, we hope to proceed relatively soon to clinical trials in patients.

What’s the best thing about working in HPC?

HPC is a very versatile field because every product we use, from cell phones to cars to aeroplanes to clothes, at some point goes through a stage of testing, which uses HPC.

My work involves using simulations to investigate how mutations in proteins can lead to cancer. Using data acquired from these simulations allows us to design candidate drugs can bind to mutated proteins and inactivate them. These candidate drugs are then tested experimentally our collaborators. By using HPC simulations and making predictions as to which are the best candidate drugs, we can shorten the time and the cost of the development of the drug. Our work is a good example of how computers help develop products that have the potential to save millions of lives worldwide without wasting valuable experimental and human resources.

If there’s one thing about HPC you could change, what would it be?

This is a challenging question because I have a few ideas that would make HPC more efficient:

  1. Hire system administrators that have scientific training – They can immediately help on code optimization and setups that can bring a tremendous speedup of the calculations that scale well with increasing number of processors
  2. Produce specialized HPC systems depending on discipline. For example, ASICs for performing MD simulations or the advent of GPU programming to speed up scientific calculations.
  3. Bring HPC into schools and provide equal opportunities to underrepresented groups like disabled, women etc.

What’s next for you in HPC?

I work on the design of anticancer drugs because my biggest ambition is to make a substantial contribution to finding new treatments for cancer. Of course, following the design of a candidate drug, the necessary preclinical tests that check the toxicity, activity, and other important parameters for a candidate drug are needed.

If preclinical studies are successful then we proceed to the clinical trials process. To this end, BRFAA, in collaboration with the Sotiria Hospital in Athens, Greece, has set up a standard clinical trial unit to conduct bioequivalence studies of generic drugs, as well as to test prototype drugs such as those we design in our laboratory. So, my dream is to be able to produce Greek, original medicines!

Clinical trials of new anticancer drugs, however, require a great deal of funding. For every new drug that comes out of the market the pharmaceutical industry is investing around $ 1-4 billion. But profits can be as much as $ 20 billion a year! It would therefore be an ideal partnership between Greek research institutes and the pharmaceutical industry to address this enormous cost and achieve maximum benefits for society.

And because the quest for new drugs is never over, we have now gotten access to a new PRACE project (2016153626) through which we will explore the full energy landscape of the mutated PI3Ka, which is implicated in many types of cancer.

The computational approach that we have planned is of unprecedented scale and is expected to provide us with unparalleled information and insights on designing new drugs for this oncogenic protein and set an example in the field.

Last updated: 12 Sep 2017 at 11:42