Episode Seven – The Blueprint of Modern Medicine

By using DNA to read a patient's cellular blueprint, vast new possibilities are emerging in the treatment of infectious diseases. But for genomics to work, massive amounts of data must be gathered and processed at incredible speeds, and that sounds like a job for technology.

No one wants to hear they have contracted a potentially fatal disease. Including Alicia Diggs. Through the coordination of science, humanity and technology, the field of genomics has made great progress in improving the quality of life for HIV patients like Alicia. In this episode of Technology Powers X, we explore how:

  • Geneticists are analyzing DNA to read a patient’s cellular blueprint and deliver prescriptive treatments for individual patients.
  • Researchers at the University of Cardiff are mining DNA to provide better treatments for HIV, Tuberculosis and Covid-19.
  • High Performance Computing has been crucial to research leading to new healthcare procedures with unprecedented efficiency and accuracy.
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Transcript

Danielle Applestone: Alicia Diggs will never forget the place, the date, and the exact time. It was 10:00 AM on December 13th, 2001, the first warning signs had come the previous August when she caught what she imagined to be a cold or the flu.

Alicia Diggs: I had strep throat. I had just the regular symptoms of a cold, the fever, the chills, the cough, loss of appetite, things of that sort. And then the doctor basically was like, “Well, Alicia, you’ll be fine. It’ll take a week or so to bypass.”

Danielle Applestone: That week or so came and went with little improvement. Any sense that this was just a routine illness began to fade.

Alicia Diggs: My thought was something more is going on with me. I felt like it was lymphoma cancer. So I had lymph nodes in my neck were really, really swollen. So me being a researcher, I am on researching symptoms and everything, and it just led to lymphoma cancer. Okay. Well, I’m not sure. I’m not a doctor. Let’s call the doctor, set up an appointment. So on December 13th, I went to my doctor’s appointment. I’m waiting around and I noticed the nurses chitchatting, and looking pretty serious. And I’m in a good mood, because in my mind, Alicia, if you have cancer, you can beat this. Don’t let it worry you, besides, you don’t even know what this is. So I’m in this room, I’m just waiting, and the nurse comes in and she pushes a folder in front of me. She was just looking really sad. I opened the folder, and at the bottom. It was in bold red. It said HIV positive. So that’s how I found out that I was HIV positive.

Danielle Applestone: What Alicia didn’t know at the time, but now has in common with millions of others, is that a new field of medicine, genomics, is changing everything. By using DNA to read a patient’s cellular blueprint, vast new possibilities are emerging in the treatment of infectious diseases. But for genomics to work, massive amounts of data must be gathered and processed at incredible speeds, and that sounds like a job for technology.

Danielle Applestone: I’m Danielle Applestone, engineer, entrepreneur, you’re listening to Technology Powers X. An original podcast from Dell technologies. In this episode, Technology Powers: Personalized Medicine.

Danielle Applestone: It’s hard to imagine a discipline where science, humanity, and now technology are more tightly intertwined than modern medicine. For Alicia Diggs, she had no idea that her seemingly normal story would lead her to become an advocate for HIV/AIDS. She was a single mother of two, working full-time. Though life had thrown her some curves, she was resolved to make a better foundation for her children.

Alicia Diggs: So my prayer was, by the time I turned 30, I will be married and I will be a little bit more settled. So when I had this prayer going on, I was about 28 years old. So 29, I ran into an old high school sweetheart from Philadelphia. I’m originally from Philadelphia, Pennsylvania. I went back to Philadelphia for a family reunion. I ran into him and we just went from there. He moved to North Carolina where I currently am living, and our wedding date was set for February, 2002.

Danielle Applestone: Two months before, when Alicia was diagnosed, she and her fiance chose to go ahead with the wedding, but six months after that, her husband broke the news. He had been living with AIDS, and he didn’t care that he had transmitted the virus to her. At once, Alicia confronted waves of anger, shock, and fear. It would be years after her divorce before Alicia would commit to another relationship.

Alicia Diggs: So I had two young children, and regardless to what went on with me, I had to live for my children, and knowing the fact that though I had this HIV diagnosis, and I was healthy, I had no other health issues, I am physically living. So I had to mentally and emotionally live as well for my children. And to see, will I have a future? Meaning will I be a grandmother? Will I see those children grow up? So I had to live, and I had to be as vibrant as I could for their sake.

Danielle Applestone: Though it sounds ironic, Alicia was told that because of new advances in medicine, her diagnosis had come at a good time. At the University of Cardiff in Wales, scientists were hard at work, mining DNA for insights that could revolutionize medical research and treatment. Marshall McLuhan once described technology as an extension of the body. We use ladders to extend our height, a telescope to extend our vision, hydraulics to supplement our strengths. Now, with DNA technology, scientists can glean enormous amounts of medical information, but it’s far more than any human brain can store and process. And that’s where technology, in effect, is becoming an extension of our brain. Tom Connor is a bioinformatician and professor at Cardiff. He’s also the bioinformatics lead for pathogen genomics in Public Health Wales.

Tom Connor: Well, that technology emerged in the mid 2000s, and suddenly, you had the ability to generate large quantities of data, and we’re talking about potentially tens of terabytes in a matter of days, at the very top end, generate large quantities of data in a short space of time, which then have to be analyzed rapidly, if you’re going to have some sort of benefits at the end, and that could be a research benefit, or it could be a benefit to patients.

Danielle Applestone: That’s the theory. When he began at Cardiff, Professor Connor was given a modest budget for technology with an invitation to use the university’s high performance computing system. Trouble was the Cardiff HPC lacked the capacity needed for bioinformatics. Professor Conner’s allowance was 50 gigabytes of storage. His ask was five terabytes or five to 10% of the university’s total HPC capacity.

Tom Connor: And so, the problem moves from a laboratory issue, in the old days, where you had issues around getting the samples through, and getting all of that sorted, to a bottleneck around the processing of that information.

Danielle Applestone: Before he and his team could explore the new medical frontiers of bioinformatics, Professor Connor needed the HPC system to handle it.

Tom Connor: The university HPC really wasn’t going to provide what I needed. So what I ended up doing, at that point, was to have to effectively design my own … Cost to design my own piece of infrastructure to support that research. And so, I had a startup package from the university, and that was where my first interaction with Dell came in, because I knew the university bought from Dell, and that was one of the companies that was recommended by the system administrators within the School of Biosciences in Cardiff. And so I got in contact with Dell, and we built my first piece of infrastructure, which really underpinned the start in my career at Cardiff.

Danielle Applestone: Professor Connor remembers that, at the time, no one wanted to help him build this infrastructure, but once it was built, everyone wanted to use it.

Tom Connor: And that then kind of snowballed, because what came next was the development of a piece of storage infrastructure for storing research data, because the school didn’t have a computational cluster, you also didn’t have a system for storing research data long term. And so, we worked with Dell to develop a solution to provide what I term as sort of a middle tier of research data storage, which is now the university standard data storage system.

Danielle Applestone: In the meantime, Alicia Diggs was busy confronting barriers to those with HIV and AIDS. While research was advancing rapidly, attitudes lagged behind. For instance.

Alicia Diggs: The stupid stigma is still there after all of these years. HIV is over 35-36 years old, and it’s so many advancements with HIV, and it doesn’t matter what type of new medicine comes about, what type of researchers come about, what type of research is done, the stigma is still there. There are many people who stigmatize others for living with HIV. There are unfortunately religious sects who were stigmatizing against people living with HIV, like it’s something that was supposed to happen to you because of a lifestyle, which has nothing to do with it. It’s so much stigma behind HIV still, and criminalization behind HIV, and it aggravates me to no end, but it also makes me a stronger advocate.

Danielle Applestone: Back at the University of Cardiff, Professor Connor’s HPC technology began unlocking newer, faster, more insightful healthcare procedures.

Tom Connor: As a good example, in HIV for example. So HIV is a virus. It goes into patients. It replicates inside those patients. And one of the most amazing successes of infectious disease healthcare over the past 20 or 30 years has been the fact that we now have effective treatments for HIV, such that if you are HIV positive, and you have a well-controlled infection, are you taking the correct drugs that prevent the virus from replicating inside you, you have an effectively normal life expectancy. So there is no difference between someone who has well-controlled HIV, and a normal member of the population in terms of their life expectancy. And so, that’s a great success in modern medicine, but what that relies upon is ensuring that that individual is given the right treatment.

Danielle Applestone: Traditionally, the right treatment is a product of trial and error, and often tedious process that can now be streamlined through tech-driven genomics.

Tom Connor: And what happens is, as HIV exists with an individual, and as it replicates, it can gain mutations. It can gain changes in its genome, its blueprint, which render it immune to particular drugs. And so, what we use genomics for in Wales is we take samples of HIV from patients. We sequence them, and then we identify if the HIV in that patient has any mutations that would mean that HIV is resistant to particular drugs. And by having that information, we can then inform clinicians which drugs a patient can safely be prescribed, and which drugs a patient should not be prescribed.

Danielle Applestone: This is probably familiar. You’re at a clinic for blood work, your arm outstretched. The needle goes in, attached to it is a plastic vile which quickly fills. It’s replaced by a second vile then another. Each vile has a separate colored cap, and a separate label. Each of them are for separate tests often in separate labs. If it’s determined that different tests are needed, more blood will be drawn. Now, suppose only one sample was necessary. Professor Connor.

Tom Connor: Well, the difference with genomic data is, because all the information is tied up in those text files, and the ATGs and Cs that make up the genome, we don’t have to take multiple sequences. We can take that one genomic blueprint, and then we can run many different analyses on that to answer different questions. And so, what that gives us is that gives us the power to pick the right tests, to provide truly personalized care, truly personalized medicine for individual patients.

Danielle Applestone: In a relatively short time, high performance computing gives medical professionals the tools to work with unprecedented economy, accuracy, and speed. All of which promotes better outcomes for patients.

Tom Connor: So in the case of HIV, the genomics is faster. We run it within our labs, and it’s much quicker than it used to be. It cuts the turnaround time from potentially three weeks down to less than a week to getting the results back. The test is cheaper. It cuts the cost of the test by a reasonably substantial amount, by being able to take this back in house. And also, the test for HIV actually looks at an additional class of drugs, the integrase inhibitors, which previously wasn’t part of the standard testing that was available to clinicians in Wales. And so, it’s that golden triangle, if you like, of benefits, it’s quicker, it’s cheaper, and it gives you more clinically-actionable information.

Danielle Applestone: And what about other infectious disease? It’s estimated that a quarter of the world’s population is infected with tuberculosis bacteria, and that five to 15% will become ill from it. That’s where the quicker benefit of genomics can make all the difference.

Tom Connor: TB is predominantly a disease of poverty, although there’s potentially two billion people around the world who are latently infected with tuberculosis. So it’s a major pathogen. And one of the real concerns about TB is multi-drug resistance. So resistance to antibiotics. The TB is a bacteria rather than a virus. And so, we treat tuberculosis using antibiotics. And increasingly around the world, tuberculosis is becoming resistant to antibiotics. And so, there are two things that we do with our TB data.

Tom Connor: The first thing is we use genome sequence data to identify which drugs a TB is susceptible to. And so it means we get the right treatment straight off, and by moving to genomics, we’ve gone from a stage where a identification of resistance could take sort of two or three months, down to a point at which it now takes a matter of weeks to provide the information on what the TB you need to treat your patient. What it’s susceptible to.

Danielle Applestone: In March, Professor Tom Connor and a team from Cardiff added their resources to Britain’s COVID-19 Genomic UK Consortium, dedicated to setting up a prospective sequencing program for the virus.

Tom Connor: Yeah. There’s a load of amazing research that’s going on with COVID. We build these amazing tools and data sets for research, and the continuing challenge is how to take the best from research, translate that from an academic environment into a healthcare environment, how can we enhance and extend the translation that we’re already seeing, to improve delivery of personalized medicine in healthcare systems, using genomics. And I think that’s a real challenge, and it’s an important challenge, and it’s one which is absolutely underpinned by the HPC that enables it.

Danielle Applestone: That Professor Connor’s Cardiff team moved to the forefront of COVID research doesn’t surprise Janet Morss. She works in HPC and AI solutions marketing at Dell Technologies.

Janet Morss: He started with just startup funding, and now he’s leading an effort across all of the UK to find treatments or cures using genomics for COVID-19.

Danielle Applestone: A key to this effort is the ability of researchers to pool their findings.

Janet Morss: So one of the things I actually love about high performance computing is, really, it operates as a community, where individual researchers come together to share their data and to share their discoveries, to really push something forward. For example, in this case, pushing genomics forward in order to create more personalized medicine.

Danielle Applestone: In medicine, as in many disciplines, Janet Morss is quick to tell you the sky’s the limit, when big data is combined with high powered computing.

Janet Morss: Some people laugh and say, “What are you talking about?” But let me tell you, there were things that we just couldn’t do before, because the technology wasn’t far enough along, anything from discover new galaxies, understand gravitational waves, again, really take a look at the human genome to find out how we can provide very personalized medicine. That’s how high performance computing can make a difference.

Danielle Applestone: And what exactly distinguishes high performance computing?

Janet Morss: One way to understand what high performance computers are is to think about what’s in them. You have all the elements you’d find in your desktop, like processors, memory, disc, operating system. There’s just a lot more of them, and they’re arranged in a cluster. So an HPC cluster for a small business could have as few as four server nodes, for example. The point of having a high performance computer is so that the individual nodes can work together to solve a problem much larger than any one of them could do alone.

Danielle Applestone: Every day, stories like that of Alicia Diggs play out in treatment rooms around the world, as they have for decades. Though today, many live these stories with a confidence that wasn’t there just a few years ago. In these rooms, in these moments, precision medicine is inspiring a new confidence, a sense that, thanks to great medical minds, modern genomics, and today’s powerful technologies, this is the best time to face the toughest of health challenges.

Danielle Applestone: This is Technology Powers X. An original podcast from Dell Technologies. For more information on Dell Technologies HPC solutions, go to DellTechnologies.com/HPC. If you want to read this episode’s transcript, learn more about our speakers, and check out some great links, visit DellTechnologies.com/TechnologyPowersX. I’m Danielle Applestone. Thanks for listening.

Evan Morrison

About the Author: Evan Morrison

Evan has a passion for using digital mediums to showcase the impact that technology can have across the globe. While working at Dell Technologies, Evan has produced content and web experiences across various lines of business and continues to explore new ways to tell these amazing stories. Evan is a graduate of Syracuse University and currently lives in Burlington, Vermont.