How Whole Genome Sequencing Unlocks the Potential for Personalized Prescription Drugs. A Conversation Between Nebula Genomics CSO Sam A. Beeler and Stanford University pharmacogenomics expert Dr. Russ Altman
Pharmacogenomics – a burgeoning field of research that sits at the intersection between pharmacology and genomics – is already making it possible for physicians to treat dozens of conditions with greater confidence and precision. The implications for better health outcomes for individuals and economic upside for the entire healthcare industry are profound. Whole Genome Sequencing (WGS), the process that decodes 100% of human DNA, provides healthcare professionals with the insights they need to make drug prescriptions as personal as any given patient’s unique genetic makeup.
In this second installment of Nebula Insider, Nebula Genomics Chief Strategy Officer Sam Beeler explores innovations in pharmacogenomics with Dr. Russ Altman, professor of bioengineering, genetics, medicine, biomedical data science and (by courtesy) computer science at Stanford University. Dr. Altman’s work includes research into drug action at molecular, cellular, organism and population levels. He was the founder of PharmGKB, a resource of information about how human genetic variation impacts drug response.
The Interview
Sam A. Beeler: Thanks for joining me today, Dr. Altman. Since pharmacogenomics is a new idea for a lot of people, can you explain it in simple terms for someone who might not be familiar with it?
Russ Altman: Sure. Pharmacogenomics is the study of how genetic variation creates differences in the way an individual responds to medications. Traditionally, when you take a prescription drug, you hope that it works. But everybody knows that they have their own personal response to the drug. Part of that is due to what they ate that morning. Part of it may be due to what disease they have. And part of it is due to their genetics. In fact, you inherit your response to drugs in the same way you inherit your height and hair color from your parents and grandparents. But we don’t usually sit around the family table and discuss how grandma responded to her medication. So, through pharmacogenomics we can understand and predict how you might respond to drugs differently by understanding how your DNA is different.
SB: So, this is truly changing how a physician might treat any given patient. How common is the use of pharmacogenomics in practice, right now?
RA: It’s a great question because some people think that it’s only one or two drugs where it really matters. But there are hundreds of drugs for which we can measure your DNA and make the necessary adjustments in how we prescribe them. Sometimes this means don’t take that drug. Sometimes it means it’s okay to take that drug, but at a dose that’s different from the label. And sometimes it means we need to be careful about side effects. So, this is possible now for hundreds of drugs because, for a reasonable cost, you can analyze genomic data to make these kinds of decisions. That’s where we are today.
SB: In some ways though, all of this is just a taste of what will be possible in the future. Right?
RA: Exactly. The science of genomics moves fast. So, currently most of our readouts are in what we call common genetic variations, the variations that we see quite often among the population. In the future, pharmacogenomics will allow us to understand the relationships between rare variants and hundreds of different pharmaceuticals. Rare variants are DNA changes that might be present for a relatively small percentage of the population and may even be unique to you or your family. Our ability to interpret those today is a limited because we haven’t developed the technologies to figure out what those rare variations mean at a large scale. But that’s where all the research is happening right now – and as we’re able to understand rare variation, we can bring a complete knowledge of pharmacogenomics to every individual.
SB: I see a clear parallel between bringing a comprehensive knowledge of pharmacogenomics to every individual and Nebula’s mission of bringing a comprehensive knowledge of the human genome to every individual. Let’s talk about why Whole Genome Sequencing – the kind of genetic testing we do at Nebula to decode 100% of a person’s DNA – is so important for pharmacogenomics.
RA: Whole Genome Sequencing is a game changer. I was just speaking about the rare variation. The only way to discover that rare variation is to sequence the whole genome. If we focus only on areas we already know are important for drug response, we may not even look at new areas that might have an important variation relevant to drug response. On the other hand, when we have a comprehensive picture of your entire DNA sequence (and that’s what whole genome sequencing provides), we can identify, evaluate, and act on every variation that might impact your health. And let me say, we call it ‘rare variation’ – and that might make it sound like it’s not as important as something that we’d call common. But for the person who has that variation, it’s not rare. It’s your biology, it’s how your body works, and you and your doctor need to know about it.
SB: You’ve sold me on the importance of Whole Genome Sequencing. How might this change my experience of personalized healthcare?
RA: Great question. So, let me just review how medicine has worked for the last 50 or 60 years. Physicians learn how to use a relatively small set of drugs – 20 to 30 drugs that they prescribe all the time. They know what conditions they treat; they know what dosages are effective and how they interact with other drugs; they get to know the side effects; they use them with a high level of confidence but can’t perfectly predict how any given patient will respond. That’s why you typically go back to see your doctor a short while after starting on a new medication. In the future, as the physician is making the prescribing decision, they’ll use software – a digital advisor, if you will – that helps them understand how the unique genome of the specific patient determines which drugs should work best, what dosage should be most effective, which side effects are most likely, and what medications to stay away from altogether. Now, rather than being limited to the 20 to 30 drugs they know, doctors will be empowered to make much more precise decisions about prescribing every drug on the market. This results in more patients having a better experience with their medication.
SB: If you don’t mind, I’d like you to take us through a specific example. Cancer is a terrible disease that affects so many people, both directly and indirectly. What are the implications for cancer care when you add Whole Genome Sequencing and pharmacogenomics into the mix?
RA: So, dealing with cancer is interesting – and I use that word with full respect for how serious this disease is. You have not one but two genomes to think about. You have the genome of the cancer itself. Cancer is derived from your body, but it has mutated and has new dangerous properties (like uncontrolled growth and metastasis). And then you have the normal genome of the patient that is going to determine a lot about how they respond to drugs. In cancer, the doctor’s first prescribing decision is vital, because we know that we have the best chance of killing the cancer when it has never yet seen a medication. You want to hit the cancer hard and with precision from the very start. After that, when it has seen various medications, it can start to develop resistance, and treatment gets harder.
So, in the future of cancer therapy, we’re going to sequence the genome of the cancer to see the mutations that indicate where it might be vulnerable to which treatments. Then we’re going to sequence the host genome (the genome of the patient), mostly to be certain the patient can metabolize the medication fast enough, so it gets out of their system without causing kidney disease or liver problems. This combination of how the genome of the cancer responds and how the genome of the patient responds allows us to make better first treatment decisions. And then of course, we use the same logic to prescribe any other treatments required down the line.
SB: Unfortunately, cancers are common so the potential for genomics in that area are huge. Can you share your thoughts on why Whole Genome Sequencing is just as important for rare diseases?
RA: Absolutely. Whole Genome Sequencing is also a game changer for rare diseases for two reasons. First, we’ll be able to diagnose a rare disease because we’ll have the whole genome, along with the complete rundown of the patient’s symptoms and signs and history. And those two things together have already been shown to be very effective for finding the responsible changes in the DNA. So, significantly improve the probability of making a definitive diagnosis–even if there’s no current treatment a clear diagnosis has a benefit to the patient and their family because it ends their search for a cause. But the second thing is on the treatment side. It may be hard for pharmaceutical companies to put in the capital to generate novel drugs for diseases that are rare because they feel that the market just isn’t there. But we do have this idea of drug repurposing. If we can understand the specific genetic variants that cause a rare disease, we might be able to identify ways that existing drugs can be used to treat them and create entirely new markets for these existing medications.
SB: This is fascinating. Now as you know, Nebula is committed to making clinical-grade Whole Genome Sequencing accessible and affordable for billions of people around the world. Given that context, I’d like to pivot from personal wellness to population health. What do you see as the implications of pharmacogenomics through the lens of population health?
RA: We’re expecting that, in general, the effectiveness of the drugs that we choose will increase, which means that patients will have a better experience with their healthcare providers. They will, I think, gain more confidence that the healthcare system is working for them. You could imagine a whole new world of patients who no longer avoid going to the doctor, who see how well more informed prescribing decisions are working for them, and who feel that they can trust their doctors more. They can trust the whole healthcare system more. They’ll experience better, faster outcomes because all the time spent picking the right drug and right dose is reduced. The cost of quality healthcare will likely decrease too because the patient is getting the right drug on the first try and are not pouring multiple unsuccessful pills down the toilet every time something new is tried.
SB: There’s so much opportunity here, so I’d like to break it down a bit more. As you were speaking about population health, you began talking about the healthcare system too. You touched on some of the ways pharmacogenomics can build a better healthcare business. When you think about the various players that make up the business of health, what do you see as some of the biggest transformative effects – starting with providers?
RA: So, as I said earlier, a doctor might know 20 or 30 medications well – and now, you’re asking them to think about hundreds or thousands of drugs. Surveys show that doctors are extremely interested in using genomics to make better prescribing decisions. They want the best for their patients. But they also don’t feel prepared. So, we need to educate physicians (and all clinicians) through the medical school curriculum and professional education to use genetic information in this way. I also think we’re going to see an increased role for pharmacists. Pharmacists are a great resource. They care about drugs; they know about drugs—and they sometimes have more time to focus on the patient’s drug therapy than the physicians. So maybe we’ll have a world where there’s more communication and coordination between physicians and pharmacists who work together to make the best possible prescribing decisions, avoid potential drug interactions, minimize side effects, and deliver better health outcomes. And I think clinical decision support systems that help physicians and pharmacists identify the right medication for a given patient will reassure them that they’re making smart decisions.
SA: That all makes sense. How about payers?
RA: They should love pharmacogenomics because they know that inappropriate medications cost them hundreds of millions of dollars each year. Beyond the cost of the drugs themselves, patients with inappropriate prescriptions tend to see doctors more often than necessary. They might even be hospitalized because of adverse drug reactions. All of these can be reduced because of pharmacogenomics. The best part is that there’s a real alignment of interest here. The individual wants to take the minimum number of medications to get the results they need. Their provider wants to deliver the best possible health outcomes for their patients. And the insurer knows that healthier patients who are experiencing better outcomes are less expensive to manage.
SB: We’ve covered a lot of ground here. Before we wrap up, I’d love to know what excites you most about your work in genomics.
RA: I feel extremely privileged to be working at a time when two amazing streams are joining one another. The first stream is our ability to collect genomic data completely. Whole Genome Sequencing is the end of the discussion. It’s every piece of DNA in your genome, measured and stored securely. The second stream is artificial intelligence. This is a huge thing because it allows us to think about the analysis of that data with the most powerful algorithms that can identify the most important things for health. I’m excited about the future in which an AI-powered analysis of your genome – again stored securely and applied ethically – is going to create across-the-board benefits for health. And that really should accrue to every human because whole genome sequencing is becoming more accessible to a level where no matter where you are in the world, and no matter what your socioeconomic status is, your healthcare system should be able to put together a plan to get that data for you in the near future. And in some places, it will happen within the next five years.
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About Russ Altman, MD, PhD
Russ Altman is the Kenneth Fong Professor of Bioengineering, Genetics, Medicine, Biomedical Data Science and (by courtesy) Computer Science, and past chairman of the Bioengineering Department at Stanford University. His primary research interests are in the application of computing (AI, data science and informatics) to problems relevant to medicine. He is particularly interested in methods for understanding drug action at molecular, cellular, organism and population levels. His lab studies how human genetic variation impacts drug response. Other work focuses on the analysis of biological molecules to understand the actions, interactions, and adverse events of drugs. He helps lead an FDA-supported Center of Excellence in Regulatory Science & Innovation. Dr. Altman holds an AB from Harvard College, an MD from Stanford Medical School, and a PhD in Medical Information Sciences from Stanford. He is the host of the “Future of Everything” podcast. Dr. Altman serves as an advisor to Nebula Genomics.
About Sam A. Beeler, MBA, MS
Sam A. Beeler is Chief Strategy Officer at Nebula Genomics. He is an accomplished healthcare executive with over 18 years of leadership experience spanning multiple ecosystems, including hospital-based medicine, multi-specialty private practice, clinical research, and community health. Sam has served in progressive enterprise leadership, strategy, and operations roles for The Advisory Board, Advantage Care Physicians, TeamHealth, PivotHealth and more. He is the co-founder of a disruptive clinical research and human performance laboratory with clients that include championship athletes from the NFL, NHL, and MLB, gold-medalist Olympic athletes, the United States Navy Seals, and high net-worth clientele from around the world. He was also appointed as Director of Health & Human Services for one of the most densely populated cities in the United States. Sam holds an MBA from Cornell SC Johnson Graduate School of Management, a Master of Science in Healthcare Policy & Research from Weill Cornell Graduate School of Medical Sciences, a BA in Philosophy from Rutgers University and has completed executive-level coursework at Harvard Business School on Sustainable Business Models.
