Harsh Thakkar (00:01)
All right, welcome to another episode. My guest today is Sarah Rogers, and we are going to be diving into the world of pharmacogenomics and why this is such an important topic for the personalized medicine space. So I know you're probably wondering, whoa, pharmacogenomics, what is this? I'm not from life sciences. I don't know what this means. Don't worry, we're going to start slow. We're going to build upon the concepts.

We're also going to talk about what are some hidden obstacles that maybe we don't know about, but experts like Sarah know, and they're working towards removing those obstacles to make this more accessible to the patients. Why should you listen to this episode? I could go on and on with all the credentials about Sarah, but she is the co-founder and president of American Society of Pharmacovigilance. She is also an assistant professor at Texas A and part of

a of industry organizations and committees like the National Institute of Health. So I'll stop there. If that wasn't enough, I think you should listen to this because it's gonna be a really great conversation and let's dive in. Welcome to the show, Sarah.

Sara Rogers (01:14)
Great. Thanks so much, Harsh, for the introduction. It's great to be here. Look forward to chatting with you.

Harsh Thakkar (01:19)
Yeah, so we've had, you know, we get a lot of audience that's already from life sciences and they're probably familiar with pharmacogenomics and personalized medicine, but we also might get people that are new to life sciences and want to learn about the industry and the terms. So to start off, can you break down, how would you explain pharmacogenomics to a five or 10 year old before we go into the nitty gritty of it?

Sara Rogers (01:44)
Yeah, of course. And at ASP, we're really interested in advancing precision medicine, but really simply put that is getting the right drug for the right patient at the right time. And how can we leverage data, including relevant genetics data to navigate all of the different treatment options that are available and even be able to identify in the first place what the right medication is for a specific patient. So.

Just imagine knowing exactly how your body will react to a medication before you even take it. That's kind of the power of pharmacogenomics and it's transforming how we approach medicine.

Harsh Thakkar (02:25)
Great, that's very powerful. What if you can remember, or I'm sure you remember this, but what was like that moment in your career where you were drawn to this area of life sciences?

Sara Rogers (02:39)
So I I got my start in oncology. I was an ambulatory treatment center pharmacist at MD Anderson Cancer Center. And back in 2018, when I was at Anderson, I was working on a project with a friend of mine, Ben Brown, and it was kind of a research project. We were looking at topical preparations to treat neuropathic pain.

Harsh Thakkar (02:48)
Mm.

Sara Rogers (03:07)
And we pepped coming up against statistics about adverse drug events. And it turns out that adverse drug events are the fourth leading cause of death in the U.S. And although I trained as a pharmacist, I had no idea the extent of the problem. And so we just kind of started digging into what were the contributing factors for this. And as it turns out, the Department of Health and Human Services put out a national action plan

for adverse drug event prevention in 2014 talks about things like medication errors. Sometimes we just give somebody medication or the wrong dose, something other than what they were supposed to get and it was an accident. But not all medication errors result in harm to a patient. And it's that actual harm that's the adverse event. And what we found is that

The biggest contributor to these adverse events are actually something called adverse drug reactions, something that you and I might call a side effect from a medication. And these are medications taken as prescribed at typical doses. And that's where we find that pharmacogenetics testing can play a major role. So we filed the papers to form ASP in 2018, and our initial focus was around advancing precision medicine.

Harsh Thakkar (04:11)
Right.

So yeah, and from a patient perspective, What are some like, is there like a surprising way why understanding the patient genetics can help with the treatment or the end goals for that patient?

Sara Rogers (04:50)
Yeah, so when we do the testing, we're really looking at genes that are related to drug response. So there's these enzymes in your liver and the genes that encode those enzymes. There's drug transporters that are needed to get the medication to the site of action. There's different adverse related, event related genes where we know if somebody has a variation there that they're just more at risk for an event when taking certain medications.

So we're not looking at disease risk. We can't tell you what's your risk of cancer or how likely is it that you'll get Alzheimer's disease. But what we're really trying to do is stratify patients into these buckets of are they a poor metabolizer? Do they process that medication really slowly? Are they rapid or normal metabolizers? And then, you know, just as an example, so we run a pharmacogenomics clinic at Texas A Health in our family care clinic.

Harsh Thakkar (05:35)
Mm.

Sara Rogers (05:44)
and we're looking at polypharmacy patients. So these are people taking multiple medications, more than five medications, sometimes they're taking 15 or 20 medications. And we actually developed a tool called the Clinical Semantic Network that's running these kind of artificial intelligence algorithms, continually assessing these different inputs and all the different clinical factors that play a role and better understand the interplay between

drugs, genes, and other clinical factors. So what we find when we test patients is that most patients do have an actionable genetic finding that impacts at least one medication that they're currently taking and explains the symptoms that they're having, which aren't actually symptoms from their medical conditions, they're side effects from medications. And once we identify that, we can deperscribe or take medications off that people don't actually need.

Harsh Thakkar (06:29)
Mm-hmm.

Sara Rogers (06:41)
and optimize the regimen as a whole instead of just drug by drug or looking at a specific condition.

Harsh Thakkar (06:48)
Right, and as you're talking about testing, that reminds me based on some conversations I've had with other guests on the podcast on this topic in the past, and also preparing for this episode, going over all the work you've done in this space, that standardizing these tests, you call it like PGX tests, seems to be a massive challenge. So what's one of the...

biggest roadblocks you faced in all the work you're doing with these different organizations and the hospital, and how close do you think we are to achieving that standardization?

Sara Rogers (07:27)
That's a great question. And there's just a lot of different stakeholders involved in the pharmacogenetics testing ecosystem. If you look at the life cycle of just one PGX test, would go something like this. The provider orders a medication. It is then, you send a kit.

Harsh Thakkar (07:47)
Mm-hmm.

Sara Rogers (07:52)
to, or you take a cheek swab to get the information that you need. collect the sample, you send the sample into the lab. There's all of these different, you know, tools to run the sample. There's different assays, there's different techniques that can be used. And then there's this process that's a little bit different than other types of genetics testing, because it's not just yes, no, do they have that variation? It's also, what do we expect? the response be?

And how do we translate that response into a clinical decision? So that data analysis piece, how you get that information back into the electronic health record, and then what does the provider do with that information? And then how has the medication changed based on that information? So if you think about all of those steps in just ordering one test per patient and getting those results back, there's so many points in the process where there can be differences in approaches.

Harsh Thakkar (08:33)
Yeah.

Sara Rogers (08:48)
And there are so many different stakeholders involved in just that life cycle for that one test. So you've got payer organizations, whether or not that test is even covered, what are the protocols at the hospital or the health system where that patient's being seen? There's different regulatory groups, there's different databases and evidence evaluation frameworks. And then there's a lab which may have different panels and composition of their panel, different genes that they test.

Harsh Thakkar (08:58)
Hmm.

Sara Rogers (09:17)
So I would say, one of the biggest challenges is just because it's a slow process, it's an evolving landscape, but it's just really aligning stakeholders and developing solutions and then even prioritizing which challenges to address first as an important part of the process.

Harsh Thakkar (09:30)
Mmm.

Yeah, I'm so glad that you mentioned the ecosystem and all the stakeholders involved because I was going to ask you about how does this process look like? And you basically summed it up really well there with the insurance agencies and all the payer organizations. And also you mentioned, I want to ask you this hypothetical question. If you had the keys to the kingdom and you wanted this to be extremely seamless, fast adoption,

the whole workflow to run like a well-oiled machine, what are some of the levers or changes that you would make or you think should be made to make this more accessible?

Sara Rogers (10:21)
That's a great question. I think one of the focuses for us have been around evidence evaluation. And we're really finding that although we have the same body of evidence, we all have access to the same studies, we may interpret that differently and come up with a different recommendation based on how we as unique organizations or clinicians interpret.

that evidence and I think anybody that was working in pharmacogenomics 2018, 2019 will remember the safety communications that FDA sent out to laboratories offering the testing because of these differences and how the test results were being translated into a clinical decision and that information was being given back to providers. And so that's how we initially

And at the time, one of the recommendations from FDA was that the community come together and establish what's called a collaborative community. And that's the STRIPE initiative. So it stands for Standardizing Laboratory Practices in Pharmacogenomics. It's collaborative communities of framework that FDA Center for Devices and Radiologic Health set as a strategic priority to participate in 10 collaborative communities.

Harsh Thakkar (11:21)
Mm-hmm.

Sara Rogers (11:39)
for 10 different medical devices. So Stripe is kind of the collaborative community for pharmacogenetics testing. We also have CDER, the Center for Drug Evaluation and Research that participates in Stripe through a separate mechanism to engage with stakeholders called Public-Private Partnership. And, you know, that's been our platform to bring together stakeholders, which are not only individuals, they also represent

Harsh Thakkar (11:54)
Mm-hmm.

Sara Rogers (12:04)
their organizations and serve as a liaison between Stripe and their organization so that we can develop solutions that are helpful to all of the different stakeholders that are part of the ecosystem.

Harsh Thakkar (12:16)
Yeah. And, you know, this constantly amazes me because, you know, patients or just people who are not in life sciences, to them, they don't really get a full picture of, you know, how a drug or a medicine goes from the initial research in a lab to a pharmacy or a hospital, right? But this type of conversation that we're going into, as you're talking about all these different organizations, the FDA, the communities,

I love this because this helps people understand like, it's not easy. This is why it takes, you know, 10 years, 15 years to get a drug or medicine to market unless, you know, it's a very rare drug where you're going to get some faster timelines and stuff from the regulatory agencies. Otherwise there is a lot of cooks in the kitchen, so to speak. Yeah. So

Sara Rogers (12:58)
Mm-hmm.

Right, yeah.

Harsh Thakkar (13:13)
I want to go back into the previous topic about adverse events. So you mentioned about adverse events, but I wanted to ask you, do you know any real world examples or something that you've seen where doing this genetic testing or doing the pharmacogenomics has actually helped prevent the adverse event or maybe reduced the severity of what happened after the adverse event?

Sara Rogers (13:40)
Classic example that comes to mind is clopidogrel or plavix. That's something a lot of people take. Maybe they've had a heart attack or a stroke and it kind of thins your blood. It prevents you from having additional events. It's standard of care to receive a medication in that class of drugs. And most people may not know this who take the medication, but there's a black box warning on the drug label that says, if you are a

Harsh Thakkar (14:06)
Mm.

Sara Rogers (14:08)
poor metabolizer of cytochrome 2C19. It's an enzyme in the liver that basically activates that drug into the form that has a therapeutic effect. So if you can't process clopidogrel and turn it into its active form, you're never going to have benefit from taking that medication. And what they found is that it's not a rare variation. In fact, 30 % of

Pacific Islanders are poor metabolizers for cytochrome 2C19. And the state of Hawaii actually sued the manufacturers of clopidogrel for not making that information available because of all the significant increase in events because they weren't adequately receiving the therapy that they needed. And there's a lot of use cases like that where it's, you know,

Harsh Thakkar (14:42)
Hmm.

Sara Rogers (15:07)
one gene, one enzyme that's really contributing a lot to whether or not you're going to have side effects or whether or not it's going to work for you. And that's kind of one example that is really, I think, a strong example.

Harsh Thakkar (15:20)
Yeah. And, yeah, that's a really good example. And again, this is, you talked about labels and black box warnings. Very few people are going to read the entire label start to finish. mean, they might read the directions or stuff like that, the basics, but I've seen some labels are like, you basically peel off and it's like the small print and it's tons of stuff.

But it is important, as you mentioned, that's a great example. I also wanted to go into a different area about electronic health records. You also mentioned that earlier on and you said how important it's to integrate the, integrating the pharmacogenomics into the electronic health record. So if you were to imagine a scenario where, you know, doctors or providers had

all the data at their fingertips instantly available, what do you think is an outcome or a breakthrough that would happen if that were a possibility?

Sara Rogers (16:31)
That's a great question. And for me, I think it's extremely important to have the information and what I think not just with pharmacogenetics testing, but with different types of laboratory tests. They're not integrated. That information is not integrated into the EHR in the same way as other types of data. And often we'll get this kind of PDF report that may be uploaded. It may have been ordered a while ago. We may not have be aware of that.

Harsh Thakkar (16:47)
Mm.

Sara Rogers (17:00)
at the time that medication therapy is being considered for a patient. So, and I mentioned a tool that we developed, it was kind of a separate EHR. What we're doing now is building those tools into the EHR that the clinic uses. And we're looking at an integration that will actually take the results from the report and put it directly into the laboratory section. And if a medication is going to be prescribed,

Harsh Thakkar (17:25)
Mm-hmm.

Sara Rogers (17:29)
where there's relevant information, there would actually be, that would be flagged. And then the provider can go in and see what is that interaction? What are the alternatives to that? And be able to leverage that information at the point of prescribing. I think the next step is also how do we integrate all of the different clinical factors? Because while genetics information is a really important factor,

It's one of many factors that can impact a given drug. So bringing all that information together, I think will be kind of the next step after having that information at the time that it's needed.

Harsh Thakkar (18:08)
Yeah. And again, you know, we're getting more and more connected in all areas of life sciences, especially wherever there's data. And, know, with the rise of adoption of AI and machine learning, we're seeing a lot of examples where data is processed or extracted or converted or made available. So I'm seeing a lot of these examples, and maybe this is one use case where we'll see a lot of movement in the next five or 10 years.

Sara Rogers (18:40)
Yeah, and I think that's what's really exciting about AI is getting to a point where we can predict adverse drug reactions before someone ever even takes that medication. Right now we're at a point where we just need to be able to realize when a patient's having a side effect versus a new condition. So I think there's a lot of interesting opportunities. One thing that we're looking at is a concept called digital twins.

Harsh Thakkar (18:49)
Mm.

Sara Rogers (19:09)
where you can create kind of a computational analog of a patient or a population and kind of test your medication on this digital twin so that the twin has the reaction versus the patient. So that's something we've been interested in.

Harsh Thakkar (19:26)
Interesting. Okay. Yeah, I have heard of that term, but I had never, I never dug into it, but I'm going to after this episode. So there is this phrase, you know, if you want to be an expert in something, spend 10,000 hours or, then you'll be an expert. I don't know if that's true or not. And I don't know if you've spent, maybe you've spent 10,000 hours or more in pharmacogenomics in your career. But the question I have for you is,

When you look at your career today, is there a specific lesson you've learned from your day one into this space and today that maybe nobody told you about when you started in this field?

Sara Rogers (20:11)
For me, and I went to pharmacy school maybe more than 10 years ago, we didn't learn about pharmacogenomics. And I think there's a lot that you don't learn in school, but when you get out into practice and you get out into the real world, you start to observe these problems. And for me, I was fortunate because I found a problem that was really compelling for me and my training as a pharmacist. felt like that was something that was really my responsibility to try to tackle.

Harsh Thakkar (20:27)
Mmm.

Sara Rogers (20:40)
But what I would really say is the way that I've really learned a lot is by saying yes to opportunities. So if there was a chance to participate in a committee, maybe I'm not an expert, but by joining that committee, getting involved in tackling whatever the charge of that committee is, you do that on the fly research and that's how you slowly build up your 10,000 hours. It's not necessarily gonna be.

you know, what you learned in college or, you know, kind of some of your initial training, it'll be really rolling up your sleeves when there's a problem right in front of you that you need to figure out how to solve, because no one's going to tell you how to solve the problems. It's just that process of learning from others and learning on your own.

Harsh Thakkar (21:29)
Yeah, and I 100 % agree with that because I've shared that same advice with tons of people who've asked me and you have to, like you said, be willing to say yes to tons of opportunities, especially when you're learning or you want to get access or get close to the other people who are also in that same phase. Because if you don't say yes, you're not gonna be in that room or that organization or that committee and...

people often feel like they have to have the 10,000 hours before they can be an expert. And that's, to me, it's not true. You become an expert by saying yes, failing, experimenting over and over again. You don't have to wait until you get those 10,000 hours. So I'm glad you shed light on that specific one.

Sara Rogers (22:17)
It's

so true. And I was actually talking to a friend of mine who's a collaborator in the Stripe Initiative, Ryan Nelson. He's a medical director at ARUP Labs. And we're just kind of talking about how life is kind of like a game of Plinko. And I don't if you know the game Plinko, but it's, you might have a slot that you really want to hit. You can position your chip to go into that slot, but you get kind of nudged and bumped and redirected along the way. I mean,

Harsh Thakkar (22:24)
Mm-hmm.

Yep.

Sara Rogers (22:44)
These kind of opportunities present themselves in ways that you might not expect or imagine. And so you have to be able to adapt and pivot while keeping that broader goal in mind.

Harsh Thakkar (22:55)
Yeah, absolutely. so that's a very powerful lesson. And now when you have devoted all this time, you're part of so many different organizations and committees, you are talking to dozens of experts in this space. When you see the future, maybe five years, maybe 10 years, I don't know how far you're reflecting or what you're seeing, but

If there is one thing that you maybe wish to see in this space, whether it's in pharmacogenomics or personalized medicine, is there something that you feel is about to happen that you're excited about, or is there something that you feel should happen, but you don't know when and if it will happen?

Sara Rogers (23:48)
I think just in terms of the landscape, something that's really exciting is the advances with sequencing the human genome. we think about, it's been about only 20 years and the scope of things, it's not a huge amount of time that the first genome was sequenced and it costs, I don't know how many hundreds of millions of dollars to sequence that one genome. And now,

they can do it for a couple hundred dollars. So thinking about, you know, could we start, you know, getting full human genome sequences for people and using that to interrogate at the time that they need it. So maybe now we're prescribing a medication, maybe in the future we're trying to figure out, you know, if they're a candidate for, or they're at risk for breast cancer, a candidate for a certain type of, you know, breast cancer treatment, that type of thing. And just,

really having that information available when it's needed, I think is something that seems futuristic, but, there are going to be challenges to implementing something like that, but I think we're getting closer and closer even just with the costs going down.

Harsh Thakkar (25:03)
Yeah, yeah. No, that's a very good point. also the human genome understanding that has given rise to a bunch of different types of companies and startups. So because it is such a big topic and it has such a broader impact. I've definitely heard that same sort of excitement from other people in other spaces in life sciences.

Yeah, for anyone that maybe knew a bit about pharmacogenomics and after this conversation, they know a lot more, or for somebody who didn't know anything and maybe they got a glimpse of what it actually is and how things work, maybe they want to know more about the organizations that you're working with or read some of your stuff, stay in touch. What's the best way for them to get access to you?

Sara Rogers (26:02)
So we're on LinkedIn, American Society of Pharmacovigilance has a LinkedIn page. Stripe has also a separate LinkedIn page. We're doing a big meeting later this month in kind of the DC area. It's gonna be a consensus development conference. So we're taking on a lot of these topics, bringing everyone together. We're on Twitter at amsocietyfarm. And we also have a newsletter as well.

definitely encourage people to sign up for the newsletter.

Harsh Thakkar (26:35)
Okay, yeah, and we'll put all those links in the show notes so it's easily available for the listeners and viewers.

Sara Rogers (26:43)
Great.

Harsh Thakkar (26:44)
Before we drop off, thank you so much. It's been pleasure talking to you and learning more about this topic. If there's one thing you want people to take away from this episode about pharmacogenomics or healthcare or personalized medicine, what's your final word?

Sara Rogers (27:05)
The biggest takeaway for me is really just to advocate for your health. We're all users of healthcare and your healthcare team is making decisions based on the information they have, but they may not always have the information they need to make the best possible decision. So ask about side effects and warning signs anytime you get a prescription and ask about pharmacogenetics testing. 99 % of us have a genetic variant.

variation that's going to affect how we process medications, which may lead to a different medication or a different dose that will be a good option. you know, if you get the wrong medication, you're the one that's going to be impacted. And so just always ask questions and we have to just really be vigilant when it comes to our health.

Harsh Thakkar (27:53)
All right, yeah, that's a very important message is to ask questions and be more involved because as the industry's going, we're getting more and more patient-centric and the patient has a lot more power to decide or make informed decisions with technology, apps, and so on. So yeah, that's a powerful takeaway.

And that's all we have for today. I hope you learned something about the topic of pharmacogenomics and how Sarah and all the other stuff that she's doing in the industry, all the whole ecosystem, the stakeholders. I hope you found some value there. So if you want to stay in touch and listen to some of our future episodes, please follow us on Apple and Spotify. And if you want to watch these episodes, go ahead and subscribe on the YouTube channel. We'll link everything in the description below and I'll see you in the next one.