Greg Kefer: (00:07)
Welcome to Digital Conversations. I'm Greg Kefer. And today I'm joined by Nik Kolatkar VP of Evidence Generation, US Medical Affairs at Genentech. Nik, it's great to have you on the show.
Nik Kolatkar: (00:20)
Thank you so much, Greg. Great to be here.
Greg Kefer: (00:21)
So Nik, we're going to have a great chat about what Genentech is doing in the realm of clinical trials, which, you know, I think everybody in the world knows about based on the whole COVID thing last year, but before we get started, I thought maybe you could just level set. I think everybody knows about Genentech, but they probably aren't aware of exactly what you do in your respective roles. So maybe you can just talk about what you do, and what Genentech does in the clinical trial arena before we get started.
Nik Kolatkar: (00:49)
Sure. So Genentech is the world's largest biotechnology company and really one of the first large biotechs in the world that really pioneered the industry and has really developed a number of pioneering therapies, you know, over the years, and really focuses on innovative first-in-class best-in-class medicines for patients. So it's really a great mission the company has had from its beginning and through its merger with Roche, now also has global scale. So it really has, you know, one of the largest footprints throughout the world in terms of clinical research and clinical trials. And historically our portfolio has been largely focused in oncology. That's the biggest part of our portfolio, so cancer medicines, but we increasingly have a number of medicines in other areas as well, such as neuroscience, ophthalmology, eye disease, and other areas as well. So within Genentech, I work in a group called the us medical affairs, which is focused on the us and really focused on trials that are after a drug is approved. So there are all of the trials that are needed for the FDA and for global regulatory agencies to get drugs approved. But then once drugs are approved, there are many times additional trials that need to be done to help answer questions that physicians have. And to also help answer questions that payers have to reimburse medicines. So my group leads a portfolio of almost 500 clinical studies within us medical affairs, Genentech, and the bulk of those are actually investigator initiated studies. So studies that are run by investigators that Genentech funds through grants and financial support. But we also have a number of studies that we run ourselves. They're so-called sponsored studies and we have around 30 of those. So I lead the group called evidence generation and my group really has end to end capability to execute, you know, all of these trials and not only to execute them, but to design them from the beginning and to analyze the data. So we have statistical scientists in my group. We have data scientists, we have experts in artificial intelligence, machine learning. We have clinical operations experts as well as experts in clinical trial systems and technologies.
Greg Kefer: (03:05)
Wow. It sounds complicated. You know, I'm not a clinical trials guy. I mean, I think the world got a dose of the clinical trial world, I guess, pre FDA approval last fall, right. Where the race to get a vaccine was on and everybody was clamoring for this to be done. And it was done at amazing warp speed. You know, I'm sure people in your shoes were amazed at how fast those things came to be. But also, you know, one of the challenges that came out and was also in the headlines was just the ability to, you know, bring the underrepresented communities into the trials because they were disproportionately affected by the disease. But I've got to imagine that's been a challenge with clinical trials forever that, you know, sure, it was headlines in fall of 2020, but that's probably something you've been dealing with for a long time. Is that a fair statement?
Nik Kolatkar: (03:55)
Yeah, you're right. I mean, I think very much, I think it opened people's eyes, you know, as the pandemic was emerging, the world started to see that there were differences in outcomes between certain race and ethnic groups. And there are probably many reasons for that, but we needed to understand why, but, you know, unfortunately, as you said, I mean, what was emerging was many of the clinical trials that were being done in COVID, you know, unfortunately weren't including some of the patients who had some of the worst health outcomes, particularly, say African-American or black patients as well as Hispanic or Latino patients. So I think it opened the industry's eyes and it certainly opened our eyes as well that we need to do more as part of our routine way that we do clinical research to include underrepresented patients. So that the trials that we do are more representative of people who have the disease. That's ultimately what we want to do. And COVID, we actually really put our money where our mouth is so to speak. And we did a dedicated underrepresented minority study in COVID patients with COVID pneumonia. Uh, this was called Impacta, and this trial was very unique in that 84% of the patients were from minority populations. So over half were Hispanic or Latino, uh, about 15% were black and 13% were native American, which is another group that often is missing from clinical studies. And the great thing about Impacta, was that it helped answer some of these questions that the scientific community had. And, but it also showed to us that we can enroll diverse populations in trials without it coming at the cost of speed. Because I think there had been always this concern that, yeah, we can get a broad population in our studies, but it's really going to slow things down. And in fact, in Impacta, we recruited that study in record time was actually the fastest study Genentech has ever done. Um, and it went from the protocol concept to published in the New England Journal of Medicine in six months, with a positive study. So really, you know, it showed that we can enroll diverse patients in record time, and with high quality.
Greg Kefer: (06:01)
Right. I've read that, you know, a lot of the challenges, you know, maybe you see the same thing are things around recruiting and getting diverse communities into these trials, you know, issues around trust, the cost... You know, if they work on a, at a factory or, you know, they got to take a whole day off for a one hour appointment, and just the education dimension, just understanding what they're signing up for are all big, big challenges in that arena. Is that what you've seen? Or are there other dimensions in play?
Nik Kolatkar: (06:28)
Yeah, that's very much right. I mean, we saw this and Impacta too and really to be successful in reaching many of these underrepresented patients, you need to really take the clinical trials to where the patients are. Because I think historically the paradigm for clinical trials have been that patients need to come to these ivory tower academic centers and the patients need to come to the trials, but we know that most of the care in medicine is delivered in the community and that's where patients are. So, really with Impacta, we went to sites that were non-traditional clinical research sites or at sites that saw large numbers of underrepresented patients, but weren't necessarily big participants in clinical research. And we helped equip them with the infrastructure they needed to do the studies as well as the soft skills, because I think that's very important. You know, the materials need to be very easy to understand they need to be potentially in multiple languages. And even the investigators, oftentimes, you know, the training is critical so that the trials are presented in a culturally sensitive way. Because as you said, sometimes there's a mistrust in various communities about clinical research. But if it's explained in the right way, you know, people understand them, and really many times they want to be part of helping advance science and helping bring some of that science back to their own community. So we had to include all of that as part of our Impacta study. And it really opened our eyes that we need to make this more of a routine part of the way we do studies moving forward. I think the other piece that is super helpful now is technology, right? Because I think technology now can really help in this mission of bringing clinical research to where the patients are.
Greg Kefer: (08:12)
Yeah. You just preempted my next question with that, because when you say, you know, reaching patients where they are, you know, that has total technology implications and, you know, this podcast is a healthcare technology podcast. So we talk about this all the time and often draw comparisons to travel and retail and banking. If you just think over the last 10 years, you know, how much it's changed, you know, I think you mentioned the other day when we talked about banking and how different banking is today than it was in 2009. You know, that's not that long a time yet. It's totally different. Yet healthcare in general is... I think it's a decade behind, I think it's a full decade behind retail. And I happened be in the retail industry before this job and saw this thing called Amazon, come onto the scene and watch all these bricks and mortar retailers scramble. And their solution was to set up an e-commerce site on the web. And that wasn't enough because Amazon was already well on their way to mobile. And you know, when you think about diversity and hard to reach communities and mobile, a lot of them don't have a laptop with a home wifi network. Their phone, their smartphone is their connection to the world. And, you know, I've got data that shows penetration rates in the 85-83% range. So it feels like that's the place to go in order to provide that capability yet, I'm not sure the industry has totally figured out exactly how to do that. Um, and I think you're on a path to do it a different way than say, building a big elaborate app that's complex and hard to use, and you've got to download and set up an account and password. Maybe you could talk a little bit about that vision that you have that you're executing against.
Nik Kolatkar: (09:55)
Sure. That's right. Yeah. And as you said, I mean, I think we've seen the benefits of leveraging technology to help meet customers where they are in other industries, you know, as you said, banking, I mean, it used to be that, you know, everyone had to go to the branch, and you had to do everything in the branch and you had to wait in line there and you know, and now through mobile banking, I mean, many people, I can't even think of the last time I've even been to a branch. And so it's much more convenient, and a better customer experience, and more efficient. I think there will always be the need for bricks and mortar places, right? Because I think the interpersonal interactions are important. Face-to-face contact, you know, is important for some people. So even with the banks, you know, they haven't just completely disbanded their branches, but they've changed them so that the branches themselves are focused on certain tasks. Whereas certain tests are, you know, focused on the mobile platform and same thing in retail. But, as you say, I think in clinical research and even in clinical medicine, I think it's still a number of years behind, but I think now there's been a Renaissance in terms of healthcare, you know, starting to at least take some steps to finally catch up and the industry is also having to solve, how do you do that within a highly regulated environment? So how do you create, you know, mobile exchange of healthcare data that, you know, people aren't going to be worried about it getting hacked, right? Or the data getting stolen or something like that. And it's going to be acceptable to the global regulators. So there's a lot of behind the scenes pieces that need to be worked out from a technology perspective, but that's starting to emerge now and you're starting to see companies really whose whole business model is really to help provide solutions for pieces of the puzzle. So it might be instead of having a traditional paper consent form, you know, that a patient has to read a 20 page document, they have to be in the clinic, read it and sign it, you know, that can be delivered electronically through an app with a video of somebody explaining it and easy to use language and electronically signed by the patient at their home. So there are examples like this that are pieces of the puzzle. I think what we're trying to do though, is also think about how do we create a very seamless experience for the patient, right? Because if a patient is having to go to one app for this, you know, another app for this, another app for this, it's likely they may just get lost in all of that. Um, so, you know, it's almost like how do you create the glue that kind of helps stitch that together? How do you create almost a digital navigator, you know, to help patients while they're in a clinical study to make it very easy, and also, how do you also use that to maybe get a quick pulse of the patient experience during a trial? Right. So because many times, you know, historically we had done studies and at the end of the study, we've sent out surveys saying, oh, you know, how was your experience in our trial? The only problem with that is by that point, it's too late for us to do anything about it. But now with technology, there's also a very easy, low friction way to get a sense of the physician and the patient experience during our trials. So we can actually take action and do something about it.
Greg Kefer: (13:08)
Yeah. We often have guests on the show that are from healthcare providers that often are faced with the very same challenges. And it was funny cause as you were describing signing forms and things, you know, Banner Health for example, is virtualizing waiting rooms. They've they discovered during COVID that the waiting room, well, they had to open and they couldn't have waiting rooms with a bunch of people infecting one another. So they virtualized the whole thing and did all of that in advance through a mobile chatbot and handled all the forms and rolled it out across a thousand clinics. And it sounds so similar to what you just described because at the end of the day, it's all about getting somebody to do something successfully and whether that's, you know, enrolling in a trial or showing up for an appointment or checking in, it's not that different than if you had just seen a doctor and they wanted to follow up with you and make sure you're taking your pills on time. So it's very similar. Do you look across the aisle at healthcare providers and try to mimic or aspire to what you're seeing over there?
Nik Kolatkar: (14:09)
Yeah, very much so. I mean, I think clinical care and healthcare in general, I think also, as you said, it's still a little bit lagging behind in some of the use of the technologies, but it is catching up. I mean, I've seen, for example, a One Medical, you know, the listed company that is really trying to sort of have a technology-first healthcare experience. And you know, we've looked at that and the app they use and how they make the sign-up very user-friendly and the whole process is just very user friendly. So we're trying to bring some of that same thinking in, into our clinical studies. And, um, I think, you know, you mentioned chatbots, I think that's another thing we're looking at and we're actively working on is, you know, can we use a very conversational chatbot, and the nice thing about that too, is that almost everybody is familiar with text messaging, right? And you don't need to get into complex apps and, you know, download things onto your phone and, you know, it's just a very seamless way to, so we're trying to see, can we use chatbot technology to help form this glue to be this digital navigator. So that it can, say, okay, you know, "This is the electronic consent. Let me show you a video, just click here in the chat," ask a few quick questions around, do they understand certain things, electronically sign it, then the chatbot can also ask them, "Now that you've signed the consent, would you like to schedule your appointments?" Right? Um, can help schedule the appointment if they do need to come into a physical site, they can work to even arrange transportation. Right? So we're working with a company, for example, called Ride Health. That is a sort of Uber like kind of application for healthcare. But, "Do you want to schedule your ride pickup, you know, to take you to your clinic visit?", just making it a very seamless user-friendly experience. And chatbots, I think can be a great tool to serve as this kind of digital navigator and glue to stitch everything together.
Greg Kefer: (16:03)
Yeah. Chatbots, you know, I think I've used the word chatbots on the Digital Conversations podcast, about 500 times over the past couple of years, it's a, it's obviously a topic that's near and dear to our hearts. And I don't think the market fully understands what those things are. I think that, you know, a lot of people, when you say chatbot, they think, oh, I go to a website and this little thing pops up in the lower right corner. It says, "How can I help you today?" And you type in some question and it might or might not understand you. And normally it'll give you a link to a PDF or a webpage, but what you're describing is something very different. I mean, you hit on it a little bit, but this idea of messaging and language, which of course takes away the hurdle, the friction of learning a user interface. And it's also using the native capabilities of a phone, you know, that SMS and browsers and maps and cameras are native. They come pre-installed. So there's no need to have a patient go out and learn, go to iTunes and remember that password and then set up account and remember that password. So, you know, I feel like the market is beginning to understand this. I mean, that virtual waiting room thing that I described at Banner is a chatbot that's doing all of that. These things are pretty robust, but the ultimate goal of them is to get the patient successfully into whatever you want them to do. I mean, it's not a, it's not just information I guess, is what I'm getting at. Right?
Nik Kolatkar: (17:25)
That's right. No, it's very much a two-way conversation. You know, I think chatbots, as you said is maybe a little bit of a misnomer because I think the word "bot" just makes it sound very robotic and kind of automated and you know, lifeless, so to speak. But I, I think what we're talking about really is conversational technology, right? It basically to the patient is almost like they're speaking to a live person and it's in language they understand, you know, and is intuitive. And also, as opposed to something like search, you know, where a patient just searches for something on a website, you know, gets a whole list of things then has to narrow it down, figure out which link they go to. I mean, the nice thing about a chatbot is it can be iterative, right? So a chatbot can ask a question then based on the response can give a tailored reply, or a tailored search result, and can further iterate. So I think this whole, um, conversational two way element is a key value of the whole conversational technology that is getting better and better by the day.
Greg Kefer: (18:27)
Right. And I would imagine in your industry, this idea that AI would just magically, you know, talk by itself is not a good thing because you're somewhat regulated, right? You've got to have a compliant dialogue in the world of pharmaceuticals, right?
Nik Kolatkar: (18:41)
That's right. So, what we're talking about is not really that you create this conversational technology and you just set it loose. It's really behind the scenes quite structured, so that it's compliant with all the regulatory guidance. Many times the way the questions are asked patients can't necessarily just enter free text. They pick amongst choices. So, the way these conversational technologies and tools are designed is very important because as you said, patient safety, patient confidentiality, meeting all the regulatory requirements is critical. Otherwise these are going to be of no use in clinical research, you know, that has to come first.
Greg Kefer: (19:21)
Yeah, yeah. I often use the analogy of the, of a jukebox, you know, back in the days when you'd go to a bar and there was a big jukebox there. And if you could liken that to this, it might know that you like country Western music when you walk in, because you know, an RFID thing is pinged and it starts playing Garth Brooks for you like a playlist. But what it's not doing is creating the music, right? If it did that, it would be terrible, right? So, I feel like that, you know, that ability to kind of craft a flow that you control, uh, you know, so that it doesn't go off the rails and take somebody down a path that could be deadly is very important, not just in pharmaceutical clinical research, but just in healthcare in general. I just don't think it's the same thing as, you know, ordering a new four ounce bottle of Tide or something, you know, that Amazon can do.
Nik Kolatkar: (20:06)
Yeah, no, that's right. Yeah. That's right.
Greg Kefer: (20:08)
So you've actually experimented with the stuff you've done some work in this realm. Um, maybe you could just walk us through an example of where this chatbot conversational technology has been deployed and what happened, because you told me some stories the other day that sounded like it really, really is doing what you want it to do.
Nik Kolatkar: (20:25)
Right. So we have some real-time examples that we are actively deploying right now. And many of them are really, well, one of them in particular is right at this intersection of using technology to help us advance the mission of more inclusive research, you know, that we talked about before in reaching more underrepresented patients. So right now we have a study that my team are running called Chimes, which is a study for patients with multiple sclerosis, a devastating neurologic disease. And we have a study that is dedicated to underrepresented minority patients. It's particularly looking at black African-American patients, as well as Hispanic, Latino patients. Uh, because again, in that field, those patients have been historically underrepresented in clinical studies. So what we're doing is we're deploying the chatbot conversational technology, really to help serve as a digital navigator. So right now we are in the midst of working to deploy this, to try to deliver an e-consent platform. So, electronic consent. And then also, as I mentioned, to serve as this digital navigator to basically help patients schedule an appointment and help patients book transportation to the trial. So we don't have that fully deployed yet. It's actually happening in real time as we speak, but that trial is actively recruiting right now. And we're hoping to get that in place in the next month or so, over the next few weeks, really. And to just try rapid prototyping, get something out, you know, try it, and iterate on it quickly and see how we can further enhance it. That's one real time example. The other one we're trying is using a conversational chatbot in another one of our studies in multiple sclerosis to administer a patient reported outcomes questionnaire. So these are so-called PROs, that you may have heard about. And really the nice thing about PROs is they help us better understand how the patient is feeling and what the patient's symptoms are as opposed to just their measurements and their physical signs. But many times these PROs, so to speak, have been large, you know, lengthy paper documents that are cumbersome to fill out. And, you know, they're just not that convenient for patients. So we're trying to see again here, can we deploy the conversational chatbot technology to help ask the questions in the PRO in a very patient friendly way and to create a much better experience for patients. And then hopefully it can be a real win-win because we can get better data on our side because more patients may fill out the questionnaire and a better experience for patients themselves.
Greg Kefer: (23:04)
Right, and that's all stuff that maybe was once handled by humans that doesn't necessarily need to be handled by humans. It's such a natural way to have a digital assistant check in with you to see how things are going and give them a few options to respond. And you've got nice clean data – compliant data – coming back into you so that you can run the analytics. It sounds like a natural way to innovate to, you know, tackle these challenges.
Nik Kolatkar: (23:27)
Yeah, exactly. I mean, I think this is just one tool that we're employing. I mean, we're trying to actually explore a number of different tools in our digital toolbox, so to speak, but the conversational technology is a key one. Another one that we're using that we actively just finished a study in, was really mobile nursing and mobile delivery of care at the home. So for example, for breast cancer patients during the pandemic, you know, it was very hard for them to continue their chemotherapy because they were afraid to come into the infusion centers and they were afraid to get COVID. So many patients, even with metastatic breast cancer were foregoing their lifesaving chemotherapy. So we had come up with a new way to give our chemotherapy that our breast cancer medicines that Genentech makes as a subcutaneous form so that it doesn't have to be done through an IV infusion and infusion center. It can be given under the skin as a subcutaneous injection. So we created what's called an expanded access program, which is a study basically that would allow this to be given at the home, through mobile nursing during the COVID pandemic. And that was just another example of meeting patients, where they are in the community. And part of that is also using digital technology, and the mobile nurses and things, using digital tools and technologies to help do that.
Greg Kefer: (24:49)
Right. Cool. So cool. I, you know, I think that the work you're doing here, you know, especially in, you know, the diversity efforts that you're making are really gonna light a path for the industry to finally solve this challenge. And I, you know, I think it's the right way to go. We're fans here at Digital Conversations about conversational technology, and chatbots, and mobile. So, it's great to have you, and a company like Genentech kind of, you know, blazing the trail through the snowy mountains to make it work. So wow, we've already gone for 30 minutes, I think we could probably go for another hour easily. So that means we're going to have to come back. I'm gonna have to check back in with you in a few months and see how it's going, but Nik, thank you so much for coming on today. It's been just a fascinating discussion.
Nik Kolatkar: (25:29)
Thank you, Greg, this has been amazing, and we have more to come. We're right now, designing a study in triple negative breast cancer in underrepresented African-American patients or patients of black or African origin. And we have a study coming where we're going to be looking at diabetic macular edema in underrepresented patients. So diabetic eye disease and underrepresented patients. And in these two studies that we're going to be starting later this year, we are actively looking to how do we use technology to make those as patient friendly as possible, and to really, really help us reach as many patients as possible.
Greg Kefer: (26:06)
I imagine there'll be a role for conversational AI in that, but, uh, good luck with that. And thanks so much, Nik.
Nik Kolatkar: (26:12)
Thank you, Greg.
Greg Kefer: (26:13)
Okay. This has been Digital Conversations. Thanks for listening to Digital Conversations. If you liked our show, you can always subscribe on iTunes, and feel free to like, retweet, and share on your social networks. This and other episodes are available on iTunes, Spotify, and Linkedin.com. We'll be conversing again soon with a new episode. So long.
