Latest / Becker’s Healthcare Podcast / Dr. Shridar Ganesan on Advancing Precision Oncology Through Molecular Data and AI

Transcript

Dr. Shridar Ganesan on Advancing Precision Oncology Through Molecular Data and AI · Becker’s Healthcare Podcast

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  - Hello, and thank you so much for tuning
• 1:00
  - into the Becker's Oncology Leadership Podcast.
• 1:03
  - I'm Elizabeth Gregersen, a reporter here at Becker's.
• 1:07
  - And today, I am talking to doctor
• 1:10
  - Streeter Ganesan,
• 1:12
  - director of the Center for Molecular Oncology
• 1:16
  - at NYU Langone Health. Doctor Ganesan, thank you
• 1:20
  - so much for taking the time to speak
• 1:21
  - with me today.
• 1:22
  - It's a pleasure to be here.
• 1:24
  - Perfect. And before I dive into my questions,
• 1:26
  - I would love if you could share just
• 1:28
  - a bit about your background and your role
• 1:29
  - at NYU Langone for our listeners.
• 1:32
  - Sure.
• 1:33
  - So I'm Sride Ganeshan. I serve here as
• 1:35
  - the director for the Center of Medical Oncology,
• 1:38
  - a medical oncologist,
• 1:40
  - with a focus on breast cancer and rare
• 1:42
  - cancers, and I also run a basic science
• 1:44
  - laboratory focused on data repair and cancer genomics.
• 1:48
  - At the institute, my, charge is really is
• 1:50
  - to integrate
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  - molecular profiling studies across the center for all
• 1:54
  - our patients.
• 1:55
  - Amazing. And I'll just dive right into my
• 1:58
  - first question.
• 1:59
  - From your standpoint at NYU Langone, what do
• 2:02
  - you feel is your biggest priority right now?
• 2:06
  - Well, I think, you know, in as part
• 2:07
  - of this large integrated health system at NYU,
• 2:09
  - the cancer center serves a really important role.
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  - And I think, you know, one of our
• 2:12
  - big priorities
• 2:13
  - other than, of course, ensuring, you know, you
• 2:15
  - know, that we deliver, you know, the world's
• 2:18
  - best care and provide research and teaching to
• 2:20
  - our our our trainees
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  - is really that we need to provide an
• 2:23
  - integrated platform for all our patients because we
• 2:26
  - see them both before their cancer diagnosis many
• 2:28
  - of the times. During the cancer diagnosis, we
• 2:30
  - get multiple streams of information, radiology, genomics,
• 2:33
  - clinical information,
• 2:35
  - and through integrated MR. And I think one
• 2:36
  - of the big challenges is how do we
• 2:38
  - integrate all this data to make sure that
• 2:40
  - we are serving each patient,
• 2:42
  - as best we can, you know, and that
• 2:44
  - we're learning from each patient, you know, from
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  - all the data that's being generated in the
• 2:47
  - health system. Often, we generate a lot of
• 2:48
  - data and it gets, you know, tucked away.
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  - And we wanna make sure that the data
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  - we generate, molecular, pathologic,
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  - radiographic,
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  - and others, are all available
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  - for us to learn
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  - from each individual patient's journey so that we
• 3:01
  - can continuously
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  - improve
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  - both provision of our standard care as well
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  - as learn more about individual patient's diseases.
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  - Absolutely. I feel like that's something I've heard
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  - come up before of just kind of, you
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  - know, what's
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  - what's the good in having all this data
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  - if it's siloed or if it's inaccessible.
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  - So I I love to hear, how NYU
• 3:21
  - is, you know, focusing on kind of integrating
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  - all of that. Are there any sort of
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  - other pressures that you think cancer centers or
• 3:29
  - even oncology service lines are facing right now
• 3:32
  - that maybe aren't getting talked about enough?
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  - Absolutely. And, obviously, oncology,
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  - service line is very important for most, remote
• 3:39
  - health systems,
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  - and,
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  - is very important. And I think there's a
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  - little bit tension between, you know, we had
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  - to provide
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  - what we know how to do now very
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  - well. I provide the best care that we
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  - know how to give right now, but we
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  - also have to constantly that's not enough for
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  - our patients. Right? Doing what we know how
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  - to do now very well
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  - is often not enough for our patients.
• 4:00
  - So we have to continuously work to move
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  - the needle
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  - for patient care. And to do that, that
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  - means we have to balance
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  - both provision of standard care and the provision
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  - of clinical trials and other things to make
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  - sure that access is there and we're doing
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  - everything we can to improve the needle on
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  - outcomes.
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  - Alright? And so I think there's a little
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  - you know, we have to balance both providing
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  - standard care and also making sure we're always
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  - involved in research to improve outcomes across the
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  - board.
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  - Absolutely. It's kind of, like you said,
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  - giving the best possible
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  - care that you can now, but you're constantly
• 4:33
  - still moving forward.
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  - I know one of the ways a lot
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  - of cancer leaders
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  - are and, you know, cancer institutes across the
• 4:43
  - country are thinking about kind of that accelerated
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  - pace.
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  - AI is definitely a piece of that. And
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  - I'd love to know
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  - either for you personally or for NYU Langone
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  - at large,
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  - how you are thinking about AI,
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  - if you've seen it, you know, genuinely
• 5:00
  - helping to move the needle, or are there
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  - spaces where maybe,
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  - you know, the promise has not been met
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  - yet? Are there safety concerns
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  - that keep popping up? What's kind of your
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  - experience with AI right now?
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  - I think, you know, AI, like any other
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  - tool that we have, has enormous, you know,
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  - potential promise,
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  - to,
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  - address some key, you know, pain points.
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  - Part of that is, you know, can you
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  - know, how do we address the vast point
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  - information as we discussed earlier that's being generated
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  - by patients and how do we rationally synthesize
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  - that to something that's understandable
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  - for both treating physicians, for the system, and
• 5:36
  - for individual patients.
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  - And I think that's one of the promises
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  - of AI is can we take the large
• 5:42
  - disparate health care data that every patient has
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  - and can we synthesize it somehow in a
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  - regular,
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  - reliable, and high quality way to reduce the
• 5:51
  - fragmentation of care and data that is present
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  - for patients that often see multiple health systems.
• 5:59
  - Absolutely. It kinda ties back to, you know,
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  - what you said your biggest priority was now.
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  - No. I think, you know, there's a I
• 6:05
  - think AI has a lot of promise, but
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  - I think the key thing is what are
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  - the specific use cases that health system can
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  - do to show both the power
• 6:13
  - and potential for this both now and in
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  - the future? I think those are some of
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  - the challenges we have to really figure out.
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  - Absolutely. And I'd love to kind of keep
• 6:22
  - looking towards the future
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  - if we can.
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  - For my next question.
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  - When you think of the next generation of
• 6:29
  - oncology leaders and kind of the landscape that
• 6:32
  - they're going to be navigating,
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  - are there any challenges you think
• 6:37
  - they're gonna have laid at their feet that
• 6:40
  - they're gonna need to solve that maybe the
• 6:41
  - field isn't fully tackling right now or maybe
• 6:44
  - even not even looking at right now?
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  - Well, I think, you know, I think oncology
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  - has become more complicated.
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  - I think our diseases are gonna become more
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  - more, you
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  - know, break down into multiple, you know, different
• 6:57
  - diseases. Like, I think, you know, one of
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  - the biggest problems in oncology is we have
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  - not we have organ based syndromes instead of
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  - a set of real well defined diseases.
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  - And as we start to get understanding molecular
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  - path physiology as our treatment is more guided
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  - not more by then just where the lump
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  - is and what it looks like under the
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  - microscope by just anatomy and histology
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  - and by the molecular, you know, makeup of
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  - individual tumors, our care is gonna get more
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  - complex.
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  - It may break down our traditional organ based
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  - systems and surgical approaches may be, different. I
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  - think that is a challenge that we have
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  - to think about in the future. How do
• 7:29
  - we do that as our definition of diseases
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  - slowly will change, hopefully,
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  - you know, over the next ten, twenty years?
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  - Absolutely. And I feel like I've seen or
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  - heard, you know, the definition
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  - of diseases or even staging
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  - of cancers is already shifting. So I think
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  - that's such a interesting concept that you brought
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  - up of just, like, how treatment and disease
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  - and how we think about it is really
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  - gonna shift too. Absolutely. You know, the way
• 7:56
  - I think about it is when there's no
• 7:57
  - effective systemic therapy, often our diagnosis, classification, and
• 8:00
  - treatment is focused around surgical anatomy.
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  - Mhmm. As we get more in effective systemic
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  - therapies,
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  - then, you know, our our entire staging and
• 8:08
  - view starts to shift. We've seen that in
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  - hemalignancy early on. I think that's gonna occur
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  - as we start to develop more and more
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  - and more effective systemic therapies for many of
• 8:16
  - the solid tumors. That shift may also occur
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  - there,
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  - if we're lucky.
• 8:21
  - Right. Right. Yeah. Well, I guess speaking of
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  - luck too, when you think about the future,
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  - is there anything that's giving you hope or
• 8:28
  - excitement
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  - where you're, you know, looking forward to seeing
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  - where things go or are optimistic about how
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  - things will change? Well, in some ways, I
• 8:35
  - think the science of oncology or understanding of
• 8:37
  - cancer and of understanding of normal organ physiology
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  - has expanded so much in the past decade
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  - that I'm the most excited and optimistic there
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  - is that we can really start to understand
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  - the individual pathophysiology,
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  - you know, what is making this person's cancer
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  - different than their normal cells and can we
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  - use that information to really leverage,
• 8:56
  - treatments. And I think, hopefully, we will get
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  - to more
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  - rational
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  - targeted treatment approaches that will lead to better
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  - outcomes with less toxicity,
• 9:05
  - you know, even though that comes with a
• 9:07
  - multiple challenge. And I think the science is
• 9:08
  - really showing that. Who would have thought that
• 9:10
  - we can we have so many, you know,
• 9:11
  - targets for KRAS right now
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  - and, other things that, you know, were considered
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  - unreachable before. And I think that's just the
• 9:18
  - tip of the iceberg
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  - as really, you know,
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  - the basic science advances,
• 9:23
  - as the ability to generate drugs and the
• 9:25
  - pharmaceutical industry advances, and our ability to really,
• 9:29
  - interrogate the biology of individual cancers in individual
• 9:31
  - patients also expands.
• 9:34
  - Absolutely. And I'm excited to watch, you know,
• 9:36
  - what's gonna come out of the Center for
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  - Molecular
• 9:39
  - Oncology at NYU Langone too,
• 9:42
  - as as more of those advancements come out.
• 9:45
  - Doctor Ganesan, I just wanna thank you again
• 9:47
  - for coming on the podcast and taking the
• 9:49
  - time to share your insights with our audience.
• 9:52
  - No. It's a real pleasure, and I hope
• 9:53
  - in the future, we'll we can come back
• 9:54
  - and show what advances we've made.
• 9:56
  - Absolutely.
• 9:58
  - Alright. Thank you to our listeners as well
• 9:59
  - for tuning in to Becker's Oncology Leadership podcast.
• 10:02
  - I invite you all to check out even
• 10:04
  - more Becker's Healthcare podcasts
• 10:06
  - at beggerspodcast.com.
• 10:09
  - Thank you again, doctor Ganesan, for joining me,
• 10:11
  - and thank you to our listeners. Have a
• 10:13
  - great one.