0:00

The most interesting one that I've

0:02

seen is is actually

0:05

a cure for a treatment for lazy

0:07

eyes. No, a lot of

0:09

kids are born with the two eyes that don't

0:11

have binocular vision. You know, they work kind

0:13

of independently of each other when they

0:16

should. So what this company is doing is

0:18

they created a game a game, they

0:20

gamified it. They worked actually with the gaming company,

0:22

you'll be solved, I think. And they said let's create

0:24

a game that exercises that forces

0:27

the eyes to align. So it's a video

0:29

game out, literally looks like a video

0:31

game, but they have proved

0:34

that it will actually fix your lazy

0:37

eye. So

0:49

thank you very much for joining us. My pleasure

0:52

and very honored to be here. so just to start

0:54

with, I wanted to ask you about something which is very

0:56

near and dear to my heart, which is sleep.

0:58

Vasanth. And I have had some debates about whether,

1:00

you know, there's all these companies that sell mattresses.

1:03

They'll give you a better night's sleep and all these sleep trackers

1:05

that are on your arm. And we've had some debates

1:07

about whether you could actually get like nine hours

1:09

of sleep in seven hours with these new pieces of technology.

1:12

I personally don't believe that's true.

1:15

What do you think? Are you bullish on this or bearish? I

1:17

don't know yet. I don't know yet because it's,

1:19

it's a little complicated. It's a matter

1:21

of the technology can only do so

1:23

much, right? The technology can help

1:25

you pick up what's your sleep patterns, right?

1:27

So it can help you. You wear all these sensors, you

1:29

sleep on the mattresses that are sensing how

1:32

long you're sleeping. What's the quality of your sleep.

1:34

Do you move around too much? Do you snore, et

1:36

cetera, et cetera. And it can

1:38

help you create a pattern

1:41

of your sleep habits. There

1:43

are, you can also look at evidence

1:45

and based on the evidence, you can create

1:48

apps and other kinds of software

1:50

that can tell you how to behave

1:53

so that you can make your sleep better. Right.

1:55

So if you're, if you're sleeping, You

1:57

know, really late after midnight and

1:59

your sensor picks that up. It

2:02

might give you a nudge that, Hey, you

2:04

might consider having an earlier bedtime, but

2:07

to really, for you to sleep the nine

2:09

at 10 hours, you have to follow that

2:11

advice. And. As

2:14

humans, we are notoriously

2:16

irrational, you're notoriously

2:18

international, especially when it comes to things

2:20

that are you know, to do with our help and

2:22

to do with our financial

2:25

wellbeing, things like that, things that are

2:27

really important. We rarely follow

2:29

the, the, the good advice on that. So

2:32

that to me is the bigger problem to solve,

2:35

you know, to have that behavior modification

2:38

that comes out of nudges. Now.

2:40

Today, there are a lot of There's a lot of

2:43

technology. There's a lot of software, a lot of mobile

2:45

apps that do a pretty good job

2:47

of understanding human behavior

2:50

and therefore trying to modify it. But

2:52

I haven't seen anything that's highly,

2:55

it's been highly successful at changing human

2:57

behavior. There really isn't a

2:59

great habit building app, which

3:01

is, which is what you would meet. Right.

3:03

So, which is what you would need that, that really understands

3:06

why you behave a certain way and

3:08

then give you that actionable insight

3:10

on what to do about it, to change that behavior.

3:13

Once we close that loop from

3:15

understanding our sleep patterns, to

3:18

getting the proper nudge, to actually acting

3:20

upon the nudge. It's getting better. Right.

3:23

I actually read a book by this by

3:25

this very prominent sleep scientist at Berkeley

3:27

and in Matthew Walker, he wrote this book called why we sleep.

3:30

So he said in it that most Americans

3:32

only get like six hours of, of decent

3:35

sleep at night. And it's not because they

3:37

don't get in bed for eight hours. It's because

3:39

they just blast their eyes with blue lights

3:41

because they drink a cup of coffee, like three hours beforehand.

3:44

So. It does make sense. It

3:46

does make sense that if you can actually have data that says

3:48

like, Hey, like you're in bed, which

3:50

we're not actually getting good sleep, then

3:52

that insight could at least in theory,

3:55

prompt better behavior. Yeah.

3:57

I've been thinking about the Berlin and FinTech,

4:00

right? If you have a great banking app,

4:02

which, which a lot of them are now, which

4:05

gives you your spending patterns, right. You

4:07

can look at it and with great data

4:09

visualization, you can look at it and go.

4:12

Dang. I didn't realize that I, I spent

4:14

so much of my money eating out. And

4:17

then you might do something about it yourself,

4:19

or if the app is even

4:21

better, or if you have another way of,

4:23

of reminding you in the moment

4:26

that the next time you're going out, it senses

4:28

that you're blowing out and tells you stop. You

4:30

know, you're, you're going to regret this. This is going to

4:32

blow your budget. That will drive real

4:34

behavior change. Right? So it's the same with helpful

4:37

behaviors. You know, if you have, if you have

4:39

the right insight and you have an aha

4:41

moment, you'll be that much more motivated

4:44

to change your behavior. I definitely

4:46

agree with that. I think that like billions

4:48

of dollars of startups have come out of like, not

4:50

necessarily brand new technology, but

4:52

UX solutions like Twitter is

4:54

nothing but a UX solution. Slack is nothing but

4:56

a UX solution. And I say nothing,

4:58

but as if that's a small thing, but it's a massive

5:01

thing. It completely changes like how human

5:03

beings interact with the world. Yeah,

5:05

no, I, I you're, you're talking about

5:07

a subject that I'm so passionate

5:09

about. I always see I'm a, I

5:12

usually say I'm a technologist, right.

5:14

But actually I'm not, I'm actually

5:17

much more passionate about the

5:19

use of technology. Right? How

5:21

do people use it? How, how do you

5:23

design it so that the impact

5:26

of technology is even greater that

5:28

the intended use actually drives.

5:31

The expected output, right? So

5:33

the technology is almost, you

5:35

know, it's just it's just the infrastructure,

5:38

right? It's what you do with the technology. That's

5:40

more important and, and how you, how

5:42

you design it so that do the end user,

5:44

the technology should be invisible, right? So

5:46

it's not so much that technology for

5:48

technology's sake, but the it's

5:51

it's, as you said, it's the user experience

5:53

of that particular technology. So,

5:55

how do we solve this? How do we solve these problems? You said

5:57

that like you, you know, these apps will tell people

5:59

to go to sleep at this time, but they won't actually listen

6:02

to it. So what are some ways

6:04

that this can actually succeed in digital health? It's

6:06

the holy grail, right? How do you change human behavior?

6:08

It's it's not, it's not easy. You'll

6:11

see a little bits

6:13

of brilliance and the more you personalize

6:15

it, the more you understand individual drivers

6:18

of human behavior, the

6:20

better you can be at designing technology.

6:22

Right and designing the solution. So

6:25

in digital health, I'll give you a very

6:27

common problem is on adherence

6:29

to medication. You finally

6:32

went to a doctor, told them your symptoms

6:34

got a diagnosis. They wrote you a prescription.

6:37

You'll take it the first two days, and then slowly

6:39

your habit starts deteriorating.

6:42

And the number of people

6:44

who are what we call nonadherent or noncompliant

6:47

to their, to what the doctor

6:49

said about taking the medication about,

6:52

you know, lifestyle choices, et

6:54

cetera, is tremendous 50%

6:56

of the people in many areas in many fairly

6:59

significant diseases fall off

7:01

treatment. Or they'll start delaying treatment

7:04

and it's not always forgetfulness.

7:07

So non-adherence is not really a problem.

7:10

It's the symptom of something that's going

7:12

on in their lives. Right? So some

7:14

people might have beliefs about medicine

7:16

saying, eh, I don't think you

7:18

know, this, this has too many side effects. I'm sure

7:20

this is poison. I'm not going to put stuff in my body.

7:23

That's poisonous. I think my disease

7:25

is fine. It could be completely erroneous,

7:28

completely erroneous in that case.

7:30

It's a different solution than somebody who just

7:32

forgets. Right? So somebody like

7:35

me, I just forget to take medication on time

7:37

because I'm not disciplined. So for me,

7:39

a timely reminder would be a highly effective

7:42

solution in getting me to change

7:44

behavior. But for the person who has believed

7:46

that, you know, I, I don't really think

7:48

this, I should be taking this I'm okay. Even

7:50

though the doctor said, so. Then there

7:53

is you have to treat it differently that

7:55

the design should push perhaps proper

7:57

education for them, you know, and,

7:59

and maybe connecting them to people

8:01

like them or people that they trust

8:04

telling them more about the drug or whatever.

8:06

There could be some people who without telling

8:09

their doctor actually find the

8:11

copay too expensive. So

8:13

for them, if you send them a reminder, they're only going to

8:15

be more upset about it that, Hey, stopped reminding

8:17

me that I have to take this every day. I can't afford this.

8:20

Right. I can only afford to take it every

8:22

other day. In that case, perhaps

8:24

the solution is you,

8:27

you showcase some of the

8:29

financial programs that

8:31

companies offer government software, et cetera,

8:34

that they may not be aware. So the, the

8:36

point is that. It has to be that

8:38

much personalized. The intervention

8:40

has to be personalized. It has to be at

8:42

the right time. It has to be using the right

8:45

channels. Some people respond

8:47

really well to SMS messages, others

8:49

respond to their, their

8:52

child picking up the phone, calling them, right.

8:54

So somehow you have to really talk

8:57

fully create a very individualized

8:59

solution for them. Very difficult to

9:01

do, but we are heading towards that. You're

9:03

heading, we've already had it to where we already have

9:06

personalized medicine, right? People are doing,

9:08

finding out exactly what genetic makeup

9:10

you have and therefore you should be using this.

9:12

Therapy versus that. Similarly we

9:15

are getting better and better with the AI

9:17

and machine learning algorithms, but understanding

9:20

human behavior and even predicting

9:22

as I had as working on a project

9:24

where we were developing an algorithm, which

9:27

we. We're predicting, who's

9:29

going to drop off the treatment after the, you

9:31

know, out of the a hundred people,

9:34

which ones would drop off because

9:36

it's a machine learning algorithm and based on multiple

9:38

inputs, you could start

9:40

seeing patterns. If you have great data.

9:42

There are large amounts of it and smart

9:45

people looking for signals in that data,

9:48

you could perhaps pick up enough

9:50

patterns to figure out, ah, this person

9:52

they're respond better to this message

9:54

sent by this channel at this time.

9:57

And then they'll do something about it, right?

10:00

It sounds almost like you've built an algorithm

10:02

that tells you the people that are the most self-destructive.

10:07

Yeah, I guess. Yeah.

10:10

I think there's like some very obvious parallels. I mean, I think

10:13

it just extends beyond trying to change human behavior

10:15

to help other humans, like,

10:17

let me change your behavior so you can help yourself is

10:20

such a hard thing to do. Even, even in

10:22

if you look at like the financial markets, all the

10:24

apps that are being developed to help people trade really

10:27

the, they sort of incentivize self-destructive behavior.

10:29

I've talked to farmers about this a lot, but it's like, I

10:32

I'm not even certain that it's a UI. Whether a

10:34

UI fix will help people change their behavior.

10:37

I think it's like an incentive issue, which I think you mentioned

10:39

what would you say are sort of the best

10:41

incentives to that?

10:44

That actually change human behavior? This will incentivize

10:46

you to not be self destructive. Is there something

10:48

like that in the digital health space? So

10:51

that's what we look for. So in patients,

10:53

what we are finding that if you tell them, Hey

10:55

you will get better. Your blood pressure will

10:58

drop by this much. And your, you

11:00

know, this particular LDL will

11:02

drop, will drop by this much. If you stay on

11:04

treatment, that message doesn't

11:06

always resonate. What resonates

11:09

is something deeply personal? So,

11:12

you know, for somebody who

11:14

has a heart condition, let's say, and

11:16

they have a hard time keeping on medication, they

11:19

respond better to their own

11:21

metric and say, you will, you

11:23

have a higher chance of attending your

11:25

grandson's graduation. If

11:28

you take this medication versus not.

11:30

Right. That resonates. That's a big

11:32

driver for them because that's really personal.

11:34

So again, everybody's motivation and

11:36

drivers are personal. That's why it's so

11:39

hard to solve. So not everybody

11:41

thinks about how I'll do better,

11:43

because look, my LDL will get better.

11:46

They have different metrics that they measure. So

11:48

people who have mobility issues. Every

11:51

time we talk to them about, you know, certain

11:53

validated biomarkers

11:56

that, oh, this particular level of this biomarker

11:59

in your blood is reducing and your RH

12:01

factors reduce. It didn't mean anything

12:03

to them. We told them, Hey, do you remember that?

12:05

You used to be able to walk the dog one

12:08

block. Now you walk at five blocks and

12:10

they go, oh yeah, that makes sense. Yeah. My medicine

12:12

is working. So that drives.

12:15

Motivation is very

12:17

different and it's very personal and

12:20

that's why it's so hard to design for. But,

12:22

but if you can personalize that motivation for

12:25

someone like me, I don't,

12:28

I don't respond not deliberately, but I don't

12:30

respond well to Hey, you'll feel

12:32

better. I respond better

12:34

to, Hey, you, you need to be better

12:36

to, to be better for your,

12:38

to be able to help your kids. Right.

12:41

So it, it, to me, it's a little

12:43

bit more external, so it really depends

12:45

on your personality type. And what drives

12:48

you? I think this kind

12:50

of goes back to the UX thing that

12:52

I was mentioning earlier as well, in the sense that

12:54

like Facebook has absolutely

12:56

dominated adherence. Like I think the

12:59

average person spends like two hours a day or something insane

13:01

like that on social media, Facebook, Twitter,

13:04

Instagram, whatever. And they employ

13:06

a lot of, kind of maybe dark shady tactics

13:08

to do this, but a big one that they use is emotion.

13:11

That's why they show you stuff that gets you angry

13:13

or gets you excited or joyous.

13:15

And it, yeah, it kind of sounds

13:17

like you guys are. Maybe employing some of the similar,

13:19

similar techniques, but for good, rather than

13:22

for lining your wallet. Yeah.

13:25

I mean absolutely. When you design for

13:27

behavior change you have to connect

13:29

with the emotion. Right? Most of human behavior

13:32

is driven by us feeling

13:34

good about ourselves doing something.

13:36

If it doesn't make you feel good, you're not gonna do

13:38

it. Right. Most people don't stick to exercise

13:40

regimens because it's so darn

13:42

painful the first few weeks it's so uncomfortable,

13:45

right? If you get past that threshold,

13:48

you start feeling good. You've got that endorphin

13:50

rush in and things like that. Apparently

13:52

it becomes addictive. I said, apparently

13:55

because I haven't been, I

13:58

haven't treated that, that threshold.

14:00

It's always painful for me. So people will do

14:02

things that make them feel good. So

14:05

for Facebook and that instance. The

14:07

number of likes, they were getting the

14:09

number of people responding or commenting

14:11

to them about things that they posted

14:14

is a huge driver. You feel good? Oh,

14:16

I got noticed, right. Similarly

14:18

able to express your anger about

14:21

other things and your frustration, et cetera,

14:23

by, you know, commenting randomly on

14:25

things and, you know, making angry faces.

14:28

It also makes you feel good. You know, you got

14:30

to let out all your angst. So,

14:33

so they, everything has to tap into behavior.

14:35

That's why, I mean, you have to have been doing

14:37

the designing helpful

14:40

products and helpful technology. You

14:42

really have to be with really very

14:44

empathetic to the patient. It's

14:47

it's it's consumer technology is actually

14:50

easier because most consumers

14:53

will, as you said, you know, 90%

14:55

of behavior will be the same. Most people feel

14:57

really good about being able to get noticed

14:59

and in when you're a patient

15:02

you're dealing with so much else,

15:04

right. You're, you're dealing with the

15:06

disease burden. In addition

15:08

to being irrational human beings. So

15:11

it's that much harder to have empathy

15:13

for the disease burden and what it's doing to the

15:15

life, to their life. And

15:17

also to kind of figure

15:20

it out that they're not just a patient

15:22

and most of them don't want to be reminded of

15:25

their sickness. They want to be reminded

15:27

of their health. That's. All

15:30

of that has to factor in, into designing a good

15:32

digital health solution that,

15:35

that that can actually drive behavior change

15:37

and have an impact on, on

15:39

their health outcomes. So are there any

15:41

kind of like takeaway home tips for this,

15:43

like, forget building something digital, but just what

15:45

you've learned about habit forming. Like if

15:47

you wanted to stick to some exercise program

15:49

or follow some good diet, like what techniques would

15:51

you use to self motivate that like I could

15:53

employ a restaurant could employer, our listeners can employ.

15:56

It's, it's fairly well known

15:58

now because of there's. So many people have been working

16:00

on it. You have to

16:02

divide, you

16:04

have to set a goal, an

16:06

achievable goal. So there's a target

16:09

goal that you have to help the person set.

16:11

Right? And then you have

16:13

to divide it up into small achievable

16:16

steps and, you

16:19

know, help them. Get to their

16:21

final goal by, by these incremental

16:23

steps so that they feel successful at

16:25

every stage. That's number

16:28

one, you have to constantly remind

16:30

them of why they are doing that. So

16:32

what is that inner motivation? So

16:34

if their motivation is to attend

16:37

their daughter's reading and therefore

16:39

they need to feel better by then by next

16:41

year, keep reminding them of that so

16:44

that they stay motivated. You have to

16:46

do it in such a

16:48

way that they feel supported.

16:52

Right. So for people who are, who need

16:54

that coaching and that constant support

16:56

coaching really works. So whether it's a human

16:59

or it's a, or it's a chat bot doing

17:01

the coaching, it just depends on the person. That's

17:03

really powerful too. You have to design

17:05

a coaching program, a coach that's constantly

17:08

encouraging and. You have to tell them if you

17:10

fall off the track, it's okay. It's

17:12

okay. You'll get back. Right. So that they don't

17:14

feel like complete failures at any point. So

17:17

there's a bunch of things, but the first and foremost

17:19

is to help them understand what

17:22

things are getting in the way of them not achieving

17:24

their goals. You know, so that the collection

17:26

of data, we are using sensors,

17:29

et cetera, and visualizing it for

17:31

them. This is what you actually

17:33

do is a huge motivator.

17:35

You know, they themselves go, my God was I really

17:37

spending. Four hours

17:39

a day of sitting on the couch, watching TV.

17:42

I can't believe it. Right. So I didn't think

17:44

it was that long. And so once you start

17:46

looking at that you, you, you can get

17:48

a better sense of the design. So apple

17:51

has done a pretty decent job of driving

17:53

healthful behaviors with the apple watch

17:55

and, you know, closing the rings and all that. This

17:57

apply a lot of those principles. The data visualization

18:00

is really simple and, and.

18:02

You know, immediate, so you have to keep it simple.

18:04

Don't make it complicated. Don't make it seem hard

18:07

to then just be kind of positive

18:09

about it. Great example.

18:11

I, at first I, I

18:14

found the stand-up every hour notifications

18:16

on my apple watch to be like the most annoying thing

18:18

in the world. But once I closed

18:20

those rings and got those really fun animations

18:23

a few times now, like I'm

18:25

chasing that high every single day, right?

18:28

Yeah, exactly. So

18:31

speaking of apple, I think they're making,

18:33

I've heard, they're making a lot of plays in the, in the health

18:35

space. So can you kind of expand on what

18:37

exactly their role in this? Yeah,

18:41

so it was interesting deal a

18:44

few years ago. Let's say 10 years give

18:46

or take, right. It's been 10 years now. I can't

18:48

believe it. Well, the, the

18:50

use of technology in health

18:52

care or rather sick care, you

18:54

know, we call it healthcare, but really we

18:57

it's sick care, the use of technology

18:59

and healthcare. Can we, sorry, can you,

19:01

can you expand on that? Like what do you mean by sick care versus

19:03

healthcare? So, so when

19:05

I think about the healthcare ecosystem,

19:08

I'm thinking of doctors, I'm thinking of

19:10

pharmaceutical companies, et cetera, right?

19:12

So these are not talking.

19:16

Actually, if you think about, are they taking care of sickness?

19:18

They're not care of health as

19:20

such what we call. Health

19:22

care actually takes care of sick people.

19:26

Right? And the other piece

19:28

where you're promoting healthy habits and prevention

19:30

of disease is doesn't

19:32

fall under the, probably more

19:34

like I've heard that's more effective. Preventative care is better

19:37

for you than, than like reactive

19:39

of course. But think about it. How many times would

19:42

it, would your doctor, would you go see your doctor

19:44

and get prescribed? I'll go to the gym five times

19:46

and be monitored, right? It's

19:48

it's we do take care of, we

19:50

do. You know, we've got our language

19:53

mixed up here, I think. But apple

19:55

was so the use of technology helped the

19:57

healthcare ecosystem. Let's say all the

19:59

players in the healthcare space, doctors,

20:02

pharmaceutical companies, nurses

20:04

insurance companies, not

20:06

early adopters of technology, not

20:09

early adopters, they're way behind

20:11

the way behind it, the adoption of, of

20:13

cool technologies. So.

20:17

But about 10 years ago, all that changed, right?

20:20

Everybody decided that, Hey, you

20:22

know what, we can't, we can no longer

20:24

just be prescribing drugs. We, it

20:26

has to be more holistic because we're spending

20:28

a lot of money and it's costing our healthcare

20:30

system, a lot of money because people

20:32

are ending up in hospital and having

20:34

all these challenges. So we have to do more. We have

20:36

to do more preventive preventive care, as

20:39

you said, and we have to also make sure

20:41

that once a person has been diagnosed with

20:43

a disease, ensure the best

20:45

possible outcomes, because not only

20:47

is it better for the patient, it's actually better

20:49

for the entire healthcare ecosystem.

20:52

It's cheaper, right? For overall,

20:54

it's cheaper to keep people out of hospital

20:56

and maintained and, and, and on a healthier

20:59

path then B that have them admitted

21:01

in the hospital. So when that

21:03

happened The tech companies

21:05

started going, Hey, I can do stuff. I know technology.

21:08

I can do a lot of cool stuff here. So

21:10

they started getting into the healthcare space and

21:12

then pharma companies, I worked for a big pharma.

21:15

We started going, oh, I can do technology

21:17

and I can, you know, so, so

21:19

all the, all the technologies wanted

21:21

to become healthcare people and the healthcare

21:24

people, pharma, et cetera, wanted to suddenly

21:26

become technologists. So apple

21:28

was one of the first ones because they had

21:30

hardware and they had software and they have

21:32

a fan following of their products

21:35

there. So they've a beautifully

21:37

poised to make a difference.

21:39

So a couple of years ago, Tim cook, I don't know

21:41

if you guys remember. He even said

21:43

I think it was 2019 is talking about the apple

21:45

watch and other services coming up, that

21:48

if he looks to the future, he

21:51

will he predicts that apple

21:53

will be known for making the biggest difference in healthcare.

21:56

Which at that time was like, wait, what? And

22:00

then you started looking at the investments that

22:02

we're making and what they're doing

22:05

is actually, it's actually pretty phenomenal

22:07

because they have the reach, right? So

22:09

to be able to influence lots of lots

22:12

of human lives, they have the fan

22:14

following the habit captured patient.

22:16

Patient population, right? So

22:18

they do not have to reach out to two

22:20

people and force them to adopt anything. People

22:22

already use their products so much.

22:25

Right. So what they do is what

22:27

they've done in the, in, at recently

22:29

is They've added more and

22:32

more health related features

22:34

into their products. So the apple watch

22:37

it has it has all kinds of sensors in

22:39

there that can predict even heart conditions

22:42

and pick up and diagnose heart conditions.

22:44

Before the patient themselves is aware that I might

22:47

have an issue. Right? So

22:49

one of the, so there they're

22:51

started partnering with a lot of pharma companies. They

22:53

did a lot of health study and, you know, apple

22:55

health study with millions of people at

22:57

bear. They're collecting data through the sensors,

23:00

in their watch and through the

23:02

demographic data for the, from the use of their phone

23:05

and based on all that. They

23:07

can, they're coming up with algorithms that

23:09

are pretty good at predicting certain diseases,

23:12

they're diseases or disorders

23:15

or conditions that can be picked up. Depression

23:17

can be picked up. As I said, heart-related

23:19

a lot of things can be the sensors can sense.

23:22

They're starting to actually have go

23:24

into the space of medically regulated

23:27

devices, right? So you're, you have

23:29

to get an FDA clearance. If you're going to say, Hey,

23:31

I can predict heart failure. But you have to have,

23:33

you have to get the evidence and show it to the

23:35

FDA. So that's happening. So I think

23:37

that they're doing a fairly good job of this. The,

23:40

the, where

23:43

I think they can do better is.

23:45

Working in the regulated space, because at,

23:48

at its heart, apple is a, is a consumer

23:50

company. And they'll have

23:52

to work with the FDA and with with the

23:54

regulating bodies to make, to

23:56

figure out how do you regulate a consumer

23:59

device, which has so many medical

24:01

features in it, because almost everything gets

24:03

regulated as a medical device. And then

24:05

it's really difficult to update

24:07

it and to test it and to produce all the right

24:10

evidence, et cetera, et cetera. I

24:12

wanted to talk about that because Yeah, sort of, sort

24:14

of, one of the hardest things about building in healthcare is because the

24:16

biggest bottleneck being the regulation,

24:18

you have to go through all these sort of watchdogs

24:21

and the FDA you were mentioning. And

24:23

so for us and I always talking about, well, when is

24:25

the quote, unquote two

24:27

guys in a, or people in a garage

24:30

going to build the next great software company.

24:32

Is that even possible in the healthcare space?

24:35

How are you going to go up against the sort of behemoths

24:37

that are no other way around all these regulations?

24:39

It's possible. If you partner with the right people,

24:42

that's the business model. I've seen a lot of the

24:44

startups take. They, they

24:46

have a great idea that really innovative.

24:48

And I work with a lot of startups, right? Because

24:50

the real innovation comes out of

24:53

this kind of passion that people have. So,

24:55

what they'll do is, and there's a lot of investment

24:57

money right now flowing into digital health, a lot

25:00

of investors and kind of, sometimes

25:02

it cockamamie things. You go really, they got,

25:05

they got funded for that idea, right?

25:07

So you will always get seed

25:09

money if your idea's good. And if you can show value.

25:12

Right. So the question is now,

25:15

how far can you take it as two

25:17

kids in a garage? You have to start

25:19

getting in and talking to people and leveraging

25:21

the external partnerships. So

25:23

that's, that's a very common business model. So

25:25

I rebook with a lot of startups. They

25:27

have cool ideas. We know

25:29

the FDA, we know what it takes to do clinical

25:31

research and to produce the evidence

25:33

that's required by the FDA. And

25:37

it's a win-win. So, so

25:39

what happens is these partnerships

25:42

made in heaven, but they're not always successful

25:44

because, you know, if you're talking to a large

25:46

company, there's a lot of bureaucracy. There's a lot

25:48

of things like that. And, and smaller

25:50

companies, just the startups

25:53

with two kids in a garage have a very different mindset.

25:56

So it has to be done carefully,

25:58

but that's one Bible will do it. The

26:00

other way is if you start showing incremental

26:03

value, you know, so if you start

26:05

showing incremental value, you will get the investment.

26:09

So I have a lot of examples of companies

26:11

that are, can you give us, can

26:13

you give us some something you'd like to highlight? Yeah.

26:16

So there's, there's there's a few different companies.

26:18

There's one that we worked with in the heart failures.

26:21

Young peoples decided that let's

26:23

start collecting data of

26:25

all kinds, temperature blood

26:27

pressure, heart rate, heart rate, variability,

26:30

and weight, weight, gain

26:33

shortness of breath, things like that, whatever

26:35

we can collect and see if we can figure,

26:38

feed it, to do an algorithm and figure out if it's

26:40

heart failure. Right. So figure it out and,

26:42

and, and be able to predict

26:44

heart failure before. It becomes

26:46

really apparent. So there's

26:48

a company called bioform. This has a lot

26:50

of good AI algorithms. They

26:54

just have a great credibility

26:56

because they partnered first with the right academic

26:58

institutions to, to went

27:00

to the really credible institutions

27:03

and Did studies with them

27:06

first they're smaller studies that perhaps don't

27:08

require as much of an investment.

27:10

And then they started talking to other bigger

27:12

companies and other bigger investors saying,

27:14

Hey, we do a larger study

27:16

than perhaps this this particular

27:18

algorithm that we're using might get widespread

27:21

adoption. And, and

27:23

the journey continues from there. So there's

27:25

a, quite a few companies like that.

27:28

It's a hard field only because

27:30

of there's so much uncertainty around how,

27:33

what is the exact business model? How do you make money?

27:36

You know, who pays for this? Did that's the harder

27:39

problem right now? You know, people have a lot

27:41

of ideas. What is unclear and what

27:43

you don't have control over is

27:45

who pays for this stuff. So

27:47

would a patient. Pay

27:49

for something. Patients are so used to their

27:52

insurance companies, paying for everything, and

27:54

they're paying just a small copay. That's

27:56

psychologically you, if you tell

27:58

them, oh, this will help with your heart failure.

28:00

The first thing they ask is, wait, is this covered

28:03

by my insurance? And

28:05

insurance companies are harder to convince.

28:07

Doctors are harder to convince is

28:10

this recommended by my doctor? That's the other

28:12

question? Right? So those

28:14

are some other aspects that will prevent

28:17

people from building

28:19

a successful business and that have to be sorted

28:21

out. That whole thing is just being sorted out. Would

28:24

this be easier in a country like Canada,

28:26

where they have government provided healthcare?

28:30

Well as long, but then you have to

28:32

cover the government, right? The government is still the

28:34

payer. So you have to, who is the payer?

28:36

You have to convince them. So

28:38

it either has to be the patient it's actually

28:40

easier. And whether their self pay. So

28:44

where people in countries where people are so much

28:46

used to just paying out of pocket for medicines,

28:48

they'll go. All right. One other thing I have to pay for,

28:50

for being healthy. So they're

28:52

there. The psychology is a

28:54

little better to overcome. But in

28:56

countries where you're used to somebody else.

28:59

Paying a majority of your costs, either your employer

29:02

or your insurance company or the

29:04

government, it becomes much harder

29:06

because now you have other people to convince you have

29:08

got the whole ecosystem to convince that, Hey,

29:10

that, so this is, this is one of the challenges

29:13

in digital therapeutics. So

29:15

It's a relatively new area where we

29:17

are not just saying in digital

29:19

health where we are not just talking about solutions

29:22

that you give in combination

29:24

with the medicine. You're actually making

29:26

claims that the software is

29:28

the medicine. Right? So it's

29:32

yes. And imagine the evidentiary

29:34

burden there, because now you have to show

29:36

that the piece of software, somebody

29:38

using the piece of software compared

29:41

to somebody who's getting the standard of care.

29:43

Right or not using software, but getting the normal,

29:46

whatever treatment they get is will

29:48

do better because it, software is actually curing

29:50

whatever disease. So exactly. Yeah.

29:52

Yeah. So this is for like mental health things

29:55

or it's also for physical elements. It could

29:57

be for physical elements, especially for physical

29:59

ailments as well. Right. Because mental health

30:01

is great. Right? Mental health is the obvious one.

30:04

Because meant a lot of mental, mental

30:06

health related conditions can be treated by

30:08

counseling. Now whether the counselor

30:10

is human versus AI,

30:13

if your AI is really, really good and you're

30:15

using the same principles of cognitive

30:17

behavioral therapy, et cetera, the standard

30:19

psychologic psychology principles

30:22

that that that our counselor would use. You

30:25

know, it, it will be effective. So that's

30:27

one area. The other area of physical

30:29

is a lot of things can be solved

30:31

with physical exercise. So, so things

30:33

that are more actually physically

30:36

structurally you know, effecting your structure

30:38

you can provide the same kind

30:40

of. Physical therapy to an

30:42

app and you could through through digital

30:44

means than you would through having them go

30:46

to a physical therapist. The,

30:49

the most interesting one that I've

30:51

seen is is actually

30:54

a cure for a treatment for lazy

30:56

eyes. No, a lot of

30:59

kids are born with the two eyes that don't

31:01

have binocular vision. You know, they work kind

31:03

of independently of each other when they

31:05

should. So what this company is doing is

31:07

they created a game a game, they

31:09

gamified it. They worked actually with the gaming company,

31:11

you'll be solved, I think. And they said let's create

31:13

a game that exercises that forces

31:16

the eyes to align. So it's a video

31:18

game out, literally looks like a video

31:20

game, but they have proved

31:24

that it will actually fix your lazy

31:26

eye. So there's a lot of things like that.

31:28

Similarly, ADHD, you know, with

31:30

ADHD, there's a, there's a, there's

31:32

a company Akili interactive. That's

31:34

done clinical research to show

31:36

that there. Quote unquote

31:38

game, but you know, it isn't really a game

31:41

it's, it's basically software as

31:43

a therapy. We'll train those

31:45

areas of the brain that can help people focus

31:47

better. No. So, so

31:50

it's like with neurofeedback and

31:52

those mechanisms it's based on solid science,

31:55

but the manifestation is instead of eating

31:57

chemical, now you're making those same changes

32:00

in the brain, but using software. So

32:02

yeah I think going back to this idea of having a really

32:05

high evidence burden that the FDA

32:07

requires, or a lot of these sort of companies require.

32:10

Is that a good or bad thing? I almost feel like having

32:12

the bar be set so high would disincentivize

32:15

people from even attempting to

32:17

solve real problems. I like the idea of solving

32:19

like ADHD or lazy eye, but you know, like the really

32:21

big sort of inherent problems that

32:23

exist within large, large societies.

32:26

Yeah. Is evidence burden too high, but

32:28

you're risking people's health too. Exactly.

32:31

Exactly. I think the evidence burden is high

32:33

because the cost is right. If you,

32:35

if you don't have, if you can't

32:37

prove safety and efficacy to

32:40

to a high standard, then

32:42

you might cause harm and in

32:44

healthcare, that's what you have to be aware of.

32:46

Right. So if you're, if you're. If you have a bug

32:48

in software and in a mobile

32:51

phone and it drops a call, no big deal

32:53

right here, it could kill people

32:55

or, or, you know, that's at its

32:57

at its worst case. Then you start to

32:59

start, have to worry about, Hey, what's the evidence.

33:01

So yes. We,

33:04

we always, as pharma, we,

33:06

as a pharmaceutical working for a pharmaceutical

33:08

company, I always feel like, yes, it takes

33:10

forever and sometimes frustrating, but I can

33:12

totally understand it. I think that there needs

33:15

to be a standard of evidence, truly burden.

33:17

If you're claiming it depends on what you're claiming.

33:23

You're claiming that your, that

33:26

your piece of software is curing

33:28

disease. You have to,

33:30

you have to be pretty sure that it is. I

33:33

think that's a, well, I think that's a good answer. Like

33:36

since I've been developing software for some time,

33:38

I think most other software engineers would agree with me

33:40

that. Once you read enough

33:43

software, you realize how crazy it

33:45

is that we're depending on other software developers

33:47

work for like driving a car

33:49

or like flying an airplane. Like that's some code

33:51

somebody wrote, they probably Googled answers

33:54

and copy and paste it from stack overflow.

33:56

And we're like, depending on that for our

33:58

lives. But the reason we can is because they have

34:00

these. Yeah. I, I think, I think regulation

34:03

is important. The more, the more you like the

34:05

more code you write, the more you realize, like we should have more.

34:08

So let me ask you this. See me. If you were starting a digital

34:10

healthcare company today, is America the

34:12

best place to start it? Would you go somewhere

34:14

where, like, if you personally wanted to create a company

34:17

that made money help people, is America

34:19

the best place to start it? I don't see why not,

34:22

you know, we are. We

34:24

are one of the most innovative

34:26

nations in the world. We are risk

34:28

takers. So I,

34:32

I actually think that we can drive.

34:34

So evidentiary burden is important, but

34:36

the other thing that's important is

34:38

that you have to right size, the evidentiary

34:40

burden don't make me produce.

34:44

You know, mountains of evidence that

34:46

something works. If all I'm doing is reminding

34:48

a patient because see, what's the worst that can happen.

34:50

That I send them a reminder of the wrong time.

34:52

Right. Big deal. Right. So,

34:54

so in those you have to right size

34:57

the risk with evidentiary burden. If

34:59

I'm creating like something that would

35:01

affect their heart or their lungs

35:03

or something like that. Great. Hold

35:05

me to a high standard. But if

35:08

all I'm doing is very slight

35:10

modifications in their habits, then

35:13

you have to right-size that regulation. So

35:16

the good news is the FDA

35:18

is actually working very hard

35:20

and understanding how to regulate

35:22

digital software that

35:24

is closely tied to diseases

35:27

in the right way. So that's why I think

35:29

it is the right place to start a digital

35:31

health company because you'll get the

35:33

investors are here. The risk takers are

35:35

here. People are willing to put their money

35:37

where their mouth is. So you'll get a lot of. You'll

35:39

get a lot of encouragement. You'll

35:41

be had credible

35:44

testing test beds. So

35:46

all the most of the big

35:48

healthcare systems and universities

35:50

and the, and the culture of research

35:53

and, and really high quality research

35:55

all exist. So I

35:58

actually think this is a wonderful

36:00

place. I think digital health solution

36:02

developed in the U S as a higher

36:04

credibility than in a country where

36:06

the regulations were relaxed because

36:09

you know that you've met a higher bar. So you

36:11

have a higher chance of making an actual impact

36:13

on a patient's life. That's fair.

36:16

Totally fair. So,

36:18

one question I did want to ask is with

36:21

regard to digital health particularly apple

36:23

they have all these incredible sensors

36:25

and all this incredible technology, but not everyone can

36:27

afford an apple product. So as digital

36:30

healthcare, just for the rich. Sometimes I do

36:32

sometimes feel that we are solving first world

36:34

problems. But apple is, is

36:36

not the best example if you're talking

36:38

about affordability agreed,

36:41

but there are a lot of solutions that are really,

36:43

really inexpensive and

36:46

they are actually meant

36:48

to be deployed in the

36:50

underserved areas of the world. So

36:53

I was. Blown away by some

36:55

of the really great work that

36:57

a small digital tool

37:00

can do in tuberculosis, for instance.

37:02

So there are all these remote villages let's

37:04

say in Africa or in Asia

37:07

where it's very difficult first. There's not

37:09

enough hospitals. It's not enough doctors. So

37:11

what happens is you've got somebody going on a

37:13

mobile clinic trying to diagnose people with tuberculosis,

37:16

and then there's. The added issue

37:19

that first you have to diagnose them. And then the

37:21

treatment regimen is fairly intense. They

37:23

have to be on all kinds of drugs for six

37:25

months or so. And you have to monitor

37:28

whether they're making progress or not very,

37:30

very difficult in an underserved area,

37:33

but under-resourced area. There

37:36

is a digital, there are several digital

37:39

solutions where the,

37:42

they run out AI algorithms

37:45

and machine learning algorithms to

37:47

to kind of pick up signals of tuber

37:49

closest. We are just how the patient

37:51

cops. So they can pick up a phone

37:54

and a doctor in a central

37:56

place anywhere in the world can listen to their

37:58

cough and the AI will read

38:00

it and say, tuberculosis, this cough

38:03

is due to tuberculosis, versus that it

38:05

can also pick up whether or

38:07

not the treatment is working. If the cough is getting

38:09

better, just because it gets the

38:11

digital signature of a tubercular cough

38:14

versus other types of cough that

38:17

is life changing for these areas.

38:19

So. There are, I don't know

38:21

if apple is the best example for four,

38:24

but digital health is actually should.

38:26

The maximum impact is it'll have is

38:28

in these underserved areas. This technology

38:31

is relatively cheap, right?

38:33

Humans, doctors. And

38:35

human resources are expensive, right?

38:37

Specialist resources are expensive. Technology

38:40

solutions are the great equalizer,

38:42

right? Everybody in, in, in a lot of

38:44

countries, data is become very, very

38:46

inexpensive. Everybody has a cell phone.

38:49

So using the cell phone as a

38:51

means of it, doesn't have to be an apple phone,

38:54

but using a cellular phone as a means

38:56

of delivering healthcare through different

38:58

technologies is going to be really

39:00

impactful. If the, if the willingness is there

39:03

and it is, I mean, there's a lot of. Lot of

39:05

initiatives in Africa and other

39:07

underserved areas that is doing that.

39:10

We have deployed a lot of digital health solutions. I

39:13

think so technology has this sort of great pulling

39:16

power that over time it tends

39:18

to begin, you know, it goes into like some sort of

39:20

new industry, it builds some new innovations

39:22

and then before, you know, it they've taken over the industry.

39:24

We're seeing that with Hollywood right now. There's any number

39:26

of examples. And so if we look at sort

39:28

of the digital health space right now, the big tech companies

39:31

like apple and the Googles of the world, maybe

39:33

in terms of like the total GDP being built. In

39:35

the space, they take up 5% and

39:37

the remaining 95% is being done by

39:40

I dunno if this proportion is correct, but the remaining 95%

39:42

is being done by the existing sort of big pharma

39:44

companies, 30 years from now. What

39:46

does that proportion look like? Where does

39:48

tech stand up against the big pharma

39:51

companies? I don't think

39:53

that it's tech versus big

39:56

pharma. Really. I think

39:58

it's tech versus. A physician.

40:01

Hmm. So there is the

40:04

tech will produce algorithms,

40:06

very good algorithms. It's already

40:08

producing algorithm that can diagnose disease

40:11

that can produce treatment

40:13

regimens and also

40:15

treatment plans, and then provide

40:18

the continuous care continuum

40:20

to keep a patient healthy as possible. So

40:23

there is that. A lot

40:25

of discussion going on in the space of is

40:27

it is an AI bot

40:29

going to replace a physician.

40:32

So that's, that's been debated

40:34

forever. And I don't think, I think it's a matter

40:37

of how you view it right now,

40:39

at least in the short term. I

40:41

think I think of tech as

40:43

enhancing the position's powers. Right.

40:45

So giving them additional information,

40:47

additional knowledge, making their life easier

40:50

eventually ever evolves

40:52

to get the same kind

40:54

of you know, features,

40:57

et cetera, that, that experience

40:59

and common sense

41:01

and empathy that a human has

41:04

that a human physician has. I

41:06

don't know, but that's way into

41:08

the future in the short term, I don't, I just

41:10

see tech as being highly helpful in,

41:13

in removing some of the inefficiencies

41:15

that are inherent in healthcare right now in optimizing

41:18

healthcare. That's the first thing that

41:20

it should do and is doing now right.

41:22

Slowly. It didn't. That is pretty slow. DEC

41:24

versus pharma currently, the

41:26

way we use the pharma's core businesses

41:28

creating is making medicines

41:31

right now. Our drug

41:34

discovery process is very

41:36

slow and very labor

41:38

intensive and time incentive and

41:40

resource intensive. That

41:42

is helping a lot there too. It's helping us

41:44

identify targets to

41:46

and what kind of molecules to create. It's making

41:49

our manufacturing, operations faster

41:51

R and D operations faster or clinical

41:53

trials faster. Will it ever replace

41:55

it where it can, you can create a model

41:58

of of of a compound and then create

42:00

a medicine out of all. That, to me sounds

42:02

very futuristic right now. And

42:05

so futuristic and I mean,

42:07

I'm sure it'll happen, but it's so futuristic that I

42:09

feel like we shouldn't be worrying about all that right now.

42:11

Let's use tech for good and optimizing

42:13

and helping get better

42:16

patient outcomes today and

42:18

tomorrow we'll take care of it. So

42:21

let's say that one of our listeners

42:23

is software engineer and they hear

42:25

this and they say rather than making

42:27

my own social media app, I want to

42:30

make something good for my legacy and for the

42:32

human race. And I want to work

42:35

in health and digital health. What

42:37

advice do you give to them? Who should they link up with?

42:39

What should they start reading about? How do they do this?

42:41

So get educated is

42:44

the first thing. Right? And then there

42:47

isn't anything. I

42:49

think, keep that motivation alive if

42:51

they're doing it for the right reasons, right.

42:54

They're doing it truly because they feel like

42:56

I need to leave a legacy and leave something

42:58

behind. They're already

43:00

way ahead. Like they're already way ahead

43:03

and they're already poised for success. So

43:05

all they have to do is now kind of use

43:07

this motivation and use this drive.

43:10

To, to get educated

43:12

and into what are the real patient

43:14

problems to solve, right? What are those things

43:17

that really make an impact and start

43:19

small, choose one thing and usually

43:21

choose something that's really personal to you. If,

43:24

if, if you live in there's a lot of

43:26

digital health solutions that came out of somebody

43:28

watching their grandfather struggling

43:30

through a condition, right? So choose

43:32

something personal. If you can choose that and want

43:34

to work in that space, that would be fantastic. I

43:37

do you are, you have a very high chance of success.

43:39

I think working in pharma is a great way

43:41

to go. I think working in

43:43

health tech, meaning the,

43:45

the health or life sciences

43:48

side of big, technology's a great

43:50

way to go and

43:52

help and working in

43:55

the intersection of these two is

43:57

the ideal way. You know, where you're looking

43:59

to see where is big

44:01

tech partnered with. With pharma

44:04

and biotech to make really cool

44:07

solutions right. And working

44:09

in that space is, is always a good

44:11

thing. I don't know. I haven't really given it too

44:14

much thought about. Digital

44:16

health. I just don't see it as very

44:18

different than any other career. Right.

44:21

Other than the motivation part, it's just the use

44:23

of tech in a space that

44:25

in a new space it's, it's the use case

44:27

is different. So get really if, if, if

44:30

it's a software engineer get really good

44:32

at software, it's really

44:34

good at the user experience and

44:36

then go for it all comes back to

44:38

user experience. I, you know,

44:40

I love this and I'll always

44:42

start and end on that. Well, I think that's a great note

44:45

to wrap things up here. So to start our

44:47

final question that we wanted to ask,

44:49

what is a great piece of technology

44:51

that you want to highlight that you think

44:54

is one of the most interesting, fascinating,

44:56

best piece of technology you've encountered

44:58

in recent memory or even of all time? It could

45:00

be software, hardware, and whatever, whatever

45:03

floats your boat. Okay. If it's

45:05

software, I would hands

45:07

down, hands down, say the Google

45:09

search engine. And it's probably

45:11

an answer you've heard before. And that's because

45:13

I think it was truly transformational

45:15

for everybody. Right. For everybody, everybody

45:18

Googles, everything. Right. And

45:20

it has become part of your vocabulary. So I

45:22

think that, I think attracts, I

45:25

think it's by far the number

45:27

one piece of impactful software

45:30

that everybody uses in their daily lives.

45:33

That's our episode for this week. Thank you so much for listening.

45:36

Make sure to subscribe to us and rate us on Apple

45:38

podcasts. We would really appreciate

45:40

the support. You can also follow me on

45:42

Twitter at F Z from Cupertino

45:45

and Busan. The ad next facade.

45:47

See you guys next week.