ROCHELLE LONG: Hello I'm Rochelle Long, a division director at NIGMS, which is the National Institute of
General Medical Sciences at NIH.
Today I want to start with a few announcements.
First and foremost, we want to thank all personnel
working in health care and public service
at the time of COVID-19.
Our thoughts go out to everyone who's been
directly affected by this pandemic. One thing
we thought we could do at NIGMS is to
create a webinar series designed for students,
fellows, and faculty.  For each webinar, we'll
have a 10- to 15-minute presentation followed
by a Q-and-A session. We hope these webinars
will offer content that's both interesting
and useful at this time of distance learning.
Today, as we begin, I want to let you know that you can
submit your questions live after the speaker
has concluded. To do so,
please use the chatbox because everyone's
microphones are and will remain muted.
Select the moderator's name.  Today,
that's my name--
Rochelle Long--and we'll get to as many questions
as possible.
Each of these webinars will be recorded and
posted at our
NIGMS homepage as soon as possible.
And, finally, future seminars in this series
can be found by following us on Twitter, using
@NIGMSgenes or at @NIGMSTraining, or on
our NIGMS homepage.  And now, today, I'd like to
introduce today's speaker, Dr. John Younger.
John grew up in a small town in Missouri and
did his undergraduate and medical training at
the University of Missouri--Kansas City.
He pursued his clinical training in emergency medicine in Orlando, Florida,
and then he moved to a research fellowship at
the University of Michigan.
He stayed for the next 20 years, where he built
a research program, met his future spouse, and
started a family.  In 2014, an invention stemming from John's research
showed promise as a new research tool.
With the encouragement of an early group of investors, John became a co-founder and
chief technology officer for Akadeum Life
Sciences where he worked for the next half-dozen years.
In 2019, he relocated with his family to Philadelphia, P.A.,
where John is currently the vice president
for science and technology at the University
City Science Center,
a long-standing innovation hub, startup accelerator,
and investor in early technology companies.
John has authored over 80 peer-reviewed publications,
obtained over $4 million in federal
grants, and raised over $6 million in venture
investment. He has many publications, awards,
and has involved, been involved in mentoring
and service activities for his entire career.
In fact, he was an Eagle scout.  John is especially
well positioned to speak today based upon
his professional interests in shepherding
early-stage biotechnologies and the intersection
between federal, philanthropic, and venture
funding for new tools and diagnostics.  For
today's seminar,
John's titles, talk title, is "Entrepreneurship
and Careers in the Biotechnology Industry."
Now, let's welcome John Younger.
JOHN YOUNGER: Thank you very
much.
I hope that everyone can hear me. I hope that
we're going to have reasonably good success
with the, with the broadcast today.
I first wanted to say thank you for the invitation.
This is really amazing.
It's a real honor to have this opportunity
to speak with you, Rochelle, and to think out
loud about some of these things.
I don't know if there is a more challenging
week in the history of United States to try
to be thinking about what to do about our
careers than this week is, but I think that
there's some useful things that we can talk
about and I think maybe some general guidelines
for how to approach what is hopefully a unique
moment in all of our careers.
I will tell you that if you're having uncertainty
about your career as a trainee, you are not
alone on that.
Everyone right now is trying to figure out
exactly what is going to happen next and how
best can we be positioned for it professionally
and personally. So I'd like to spend the first
few minutes of this talk, before we get into
the questions and answers, just giving
you a sense of how I kind of think about this
question.
So, when I think about myself and I think about
you as scientists at various stages of your
career, I kind of think of you as this little
knowledge-generating engine, right?  And, in
your job, your energy in the day is spent trying
to create new knowledge, new information, and
that knowledge may be highly focused on a,
on an important application, that knowledge
may be really for knowledge's sake and both
of those have an important role,
I think, demonstrably, in what, you know, what
the world is trying to accomplish.  As this
engine, you are driven by a few things, you
have a few important characteristics.  Clearly,
and not necessarily always acknowledged, is
you have a lot of creativity--you are thinking
of new things, you're looking at a problem
and trying to solve it in a new way.
And that's very valuable.
I think that there is a spark, there's something
that has a pile of manuscripts next to your
bed that you go to sleep with at night.  There's
something that makes you answer emails at
midnight.
There's some drive that all of us bring to
trying to do something new and then I think
really importantly, but not necessarily acknowledged
as it should be,
is that, is that for all of us,
this is really tempered and really disciplined
in this idea of scientific method,
right?  There are a lot of ways of looking at
the world and in some of them are useful
in some circumstances, some in others.  But as
someone who's been specifically trained to
understand and really follow scientific method,
that makes the application of your creativity
and your passion unique and I think important
in how new knowledge is generated.
Now, this is you as an engine of new thinking.
It doesn't really comment on what the thing
is you're thinking about.  Are you thinking
about structural biology?  Are you thinking
about traffic patterns in major cities?
I don't know.
But in some ways it doesn't matter.
In some ways, you have been trained to interpret data, to generate new data,
and to draw conclusions from it.
Historically, when we've looked at, like say,
trainees and trainee grants, you would look
at this and say, "Well, what's the topic you're working on?  You know, is this topic really super important?
You know, are the details of the science really key?"
And historically that's been, that's been the
focus. I think, increasingly, in this is, you
know, as an example of the MIRA program within the NIH.
Increasingly, we're looking at you as the engine and saying, "You will figure out the right questions
to work on.  What we want to make sure we're doing is supporting you as a scientist and
then letting you figure out where does the
science need to go next."
Right?
And because of that, you as an engine of new knowledge, can find yourselves in a lot of
different circumstances, all of which could
be both very helpful and also, you know, can make
a great career for yourself. So most of you
at this point are probably sitting in an academic
institution.  You're in a university or some
other research organization, and your engine
is turning based on revenue that's generated from basically three different areas.
There's grants, which we all know about.
There's organizational funding so your school may pay you to do particular work, and there's
philanthropy.  There may be a donor that's paying to do this work and all of those funds come
together to support what you're doing as a
thinker.  Surrounding all that, though, are all
the things that sometimes are a boon and sometimes kind of a headache for you, which is all the
other stuff inside of universities.
You have teaching requirements.  There are legal and regulatory things around the work that
you do.
Someone's got to make sure the parking lots got lines painted on it.
All those things are things that have to happen in universities.
And sometimes I think it's easy to forget
how much of a big company universities can
be, but they are. And if you think about what you're doing right now and you were to change
one part of this diagram, which is where the money comes from, say, organizational funding,
grants and philanthropy, and change it to commercial revenue, it's still sort of the same.
Most of those pieces are intact.
And, so, when we think about working in academia or working in industry, they are a
lot more similar than they are different.
And I think that's really important.  It's important because it will temper your expectations
about working in the future in one or the
other,
but it also should lower the energy barrier
to making a jump from one to the other.
These are big organizations,
many people work there,
they're trying to generate new knowledge for one motivation or another, but they have a
lot of similarities.  So I basically put the
similarities between academia and commercial
or industrial enterprises into these sort
of buckets like,
what's the motivation?  So for academia,
typically, the motivation is pretty basic--to
generate knowledge.
We want to generate new things, things that were not known before
that could be really basic or
it could be somewhat applied for organizations that are spending a lot of time thinking about
potentially generating IP.
There may be a lot of applied knowledge formation going on within an academic enterprise.  Within
a commercial enterprise,
it's pretty focused on applied knowledge.
This is an enterprise to try to learn something
about a thing that can be commercialized, could be sold, and it can be turned into a product.
That's not exclusively true and, certainly,
once organizations get big enough even, even
the most industrial commercial programs can generate basic knowledge for basic knowledge's
sake and that's, that's great.
The revenue stream in academia typically consists of grants, philanthropy, commercial revenue
occasionally, and then clinical and academic outcome, right?
So tenure, excuse me,
so tuition has to be paid.  There may be
clinical dollars that roll back into the research enterprise
But these are the usual ways in which academia  is funded.
In commercial enterprises, it's really revenue.
So, the company can spend what the company makes, and those are important differences.
Now, it's true that academia will say that
a major value proposition is that
the research you do is self-directed.
You get to pick the thing you work on.  You're not kind of told what to work on.  That's generally true,
but it is also the case that it's self-directed as long as you can find someone to pay for it, right?
And so if you're having success writing grants, then the research you're doing is the research
you want to do,
but if you're having a hard time finding funding you may have to redirect what you're working on.
In an industrial enterprise, typically,
there is a goal of doing something that will
produce a near-term clinical benefit, something
that will change patients' lives or create
a drug or create a diagnostic, and that's really the focus,
and there's a lot of discipline around sticking to the focus.
There's an opportunity in industrial enterprises, compared to academic enterprises, that you
may get to share some of the profit, right?
So if, if the product does well, there may be
profit to be shared. And another thing that I think
about when I think about industry versus academia, and this may seem counterintuitive, is that
in industry, you actually have a lot of mobility.
So as you sort of mature in the company that you're working for,
it would not be out of the question that the company would move you into a different silo of the organization
altogether, in order to make you a little bit more well-rounded, to give you some exposure
to other parts of the business, and you may
find yourself in several different parts of
the company before all is said and done.  Within academia, as a faculty member or as a scientist, you're
going to pretty much be in that role.
You may have responsibilities added, but it's unlikely that you would, that you would migrate
from, say, a research position into a completely administrative position unrelated to research
in order to sort of broaden your horizons.
It happens, but not that much, actually.
And so in industry I think that there's
an opportunity to be a little bit more mobile.
Now the threats to both of these positions
are also real.
In academia, you eat what you catch.  If you can generate a grant that is successfully
funded, you can do that work.  If you cannot, you will not be able to do that work over the long term.
As I mentioned, there may be some relative
immobility in academia and, importantly, I think,
you need to understand, especially in this moment, that there's some impermanence as well, right?
So academic units come and go over the course of time and if you're in academia long enough,
you'll see whole programs that you thought
would be around forever slowly start to become
less important and finally disappear.  Whole institution can do that, although that
doesn't happen very often.
Similar set of threats happen in industry.
That is, there has to be a lot of discipline
now what's worked on and the thing that you're working on today may not be a thing that gets
worked on in the future.  And so programs can be wound down because there's not an opportunity
there anymore and
they may pick up in some other way.  But also companies come and go as well.
They may go bankrupt.  They may be acquired. All those things are real and they're not
all that different, I think, between academia
and industry. So, a startup is different.
So, a startup is a really completely
distinct entity and I like this definition
by Steve Blank.  So, Steve Blank is someone from from Silicon Valley who's done a lot
of thinking about startups, and sort of startup theory, and Steve describe the startup as "a
temporary organization used to search
for a repeatable and scalable business model."
And what this means is that if you jump into
a startup compared to jumping into, say, a pharmaceutical
company, you are going to be as an engine
of knowledge generation trying to apply your
work towards a very limited question:
Is there a thing here or not?
Is there an opportunity for this idea to become a company?
It could be an amazing opportunity, you may find out that in the end what you're working
on is not all that important, or you may find
out that it's not important at all. Your job
inside of a startup is different than your
job inside of academia or in industry in
that your job in a startup is to understand,
"Is this a thing or not a thing?"
If it's not going to be a successful thing,
the goal is to find that out as quickly and
as inexpensively as possible so that you can drop it. Unlike other things you've done before,
when you work for a startup, part of the success is if you figure out very quickly it's done
and then it needs to stop,
that's a good thing, and you will actually
be valued in your next undertaking for someone
who can very quickly sort of cut to the chase and decide, "Is this a thing or not?"
So I put all these out here to kind of give
you a framework for how we're gonna have this
conversation today and sort of think about
what your job is and what the opportunities are.
I don't want to spend a lot of time talking
about a lot of details about all these choices
but I want to just sort of say these are kind
of the taxonomies that I use and the sort of
general thinking that I use when we start
talking about about career choices
and about going forward.
Now all this stuff was great and as of eight
weeks ago, there were a lot of great data to
suggest your decision to do a career in life
sciences was a really great decision.  I think
that actually is still very much the case
maybe, even more so than it was at the beginning of the year.
Employment in the life sciences, investment
by companies in R&D, and in total investment
by, you know, a civilization, by the government, by industry, by investors, all of those things
have been on the rise for some time.
They continue to be on the rise and I think
that in the current moment, there is plenty
of evidence that there is a lot of opportunity for new thinking and for new creation of both
basic science and applied sciences as well.  And so even though we're in this crazy moment,
this is a great field to be in and the
things that you know and the strategies that
you've learned are really great strategies
to have on hand.
And so I'm actually very optimistic about
what's going to happen going forward.
That said, in the exact moment not necessarily,  right?
So it's really hard to know right now as a
scientist and as a dad, and just as a
person, what is going to happen next?
And this is sort of the moment we've all been waiting for, right, when we've read the instructions
on our safety instructions on the plane a
gazillion times and never really had to think
about them.
Well now, actually, might be a time to think
about it.
And I've been trying that personally. I've been working on this with my team, with my kids.
What does this moment mean and how do we sort of best prepare for it so that we can take
the most advantage of what's happening right now?
So, I think I would point out these things
and I think we should probably spend a lot
of the talk today thinking specifically about
these issues.  For moving forward, for you
as a junior investigator, as a young scientist,
I think the most important thing for you to
do right now is to have no assumptions about
anything regarding your career.
You should not assume that your job is safe.
You should not assume your job is at risk.
You shouldn't assume anything.  What you should do is you should make sure that you're having
conversations with your mentor or your department chair or whoever your boss is about what's
going on and about what your specific position is within the organization.  Is there a long
term or a short term future for you?
Is it solid?
Is it not solid?  But you need to sort of understand,
where are you?
How does your organization think about you?
And it's neither right or wrong,
but it's important to know because it will
influence a lot of decisions that
you have going forward.
You don't want to proceed without having asked
questions about your standing and about what's
going on with your organization.
You don't want to make guesses about those
things. I also think it's really important
to be very flexible.
Remember, at heart, you're a trained problem solver, right,
so you're an engine that knows how to evaluate
data and to create new knowledge.
The fact that you might be doing it in structural biology right now is great, but not necessarily
critical to what you bring to the table.
And so I think it's very important for all
of us to make sure that we understand the
difference between what we know and what we
know how to do.
There's a lot of things that you know that
with enough time, I could probably Google the
answers, but you as an investigator and
sort of as a tenacious learner, that's special.
And do you need to be prepared to take that specialness and maybe put it into a context
never really imagined before.
That flexibility will treat you very well
and it's a real asset and not everyone's as
fortunate as you
to have that kind of asset available.  What
I'd tell everyone before they start making
career decisions is, "You need to make sure
you have a handle on your personal financial
situation."
This is really important.
You don't want to be making decisions based
on guesses or based on not full understanding
about what's going on with your life and what's
likely to go on with your life in the next
couple of years.
I always encourage people to bone up on financial
literacy, learn about how money works, learn
about how loans work, how profits work.  Just
learn about money because it will be important in
how you make your decisions.  You should definitely
understand your benefits package in your current
employment.  You should understand your own
personal budget.  What are you likely to spend
money on, where could you save money going forward?
But spending time, like honest time, studying
your numbers and what's happening in your
career,
that's really valuable time spent and so I
always encourage people to make sure they
understand numerically Where are you at in
terms of what you're trying to accomplish.
And the last thing that I would always encourage
people to do is to make sure in the event
that you are not working in isolation if you
have a life partner.
If you have kids that you really have talked
through with them your strategy from going
forward.
So I'm in a two-professional household--my wife
is a research cardiologist--and we have to
have this talk in the event of something really
unexpected happening, who takes time off, right?
So if one of us is gonna stay home and teach
the kids, who does it?  We haven't decided that,
but what are the rules by which we would decide it?
How do we decide who does what and when it's
time for someone to take their foot off the
gas for their career,
who does it,
how do they do it,
what are the rules that we have sort of in
the family?  As they like to say in Michigan,
ultimately, it's all about the team, the team,
the team, and we're very thoughtful about trying
to make sure that we are all on the same page
in terms of what we're trying to accomplish.
So these things:  Assuming nothing,
making sure you're being flexible about how
you define yourself, making sure you understand
your finances to the best that you can, and
making sure that you're communicating with
everyone in your life about what the rules
are for how you're going to make decisions
about the next step in your career.
Those are all things that are are good kind
of on a normal day but I think you're really
especially important right now.
So with that said, I'd like to just open this
up and, Rochelle, I know you have some questions.
I just want to say thank you to everyone for
joining today and please fire away,
let's talk about some good stuff.
I urge you to ask whatever you want to talk
about.
LONG:  Thanks, John,
that was great.
So, now I'd like to remind everyone the way
to ask questions is to put them in the chat box.
Use the drop down menu to pick my name,
Rochelle Long, and I'll be watching for them.  
There were a few questions that I got in advance
that people wanted to know about you, John. For
one thing people wondered when they learned
your background training, how being an emergency
department physician might have prepared you
for an entrepreneurial career.
YOUNGER:  So, it's a good question.  So, one of the things that I really sort of appreciate over
time and probably everyone here has had this
experience in a similar vein, is that
I'm always surrounded by people who think
very differently than I do and, certainly, there
are tribes within science and there's tribes
within clinical medicine.
And sometimes it can be hard to figure out
how all of these things sort of self-sorted
into these groups.
But I think a lot of it has to do with the
sort of your intellectual style, right, and the
people that do emergency medicine are sometimes,
they're sometimes portrayed as adrenaline junkies, right?
I think I'm actually not an adrenaline junkie, but if you look at the practice patterns
of people who do emergency medicine,
they actually do everything possible to make
surprises go away.  But, actually they're not
actually that into the surprise and if there's a way to sort of minimize risk, that's great.
But what we do as a group have in
common is that, is that we are comfortable
making decisions pretty quickly, right?
So, in emergency medicine, you don't get
to mull stuff over for a few weeks, you know,
you get about 10 minutes.  You'll know what
you're going to know and you're not going
to know, and you're going to decide.
And that decision is
based on some data, some of it's not very good.
That decision has to be both informed by and then ultimately bought into
by people that you just met, right?
And so you meet a stranger and you have a conversation
and then, suddenly, you're making plans that
impact their entire life, like, literally, their
life.
And there are people that like to do that
and there's people that don't.  That sounds
great when that's the tool that you need,
that not everybody, not every circumstance
calls for someone that will decide something
in 10 minutes, right?
And so, there's a time and a place for deciding
quickly and executing on that plan and there's
other times that I'm not the right guy for
the job.
And I think for starting a company, where there's
so much uncertainty and there's such a time
pressure to make a decision, that being able
to make sort of the best decision you can
with really poor data in a very tight timeline,
that's a great thing for how I think.
I will tell you that within my own company,
there was a moment when we started to outgrow
that and where what the company needed most
was not someone who could make a split decision
but someone who would not make a split decision.
That's not, that was not the thing that needed
to happen next. And so I think that sort
of cognitive style issue comes up, I think, in
a lot of fields, right, that's how that's how
that's how organizations are robust,
they have lots of different thinkers and lots
of different strategies and figuring out where
you fit into that realm and where that
type of thinking style is most useful
will be very helpful.
Now, it took me like 50 years to figure that
out so, hopefully, people will figure it out
faster than that,
but that's kind of how you go about it.
LONG:  You also said making decisions
on incomplete data, so
this is a style or a thought process,
and I have a whole slew of questions here
to ask you because a lot of people are interested
in what you talked about.
So let me try some of them.  Here we go.
Do you have any insight into the scientific
work environment difference in a CRO/CDMO
setting as a scientist versus a private company in industry?
YOUNGER:  You know, not firsthand, but,
you know, but my my sense is, is that
with CROs and similar
manufacturing organizations, things like that,
that things where you are being contracted
to get to a specific answer,
that's a very focused thing, right, and there's
some good things about that, right?
So, there is an exact question in front of
you,
there is an end to that question, right, so you
ask the question, you'll get the answer.
Full stop.
Next project.
So those things I think are good.
And so if you like being able to,
you know, quantize the work that you do, I
think those are really great opportunities
and there's plenty of it.
One of the things that's happened in the last, you know, 
probably 10 or 15 years and I was part
of a discussion last week to talk
about this, this sense that, you know, 15 years
ago, Big Pharma was all of these things at
once and now Big Pharma has figured out that
early research, someone else should be doing
that; early commercialization, someone should
be doing that; the clinical trials, someone
should be doing that.  And big pharmaceutical
companies have figured out that there is a
lot of value in sort of trimming down the
big shop and outsourcing these key things
and so and so ...
LONG:  There are questions coming up about that, too, I see
so many. I'm going to push you a little bit just
to see you get to many of them.  Talk about fragmenting
or separating elements of the industry.
One question was,
"What is the best strategy
for a biomedical research scientists to move in,
how is it different from startups versus large
biotech versus medium pharma?
YOUNGER:  I think it probably
depends on how you want to spend your day.
Are you looking for,
are you looking for a lifelong job,
are you looking for a five-year job,
are you looking for a one-year job.
Those are
all things that you should understand
about yourself.
So I think part of it is probably the duration of
the job.
Part of it is, is likely going to be, "Do you
want to manage kind of the outsourcing
of work to other organizations, right?
So would you be more comfortable as a scientist
who's managing the work by other companies
that are doing science for you and then you
sort of synthesize all those results and move
them forward in your company?
Do you want to have a pipetter in your hand,
right?"
Those are all things, and those are all these
are all different approaches to being a scientist, right?
That as companies delegate more
of the kind of fundamental work outside of
the sort of normal wall, where do you want
to be?  Do you want to be, you know, accumulating that
information and then acting on it?
Do you want to be generating that information?
Those are things you have to be comfortable
with.
And I will say that there is no ... you don't
have to get the answer right.
Try one and see what happens
and then try again.
So there is no loss for deciding
this was what I thought I was going to do
next but it turns out it's not a great fit.
I'm going to move on.
That's all fine, right,
you can always run the experiment, see what
you think.
LONG:  So, it's funny that you're describing fit because
we have a question in the chat box:
How might we view the importance of cultural
fit as we look at employers in this time of
uncertainty?
Is it still worth taking a position with less
responsibility--
let's just start somewhere in a company we're interested
in, compared to a senior position elsewhere
where you might not have been a first choice?
How do you find your fit?
YOUNGER:  So I think it may be partly by trial and
error, it may be, you may just hit it right but
I don't think it's ever inappropriate,
you know, before you sign to really 
sort of set aside all of the, you know, all
the Excel spreadsheets that you have with all
the pros and cons of the different jobs and to
say, "Does this feel right or not?"  That matters
a lot.
You've got to get out of bed in the morning,
you've got to go to bed happy, and thinking
about culture is really important and I think
that anyone that's been doing this for a while
understands that culture is certainly not
the domain of academia or industry or startups,
you can find great cultures at all of those
spots and you can find not-great cultures.
And I think that there's probbaly not
sort of like evil cultures as people think.
But when a culture doesn't fit with how you
view the world and what you prioritize, it
seems like a bad culture.  What it is, it's a
bad fit.
There are places for you no matter what your
style, right,
and it's really just a matter of finding that.
But I can't tell you how important it is.
You know, life is short and and you will succeed
in a place where you feel lined up, where you
feel like you're making a contribution, and
where you feel like people kind of think the
way you think about lots of things in the
world and so don't underestimate how important
that is, right.  So
I'd hate for someone to make a decision 
about a job based more on what the retirement
package looks like compared to whether or
not they feel at home when they walk in the door.
LONG:  So speaking of retirement and finances, we
did get a couple of questions that relate
to money, money personally, some of the points
you raised in your last slide.
So one of them is:  "Thanks for mentioning personal
finance.
Do you have any recommendations for sound
resources on that topic,
and, also, how do you learn about money from
a business sense, especially for somebody who
doesn't have a business degree?"
YOUNGER:  Well, we can do the second one first.  So, when I started doing this, I didn't know anything,
I didn't know anything about this.
So, there's there's a great Web site and it's called investopedia.com
So, Investopedia is like the investment
Wikipedia and they have a word of the day.
I would suggest if you can enroll in the word
of the day and do that for about six months,
you'll know most of what you need to know.  I don't
want to say anything about MBA programs--
you learn a lot just from getting one vocabulary
word a day.
But those sort of, like, passive, little bits
at a time are good.
If you really want to know about finance, like,
you know, off line get hold of me I can recommend
some, you know, chunkier tomes about, you know,
about how to think about entrepreneurial finance
and things like that.
But those things are fine.
I don't think it's probably ever wrong to potentially
spend a little money on a financial adviser,
just a one-time look--here's what, here's
what they think, here's how they would proceed.
They might be a little bit better than just
sort of like getting online and answering
a bunch of questions on some website and
you don't know kind of what those data are
going to do but, you know, just a one-on-one chat with someone to say, "Here's where I'm at,
What do you recommend?"
I think that actually could be money
very well spent, right, because those
people will hang with you because they'll
understand that you're at the front end of
your career and that you can be a customer for
life.  And so
I certainly have been working with someone
for a very long time and I, you know, I just
email them once in a while and say, "Help me,
help me think about this," and they've always
been very supportive.
LONG:  OK, so speaking of thinking about things, I have a
question in a different vein here:  "There are
a lot of research publications from academia
that are not replicable due to ethical issues.
Do you think research done in industry is
more
ethical since the whole downstream pipeline depends upon it?"
YOUNGER:  So, ah-hah, so
so I don't know if I completely understand
the question about things not being replicable
because of ethical reasons to reproduce
the experiment.
I don't know about that.
I mean, if things are unclear, they're unclear
and I think you can ethically justify, you
know, the effort to clarify them.
I do,
I am thoughtful but I haven't really concluded
what to make about about reproducibility issues
and whether or not they're different inside
academia and in industry.
You would, at first pass, think that industry
has a lot more on the line if they get it
wrong, right?  Industry can find itself, you know,
a company can find itself way downstream with
very expensive programs and being surprised
late in the game by early data is extremely
problematic for them,
more so maybe than for an academic.
That said, academics, you know, there's a lot
to making sure that you manage your reputation
and it's a very hard problem.
I will say that the financial consequences
to the organization are probably much more
substantial for irreproducible data in
industry.
But the, you know, the reputational and
just sort of, you know, other implications to
academia are also really substantial.
So I don't know there's a right answer
to that.
And if I was smart I'd probably not pick one
anyway.
LONG:  OK, here's a question in a slightly different
career or life-development sort of vein.  The
question is:  How much risk do you recommend trainees
to take?  For example, when you start a company
the future is unclear.
How did you reach the conclusion that jumping to a startup position
is better than staying the course.
What if this move throws a person into a financial
nightmare?
YOUNGER:  Ah-huh-huh!  So a few things.
So, when I made the jump, so I had two active R01s.
I was associate chair in my department when I quit.
I resigned basically, right?
And so that, that was hard.
It took me about a year to work through that decision. It wasn't like overnight,
I just decided, that was not, actually, one of
my 10-minute decisions,
that was a year decision.  And the way that
I made that decision was based in two parts.
So the first part was we did a lot of work
talking to potential customers, folks that
would use our technology if we could get it
to work and there was so much enthusiasm by
end users that said, "Yeah we would
use this.
Here's how much we would pay for it."  A lot
of people said, you know, "Yes, please.
We would like to see that."
That was very influential in helping me sort
of do the first pass at de-risking, right?
I mean, arguably, you know the investors took
a risk but the founders take a much bigger
risk when they joined a company, and the early
employees take a much bigger risk, right, so
that the investors will walk away but the
team can't, right,
and so I  de-risked in two ways.  One was by hearing
how much customers wanted it.
Well, maybe three ways.
The second was that investors were ready to
come in.
So, we had early investors that said, "John, if
this is such a great idea, we'll fund it, but
we're not going to fund it unless you convince
us it's a good idea
by quitting your day job and coming in.
And so we closed our first round of finance
predicated on me resigning my position and
so the investors were in.
And so I assumeed, and I assumed correctly, that
they knew what they were doing.
So if they're going to write a check, they
kind of knew that this was a thing as well.
And so I used that.
And then the last thing was, is, you know, I spent
time talking to my wife about this and saying,
"What should I do,
and what is the actual downside risk?"
Now it's really important, you know, as a 45-
year-old tenured faculty to make,
whose spouse is also a tenured faculty,
for me to decide that this was worth the risk
is very different than the decision right
out of grad school that you're going to take
the risk.  But, there's the way that you should
think about it is, "Does this fulfill a longer-
term sort of experiential need that I have,
right?"
You're unlikely to get rich.
You're most likely not going to make any money
off of your first startup.
Most likely, I mean, clearly in excess of 80
percent, it will fail.  Does it fulfill that
experiential need that I have as part of my
longer term plan?
And am I well suited to the work?
There's not a lot of downside if you take
a job in a startup for a couple of years and
it fails, you haven't lost anything, right?
And so the risk is sort of modest.
You know, the real risk is sort of taking
a job in a startup and not necessarily getting
a paycheck, right?
So I don't really advise anyone launch a startup
and then just work for options or just work
for free until something magical happens.
I don't know that that's very wise.
But in genera,l I think the risk can be mitigated
and if it feels right,
I think you should try it.
LONG:  So describe to us in your career progression,
you took a couple of forays out of your conventional
educational path.  For example, a sabbatical you
have taken was a little different than some
others might have done it.
How did you sort of jump in or taste the waters
in different fields that helped guide your
future decision-making?
YOUNGER:  So I have always tried, when looking at new
opportunities, to look at the opportunities
and say, "Is this a thing that needs to be done,
and if so, am I passionate about this thing?"
Then saying, "Well, what do I know about this
thing, and do I have the training for it and
if I don't,
what do I not have that I would need?"
And that's kind of a different approach then sort
of evaluating all your opportunities based
on your current skill set, right?
So, this is a thing that I do.
These are the jobs that are available to me.
I don't treat it like that when
I say, "These are the things I believe are passionate
and great opportunities.
How do I sort of springboard from what I know
now into this next thing?"
And I think both of those are actually very
acceptable paths.
One of them feels a little bit riskier sort
of on the front end, but on the back end,
you get to explore a lot of other ideas and
I don't think there's ever been a
career decision that I made that I regretted.  Certainly,
some of them were not in the direction that
anyone planned and, certainly, when I
resigned from the University of Michigan, people
didn't understand that at all.  But, sort of 
in the fullness of time people would go,
"Of course that made good sense," right?
It was the right thing to do.
So I think that there's ways.
LONG:  OK.  You know there's
a lot of curiosity about sort of what makes it
different from academia.  Here's a couple of
questions.  "If I were hired as a scientist or
a researcher in the company, would I still be
expected to contribute to the budgetary and
financial issues?
Would there be an expectancy for me to know
how the financial wing works within a company?"
And there's another question here:  "How are
the ways that you do get funding for a startup?"
YOUNGER:  So I know so you're using Akadeum as an
example.
And we had people at Akadeum that were
very closely tied to all the operational components
because there are a lot of operational
components.  You've got to
have a place where you're gonna order your,
you know, your paper towels from.  You've got
to have a way of, like,
filing receipts.  There's so many
operational things and within the first couple
of employees of a startup, everyone's gonna
do everything and you're going to be intimately
familiar with all of it because you have no
choice.  There's no one else to do it, right?
As the company grows to, even probably
five or six employees, there starts to be the
ability to specialize in such a way that you
can sort of work on the thing that you really
came there to work on.
And so, so there is an expectation that you sort of work within the confines what's
possible, but only at the very, very
beginning are you going to be there with an
expectation, you know, "Can you set up QuickBooks,
so we have accounts receivable, right?"
That doesn't happen except at the very beginning.
The way that you fund it is through a
few ways.
So, a startup could be funded because you paid
money out of your pocket.
I don't personally believe that first-time
founders should be paying money out of their
pocket because they're not smart enough to
know whether it's a good investment.
If an investor wants to pay money for it, yes,
you will give up some of the company but you're
taking someone with a lot of experience in
the field and they're saying this is worth
doing and if they're a good investor, they
will help you.
So I think drawing early investment
I think is very important.
I actually think maybe more important in most
circumstances than SBIRs and STTRs.  There's
a lot of discussion about whether or not that
is the right mechanism or not, but there is
there is a certain rubber-to-the-road feel about
going in front of an investor, that while you
had to sacrifice part ownership of the company, 
kind of gets you into a very different mindset
than you would get into from a grant perspective.
That said, there are plenty of reasons why
you would write a grant as an early-stage
company but I think there's nothing that compares
to getting someone who does this for a living
to give you their money because if they've
done that then you've clearly demonstrated
a bunch of things that suggest that this is
good going forward.
LONG:  So, thanks.
I want to ask a couple questions about scientific relationships, in particular, collaborations.
I was asked what types of collaborations are
useful to entrepreneurs and how do collaborations
with entrepreneurial relationships differ
from those in strictly an academic environment?
YOUNGER:  You know it's really interesting because I
think one of the things in my experience from
the startup perspective, is that it became
actually very difficult to have traditional
scientific collaborations and
for a couple of reasons, I think, you know for someone that sort of left academia,
there is a sort of questions about what, what's going on with you that you would leave?
And so it's you certainly put yourself in
a different spot, but the thing is that
that there a lot of concern over intellectual
property and I think far more than there needs
to be.  Founders are concerned that universities
are going to scoop their intellectual property
and they'll make a lot of entanglements.
Universities are concerned that their faculty
may give away an important idea and that an
opportunity to generate some royalty revenue
would be left on the table.
You find yourself in these discussions
that generate a lot of paperwork and certainly
generate some legal fees but not necessarily a lot of
value and
so I was quite surprised at how to how to
recalibrate collaborating with investigators
once I left academia.
And I still don't know that I have it completely
right.
It is hard, because you have to be so protective
in the startup.  You have to be so protective.  Your
IP is kind of the only asset you have.
And so it just, it requires a lot of caution and
that caution makes it complicated to just
sort of sit down and spitball ideas with people
you know because everyone just guards
more.  So, it's not easy.  With bigger companies,
as the company grows it becomes easy because
you can sort of set expectations about how
it's going to work,
but early on, especially when there is an opportunity
that, you know, there might be a financial opportunity,
but there's no there's no clear-cut boundary
between what the academics are working on and
you're working on.  It's a very difficult thing,
right, and
anyone that's collaborated with a startup
sort of shakes their head and says. "Oh my
God, these guys just keep coming back with
more forms for us to sign and negotiate."
But I'll tell you that the startups feel the
same way, right?
And it's hard to work with universities.
It's a strange, it's a strange dynamic.
LONG:  OK, now a couple
questions about timing.
When is the best time to start an entrepreneurial
career?
Do you need an MD-PhD/post-doc or experience running
an academic laboratory or are there experiences
worth pursuing that may increase an individual's
marketability when they pursue positions later?
What are your recommendations to young students?
YOUNGER:  So I will tell you that if you look at
the data, the startups that are most likely
to succeed are started by people that are
over 40.  And that's, that's just the data, right?
So, there are Mark Zuckerbergs out there.
But there aren't many of them, right?
Most startups are going to go on to succeed
are being led by people that have
a lot of experience and I think that's experience
in a couple of things.
It's specific content experience in whatever
industry is involved, right?
So if it's life sciences if it's, you
know, if it's, you know, I don't know,
kinase inhibitors, you do that for 20 years
you sort of understand a lot of things and
you can get out and go.
It's a lot of life experience and sort of
having kind of a level head and being able
to sort of, you know, survey your landscape
and make decisions about it.
So I think there is something to be said about doing it older.
That doesn't mean that you shouldn't.
And it doesn't mean that there's not an opportunity
to be involved but, you know, very early
on, a lot of times where I tell folks is that
you know if you're in your first year out
of school, unless you have an idea that's just
so compelling, and not compelling to you but
compelling to other people, that's what matters.
I mean everyone thinks their ideas are great,
but if someone else tells you, "This idea is
great."  Unless you have that, I would hunker down.
I would get a job.  I would start getting some
experience and let it go.
Remember, one way to think about this is that,
you know, sooner or later you have to retire.
And the most important dollar you save towards
retirement is the first one you save. It generates
more interest than everything after that and
so in some ways if you say across the arc
of your career when is it important to have
stability? Kind of early on.
It seems counterintuitive but early on, I think
it's actually really important to have some
stability, you know, when you can.
Now, some people just want to go and they've
got to get out
and they want to do startup
and I get that and that's great.
But I think, and this is my Midwest talking.
I think you should be cautious early on, right,
and be thoughtful about when's the right time to jump.
LONG:  So that actually segues really nicely into
another question I've gotten in the chatbox.
Do you think personality is important in surviving
in the industry, or is it a learning process?
Do you learn to be that kind of entrepreneur?
YOUNGER:  I think personality is important in surviving anywhere, right?
And, you know, not everybody that everybody
can survive in a you know, in an R1 research institution,
they don't have the personality for it, right?
That doesn't mean they have a broken personality,
it means they have a personality that doesn't
work there,
right?
And the same thing is true in industry.
You know there are people that are finishing
up their PhDs that cannot wait to get out
the door, right?
And they're just, like, they've been sending 
their CVs out since their first year, just trying
to make sure they can get out when it's time
because they know they don't want to be in
academia, they want to be in industry.
And at the same time, there are people that will thrive in
startups and people that are, that will not.
I think a lot of times you don't know in advance, right?
One of the tricks about academia is that, you
know, if you're in, you know, grad school right
now, the only real structured environment you've
probably ever been in is that environment,
right, and so you sort of assume this is what
there is.
That's not true.
There are many different cultures and there's
many different ways of working that don't
look like academia.  But I think it's really
a matter of trial and error and getting in
and seeing what happens and being able to step
back and say, you know, this was a great move
or, you know, frankly, this wasn't that great
of a move.  I don't think that there is much
risk in taking that shot and waiting to see
what happens as people think.
And people can be very scared that the minute you step
away from one thing, you'll never be back.
I will tell you that I, you know, I'm on committees
within a university again right now because
of stuff that we're doing with COVID-19, you
know, and you can find yourself sort of back
in there, sort of surprisingly.
So, I think it's important not to overemphasize
the risk and I think it's important to understand
that you give those opportunities a try to
see where your personality is the best fit.
LONG:  Speaking of COVID-19, talk to us a little bit
about what sort of opportunities have come
your way at this particular time and what
attracted you to to invest effort, spend time
on some of those things.
YOUNGER:  So, so a few things, and so the Science Center, so I work for a organization in West Philly
that's been an accelerator and an incubator
for a long time.
We also do early-stage investments.  So
we have several companies that we've either
incubated or that we currently have in 
the companies investment portfolio that
are working on specific things, and those things
that came up in advance.  They were already
working on antivirals or even specific lung
anti-inflammatory strategies that are really a
great fit right now, right?
And so it's great to sort of try to help them
out to make sure that they're seeing what,
what opportunities there are in terms of collaboration in terms of, you know,
federal funding to help support that.
But the other thing is, you know, for me personally,
which was sort of a surprise, is because I,
you know, I do have an academic and clinical
background,
I've had the opportunity to serve on a number
of groups right now that are either monitoring
the safety of current clinical trials and
so I'm participating in several DSMBs
right now because I understand the issues
but I don't have a horse in the race.  I am
truly arm's length,
I'm not a faculty at the university but I
understand the issues.  And I've also been helping
one of the region's universities think a little
bit about how do you how do you best allocate
resources to all the different clinical trials
that are being proposed?
Lots of folks are putting forward ideas.
There are as many ideas as there are
patients right now and, in a perfect world,
all the trials will never enroll because we'll
start tamping this down and the number of
patients will go down.
But in the meantime, trying to figure out as
an organization how do you prioritize,
how do you prioritize which clinical trials
should be worked on first is a very interesting,
it's a very interesting problem and it's been real honor to get to think about that a little bit.
LONG:  We could use you around NIH right about now.
People are asking questions and there are your answers to them.
YOUNGER:  I'm so close to the train station I just can't
come ...
LONG:  So, I saw a couple of questions here about
ideas.
How does one feasibly know the idea is novel
or interesting enough to merit the formation
of a startup?
Do you need a lot of legal experience or to
solicit the advice of a lawyer or investors?
YOUNGER:  Neither.  Neither of those is the right answer.
So, what you need is you need to find, you need
to go talk to 100 people that would be the
people that would buy it and find out what they
need, right?
So, at the end of the day, this is not about
whether or not the investor loves you, and
certainly it's not about whether or not your attorney
loves you because your attorney loves you.
What it's about is somebody wants it.
So when we started Akadeum, we had about 200
interviews in the can of people to try to
understand what they were doing currently
and whether or not there was a role for what
we were doing.
And I'm also happy to talk offline to people
about the sort of the formalism for doing
those interviews because it does matter how
you ask.
But the thing that will decide whether or
not you should go, is market pull.  Full stop.
That's what matters, is if you can demonstrate with reasonable assurance that people want it
then that becomes a company, right, and
the investors will follow that lead.
So the investors may have a sense in advance,
but if you come to an investor with data that
says, "We have all these people.  We know what
they do now and why it's not good enough,
and here's what we propose instead," that will
resonate, right?  The investors will follow that.
But this idea, this idea is called product
market fit, right?  If your idea is good that
it should be relatively straightforward to
demonstrate that people will pay you money for it.
I think the hardest thing I ever did in my
entire career so far is when we are thinking
about starting our company,
we took empty vials and we put labels on them
of what we sort of suppose we are going to
ultimately manufacture and we started walking
the halls of the University of Michigan and
sitting down with colleagues and sort of showing
them what the technology could do and then
saying, "That will be $400 a
bottle, please."  And, actually, instead of asking
someone, "Do you think this is a cool idea or,
you know, what would you do with this?" to ask
them, you know,
you know, "If you give me a purchase order, you
know, I can
manufacture without having to actually
charge you yet.
I don't charge you until I deliver."
But to actually say, "Would you write a purchase
order for this?" that is a life-transforming
moment when you talked to a colleague and
say, "I need some money for this idea."
LONG:  Pay for this.
YOUNGER:  But that's what has to happen, right?
If that can't happen, it's not a thing, right?
It may be brilliant, but it's not a thing, right?
And in that sort of, those sort of
interactions really were what got me off the
sidelines and helped me make the decision to do
something different.
LONG:  So I sort of got a provocative question:
Can you tell us about any opportunities that
you have declined because you thought it wasn't
the best fit for you?
YOUNGER:  Probably.
Well, yeah, sure, I guess I have one.
So I was ...
So when I left Michigan, it was about a year
after the chair of my department had
turned over to a new chairman and during that
chair search I, the dean approached me,
You know, I'd been in Michigan for 20 years and
I was approached, you know, "Do you ...
do you want the chairmanship?"
And I said, "No I didn't."
I didn't think about it at all.
I didn't want that job.
And it prompted my wife to ask, "Well, you know,
if you don't want that job,
what job do you want?"
But, but I think that was, that was probably
the first time where something that looked
like, you know, a sort of traditional kind of
arc-of-career move,
I simply, I didn't even think. I'm just
like, "This is not a thing I'm gonna do because
it's not the right fit for me," right?
And you sort of learn things aren't
the right fit by doing things and then, you
know, and saying, "Oh that was a mistake," right?
But I knew that I was not going to be a chairman
of an academic department.  There was just
no way that was gonna happen, right?
But it took some soul searching and getting
comfortable with the fact that, because that
was such an obvious next move, you know, that
there wasn't something broken, right?
It's like, you know what's wrong with me that
I would ever say no to an academic chairmanship?
And it just it wasn't it wasn't the right
job for me and I still think that's exactly
the move I should have taken.  I should not
have taken that job.
But, but you have to get comfortable with sort
of saying what are you and what are you not?
Which is not easy.
It takes time.
LONG:  You mentioned a couple times that you have a good sounding board and a partner.
Tell us a little bit about career change and
how that was influenced by having a professional
spouse and her requirements in the workplace,
how that dictated your choice.
YOUNGER:  So it dictates a lot, right.
So, my wife is one of the directors of the
Cardiovascular Institute at Penn and,
and when I, when I was thinking about leaving
my career in Michigan, she she was an early,
early-stage faculty, was just getting up her
lab, and we went out to dinner, like 2014,
and, you know, I said, "I'm thinking about
maybe quitting my job" and sort of laid out
the case.
And she just sort of nodded her head and said,
"Well, that's what you want do, that's what we should do."
And, she's actually very flexible about it,  And then, sort of interestingly, in 2018,
she took me out to dinner and said, "You know, I've been recruited to Penn.
We're moving to Philadelphia.
[laughter][unintelligible]
YOUNGER: This five-year-old IOU came out of her purse,
I was like oh I guess we are moving to Philadelphia.
There is a time and a place, right?
So I think the thing is, is that you...
one of the things that we find very useful
is that in a given year, if you look at the
productivity of either one of us, we have up years and we have down years, right?  There's years where there's
amazing things and there is years where everything
seems to drag and you can't ever get a grip
on the things you want to get done.
That happens to everybody, right?
But what we do is, is if you sum over everybody's
experience and you say, "As a team, what did
we get done this year?"  Then it becomes a lot
easier to say, you know, "We're gonna make a change because,
you know, the team accomplished this this year,
right?"
If you if you add up all the accomplishments
in the house, then you think about things
differently, right?
And so in a year where ... I didn't publish any
papers last year.  I don't know when I'm going
to publish another paper, but we still had
decent academic output out of the household,
right?
And so,
in thinking about summing across all the
people in the house--what did the team get
done?  I think that simplifies things and it
makes them less, it makes these sort of individual
scorekeeping less of a problem.
That's still there, right?
I mean, you know, that's, you know, having a partner
means, you know, trying not to keep score sometimes.
But, but making sure that you sum across everybody
and say this is what, you know, this is what
our address got done this year,
that's pretty good.  That simplifies I think, you know, how to keep that relationship honest, right?
LONG:  Well, I appreciate the team approach, there,
and considering productivity as an address.
YOUNGER:  Yeah, sometimes easier said than done.
LONG:  We're coming close to the end of the hour, so I'm going to get down to the last or question or two
I have one here.
What are the biggest hurdles or challenges
and what's your advice for overcoming these challenges or hurdles?
YOUNGER: I think the biggest
hurdles are what you, what you allow yourself
to sort of dream about what you are, right,
and I think the biggest challenge is to get
yourself past, sort of, self-imposed definitions
about what success looks like and to just
sort of say what makes me feel fulfilled and
in chasing that as opposed to chasing, you
know, what's the appropriate metric, you know,
that it's very hard and it takes a lot of
time and it takes a lot of reflection to sort
of say this makes me happy.
It may or may not look like what, what people
sort of assume sort of the median sort of
behavior is but it makes me happy, it's OK.
I think that that's a real challenge, right?
And it's true, I think, at any stage in your career.
What are you trying to get done?  And giving
yourself the latitude to do the thing that
you think is really remarkable and isn't necessarily
sort of chasing metrics that other people,
you know, traditionally have used.
It's not easy but I think that's it, right?
Giving yourself permission to do the things
that you need to do is is important, and it's
not simple.  It sounds simple but it can be
quite difficult, I think
LONG:  Oh, I think everybody appreciates that advice.
It's personalized, it's empowering, it's optimistic. No matter what,
we thank you for the time you spent with us.
We've come to the end of our hour.
I can assure you I had twice as many questions
in the box as I could possibly give to you.
I know everybody appreciated hearing from
you.
So, thank you very very much John for kicking
off our inaugural webinar in this series.
Best of luck to you as you approach the coming
days, weeks, months, thereafter.
And thanks again. Take care.
YOUNGER:  Thank you and everyone be safe.
This is gonna be OK.
It's gonna be amazing but it's not going to be
amazing quite yet.
Please feel free to reach out to me.  If
there's something I can do to help,
you know, I'm here. Once people are traveling if you come to Philadelphia,
lunch is on me.  I'm happy to take you out and
brainstorm about stuff.
But, but keep it up.
It's gonna be, it's gonna be incredible.  You're
gonna be incredible.
Just give it a little bit of time.
LONG:  Thanks.
And thanks everybody who participated
with questions in the chat box.
Have a great afternoon.
Bye from all of NIGMS and John
