
Pumas AI: A platform for pharmaceutical modeling and simulation - KenoFischer
http://pumas.ai
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KenoFischer
This is a really cool effort to overhaul the pharmaceutical software stack.
They just had their big 1.0 launch today. Also 100% written in Julia. Super
fast and uses all the latest tricks and ideas from pharmacometric science. I'm
not working on this myself (other than fixing the occasional bug they run
into), but some of my colleagues do. I'll see if I can point them here to
answer questions.

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skwb
Yeah but pharma in my personal experience is VERY conservative. A lot of them
still use SAS as their bread and butter for analysis. And guess what? All
their older trials that they have to maintain are all written in SAS. It's
basically how banking got stuck in a lot of legacy COBOL code, pharma got
stuck in SAS. Want to do healthcare economic modeling? Buy a license for
TreeAge (and it ain't cheap!). And it's not like you cannot do complex
analysis in it, it just doesn't have a sleek interface. The "biggest"
technology disputer in pharma I would argue would be Salesforce! They support
creating all tons of custom input interfaces for patient consenting and record
keeping. Enterprise ain't supposed to be sexy!

I just sorta worry if there is correct culture fit in pharmaceuticals when
there is a prevailing mentality of "no one ever got fired for buying
Microsoft".

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jogagobburu
You are right, a portion of pharma is conservative. There are two different
needs in Pharma - one is more like assembly line (pure operations) and other
other is "innovation". One has to decide what excites scientists - operations
(eg calculating group means over and over where the answer has to be exact) OR
innovation (get the questions right, designs right, analysis right, answers
approximately accurate). I think there is a place for "operations", but they
constitute "sustaining innovations". Meaning can I find the most economical
solution for this problem? Operations is a separate discussion.

Let us talk about "disruptive innovations". What if I told you I was part of
the team that approved a treatment for H1N1 flu pandemic in children without
ANY trial based on unapproved data in adults? What if I told you the
development pathway for pulmonary arterial hypertension in pediatrics was
driven by analysis performed by Pumas-like software to establish a reasonable
endpoint? These are patients who cannot perform most daily functions we take
for granted. There would have been no drugs approved otherwise. How can you,
me and others contribute to the disruptive innovation which will transform how
drugs are developed and patients are treated. Pumas is designed to disrupt
drug development and precision medicine. There are plenty of opportunities for
disruption in healthcare. these opportunities are the motivation for
Pumas..Joga Gobburu (Co-Founder, Pumas-AI)

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NicoJuicy
Which country are you tlaking about? ( cfr. "H1N1 flu pandemic in children
without ANY trial based on unapproved data in adults")

~~~
jogagobburu
USA for emergency use.

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ViralBShah
For those who want to jump into the details:

Docs: [https://docs.pumas.ai/](https://docs.pumas.ai/)

Tutorials: [https://tutorials.pumas.ai/](https://tutorials.pumas.ai/)

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bionhoward
Julia rocks! Congrats on the launch

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haolez
Slightly related: is there a good open source platform around for managing
health clinics? I've never stumbled upon a good one in my searches.

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tild3
[https://www.schrodinger.com/](https://www.schrodinger.com/) ?

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ChrisRackauckas
Drug discovery is fairly different from pharmacometrics. Drug discovery is
about finding what chemicals would likely produce the right effects by mining
models and simulation for how they would bind to proteins and how that effects
the protein's behavior. This generally uses molecular simulations, things like
molecular dynamics or DFT to compute properties of the molecules themselves.

Pharmacometrics is focused on precision dosing: given a drug in a clinical
trial, how should you be personalizing the dosing in order to have high
efficacy with low toxicity? This is different depending on many factors
(weight, metabolic factors, gender, etc.) and are a mix systems physiology
types of models of metabolic and cell signaling (quantitative systems
pharmacology and physiologically-based pharmacokinetics) and compartmental
models.

They are both useful, just at different stages of the drug development
pipeline. Drug discovery modeling and simulation is done at the very early
stages before the clinical trial to predict what drugs to test and what the
specificity of the targeting is (i.e. will it have off-target effects and
cause side effects?). On the other hand, pharmacological modeling and
simulation is done during the clinical to try and adaptively change the
dosing, understand effects on the population, and predict whether the new off-
target effects cause a system-wide toxic effects (i.e. just because drug X
accidentally blocks the binding of Y to Z doesn't necessarily mean that most
people will have a side effect, but you can predict whether certain sub-
populations might be more prone to side effects and how likely that is to
cause a clinical trial to fail). Given the cost of clinical trials is in the
billions, any mathematics that can predict whether it will fail or simply
avoid a clinical trial by proving safety through statistical means is
something that's in high demand.

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DrScientist
Do you really think you can avoid a trial by proving safety through
statistical means?

Aren't clinical trials done _because_ we don't know in advance - as the full
complexity of biology is beyond our ability to predict?

ie we do the trials to find out the things we didn't know ( and thus couldn't
model ).

Perhaps through rationalization of a trial result to avoid the call for
additional trials - but I find it hard to believe trials can be avoided in
general.

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jogagobburu
I think the key "emergency use" is missed. The question is what are we going
to do when you need something right away in a pandemic situation. The point
here has nothing to do with "avoiding" trials - that I will never advocate.
But there are enough situations that require us to think "outside the box". at
that point, magic cannot happen. we need build things systemically as science
progresses...

~~~
DrScientist
Even in a pandemic situation, I'd not sure I'd ever use a model if I could do
a phased rollout in terms of safety.

And if it's so bad - that you have no option but to give it to everyone now -
well you have no option...

I suppose the practical problem right now is not so much about the risks of
one individual vaccine, but rather choosing between the many many candidates.

How would you go about that?

