Let me just make sure everything's up and running, but it's good to see everybody today.
Welcome to the Cannabis Data Science Meetup Group.
My name is Keegan, founder of Cannlytics.
We provide analytics primarily to laboratories, but really everyone in the cannabis industry.
And it's good to see Charles and Heather, and then welcome Frank.
So real quick, I guess Charles and Heather, would you mind introducing yourselves to Frank?
And then Frank, if you wouldn't mind, you're welcome to introduce yourself to the group.
Hi, I'm Charles.
I have a long history of software development experience, and I'm transitioning into the
data science area now, and I've been working on a lot of the Washington State data, trying
to make some sense of it.
Awesome.
Heather, it's good to see you today.
Howdy, howdy.
Hi, everybody.
I'm Heather.
I'm not ex-scientist, but I've been in the lab for over a decade and then transitioned
into QA, QC work.
Now I have an interest in cannabis science, so what do I do with that?
So now that's why I'm here.
Awesome.
Well, good to have you as always.
Yeah, no, thank you.
Like the invite.
Definitely.
Frank, it's good to have you today.
Would you mind sharing a bit about your interests and passion, and what you may be doing for
work?
Yeah, I work mostly on like back end, just kind of data management for some companies
up in Washington in the cannabis industry.
And so yeah, trying to sort out all the data sources that are up there and just kind of
see what everybody else is thinking about in the data science realm.
We'd like to use more data, but they don't really have the questions to ask.
And I'm like, well, there's data around, but without questions to ask, it's kind of hard
to do much with it.
Well, you're in the right place, because that's what we're always doing, asking questions
and trying to get answers, or at least the best answers we can.
And so we happen to be looking at a data set of lab results here in Washington state.
So you can do a freedom of information request and get a data dump of all the observations
that they have in the state traceability system.
You can do this with sales, you could do this with inventory.
And then in our case, we've got all the data, but coincidentally, the lab results is one
of the smaller data sets.
And so that's one of the ones we're working with.
Well, to, I think, jump right in with me, to match everybody up to speed with what we've
been talking about.
So I'll go ahead and share my screen and then get some interesting observations for today.
So, right.
Bear with me and just let me know if there's any lag or anything and I'll do the best I
can to make things run smoother.
So long story short, we've been looking at lab results.
We were needing some questions, so we started to look at other data or analysis that may
have been done on cannabinoid testing or any sort of testing.
And so we found this Midwestern hemp database where they tested hemp.
And what's interesting is hemp has a mandated federal limit of 0.3%.
So as you can see in these charts, anything greater than 0.3% THC would actually be a
failing hemp sample and then anything below would be passing.
And what we began to notice is the threshold, the limit, is set in the middle of the, right
in the cluster of data points.
And so we were thinking that this may lead to situations where there's a couple of things
going on.
One, you're going to maybe have misleading products.
So something that technically passes at 0.29% THC that looks quite similar to a product
that fails at 0.31% THC.
So some of your conclusions about the data may be off.
Also just throwing in human incentives.
This throws in a pretty, how should we say, there's a lot of, you know, like I guess financial
value tied up with this decision, this pass failed decision.
So it puts a lot of pressure on laboratories.
So for example, the hemp producer that gets a test at 0.31% may call up the laboratory
and try to pressure them and say, oh, hey, are you sure that this was really failing?
And so, you know, that's standard business.
And so the laboratories, you know, just need to say that, you know, that's why we tested
it at.
But still, it creates that friction.
And so long story short, it may not, we were thinking, is this necessary?
Like, is this necessary friction?
So would things work out okay if they raise the threshold to say 0.6 or I think there
was talk about 0.65 or 0.7%?
In that case, there would be a handful of samples that fail.
And then, you know, the bulk of the hemp is passing.
There's not as much pressure on laboratories to, you know, to misreport THC numbers.
So we were curious about, you know, what the effect is of having these thresholds at different
levels.
So that's interesting with hemp.
We were wondering, can we apply this to research or to data in Washington state?
And what Heather had brought up was, oh, you know, sometimes these oils may make it to
the shelves and they may seem a little off.
And so we were going to start looking at, okay, what are the regulations on these, say,
residual solvents that may be in concentrates on a state by state basis?
And so here are the data sources.
And I'll post this code right after the talk.
I don't want to press the memory too much right now.
So long story short, here are the data sources where you can find the action limits.
And so here, essentially, you know, we've got the limits for Washington state.
And I picked out this set of residual solvents or this set of solvents, because these are
the ones that we have data for in Washington state.
A lot of these states test for more residual solvents.
And as you see, some test for less.
And Heather, this is where I was thinking that I had you in mind was, you know, you're
here in Maryland.
And Maryland actually has one of the least stringent testing regimes that there are.
So they only test for, you know, a little more than a handful of solvents.
Whereas for example, some, like in Washington, they'll test for acetone.
And I don't believe you test for acetone in Maryland.
And so there's variability here.
And from a data science perspective, wherever you can find variability, you can typically
do an interesting analysis of some sort or the other, because that's what makes things
interesting is the differences and variability.
So one thing, you have heptane in there twice.
Yes.
So heptane and heptanes.
Exactly.
And so you may have seen this in the data, and we may need to do a deeper dive here.
However, okay, so I've read in the data over here.
As Charles has pointed out, not all of these are valid observations, but I'm curious.
What is here?
If there's just two.
Okay, so see, it looks like there's two fields here in the leaf data systems traceability
data set.
So I think you can enter in both heptane and heptanes.
And I think the rationale may be that there are heptane-like compounds, which are your
heptanes.
Isomers?
Yeah, exactly.
So your isomers.
You may not be able to distinguish between those isomers, you know, so they'll conglomerate
with heptanes, like a hot dog, like this is what we think it is.
Exactly.
And so this may be one of these situations where we may not have entirely consistent
data entry across the board.
And so this should be something that should be noted.
However, we've got the data and one of my philosophies is never throw away any data.
So we'll keep it and work with it.
And for the most part, I've just double coded heptane and heptanes.
So if you look at the various regulations, some of them, like the Canadian limits, specify
the isomers, whereas others are less specific.
And so when you have time, it wouldn't hurt to read through some of the regulations here
where you can start seeing how they vary by, well, this is by country, but by country,
by country, by state, by state.
And here you see, for example, they have, so for like in Washington state, we test for
isopropanol.
And I believe, I'm not a chemist, so this may not be factually correct, but basically
I believe isopropyl acetate is like Heather said, either an isomer or related in some
manner to isopropanol.
So for Canada, I used their limit of 5,000.
So not entirely apples to apples, however close, for the most part, they're testing
a lot of the same compounds.
So you know, your pentane, your propane.
However, there are differences.
So for example, no one in, I couldn't find a state that's testing for triethylamine,
unless this is an isomer of some sort, you know, or nitrogen either.
Well, actually this says there's no limit.
So some places test for more, some test for less.
And so this is where we were talking about, be careful what you measure, because so in
Maryland, they're not even measuring acetone.
So this is where I was talking about, you may have something that gets stamped as PASS,
but it may have residual solvents, just not the ones that you were testing for.
So that's sort of where the discussion is leading.
So just to kind of get right into the juicy bits, because we've got some real interesting
observations here, and I'm interested to hear everyone's take and see if there's some new
leads we can take, some new ways we can go with this.
So next thing's next.
Just was going to look at, okay, so given that we have different limits in different
states, are there any samples that say may pass in Washington, but may fail in another
state?
And so the states that I've currently been working in are the follows.
And so basically, Washington state, we want to compare.
And so I'm curious, okay, well, how does that compare to Oklahoma?
Oklahoma has slightly newer regulations, and it will be interesting to compare.
And then Florida, which is medicinal only and is anecdotally has strict regulations.
So it'll be the first time I've run this for loop.
So let's hope, let's actually add a line break in here just to kind of help us see what's
going on.
Okay.
So, okay, so I think I actually need to simplify this for loop because right now I'm actually
looping over all the concentrate types and all the analytes.
So right now let's just look at all any of the sample types and just look at that.
So let's try this for loop out and maybe this will be slightly simpler.
Okay.
So this is a little better.
Okay, so what's going on here is essentially, okay, how many failures for acetone were there
in Washington, Oklahoma and Florida?
So Washington is the real, so there were seven real failures for acetone in Washington.
If we were under the Oklahoma testing regime, then there'd be 28 failures.
And then in Florida, there would be 46.
And so then if we just go down the line and just so you know, I've just looked at the
acetone numbers.
And so this is new information to me.
So it appears that, so this is quite interesting.
So look, so benzene, you know, the same in Washington and Oklahoma, quite a few more
failures in Florida, they're not measuring chloroform in Oklahoma.
I would like to look into the coding of this because this is such a large number, but it
looks like there is a substantial amount of samples that would fail for dichloromethane
in Florida, whereas you'd only have one failure in Washington state.
And so I think this is worth the drilling down on.
So like what is going on with dichloromethane?
Is this just some sort of miscoding of some sort?
So okay, so they're not testing in Oklahoma.
And so yes, so look at this.
So they allow 600 parts per million in Washington, whereas they only allow two parts per million
in Florida.
And I'll in fact, even want to kind of double check just to be 100% certain that I coded
this incorrectly.
So I may do this on my own time rather than hold you up here.
But anywho, exactly.
So look here, dichloromethane, two parts per million or less.
And so I mean, that's a staggering difference, right?
So in Washington, they're allowing 600 up to 600 parts per million and then in Florida,
too.
And so what's the effect of that?
Well, the effect is almost 5000 samples would have failed in Florida, that made it to the
shelves in Washington State.
And so you know, that's for I think for people to investigate further, like are Florida's
restrictions too strict?
Hold on, is my connection still okay here?
I can hear you.
Okay, great.
All good.
Okay, for some reason, I just let the connection may have not been 100%.
Ah, here we go.
We have Paul.
Okay, welcome, Paul.
So thought I may have heard someone trying to get in.
So good to have you.
Sorry about that, Keegan.
Yeah, thank you.
Oh, by all means.
So just to fill you in.
So I'm sure you may have noticed in the past few weeks, we've been talking about the residual
solvent limits.
And so we've now broken them down.
And so now we're saying, okay, what are the different limits for the various analytes
in the different states?
And right now, we've just uncovered our first major difference, which is dichloromethane,
which they have a fairly, they don't have a limit for in Oklahoma, to my knowledge.
And they don't, and the limit is, you know, 600 parts per million in Washington.
And so, you know, if you had applied that, you have always 5000 samples that would have
failed.
And so I won't, I think this is takes may take a little more time.
So Charles or Paul or anyone else who wants to dive into this, I think it'd be interesting
to look at these 5000 samples and find out more about them.
Like what types of samples are those?
Are they located in a specific place in the state?
You know, but essentially, you know, what's going on with those or, or then this is where
there's even opportunities.
So Fred, so this, Frank, this is where you could potentially provide value.
So you, what you could look at the actually the licensees that have this dichloromethane
in their products.
And I mean, it's public information.
And so you could reach out to them and say, hey, I've been looking at the Washington state
data, the residual solvents.
And I've noticed that, you know, your products, you know, have a, you know, a level of dichloromethane
that wouldn't be permitted in Florida.
Just thought I would let you know, in case you were thinking about expanding into Florida
or something of that sort.
And so, you know, there may be produce, there may be processors that they may think their
operation is picture perfect, but it just may be permissible under the Washington state
limits.
But if they were to say, try to operate in another state, they may have difficulties.
So for example, say a processor in Washington tries to go set up shop in Michigan or in
Maine, they're going to have trouble where they potentially could have trouble if they're
used to having high levels or, you know, high is subjective.
But if, you know, if they're used to having levels of like for methane in their products,
conversely, someone in Massachusetts, they may be even more accustomed to having dichloromethane
being permissible in their products than in other states.
I think Colorado is pretty strict.
And then it looks like California is also strict.
They're even stricter than Florida.
They have one part per million of dichloromethane.
So I think this is I think these are interesting observations here.
And so this is the first that I'm seeing the data.
So you're seeing it with me.
And so honestly, I was wasn't even sure if these numbers were going to be different.
And so Charles, this may be something that you may want to expand your prediction analysis
with.
Because so remember, we were saying like, oh, there's so few failures in Washington
State that it may be hard to to predict the failures.
Well here you could you could say, OK, you know, there's, you know, almost a 0% chance
or, you know, there's a low, you know, negligible chance that your fault fail for these solvents
in Washington.
But if you're in Florida, you know, there's this there's definitely a higher probability
of failure.
So once again, you could calculate those statistics and then reach out to say a license and then
you could make it conditional on licensee.
And so you can say, oh, hey, licensee X, you've got this probability of failing for residual
solvents in Oklahoma or in Florida or in California or Colorado or where have you.
Because Washington State has interesting rules where I don't think there's you're allowed
to have a lot of cross state operations.
I may be wrong on this.
But people have long future plans.
And so if there were a processor in Washington State, you know, and they are thinking about
expanding into another state, like they would probably I think they may benefit from dialing
in their process ahead of time.
So if they can realize, oh, you know, I'm not really failing for isopropanol in Washington
State, but I would in Oklahoma.
Well, it's time to dial that in.
And I think so we've established that there's differences here.
And so let's look at this data.
And so because I think I've done enough just pointing at numbers, but just actually plotting
these would be worthwhile here.
OK, so what am I doing here?
So I'm iterating over the solvents, which we've defined here, which is everything from
acetone to propane.
I'm getting the observations that have detected that analyte.
So these are the observations where you have measured, say, acetone, or you have measured
benzene or what have you.
And then I'm also restricting it to anything that's less than 20,000 parts per million.
The reason I'm doing this is the failure rate for most of these compounds, I believe, is
5000, maybe 10,000.
And so anything way above that is definitely going to be a failure.
And I've noticed that there may be miscoding or potentially just ridiculously high level
concentrations.
But I think there are miscoding where people have just miscoded high, say, 100,000 ppm
of solvent.
And so long story short, just sort of putting a cap on the data.
So and then just plotting them with the limits.
So for each plot, I'm going to add the limit.
And I'll post this code to GitHub afterwards so that way people can follow up on the analysis.
And so these charts just generated for the first time right before the meetup.
So they'll be interesting to look at together.
So just starting from the top here.
So here, I've essentially plotted everything that's tested for acetone in Washington State
between early 2018 to the end of 2020.
And so this excludes anything that did not have acetone detected and excludes anything
that was not tested for residual solvents.
So you could expect that these are concentrates of some sort that had some level of acetone.
And so this is supposed to be reminiscent of the plot we saw with hemp, where we were
seeing, OK, where are the limits set with hemp and what proportion of the samples are
failing?
And so this is where I think things just start out interesting.
So here you see, OK, Oklahoma and Florida have a similar limit.
And then the Washington State limit at 5,000 is substantially higher.
And what is the result of that?
Well, the result is there's a handful of samples here that pass, make it to market in Washington,
that wouldn't make it to market in Oklahoma or Florida.
And this is where I think things, they become worth thinking over.
So Washingtonians may want to take a look at things and are they OK with this proportion
of samples making it to market with acetone?
This is where we talk about the cost benefit analysis.
So if you lower the limits too far, then, well, I mean, it's subjective, right?
So maybe consumers think the limit for acetone should be zero and all of these samples should
be failing.
But then that would be thousands of, that would be thousands and thousands of grams
of oil.
And so that would be a huge cost to the processors.
So the idea is, OK, what is the permissible amount?
And from my economics point of view, I think it comes down to the cost benefit analysis.
However, everybody has their own stake in this.
And so just to move through here, does anyone have any questions or is everyone following
along pretty well so far?
So I still have a lot of issues with this data from, I sent you that report.
And there is, there's actually three, well, probably two sets of data, right?
There's a whole bunch of data at the beginning of 2018, actually all the way up to like September,
which doesn't seem like it's valid data.
It's like three quarters of the data, but it has a 0.07% failure rate.
And then there's this other set of data that has like a 4.5% failure rate that, you know,
it seems like it's more consistent.
I think, I mean, obviously, something's changed.
And obviously, there's a lot of historical data that was crammed into the beginning of
2018.
And I think this really clouds the results.
And as a mathematician, this kind of like really makes me twitchy.
Yes.
And so I think it's an interesting observation and it's tough to approach, right?
So right, we were talking about earlier, you know, never throw away data.
So we hate to just throw it away.
At the same time, it's suspect, right?
There's something, like you said, there's miscoding or whatnot.
And then the reasonable explanation is, so right here, this was the transition to the
leaf data system.
So there's just a lot of those things just getting coded in.
And so that would just be like existing inventory that gets added in.
But it's a lot of noise.
And I mean, if you don't throw away all this noise, then you kind of just have a bunch
of noise clouding up your predictions.
And if you're trying to get, if you're trying to use any sort of data science techniques
or machine learning techniques, your results are invalid because you have all this noise.
You can't learn anything.
You can't actually see what's going on because there's so much noise covering the signal.
I think you've hit on a good point.
And so I think it may be worth trying to exclude some of the noise.
So for example, like that's what I was starting to do here with excluding things below zero
and above less than 20,000.
So this is nifty because so in these plots, we're just looking at things that tested for
acetone.
So this is throwing away, hopefully, a lot of the noise.
So this will be excluding everything that doesn't have acetone.
With your analysis, you're going to have to do a bit more legwork to figure out what to
exclude and how to do your analysis.
But I think you're right.
So I think for starters, you could potentially time restrict it.
So OK, let's just look at things past 2019.
That could be a starter or just look at things past 2020.
Or even just filter out.
Yeah, there's a lot of there's a couple odd things going on.
I mean, you could filter out everything that doesn't have a valid lab ID.
That's one thing, because there are results that have valid lab IDs that start in February
of 2018 and go all the way through 2021.
But there's that other thing that the intermediate type, there's a lot of activity at the beginning
of 2018.
And then it basically drops off to being reported at zero.
And then all of a sudden in like July of 2019, it pops back up and it's in every result.
Yes.
And so that may actually be the better breaking point.
So basically what happens is Leaf Data System gets adopted in 2018.
They give everyone a lot of leeway for entering in their historic inventory.
So they give them really through April of 2018.
But then I think they still gave them a bit of leeway.
So you're looking at all the way through April 2018 just for data to get entered.
Then there was a major up was in my opinion that major.
But there was an update that occurred in July of 2019.
And it really it was actually kind of a shock for the industry.
One of the earlier meetups we were talking about, oh, there was a great metric outage
in California or wherever apparently.
And so this would be the equivalent in Washington state.
So for about a week in July or about a week or two weeks in July of 2019, there was an
update.
And what happened is, OK, so that essentially broke the API changed a little bit.
And so a lot of the software systems were no longer compatible.
And so there was a lot of software problems.
People had to update their software systems.
And so there was a lot of a lot of noise in the industry.
And so there was a period there where you have bad data entry.
So they basically Washington state permitted a tested lab results where the licensee could
attest that their sample had been tested and then that they could enter in the results.
And so so you have just a period there where there are odd results and inconsistent data
entry.
And so that could even be this period here.
Right.
And I think they squeaked in a lot of things because there's sort of like about it averages
out about two, three hundred entries a day.
And then there's this couple day period where it spikes to like six thousand entries.
So they probably had a bunch of failing product and then they attested, oh, it passed.
Well, I don't necessarily know about that.
But you see like here there's this line here.
So there's a handful of failures.
That's basically maybe they couldn't do data entry and then they just did all their data
entry on one day.
So right.
So yeah, I think anything after that seems to be valid.
I mean, everything else behind that seems really noisy.
And there's the intermediate type is missing for like months on end.
Exactly.
And this is where you could do some justification.
You could hunt down the press releases that Washington state put out saying, oh, we're
doing updates to the traceability system.
And then you can just provide some rationale for, OK, we're going to restrict our data
set to August of 2019 and onwards or even just give it a bit of leeway and just say,
OK, we're just going to restrict this from 2020 onwards just so we have a reliable data
set here.
So.
So I think you're definitely onto something, Charles.
And I like how you're not satisfied with the messy data and you're striving for top notch
analytics.
And so that's what we're all about here.
So just to bring it home, just to kind of show you some of the other charts here.
So you've got you've got your charts like benzene where everybody is essentially failing
of anything that has benzene.
And then and then here I read it.
I'm looking at this essentially brand new with you.
And so this is where we run into this situation where this is similar to the.
To the head to the hemp database we were looking at with failing hemp for high THC.
So here we see this line where, yes, it looks like a lot of things were entered all at once.
And so.
The situation here is OK.
So the limit is 5000 parts per million in Washington.
And so, you know, you have a non negligible portion of the samples failing for butane.
Florida's limit is actually slightly higher than than Oklahoma.
So but look here at Oklahoma's limit.
So Oklahoma has pushed their limit low.
It is.
One thousand.
So Oklahoma has a limit for butanes of 1000 parts per million.
And Florida has a limit of 2000.
And so this is just just drilling home the point where, OK, if you're operating in Washington,
you may be used to having one, two, three, maybe even four thousand parts per million
of butane in your final product and it still be permissible to be sold.
And this is where I was saying, you know, people aren't diving deep into this.
They're well, I mean, some are.
But if you get a certificate of analysis and it's just it says pass all across the board,
retailer may not think twice.
And they're just going to put this on the on the on their shelves.
They just they're just looking at their certificate.
They're looking for it to say pass or fail.
If it says pass, it's a go.
If it fails, it's a failure.
Right.
And so, you know, you're seeing products here that may be like forty nine hundred parts
per million, forty seven hundred parts per million.
You know, real, real close.
And so.
Does a retailer necessarily want those on their shelves?
All right.
Because say maybe a retailer has a policy.
Right.
Maybe a retailer has a retails.
And once again, I'm not certain about the cross state ownership here, but maybe a retailer
operates in a couple multiple states.
Well, maybe they have internal quality control standards and say, OK, we don't we don't
want anything with more than one thousand parts per million of butane in our store because,
OK, that's not allowed in Oklahoma.
So maybe we shouldn't allow that in Washington.
And then they all have to actually look at their certificate of analysis and see that,
OK, what is the level of butane?
So and then, you know, and then this is where the dialogue with the public comes in.
And is, OK, what is the permissible level of butane?
So.
Do consumers care about this?
Like, are they OK with this in their in their products?
What's the science behind it?
So what is the effect of consuming, you know, a hundred parts per million of butane in your
know, your one gram of oil?
Like what what is.
What is.
You know, the effect of that, like, is that a negligible amount of butane?
Is that a non negligible amount?
So I think I think these are questions that are worth being looked into.
So and then.
Just to show you some of the other charts here.
Core form.
Cyclohexane would like to do a deeper dive on this, but so this is one that's interesting
where this is not a good compound that you probably would not want in your system.
And you know, there's are things with detections, a cyclohexane, but, you know, these are making
it to market.
And then here, here where we talked about dichloromethane, where you see many samples
failing in Florida.
Whereas you really don't see many samples.
Just a handful, if any, failing in Washington state.
Similarly, this is ethyl acetate.
You see just a couple failures in Washington state.
And then you see if these were tested in Oklahoma or Florida testing regimes, then you would
see, oh, wow, you know, there's a look.
And keep in mind, I don't know the weight exactly, but this, you know, one sample represents
a substantial amount of oil that's going to concentrate that's going to be sold to the
retailer.
So this adds up.
So if these were failed, you know, that would be a cost to the processor.
And then otherwise, you know, there could be a health risk to the consumers if they
do make it to market.
Heptane.
And really, what these charts are really showing is, I didn't realize this until creating the
charts is that it, you know, Washington state has fairly permissible residual solvent limits.
So this is where we were talking about how really states that are coming online sooner
or more recently are almost leapfrogging some of the existing states.
So basically, okay, when Washington set their regulations, everyone was just setting the
bar at 5,000.
So they set their bar at 5,000.
And then, oh, somebody came along and then, oh, Canada set their bar even lower, or oh,
New York set their bar low, or who have you, California came along and they set their bar
low.
And so then the next state that comes along, well, they're just going to look at, okay,
what are the existing regulations?
And often they adopt the more stringent regulations because the policy, the person in charge of
public policy, you know, they want, they have the public health principle concern.
So you know, they don't want to risk these products necessarily making it to market.
So they'll often opt for the more stringent regulation.
And just to finish it out here are heptanes.
So this is where we're talking about coding.
So it looks like really people aren't coding in heptanes.
So it looks like heptanes is the principle thing, the principle analyte that people enter.
I think heptanes is a depreciated column.
Okay, that's what's going on here.
And so exactly.
So it looks like here in July of 2019, it gets deprecated.
So that's good information.
So exactly.
So just focus on heptane.
And then hexanes, once again, where you have Washington permitting these samples, whereas
Oklahoma and Florida would not.
And keep in mind, from what I've heard, Florida is quite strict.
Oklahoma, I don't know that much about, but it's interesting to see that they apparently
have a bit more stringent regulations than Washington as far as the actual permissible
amount of solvents.
Oh, and so this is an interesting one.
So this one's isopropanol.
And so isopropanol alcohol is used for cleaning.
And so once again, people in Washington, they may be used to having standard operating procedures
that include the use of isopropanol alcohol.
And this may wind up into their products.
If they were going to go set up shop in another state, they may need to address their standard
operating procedures to make sure that they're not contaminating their products with isopropanol.
Methanol, definitely don't want that in your products.
And so you're starting to see the consensus being lower.
And keep in mind, I just picked out Oklahoma and Florida as on a whim here.
And so I encourage you to, why don't you repeat some of these charts with some of the other
states?
So, OK, why don't we look at California and Colorado?
Or Heather, why don't you look at Maryland?
Or Paul, you could look at Michigan.
So it would just be interesting to see, OK, what is going to be allowed state by state?
And then just to show all the charts, pentanes, similar story, propane, once again.
You're seeing the Washington limit being quite high.
And once again, what is high?
So that's where the dialogue comes in.
All we can do is present the data and then cultivators, processors, regulators, consumers
can have it.
And they need to have a dialogue and discuss, OK, what are the permissible levels of these
solvents that are going to be allowed in concentrates?
Polyaline, polyaline, xylenes, definitely don't want those.
So here, the Washington state limit is catching most of them, but there are a handful that
still make it through to the market that wouldn't be allowed in Florida or Oklahoma.
And there we have it.
And so that was the analysis that I prepared for today that builds off of what we've been
talking about.
And that was in vain of what we were talking about with the hemp database, where we were
saying, OK, why don't we redo these charts with residual solvents on the x-axis?
All right.
And so just to take it home here, I've done a lot of talking today.
And so perhaps next week, we can have a bit more of a back and forth dialogue.
Because it's a meetup group after all.
We're supposed to be talking.
So sorry for just stealing the stage here.
So what are your thoughts?
Is this analysis you found interesting or what have you?
Yeah.
I thought it was interesting, Keegan.
I always keep thinking about market consolidation, which will happen at some point.
And to be able to know all these different thresholds for different states, any big players
that come onto the scene that want to start consolidating, they're going to have to understand
all this.
And I'm wondering if a strategy for somebody like a big investor would be not necessarily
to expand a chain of labs, but just to go because the labs that are in their separate
states have already fitted to the standards that are in place, if they would just go in
and try to buy up a bunch of labs and then make a chain out of all their purchases instead
of having to learn everything on the ground level at each state, just buy up the knowledge.
Well, so there are variations from state to state.
So for example, like in Oklahoma, Michigan, you've got mandated pesticide testing, don't
have that in Washington state.
However, the chemists, the ones that are doing pesticide testing, it's more just like, OK,
which pesticides are there?
So just give us the list.
We'll test for them.
So most of the laboratories, they have their own levels of detection, which are much lower
than the limits.
And so to me, I just see it as just, OK, just what the limit is.
So they'll just still test for the same pesticides and residual solvents.
And then this is where we were talking about, oh, they may need to add analytes state by
state.
So there will be some learning by doing in some places.
So for example, places with an extensive pesticide panel.
So say you're in California and you've got 70 plus pesticides, somebody operating there
is going to be much better probably at testing pesticides than somebody in, say, Oklahoma.
And I think in Oklahoma, they have maybe a dozen or two dozen regulated pesticides.
And so the method development manager there is they may not have been forced to do as
much development.
And it gets tricky when you start to.
So in Canada, they may have 100 plus, maybe 120 plus regulated pesticides.
And when you start to have to test for 120 pesticides, it becomes tricky because you
almost need two different scientific instruments to really measure them all.
So so I think you're right.
There will be some people who are experts at certain things in some states.
So it's going to be interesting to see how it shakes out over the next couple of years,
that's for sure.
But your analysis is really cool.
Exactly.
And there's going to be a lot of hard feelings one way or the other, because like I said,
like in Washington state, they've got those limits set at five thousand.
And if they were going to change those, there would be so much noise in the industry, like
all the processors.
And it's just that's just public policy.
That's what takes place.
And there would just be the deliberative dialogues.
They say, OK, we think we should lower the limits.
The processors are going to say, we don't think you should lower the limits.
And then they'll have their back and forth and they'll settle on something.
And so that's why, as you said, if you say the federal government were going to come
out with residual solvent limits, I think there'd be a big dialogue between all the
parties involved.
That's OK, what are these limits going to be?
Yeah, I wonder if some of these more, I guess, well-off labs are going to start hiring consultants
to go lobby in the various states, right, for their interest.
It's going to be interesting to see what happens.
Well, thank you.
Definitely.
And my my only point there is it's an interesting thing.
So the labs want to test for it.
So the lab says, oh, yes, I think we should test for acetone.
But the lab may not necessarily want a 2 ppm limit on acetone, because if they're having
to fail 30 percent of the samples, then that's a tough conversation you have to have with
the processors.
So I think the labs are in the situation where they probably want to test for it.
But I don't know if they necessarily want the lowest limit possible.
Yeah, as you always say about cost-benefit analysis, right, there's going to be a lot
of that going on, I'm sure.
So anyway, cool stuff.
So interesting topic.
Thanks everyone for coming.
I hope you got something out of it.
And so definitely feel free to shoot any messages throughout the week if you have any ideas
or have any avenues for further research.
Sure.
Just to keep it real quick, I'm shooting to have my full paper completed this weekend.
So if I get that done, I will forward the entire thing over to you this time.
Nice.
And I have a review that owed to you.
And so thanks for bearing with me.
And so yeah, don't worry about it.
Don't kill yourself over that, please.
It's coming.
And so everybody, stay tuned.
I'll try to get the video uploaded so that way you can review it and see anything.
And then, yeah, let's all stay in touch.
And we can pick this back up next weekend and look at some more data.
Take care, everybody.
All right.
Have a productive week.
Bye.