1 00:00:00,000 --> 00:00:14,340 Let me just make sure everything's up and running, but it's good to see everybody today. 2 00:00:14,340 --> 00:00:17,380 Welcome to the Cannabis Data Science Meetup Group. 3 00:00:17,380 --> 00:00:20,440 My name is Keegan, founder of Cannlytics. 4 00:00:20,440 --> 00:00:26,320 We provide analytics primarily to laboratories, but really everyone in the cannabis industry. 5 00:00:26,320 --> 00:00:30,960 And it's good to see Charles and Heather, and then welcome Frank. 6 00:00:30,960 --> 00:00:37,160 So real quick, I guess Charles and Heather, would you mind introducing yourselves to Frank? 7 00:00:37,160 --> 00:00:42,120 And then Frank, if you wouldn't mind, you're welcome to introduce yourself to the group. 8 00:00:42,120 --> 00:00:46,040 Hi, I'm Charles. 9 00:00:46,040 --> 00:00:52,720 I have a long history of software development experience, and I'm transitioning into the 10 00:00:52,720 --> 00:01:00,600 data science area now, and I've been working on a lot of the Washington State data, trying 11 00:01:00,600 --> 00:01:04,000 to make some sense of it. 12 00:01:04,000 --> 00:01:05,000 Awesome. 13 00:01:05,000 --> 00:01:09,480 Heather, it's good to see you today. 14 00:01:09,480 --> 00:01:10,480 Howdy, howdy. 15 00:01:10,480 --> 00:01:11,480 Hi, everybody. 16 00:01:11,480 --> 00:01:12,480 I'm Heather. 17 00:01:12,480 --> 00:01:17,880 I'm not ex-scientist, but I've been in the lab for over a decade and then transitioned 18 00:01:17,880 --> 00:01:21,280 into QA, QC work. 19 00:01:21,280 --> 00:01:23,760 Now I have an interest in cannabis science, so what do I do with that? 20 00:01:23,760 --> 00:01:25,960 So now that's why I'm here. 21 00:01:25,960 --> 00:01:26,960 Awesome. 22 00:01:26,960 --> 00:01:29,600 Well, good to have you as always. 23 00:01:29,600 --> 00:01:31,360 Yeah, no, thank you. 24 00:01:31,360 --> 00:01:32,360 Like the invite. 25 00:01:32,360 --> 00:01:33,360 Definitely. 26 00:01:33,360 --> 00:01:36,120 Frank, it's good to have you today. 27 00:01:36,120 --> 00:01:44,040 Would you mind sharing a bit about your interests and passion, and what you may be doing for 28 00:01:44,040 --> 00:01:45,040 work? 29 00:01:45,040 --> 00:01:50,440 Yeah, I work mostly on like back end, just kind of data management for some companies 30 00:01:50,440 --> 00:01:53,680 up in Washington in the cannabis industry. 31 00:01:53,680 --> 00:02:00,120 And so yeah, trying to sort out all the data sources that are up there and just kind of 32 00:02:00,120 --> 00:02:03,440 see what everybody else is thinking about in the data science realm. 33 00:02:03,440 --> 00:02:11,240 We'd like to use more data, but they don't really have the questions to ask. 34 00:02:11,240 --> 00:02:15,640 And I'm like, well, there's data around, but without questions to ask, it's kind of hard 35 00:02:15,640 --> 00:02:17,280 to do much with it. 36 00:02:17,280 --> 00:02:21,880 Well, you're in the right place, because that's what we're always doing, asking questions 37 00:02:21,880 --> 00:02:26,480 and trying to get answers, or at least the best answers we can. 38 00:02:26,480 --> 00:02:34,200 And so we happen to be looking at a data set of lab results here in Washington state. 39 00:02:34,200 --> 00:02:43,560 So you can do a freedom of information request and get a data dump of all the observations 40 00:02:43,560 --> 00:02:47,200 that they have in the state traceability system. 41 00:02:47,200 --> 00:02:52,320 You can do this with sales, you could do this with inventory. 42 00:02:52,320 --> 00:02:59,640 And then in our case, we've got all the data, but coincidentally, the lab results is one 43 00:02:59,640 --> 00:03:01,840 of the smaller data sets. 44 00:03:01,840 --> 00:03:08,360 And so that's one of the ones we're working with. 45 00:03:08,360 --> 00:03:25,080 Well, to, I think, jump right in with me, to match everybody up to speed with what we've 46 00:03:25,080 --> 00:03:27,440 been talking about. 47 00:03:27,440 --> 00:03:38,280 So I'll go ahead and share my screen and then get some interesting observations for today. 48 00:03:38,280 --> 00:03:42,520 So, right. 49 00:03:42,520 --> 00:03:56,440 Bear with me and just let me know if there's any lag or anything and I'll do the best I 50 00:03:56,440 --> 00:04:02,320 can to make things run smoother. 51 00:04:02,320 --> 00:04:06,400 So long story short, we've been looking at lab results. 52 00:04:06,400 --> 00:04:13,080 We were needing some questions, so we started to look at other data or analysis that may 53 00:04:13,080 --> 00:04:20,680 have been done on cannabinoid testing or any sort of testing. 54 00:04:20,680 --> 00:04:27,360 And so we found this Midwestern hemp database where they tested hemp. 55 00:04:27,360 --> 00:04:42,800 And what's interesting is hemp has a mandated federal limit of 0.3%. 56 00:04:42,800 --> 00:04:51,720 So as you can see in these charts, anything greater than 0.3% THC would actually be a 57 00:04:51,720 --> 00:04:57,920 failing hemp sample and then anything below would be passing. 58 00:04:57,920 --> 00:05:07,480 And what we began to notice is the threshold, the limit, is set in the middle of the, right 59 00:05:07,480 --> 00:05:10,720 in the cluster of data points. 60 00:05:10,720 --> 00:05:18,000 And so we were thinking that this may lead to situations where there's a couple of things 61 00:05:18,000 --> 00:05:19,000 going on. 62 00:05:19,000 --> 00:05:22,560 One, you're going to maybe have misleading products. 63 00:05:22,560 --> 00:05:34,800 So something that technically passes at 0.29% THC that looks quite similar to a product 64 00:05:34,800 --> 00:05:45,080 that fails at 0.31% THC. 65 00:05:45,080 --> 00:05:49,160 So some of your conclusions about the data may be off. 66 00:05:49,160 --> 00:05:52,600 Also just throwing in human incentives. 67 00:05:52,600 --> 00:06:06,200 This throws in a pretty, how should we say, there's a lot of, you know, like I guess financial 68 00:06:06,200 --> 00:06:12,000 value tied up with this decision, this pass failed decision. 69 00:06:12,000 --> 00:06:17,600 So it puts a lot of pressure on laboratories. 70 00:06:17,600 --> 00:06:25,360 So for example, the hemp producer that gets a test at 0.31% may call up the laboratory 71 00:06:25,360 --> 00:06:31,640 and try to pressure them and say, oh, hey, are you sure that this was really failing? 72 00:06:31,640 --> 00:06:35,120 And so, you know, that's standard business. 73 00:06:35,120 --> 00:06:38,960 And so the laboratories, you know, just need to say that, you know, that's why we tested 74 00:06:38,960 --> 00:06:39,960 it at. 75 00:06:39,960 --> 00:06:45,240 But still, it creates that friction. 76 00:06:45,240 --> 00:06:53,080 And so long story short, it may not, we were thinking, is this necessary? 77 00:06:53,080 --> 00:06:56,280 Like, is this necessary friction? 78 00:06:56,280 --> 00:07:04,240 So would things work out okay if they raise the threshold to say 0.6 or I think there 79 00:07:04,240 --> 00:07:08,480 was talk about 0.65 or 0.7%? 80 00:07:08,480 --> 00:07:12,880 In that case, there would be a handful of samples that fail. 81 00:07:12,880 --> 00:07:16,960 And then, you know, the bulk of the hemp is passing. 82 00:07:16,960 --> 00:07:29,280 There's not as much pressure on laboratories to, you know, to misreport THC numbers. 83 00:07:29,280 --> 00:07:38,120 So we were curious about, you know, what the effect is of having these thresholds at different 84 00:07:38,120 --> 00:07:40,600 levels. 85 00:07:40,600 --> 00:07:45,000 So that's interesting with hemp. 86 00:07:45,000 --> 00:07:55,920 We were wondering, can we apply this to research or to data in Washington state? 87 00:07:55,920 --> 00:08:06,920 And what Heather had brought up was, oh, you know, sometimes these oils may make it to 88 00:08:06,920 --> 00:08:12,240 the shelves and they may seem a little off. 89 00:08:12,240 --> 00:08:20,000 And so we were going to start looking at, okay, what are the regulations on these, say, 90 00:08:20,000 --> 00:08:26,320 residual solvents that may be in concentrates on a state by state basis? 91 00:08:26,320 --> 00:08:32,280 And so here are the data sources. 92 00:08:32,280 --> 00:08:37,160 And I'll post this code right after the talk. 93 00:08:37,160 --> 00:08:40,280 I don't want to press the memory too much right now. 94 00:08:40,280 --> 00:08:49,520 So long story short, here are the data sources where you can find the action limits. 95 00:08:49,520 --> 00:08:56,640 And so here, essentially, you know, we've got the limits for Washington state. 96 00:08:56,640 --> 00:09:06,520 And I picked out this set of residual solvents or this set of solvents, because these are 97 00:09:06,520 --> 00:09:09,960 the ones that we have data for in Washington state. 98 00:09:09,960 --> 00:09:16,360 A lot of these states test for more residual solvents. 99 00:09:16,360 --> 00:09:20,720 And as you see, some test for less. 100 00:09:20,720 --> 00:09:28,160 And Heather, this is where I was thinking that I had you in mind was, you know, you're 101 00:09:28,160 --> 00:09:31,160 here in Maryland. 102 00:09:31,160 --> 00:09:40,840 And Maryland actually has one of the least stringent testing regimes that there are. 103 00:09:40,840 --> 00:09:49,520 So they only test for, you know, a little more than a handful of solvents. 104 00:09:49,520 --> 00:09:56,080 Whereas for example, some, like in Washington, they'll test for acetone. 105 00:09:56,080 --> 00:10:00,280 And I don't believe you test for acetone in Maryland. 106 00:10:00,280 --> 00:10:07,520 And so there's variability here. 107 00:10:07,520 --> 00:10:15,040 And from a data science perspective, wherever you can find variability, you can typically 108 00:10:15,040 --> 00:10:23,320 do an interesting analysis of some sort or the other, because that's what makes things 109 00:10:23,320 --> 00:10:29,200 interesting is the differences and variability. 110 00:10:29,200 --> 00:10:34,280 So one thing, you have heptane in there twice. 111 00:10:34,280 --> 00:10:35,280 Yes. 112 00:10:35,280 --> 00:10:38,280 So heptane and heptanes. 113 00:10:38,280 --> 00:10:39,560 Exactly. 114 00:10:39,560 --> 00:10:46,960 And so you may have seen this in the data, and we may need to do a deeper dive here. 115 00:10:46,960 --> 00:10:54,960 However, okay, so I've read in the data over here. 116 00:10:54,960 --> 00:11:05,880 As Charles has pointed out, not all of these are valid observations, but I'm curious. 117 00:11:05,880 --> 00:11:19,520 What is here? 118 00:11:19,520 --> 00:11:22,280 If there's just two. 119 00:11:22,280 --> 00:11:30,760 Okay, so see, it looks like there's two fields here in the leaf data systems traceability 120 00:11:30,760 --> 00:11:32,400 data set. 121 00:11:32,400 --> 00:11:40,040 So I think you can enter in both heptane and heptanes. 122 00:11:40,040 --> 00:11:50,640 And I think the rationale may be that there are heptane-like compounds, which are your 123 00:11:50,640 --> 00:11:51,640 heptanes. 124 00:11:51,640 --> 00:11:52,640 Isomers? 125 00:11:52,640 --> 00:11:53,640 Yeah, exactly. 126 00:11:53,640 --> 00:11:54,640 So your isomers. 127 00:11:54,640 --> 00:12:00,400 You may not be able to distinguish between those isomers, you know, so they'll conglomerate 128 00:12:00,400 --> 00:12:07,000 with heptanes, like a hot dog, like this is what we think it is. 129 00:12:07,000 --> 00:12:08,000 Exactly. 130 00:12:08,000 --> 00:12:15,720 And so this may be one of these situations where we may not have entirely consistent 131 00:12:15,720 --> 00:12:18,600 data entry across the board. 132 00:12:18,600 --> 00:12:22,400 And so this should be something that should be noted. 133 00:12:22,400 --> 00:12:31,240 However, we've got the data and one of my philosophies is never throw away any data. 134 00:12:31,240 --> 00:12:35,520 So we'll keep it and work with it. 135 00:12:35,520 --> 00:12:42,400 And for the most part, I've just double coded heptane and heptanes. 136 00:12:42,400 --> 00:12:56,520 So if you look at the various regulations, some of them, like the Canadian limits, specify 137 00:12:56,520 --> 00:13:03,840 the isomers, whereas others are less specific. 138 00:13:03,840 --> 00:13:11,240 And so when you have time, it wouldn't hurt to read through some of the regulations here 139 00:13:11,240 --> 00:13:18,280 where you can start seeing how they vary by, well, this is by country, but by country, 140 00:13:18,280 --> 00:13:20,920 by country, by state, by state. 141 00:13:20,920 --> 00:13:32,600 And here you see, for example, they have, so for like in Washington state, we test for 142 00:13:32,600 --> 00:13:35,680 isopropanol. 143 00:13:35,680 --> 00:13:42,120 And I believe, I'm not a chemist, so this may not be factually correct, but basically 144 00:13:42,120 --> 00:13:50,640 I believe isopropyl acetate is like Heather said, either an isomer or related in some 145 00:13:50,640 --> 00:13:53,120 manner to isopropanol. 146 00:13:53,120 --> 00:14:05,760 So for Canada, I used their limit of 5,000. 147 00:14:05,760 --> 00:14:13,360 So not entirely apples to apples, however close, for the most part, they're testing 148 00:14:13,360 --> 00:14:15,560 a lot of the same compounds. 149 00:14:15,560 --> 00:14:19,960 So you know, your pentane, your propane. 150 00:14:19,960 --> 00:14:24,320 However, there are differences. 151 00:14:24,320 --> 00:14:32,640 So for example, no one in, I couldn't find a state that's testing for triethylamine, 152 00:14:32,640 --> 00:14:39,200 unless this is an isomer of some sort, you know, or nitrogen either. 153 00:14:39,200 --> 00:14:42,840 Well, actually this says there's no limit. 154 00:14:42,840 --> 00:14:48,080 So some places test for more, some test for less. 155 00:14:48,080 --> 00:14:56,560 And so this is where we were talking about, be careful what you measure, because so in 156 00:14:56,560 --> 00:15:02,120 Maryland, they're not even measuring acetone. 157 00:15:02,120 --> 00:15:08,480 So this is where I was talking about, you may have something that gets stamped as PASS, 158 00:15:08,480 --> 00:15:20,160 but it may have residual solvents, just not the ones that you were testing for. 159 00:15:20,160 --> 00:15:27,640 So that's sort of where the discussion is leading. 160 00:15:27,640 --> 00:15:33,200 So just to kind of get right into the juicy bits, because we've got some real interesting 161 00:15:33,200 --> 00:15:38,600 observations here, and I'm interested to hear everyone's take and see if there's some new 162 00:15:38,600 --> 00:15:45,360 leads we can take, some new ways we can go with this. 163 00:15:45,360 --> 00:15:49,400 So next thing's next. 164 00:15:49,400 --> 00:15:56,600 Just was going to look at, okay, so given that we have different limits in different 165 00:15:56,600 --> 00:16:06,080 states, are there any samples that say may pass in Washington, but may fail in another 166 00:16:06,080 --> 00:16:07,080 state? 167 00:16:07,080 --> 00:16:16,760 And so the states that I've currently been working in are the follows. 168 00:16:16,760 --> 00:16:19,840 And so basically, Washington state, we want to compare. 169 00:16:19,840 --> 00:16:24,000 And so I'm curious, okay, well, how does that compare to Oklahoma? 170 00:16:24,000 --> 00:16:30,560 Oklahoma has slightly newer regulations, and it will be interesting to compare. 171 00:16:30,560 --> 00:16:41,440 And then Florida, which is medicinal only and is anecdotally has strict regulations. 172 00:16:41,440 --> 00:16:47,680 So it'll be the first time I've run this for loop. 173 00:16:47,680 --> 00:17:06,360 So let's hope, let's actually add a line break in here just to kind of help us see what's 174 00:17:06,360 --> 00:17:09,200 going on. 175 00:17:09,200 --> 00:17:12,200 Okay. 176 00:17:12,200 --> 00:17:30,000 So, okay, so I think I actually need to simplify this for loop because right now I'm actually 177 00:17:30,000 --> 00:17:36,960 looping over all the concentrate types and all the analytes. 178 00:17:36,960 --> 00:17:51,320 So right now let's just look at all any of the sample types and just look at that. 179 00:17:51,320 --> 00:17:56,840 So let's try this for loop out and maybe this will be slightly simpler. 180 00:17:56,840 --> 00:17:58,080 Okay. 181 00:17:58,080 --> 00:18:00,440 So this is a little better. 182 00:18:00,440 --> 00:18:15,600 Okay, so what's going on here is essentially, okay, how many failures for acetone were there 183 00:18:15,600 --> 00:18:19,240 in Washington, Oklahoma and Florida? 184 00:18:19,240 --> 00:18:32,640 So Washington is the real, so there were seven real failures for acetone in Washington. 185 00:18:32,640 --> 00:18:41,040 If we were under the Oklahoma testing regime, then there'd be 28 failures. 186 00:18:41,040 --> 00:18:45,560 And then in Florida, there would be 46. 187 00:18:45,560 --> 00:18:52,480 And so then if we just go down the line and just so you know, I've just looked at the 188 00:18:52,480 --> 00:18:55,280 acetone numbers. 189 00:18:55,280 --> 00:18:58,640 And so this is new information to me. 190 00:18:58,640 --> 00:19:04,160 So it appears that, so this is quite interesting. 191 00:19:04,160 --> 00:19:11,760 So look, so benzene, you know, the same in Washington and Oklahoma, quite a few more 192 00:19:11,760 --> 00:19:21,680 failures in Florida, they're not measuring chloroform in Oklahoma. 193 00:19:21,680 --> 00:19:27,080 I would like to look into the coding of this because this is such a large number, but it 194 00:19:27,080 --> 00:19:35,400 looks like there is a substantial amount of samples that would fail for dichloromethane 195 00:19:35,400 --> 00:19:42,920 in Florida, whereas you'd only have one failure in Washington state. 196 00:19:42,920 --> 00:19:46,720 And so I think this is worth the drilling down on. 197 00:19:46,720 --> 00:19:51,700 So like what is going on with dichloromethane? 198 00:19:51,700 --> 00:19:56,640 Is this just some sort of miscoding of some sort? 199 00:19:56,640 --> 00:20:08,160 So okay, so they're not testing in Oklahoma. 200 00:20:08,160 --> 00:20:09,820 And so yes, so look at this. 201 00:20:09,820 --> 00:20:19,640 So they allow 600 parts per million in Washington, whereas they only allow two parts per million 202 00:20:19,640 --> 00:20:22,400 in Florida. 203 00:20:22,400 --> 00:20:33,680 And I'll in fact, even want to kind of double check just to be 100% certain that I coded 204 00:20:33,680 --> 00:20:40,840 this incorrectly. 205 00:20:40,840 --> 00:20:49,880 So I may do this on my own time rather than hold you up here. 206 00:20:49,880 --> 00:20:56,800 But anywho, exactly. 207 00:20:56,800 --> 00:21:02,520 So look here, dichloromethane, two parts per million or less. 208 00:21:02,520 --> 00:21:06,640 And so I mean, that's a staggering difference, right? 209 00:21:06,640 --> 00:21:13,240 So in Washington, they're allowing 600 up to 600 parts per million and then in Florida, 210 00:21:13,240 --> 00:21:14,560 too. 211 00:21:14,560 --> 00:21:16,880 And so what's the effect of that? 212 00:21:16,880 --> 00:21:27,400 Well, the effect is almost 5000 samples would have failed in Florida, that made it to the 213 00:21:27,400 --> 00:21:30,440 shelves in Washington State. 214 00:21:30,440 --> 00:21:37,960 And so you know, that's for I think for people to investigate further, like are Florida's 215 00:21:37,960 --> 00:21:41,080 restrictions too strict? 216 00:21:41,080 --> 00:21:53,960 Hold on, is my connection still okay here? 217 00:21:53,960 --> 00:21:54,960 I can hear you. 218 00:21:54,960 --> 00:21:55,960 Okay, great. 219 00:21:55,960 --> 00:21:56,960 All good. 220 00:21:56,960 --> 00:22:01,400 Okay, for some reason, I just let the connection may have not been 100%. 221 00:22:01,400 --> 00:22:03,960 Ah, here we go. 222 00:22:03,960 --> 00:22:06,960 We have Paul. 223 00:22:06,960 --> 00:22:13,400 Okay, welcome, Paul. 224 00:22:13,400 --> 00:22:18,080 So thought I may have heard someone trying to get in. 225 00:22:18,080 --> 00:22:20,480 So good to have you. 226 00:22:20,480 --> 00:22:21,480 Sorry about that, Keegan. 227 00:22:21,480 --> 00:22:22,480 Yeah, thank you. 228 00:22:22,480 --> 00:22:23,480 Oh, by all means. 229 00:22:23,480 --> 00:22:25,280 So just to fill you in. 230 00:22:25,280 --> 00:22:30,720 So I'm sure you may have noticed in the past few weeks, we've been talking about the residual 231 00:22:30,720 --> 00:22:32,560 solvent limits. 232 00:22:32,560 --> 00:22:34,960 And so we've now broken them down. 233 00:22:34,960 --> 00:22:43,160 And so now we're saying, okay, what are the different limits for the various analytes 234 00:22:43,160 --> 00:22:45,440 in the different states? 235 00:22:45,440 --> 00:22:54,480 And right now, we've just uncovered our first major difference, which is dichloromethane, 236 00:22:54,480 --> 00:23:01,800 which they have a fairly, they don't have a limit for in Oklahoma, to my knowledge. 237 00:23:01,800 --> 00:23:07,800 And they don't, and the limit is, you know, 600 parts per million in Washington. 238 00:23:07,800 --> 00:23:15,400 And so, you know, if you had applied that, you have always 5000 samples that would have 239 00:23:15,400 --> 00:23:16,400 failed. 240 00:23:16,400 --> 00:23:21,960 And so I won't, I think this is takes may take a little more time. 241 00:23:21,960 --> 00:23:27,420 So Charles or Paul or anyone else who wants to dive into this, I think it'd be interesting 242 00:23:27,420 --> 00:23:34,880 to look at these 5000 samples and find out more about them. 243 00:23:34,880 --> 00:23:40,600 Like what types of samples are those? 244 00:23:40,600 --> 00:23:47,120 Are they located in a specific place in the state? 245 00:23:47,120 --> 00:23:55,640 You know, but essentially, you know, what's going on with those or, or then this is where 246 00:23:55,640 --> 00:23:58,080 there's even opportunities. 247 00:23:58,080 --> 00:24:05,720 So Fred, so this, Frank, this is where you could potentially provide value. 248 00:24:05,720 --> 00:24:14,520 So you, what you could look at the actually the licensees that have this dichloromethane 249 00:24:14,520 --> 00:24:16,640 in their products. 250 00:24:16,640 --> 00:24:18,520 And I mean, it's public information. 251 00:24:18,520 --> 00:24:23,960 And so you could reach out to them and say, hey, I've been looking at the Washington state 252 00:24:23,960 --> 00:24:27,680 data, the residual solvents. 253 00:24:27,680 --> 00:24:37,640 And I've noticed that, you know, your products, you know, have a, you know, a level of dichloromethane 254 00:24:37,640 --> 00:24:40,000 that wouldn't be permitted in Florida. 255 00:24:40,000 --> 00:24:45,800 Just thought I would let you know, in case you were thinking about expanding into Florida 256 00:24:45,800 --> 00:24:47,920 or something of that sort. 257 00:24:47,920 --> 00:24:56,240 And so, you know, there may be produce, there may be processors that they may think their 258 00:24:56,240 --> 00:25:04,880 operation is picture perfect, but it just may be permissible under the Washington state 259 00:25:04,880 --> 00:25:05,880 limits. 260 00:25:05,880 --> 00:25:14,480 But if they were to say, try to operate in another state, they may have difficulties. 261 00:25:14,480 --> 00:25:23,840 So for example, say a processor in Washington tries to go set up shop in Michigan or in 262 00:25:23,840 --> 00:25:30,880 Maine, they're going to have trouble where they potentially could have trouble if they're 263 00:25:30,880 --> 00:25:37,600 used to having high levels or, you know, high is subjective. 264 00:25:37,600 --> 00:25:44,400 But if, you know, if they're used to having levels of like for methane in their products, 265 00:25:44,400 --> 00:25:54,840 conversely, someone in Massachusetts, they may be even more accustomed to having dichloromethane 266 00:25:54,840 --> 00:25:59,880 being permissible in their products than in other states. 267 00:25:59,880 --> 00:26:06,520 I think Colorado is pretty strict. 268 00:26:06,520 --> 00:26:09,880 And then it looks like California is also strict. 269 00:26:09,880 --> 00:26:11,400 They're even stricter than Florida. 270 00:26:11,400 --> 00:26:18,320 They have one part per million of dichloromethane. 271 00:26:18,320 --> 00:26:27,640 So I think this is I think these are interesting observations here. 272 00:26:27,640 --> 00:26:31,680 And so this is the first that I'm seeing the data. 273 00:26:31,680 --> 00:26:35,840 So you're seeing it with me. 274 00:26:35,840 --> 00:26:48,160 And so honestly, I was wasn't even sure if these numbers were going to be different. 275 00:26:48,160 --> 00:26:56,280 And so Charles, this may be something that you may want to expand your prediction analysis 276 00:26:56,280 --> 00:26:57,280 with. 277 00:26:57,280 --> 00:27:03,320 Because so remember, we were saying like, oh, there's so few failures in Washington 278 00:27:03,320 --> 00:27:09,680 State that it may be hard to to predict the failures. 279 00:27:09,680 --> 00:27:16,720 Well here you could you could say, OK, you know, there's, you know, almost a 0% chance 280 00:27:16,720 --> 00:27:23,080 or, you know, there's a low, you know, negligible chance that your fault fail for these solvents 281 00:27:23,080 --> 00:27:24,760 in Washington. 282 00:27:24,760 --> 00:27:29,180 But if you're in Florida, you know, there's this there's definitely a higher probability 283 00:27:29,180 --> 00:27:31,440 of failure. 284 00:27:31,440 --> 00:27:39,120 So once again, you could calculate those statistics and then reach out to say a license and then 285 00:27:39,120 --> 00:27:42,360 you could make it conditional on licensee. 286 00:27:42,360 --> 00:27:53,600 And so you can say, oh, hey, licensee X, you've got this probability of failing for residual 287 00:27:53,600 --> 00:28:04,520 solvents in Oklahoma or in Florida or in California or Colorado or where have you. 288 00:28:04,520 --> 00:28:09,240 Because Washington State has interesting rules where I don't think there's you're allowed 289 00:28:09,240 --> 00:28:12,400 to have a lot of cross state operations. 290 00:28:12,400 --> 00:28:15,200 I may be wrong on this. 291 00:28:15,200 --> 00:28:19,380 But people have long future plans. 292 00:28:19,380 --> 00:28:26,280 And so if there were a processor in Washington State, you know, and they are thinking about 293 00:28:26,280 --> 00:28:37,200 expanding into another state, like they would probably I think they may benefit from dialing 294 00:28:37,200 --> 00:28:39,600 in their process ahead of time. 295 00:28:39,600 --> 00:28:46,920 So if they can realize, oh, you know, I'm not really failing for isopropanol in Washington 296 00:28:46,920 --> 00:28:50,200 State, but I would in Oklahoma. 297 00:28:50,200 --> 00:28:55,480 Well, it's time to dial that in. 298 00:28:55,480 --> 00:29:02,100 And I think so we've established that there's differences here. 299 00:29:02,100 --> 00:29:06,600 And so let's look at this data. 300 00:29:06,600 --> 00:29:19,360 And so because I think I've done enough just pointing at numbers, but just actually plotting 301 00:29:19,360 --> 00:29:22,600 these would be worthwhile here. 302 00:29:22,600 --> 00:29:25,200 OK, so what am I doing here? 303 00:29:25,200 --> 00:29:35,960 So I'm iterating over the solvents, which we've defined here, which is everything from 304 00:29:35,960 --> 00:29:40,760 acetone to propane. 305 00:29:40,760 --> 00:29:48,740 I'm getting the observations that have detected that analyte. 306 00:29:48,740 --> 00:29:57,280 So these are the observations where you have measured, say, acetone, or you have measured 307 00:29:57,280 --> 00:30:00,520 benzene or what have you. 308 00:30:00,520 --> 00:30:08,040 And then I'm also restricting it to anything that's less than 20,000 parts per million. 309 00:30:08,040 --> 00:30:14,400 The reason I'm doing this is the failure rate for most of these compounds, I believe, is 310 00:30:14,400 --> 00:30:17,800 5000, maybe 10,000. 311 00:30:17,800 --> 00:30:24,280 And so anything way above that is definitely going to be a failure. 312 00:30:24,280 --> 00:30:31,240 And I've noticed that there may be miscoding or potentially just ridiculously high level 313 00:30:31,240 --> 00:30:32,400 concentrations. 314 00:30:32,400 --> 00:30:40,880 But I think there are miscoding where people have just miscoded high, say, 100,000 ppm 315 00:30:40,880 --> 00:30:43,640 of solvent. 316 00:30:43,640 --> 00:30:52,200 And so long story short, just sort of putting a cap on the data. 317 00:30:52,200 --> 00:30:58,000 So and then just plotting them with the limits. 318 00:30:58,000 --> 00:31:02,960 So for each plot, I'm going to add the limit. 319 00:31:02,960 --> 00:31:11,120 And I'll post this code to GitHub afterwards so that way people can follow up on the analysis. 320 00:31:11,120 --> 00:31:17,860 And so these charts just generated for the first time right before the meetup. 321 00:31:17,860 --> 00:31:22,480 So they'll be interesting to look at together. 322 00:31:22,480 --> 00:31:31,560 So just starting from the top here. 323 00:31:31,560 --> 00:31:42,840 So here, I've essentially plotted everything that's tested for acetone in Washington State 324 00:31:42,840 --> 00:31:50,600 between early 2018 to the end of 2020. 325 00:31:50,600 --> 00:32:00,720 And so this excludes anything that did not have acetone detected and excludes anything 326 00:32:00,720 --> 00:32:04,000 that was not tested for residual solvents. 327 00:32:04,000 --> 00:32:12,560 So you could expect that these are concentrates of some sort that had some level of acetone. 328 00:32:12,560 --> 00:32:25,240 And so this is supposed to be reminiscent of the plot we saw with hemp, where we were 329 00:32:25,240 --> 00:32:33,840 seeing, OK, where are the limits set with hemp and what proportion of the samples are 330 00:32:33,840 --> 00:32:35,720 failing? 331 00:32:35,720 --> 00:32:43,240 And so this is where I think things just start out interesting. 332 00:32:43,240 --> 00:32:52,220 So here you see, OK, Oklahoma and Florida have a similar limit. 333 00:32:52,220 --> 00:32:59,880 And then the Washington State limit at 5,000 is substantially higher. 334 00:32:59,880 --> 00:33:02,000 And what is the result of that? 335 00:33:02,000 --> 00:33:12,480 Well, the result is there's a handful of samples here that pass, make it to market in Washington, 336 00:33:12,480 --> 00:33:18,600 that wouldn't make it to market in Oklahoma or Florida. 337 00:33:18,600 --> 00:33:26,360 And this is where I think things, they become worth thinking over. 338 00:33:26,360 --> 00:33:41,000 So Washingtonians may want to take a look at things and are they OK with this proportion 339 00:33:41,000 --> 00:33:45,520 of samples making it to market with acetone? 340 00:33:45,520 --> 00:33:50,200 This is where we talk about the cost benefit analysis. 341 00:33:50,200 --> 00:33:58,560 So if you lower the limits too far, then, well, I mean, it's subjective, right? 342 00:33:58,560 --> 00:34:06,160 So maybe consumers think the limit for acetone should be zero and all of these samples should 343 00:34:06,160 --> 00:34:07,160 be failing. 344 00:34:07,160 --> 00:34:15,160 But then that would be thousands of, that would be thousands and thousands of grams 345 00:34:15,160 --> 00:34:17,640 of oil. 346 00:34:17,640 --> 00:34:21,400 And so that would be a huge cost to the processors. 347 00:34:21,400 --> 00:34:28,520 So the idea is, OK, what is the permissible amount? 348 00:34:28,520 --> 00:34:33,840 And from my economics point of view, I think it comes down to the cost benefit analysis. 349 00:34:33,840 --> 00:34:43,800 However, everybody has their own stake in this. 350 00:34:43,800 --> 00:34:52,000 And so just to move through here, does anyone have any questions or is everyone following 351 00:34:52,000 --> 00:34:56,160 along pretty well so far? 352 00:34:56,160 --> 00:35:05,600 So I still have a lot of issues with this data from, I sent you that report. 353 00:35:05,600 --> 00:35:13,600 And there is, there's actually three, well, probably two sets of data, right? 354 00:35:13,600 --> 00:35:22,360 There's a whole bunch of data at the beginning of 2018, actually all the way up to like September, 355 00:35:22,360 --> 00:35:27,120 which doesn't seem like it's valid data. 356 00:35:27,120 --> 00:35:40,160 It's like three quarters of the data, but it has a 0.07% failure rate. 357 00:35:40,160 --> 00:35:47,880 And then there's this other set of data that has like a 4.5% failure rate that, you know, 358 00:35:47,880 --> 00:35:50,560 it seems like it's more consistent. 359 00:35:50,560 --> 00:35:53,520 I think, I mean, obviously, something's changed. 360 00:35:53,520 --> 00:35:57,240 And obviously, there's a lot of historical data that was crammed into the beginning of 361 00:35:57,240 --> 00:35:58,240 2018. 362 00:35:58,240 --> 00:36:01,200 And I think this really clouds the results. 363 00:36:01,200 --> 00:36:06,160 And as a mathematician, this kind of like really makes me twitchy. 364 00:36:06,160 --> 00:36:07,880 Yes. 365 00:36:07,880 --> 00:36:15,960 And so I think it's an interesting observation and it's tough to approach, right? 366 00:36:15,960 --> 00:36:21,120 So right, we were talking about earlier, you know, never throw away data. 367 00:36:21,120 --> 00:36:23,560 So we hate to just throw it away. 368 00:36:23,560 --> 00:36:27,720 At the same time, it's suspect, right? 369 00:36:27,720 --> 00:36:32,000 There's something, like you said, there's miscoding or whatnot. 370 00:36:32,000 --> 00:36:38,200 And then the reasonable explanation is, so right here, this was the transition to the 371 00:36:38,200 --> 00:36:40,280 leaf data system. 372 00:36:40,280 --> 00:36:45,280 So there's just a lot of those things just getting coded in. 373 00:36:45,280 --> 00:36:50,920 And so that would just be like existing inventory that gets added in. 374 00:36:50,920 --> 00:36:53,440 But it's a lot of noise. 375 00:36:53,440 --> 00:36:58,960 And I mean, if you don't throw away all this noise, then you kind of just have a bunch 376 00:36:58,960 --> 00:37:04,000 of noise clouding up your predictions. 377 00:37:04,000 --> 00:37:10,080 And if you're trying to get, if you're trying to use any sort of data science techniques 378 00:37:10,080 --> 00:37:16,080 or machine learning techniques, your results are invalid because you have all this noise. 379 00:37:16,080 --> 00:37:17,320 You can't learn anything. 380 00:37:17,320 --> 00:37:24,840 You can't actually see what's going on because there's so much noise covering the signal. 381 00:37:24,840 --> 00:37:26,280 I think you've hit on a good point. 382 00:37:26,280 --> 00:37:31,200 And so I think it may be worth trying to exclude some of the noise. 383 00:37:31,200 --> 00:37:43,160 So for example, like that's what I was starting to do here with excluding things below zero 384 00:37:43,160 --> 00:37:46,040 and above less than 20,000. 385 00:37:46,040 --> 00:37:54,880 So this is nifty because so in these plots, we're just looking at things that tested for 386 00:37:54,880 --> 00:37:56,440 acetone. 387 00:37:56,440 --> 00:38:02,920 So this is throwing away, hopefully, a lot of the noise. 388 00:38:02,920 --> 00:38:08,520 So this will be excluding everything that doesn't have acetone. 389 00:38:08,520 --> 00:38:18,200 With your analysis, you're going to have to do a bit more legwork to figure out what to 390 00:38:18,200 --> 00:38:22,000 exclude and how to do your analysis. 391 00:38:22,000 --> 00:38:24,320 But I think you're right. 392 00:38:24,320 --> 00:38:28,840 So I think for starters, you could potentially time restrict it. 393 00:38:28,840 --> 00:38:37,160 So OK, let's just look at things past 2019. 394 00:38:37,160 --> 00:38:44,600 That could be a starter or just look at things past 2020. 395 00:38:44,600 --> 00:38:46,200 Or even just filter out. 396 00:38:46,200 --> 00:38:51,520 Yeah, there's a lot of there's a couple odd things going on. 397 00:38:51,520 --> 00:38:56,400 I mean, you could filter out everything that doesn't have a valid lab ID. 398 00:38:56,400 --> 00:39:00,520 That's one thing, because there are results that have valid lab IDs that start in February 399 00:39:00,520 --> 00:39:04,400 of 2018 and go all the way through 2021. 400 00:39:04,400 --> 00:39:12,080 But there's that other thing that the intermediate type, there's a lot of activity at the beginning 401 00:39:12,080 --> 00:39:13,440 of 2018. 402 00:39:13,440 --> 00:39:17,280 And then it basically drops off to being reported at zero. 403 00:39:17,280 --> 00:39:25,120 And then all of a sudden in like July of 2019, it pops back up and it's in every result. 404 00:39:25,120 --> 00:39:26,120 Yes. 405 00:39:26,120 --> 00:39:29,200 And so that may actually be the better breaking point. 406 00:39:29,200 --> 00:39:36,320 So basically what happens is Leaf Data System gets adopted in 2018. 407 00:39:36,320 --> 00:39:43,280 They give everyone a lot of leeway for entering in their historic inventory. 408 00:39:43,280 --> 00:39:48,000 So they give them really through April of 2018. 409 00:39:48,000 --> 00:39:51,000 But then I think they still gave them a bit of leeway. 410 00:39:51,000 --> 00:39:56,840 So you're looking at all the way through April 2018 just for data to get entered. 411 00:39:56,840 --> 00:40:01,400 Then there was a major up was in my opinion that major. 412 00:40:01,400 --> 00:40:07,680 But there was an update that occurred in July of 2019. 413 00:40:07,680 --> 00:40:11,760 And it really it was actually kind of a shock for the industry. 414 00:40:11,760 --> 00:40:18,480 One of the earlier meetups we were talking about, oh, there was a great metric outage 415 00:40:18,480 --> 00:40:21,520 in California or wherever apparently. 416 00:40:21,520 --> 00:40:24,320 And so this would be the equivalent in Washington state. 417 00:40:24,320 --> 00:40:33,800 So for about a week in July or about a week or two weeks in July of 2019, there was an 418 00:40:33,800 --> 00:40:35,240 update. 419 00:40:35,240 --> 00:40:45,720 And what happened is, OK, so that essentially broke the API changed a little bit. 420 00:40:45,720 --> 00:40:51,440 And so a lot of the software systems were no longer compatible. 421 00:40:51,440 --> 00:40:53,760 And so there was a lot of software problems. 422 00:40:53,760 --> 00:40:56,540 People had to update their software systems. 423 00:40:56,540 --> 00:41:01,880 And so there was a lot of a lot of noise in the industry. 424 00:41:01,880 --> 00:41:07,680 And so there was a period there where you have bad data entry. 425 00:41:07,680 --> 00:41:15,840 So they basically Washington state permitted a tested lab results where the licensee could 426 00:41:15,840 --> 00:41:22,320 attest that their sample had been tested and then that they could enter in the results. 427 00:41:22,320 --> 00:41:32,720 And so so you have just a period there where there are odd results and inconsistent data 428 00:41:32,720 --> 00:41:33,720 entry. 429 00:41:33,720 --> 00:41:36,760 And so that could even be this period here. 430 00:41:36,760 --> 00:41:37,760 Right. 431 00:41:37,760 --> 00:41:42,880 And I think they squeaked in a lot of things because there's sort of like about it averages 432 00:41:42,880 --> 00:41:45,480 out about two, three hundred entries a day. 433 00:41:45,480 --> 00:41:51,280 And then there's this couple day period where it spikes to like six thousand entries. 434 00:41:51,280 --> 00:41:57,000 So they probably had a bunch of failing product and then they attested, oh, it passed. 435 00:41:57,000 --> 00:41:59,400 Well, I don't necessarily know about that. 436 00:41:59,400 --> 00:42:02,880 But you see like here there's this line here. 437 00:42:02,880 --> 00:42:06,080 So there's a handful of failures. 438 00:42:06,080 --> 00:42:12,360 That's basically maybe they couldn't do data entry and then they just did all their data 439 00:42:12,360 --> 00:42:14,600 entry on one day. 440 00:42:14,600 --> 00:42:15,600 So right. 441 00:42:15,600 --> 00:42:19,600 So yeah, I think anything after that seems to be valid. 442 00:42:19,600 --> 00:42:23,480 I mean, everything else behind that seems really noisy. 443 00:42:23,480 --> 00:42:30,040 And there's the intermediate type is missing for like months on end. 444 00:42:30,040 --> 00:42:32,040 Exactly. 445 00:42:32,040 --> 00:42:33,960 And this is where you could do some justification. 446 00:42:33,960 --> 00:42:39,400 You could hunt down the press releases that Washington state put out saying, oh, we're 447 00:42:39,400 --> 00:42:42,520 doing updates to the traceability system. 448 00:42:42,520 --> 00:42:47,440 And then you can just provide some rationale for, OK, we're going to restrict our data 449 00:42:47,440 --> 00:42:55,320 set to August of 2019 and onwards or even just give it a bit of leeway and just say, 450 00:42:55,320 --> 00:43:03,960 OK, we're just going to restrict this from 2020 onwards just so we have a reliable data 451 00:43:03,960 --> 00:43:05,760 set here. 452 00:43:05,760 --> 00:43:07,560 So. 453 00:43:07,560 --> 00:43:10,560 So I think you're definitely onto something, Charles. 454 00:43:10,560 --> 00:43:20,680 And I like how you're not satisfied with the messy data and you're striving for top notch 455 00:43:20,680 --> 00:43:21,680 analytics. 456 00:43:21,680 --> 00:43:24,240 And so that's what we're all about here. 457 00:43:24,240 --> 00:43:31,360 So just to bring it home, just to kind of show you some of the other charts here. 458 00:43:31,360 --> 00:43:38,360 So you've got you've got your charts like benzene where everybody is essentially failing 459 00:43:38,360 --> 00:43:41,840 of anything that has benzene. 460 00:43:41,840 --> 00:43:45,720 And then and then here I read it. 461 00:43:45,720 --> 00:43:49,160 I'm looking at this essentially brand new with you. 462 00:43:49,160 --> 00:43:59,600 And so this is where we run into this situation where this is similar to the. 463 00:43:59,600 --> 00:44:05,040 To the head to the hemp database we were looking at with failing hemp for high THC. 464 00:44:05,040 --> 00:44:13,520 So here we see this line where, yes, it looks like a lot of things were entered all at once. 465 00:44:13,520 --> 00:44:17,160 And so. 466 00:44:17,160 --> 00:44:19,760 The situation here is OK. 467 00:44:19,760 --> 00:44:26,080 So the limit is 5000 parts per million in Washington. 468 00:44:26,080 --> 00:44:34,720 And so, you know, you have a non negligible portion of the samples failing for butane. 469 00:44:34,720 --> 00:44:42,480 Florida's limit is actually slightly higher than than Oklahoma. 470 00:44:42,480 --> 00:44:44,640 So but look here at Oklahoma's limit. 471 00:44:44,640 --> 00:44:48,520 So Oklahoma has pushed their limit low. 472 00:44:48,520 --> 00:44:52,840 It is. 473 00:44:52,840 --> 00:44:55,600 One thousand. 474 00:44:55,600 --> 00:45:02,080 So Oklahoma has a limit for butanes of 1000 parts per million. 475 00:45:02,080 --> 00:45:05,600 And Florida has a limit of 2000. 476 00:45:05,600 --> 00:45:13,940 And so this is just just drilling home the point where, OK, if you're operating in Washington, 477 00:45:13,940 --> 00:45:22,480 you may be used to having one, two, three, maybe even four thousand parts per million 478 00:45:22,480 --> 00:45:30,840 of butane in your final product and it still be permissible to be sold. 479 00:45:30,840 --> 00:45:35,240 And this is where I was saying, you know, people aren't diving deep into this. 480 00:45:35,240 --> 00:45:37,240 They're well, I mean, some are. 481 00:45:37,240 --> 00:45:45,400 But if you get a certificate of analysis and it's just it says pass all across the board, 482 00:45:45,400 --> 00:45:48,160 retailer may not think twice. 483 00:45:48,160 --> 00:45:51,560 And they're just going to put this on the on the on their shelves. 484 00:45:51,560 --> 00:45:54,240 They just they're just looking at their certificate. 485 00:45:54,240 --> 00:45:56,680 They're looking for it to say pass or fail. 486 00:45:56,680 --> 00:45:58,760 If it says pass, it's a go. 487 00:45:58,760 --> 00:46:01,360 If it fails, it's a failure. 488 00:46:01,360 --> 00:46:02,360 Right. 489 00:46:02,360 --> 00:46:08,600 And so, you know, you're seeing products here that may be like forty nine hundred parts 490 00:46:08,600 --> 00:46:13,080 per million, forty seven hundred parts per million. 491 00:46:13,080 --> 00:46:17,160 You know, real, real close. 492 00:46:17,160 --> 00:46:19,600 And so. 493 00:46:19,600 --> 00:46:22,480 Does a retailer necessarily want those on their shelves? 494 00:46:22,480 --> 00:46:23,480 All right. 495 00:46:23,480 --> 00:46:26,880 Because say maybe a retailer has a policy. 496 00:46:26,880 --> 00:46:27,880 Right. 497 00:46:27,880 --> 00:46:30,960 Maybe a retailer has a retails. 498 00:46:30,960 --> 00:46:36,440 And once again, I'm not certain about the cross state ownership here, but maybe a retailer 499 00:46:36,440 --> 00:46:41,600 operates in a couple multiple states. 500 00:46:41,600 --> 00:46:50,160 Well, maybe they have internal quality control standards and say, OK, we don't we don't 501 00:46:50,160 --> 00:46:56,360 want anything with more than one thousand parts per million of butane in our store because, 502 00:46:56,360 --> 00:46:59,080 OK, that's not allowed in Oklahoma. 503 00:46:59,080 --> 00:47:02,360 So maybe we shouldn't allow that in Washington. 504 00:47:02,360 --> 00:47:08,760 And then they all have to actually look at their certificate of analysis and see that, 505 00:47:08,760 --> 00:47:13,400 OK, what is the level of butane? 506 00:47:13,400 --> 00:47:20,960 So and then, you know, and then this is where the dialogue with the public comes in. 507 00:47:20,960 --> 00:47:26,840 And is, OK, what is the permissible level of butane? 508 00:47:26,840 --> 00:47:28,240 So. 509 00:47:28,240 --> 00:47:32,480 Do consumers care about this? 510 00:47:32,480 --> 00:47:38,800 Like, are they OK with this in their in their products? 511 00:47:38,800 --> 00:47:40,680 What's the science behind it? 512 00:47:40,680 --> 00:47:49,680 So what is the effect of consuming, you know, a hundred parts per million of butane in your 513 00:47:49,680 --> 00:47:51,840 know, your one gram of oil? 514 00:47:51,840 --> 00:47:54,560 Like what what is. 515 00:47:54,560 --> 00:47:55,560 What is. 516 00:47:55,560 --> 00:48:01,360 You know, the effect of that, like, is that a negligible amount of butane? 517 00:48:01,360 --> 00:48:04,100 Is that a non negligible amount? 518 00:48:04,100 --> 00:48:11,280 So I think I think these are questions that are worth being looked into. 519 00:48:11,280 --> 00:48:13,960 So and then. 520 00:48:13,960 --> 00:48:17,480 Just to show you some of the other charts here. 521 00:48:17,480 --> 00:48:23,360 Core form. 522 00:48:23,360 --> 00:48:28,840 Cyclohexane would like to do a deeper dive on this, but so this is one that's interesting 523 00:48:28,840 --> 00:48:36,000 where this is not a good compound that you probably would not want in your system. 524 00:48:36,000 --> 00:48:43,720 And you know, there's are things with detections, a cyclohexane, but, you know, these are making 525 00:48:43,720 --> 00:48:46,720 it to market. 526 00:48:46,720 --> 00:48:55,600 And then here, here where we talked about dichloromethane, where you see many samples 527 00:48:55,600 --> 00:48:58,480 failing in Florida. 528 00:48:58,480 --> 00:49:03,320 Whereas you really don't see many samples. 529 00:49:03,320 --> 00:49:08,160 Just a handful, if any, failing in Washington state. 530 00:49:08,160 --> 00:49:12,860 Similarly, this is ethyl acetate. 531 00:49:12,860 --> 00:49:17,480 You see just a couple failures in Washington state. 532 00:49:17,480 --> 00:49:27,480 And then you see if these were tested in Oklahoma or Florida testing regimes, then you would 533 00:49:27,480 --> 00:49:32,060 see, oh, wow, you know, there's a look. 534 00:49:32,060 --> 00:49:41,200 And keep in mind, I don't know the weight exactly, but this, you know, one sample represents 535 00:49:41,200 --> 00:49:47,880 a substantial amount of oil that's going to concentrate that's going to be sold to the 536 00:49:47,880 --> 00:49:48,880 retailer. 537 00:49:48,880 --> 00:49:52,920 So this adds up. 538 00:49:52,920 --> 00:49:59,600 So if these were failed, you know, that would be a cost to the processor. 539 00:49:59,600 --> 00:50:06,760 And then otherwise, you know, there could be a health risk to the consumers if they 540 00:50:06,760 --> 00:50:12,480 do make it to market. 541 00:50:12,480 --> 00:50:14,160 Heptane. 542 00:50:14,160 --> 00:50:23,520 And really, what these charts are really showing is, I didn't realize this until creating the 543 00:50:23,520 --> 00:50:33,640 charts is that it, you know, Washington state has fairly permissible residual solvent limits. 544 00:50:33,640 --> 00:50:43,400 So this is where we were talking about how really states that are coming online sooner 545 00:50:43,400 --> 00:50:49,460 or more recently are almost leapfrogging some of the existing states. 546 00:50:49,460 --> 00:50:56,600 So basically, okay, when Washington set their regulations, everyone was just setting the 547 00:50:56,600 --> 00:50:58,760 bar at 5,000. 548 00:50:58,760 --> 00:51:01,480 So they set their bar at 5,000. 549 00:51:01,480 --> 00:51:08,680 And then, oh, somebody came along and then, oh, Canada set their bar even lower, or oh, 550 00:51:08,680 --> 00:51:16,520 New York set their bar low, or who have you, California came along and they set their bar 551 00:51:16,520 --> 00:51:17,520 low. 552 00:51:17,520 --> 00:51:21,080 And so then the next state that comes along, well, they're just going to look at, okay, 553 00:51:21,080 --> 00:51:23,240 what are the existing regulations? 554 00:51:23,240 --> 00:51:37,160 And often they adopt the more stringent regulations because the policy, the person in charge of 555 00:51:37,160 --> 00:51:45,560 public policy, you know, they want, they have the public health principle concern. 556 00:51:45,560 --> 00:51:56,440 So you know, they don't want to risk these products necessarily making it to market. 557 00:51:56,440 --> 00:52:04,680 So they'll often opt for the more stringent regulation. 558 00:52:04,680 --> 00:52:09,540 And just to finish it out here are heptanes. 559 00:52:09,540 --> 00:52:12,580 So this is where we're talking about coding. 560 00:52:12,580 --> 00:52:20,280 So it looks like really people aren't coding in heptanes. 561 00:52:20,280 --> 00:52:25,600 So it looks like heptanes is the principle thing, the principle analyte that people enter. 562 00:52:25,600 --> 00:52:29,120 I think heptanes is a depreciated column. 563 00:52:29,120 --> 00:52:31,960 Okay, that's what's going on here. 564 00:52:31,960 --> 00:52:34,600 And so exactly. 565 00:52:34,600 --> 00:52:40,600 So it looks like here in July of 2019, it gets deprecated. 566 00:52:40,600 --> 00:52:42,480 So that's good information. 567 00:52:42,480 --> 00:52:43,480 So exactly. 568 00:52:43,480 --> 00:52:48,880 So just focus on heptane. 569 00:52:48,880 --> 00:53:00,360 And then hexanes, once again, where you have Washington permitting these samples, whereas 570 00:53:00,360 --> 00:53:02,880 Oklahoma and Florida would not. 571 00:53:02,880 --> 00:53:07,360 And keep in mind, from what I've heard, Florida is quite strict. 572 00:53:07,360 --> 00:53:13,760 Oklahoma, I don't know that much about, but it's interesting to see that they apparently 573 00:53:13,760 --> 00:53:22,360 have a bit more stringent regulations than Washington as far as the actual permissible 574 00:53:22,360 --> 00:53:25,280 amount of solvents. 575 00:53:25,280 --> 00:53:29,800 Oh, and so this is an interesting one. 576 00:53:29,800 --> 00:53:31,920 So this one's isopropanol. 577 00:53:31,920 --> 00:53:37,040 And so isopropanol alcohol is used for cleaning. 578 00:53:37,040 --> 00:53:49,960 And so once again, people in Washington, they may be used to having standard operating procedures 579 00:53:49,960 --> 00:53:53,400 that include the use of isopropanol alcohol. 580 00:53:53,400 --> 00:53:57,360 And this may wind up into their products. 581 00:53:57,360 --> 00:54:04,120 If they were going to go set up shop in another state, they may need to address their standard 582 00:54:04,120 --> 00:54:13,000 operating procedures to make sure that they're not contaminating their products with isopropanol. 583 00:54:13,000 --> 00:54:19,440 Methanol, definitely don't want that in your products. 584 00:54:19,440 --> 00:54:28,480 And so you're starting to see the consensus being lower. 585 00:54:28,480 --> 00:54:36,240 And keep in mind, I just picked out Oklahoma and Florida as on a whim here. 586 00:54:36,240 --> 00:54:45,120 And so I encourage you to, why don't you repeat some of these charts with some of the other 587 00:54:45,120 --> 00:54:46,120 states? 588 00:54:46,120 --> 00:54:50,960 So, OK, why don't we look at California and Colorado? 589 00:54:50,960 --> 00:54:56,360 Or Heather, why don't you look at Maryland? 590 00:54:56,360 --> 00:55:01,400 Or Paul, you could look at Michigan. 591 00:55:01,400 --> 00:55:13,640 So it would just be interesting to see, OK, what is going to be allowed state by state? 592 00:55:13,640 --> 00:55:24,920 And then just to show all the charts, pentanes, similar story, propane, once again. 593 00:55:24,920 --> 00:55:33,000 You're seeing the Washington limit being quite high. 594 00:55:33,000 --> 00:55:35,280 And once again, what is high? 595 00:55:35,280 --> 00:55:37,960 So that's where the dialogue comes in. 596 00:55:37,960 --> 00:55:48,120 All we can do is present the data and then cultivators, processors, regulators, consumers 597 00:55:48,120 --> 00:55:49,120 can have it. 598 00:55:49,120 --> 00:55:55,120 And they need to have a dialogue and discuss, OK, what are the permissible levels of these 599 00:55:55,120 --> 00:56:00,600 solvents that are going to be allowed in concentrates? 600 00:56:00,600 --> 00:56:12,360 Polyaline, polyaline, xylenes, definitely don't want those. 601 00:56:12,360 --> 00:56:24,600 So here, the Washington state limit is catching most of them, but there are a handful that 602 00:56:24,600 --> 00:56:36,920 still make it through to the market that wouldn't be allowed in Florida or Oklahoma. 603 00:56:36,920 --> 00:56:37,920 And there we have it. 604 00:56:37,920 --> 00:56:45,560 And so that was the analysis that I prepared for today that builds off of what we've been 605 00:56:45,560 --> 00:56:47,680 talking about. 606 00:56:47,680 --> 00:56:52,560 And that was in vain of what we were talking about with the hemp database, where we were 607 00:56:52,560 --> 00:57:01,800 saying, OK, why don't we redo these charts with residual solvents on the x-axis? 608 00:57:01,800 --> 00:57:05,640 All right. 609 00:57:05,640 --> 00:57:13,840 And so just to take it home here, I've done a lot of talking today. 610 00:57:13,840 --> 00:57:18,760 And so perhaps next week, we can have a bit more of a back and forth dialogue. 611 00:57:18,760 --> 00:57:20,480 Because it's a meetup group after all. 612 00:57:20,480 --> 00:57:21,480 We're supposed to be talking. 613 00:57:21,480 --> 00:57:25,460 So sorry for just stealing the stage here. 614 00:57:25,460 --> 00:57:27,960 So what are your thoughts? 615 00:57:27,960 --> 00:57:33,360 Is this analysis you found interesting or what have you? 616 00:57:33,360 --> 00:57:34,360 Yeah. 617 00:57:34,360 --> 00:57:37,280 I thought it was interesting, Keegan. 618 00:57:37,280 --> 00:57:42,440 I always keep thinking about market consolidation, which will happen at some point. 619 00:57:42,440 --> 00:57:49,280 And to be able to know all these different thresholds for different states, any big players 620 00:57:49,280 --> 00:57:53,640 that come onto the scene that want to start consolidating, they're going to have to understand 621 00:57:53,640 --> 00:57:55,200 all this. 622 00:57:55,200 --> 00:58:01,680 And I'm wondering if a strategy for somebody like a big investor would be not necessarily 623 00:58:01,680 --> 00:58:08,160 to expand a chain of labs, but just to go because the labs that are in their separate 624 00:58:08,160 --> 00:58:13,680 states have already fitted to the standards that are in place, if they would just go in 625 00:58:13,680 --> 00:58:22,240 and try to buy up a bunch of labs and then make a chain out of all their purchases instead 626 00:58:22,240 --> 00:58:30,800 of having to learn everything on the ground level at each state, just buy up the knowledge. 627 00:58:30,800 --> 00:58:38,720 Well, so there are variations from state to state. 628 00:58:38,720 --> 00:58:45,600 So for example, like in Oklahoma, Michigan, you've got mandated pesticide testing, don't 629 00:58:45,600 --> 00:58:48,320 have that in Washington state. 630 00:58:48,320 --> 00:58:55,720 However, the chemists, the ones that are doing pesticide testing, it's more just like, OK, 631 00:58:55,720 --> 00:58:57,480 which pesticides are there? 632 00:58:57,480 --> 00:59:00,000 So just give us the list. 633 00:59:00,000 --> 00:59:01,000 We'll test for them. 634 00:59:01,000 --> 00:59:07,760 So most of the laboratories, they have their own levels of detection, which are much lower 635 00:59:07,760 --> 00:59:10,120 than the limits. 636 00:59:10,120 --> 00:59:15,760 And so to me, I just see it as just, OK, just what the limit is. 637 00:59:15,760 --> 00:59:20,960 So they'll just still test for the same pesticides and residual solvents. 638 00:59:20,960 --> 00:59:26,480 And then this is where we were talking about, oh, they may need to add analytes state by 639 00:59:26,480 --> 00:59:27,480 state. 640 00:59:27,480 --> 00:59:33,360 So there will be some learning by doing in some places. 641 00:59:33,360 --> 00:59:38,160 So for example, places with an extensive pesticide panel. 642 00:59:38,160 --> 00:59:45,200 So say you're in California and you've got 70 plus pesticides, somebody operating there 643 00:59:45,200 --> 00:59:53,140 is going to be much better probably at testing pesticides than somebody in, say, Oklahoma. 644 00:59:53,140 --> 01:00:00,680 And I think in Oklahoma, they have maybe a dozen or two dozen regulated pesticides. 645 01:00:00,680 --> 01:00:10,660 And so the method development manager there is they may not have been forced to do as 646 01:00:10,660 --> 01:00:12,960 much development. 647 01:00:12,960 --> 01:00:17,040 And it gets tricky when you start to. 648 01:00:17,040 --> 01:00:25,240 So in Canada, they may have 100 plus, maybe 120 plus regulated pesticides. 649 01:00:25,240 --> 01:00:31,120 And when you start to have to test for 120 pesticides, it becomes tricky because you 650 01:00:31,120 --> 01:00:36,840 almost need two different scientific instruments to really measure them all. 651 01:00:36,840 --> 01:00:39,720 So so I think you're right. 652 01:00:39,720 --> 01:00:46,540 There will be some people who are experts at certain things in some states. 653 01:00:46,540 --> 01:00:51,320 So it's going to be interesting to see how it shakes out over the next couple of years, 654 01:00:51,320 --> 01:00:52,320 that's for sure. 655 01:00:52,320 --> 01:00:54,800 But your analysis is really cool. 656 01:00:54,800 --> 01:00:55,800 Exactly. 657 01:00:55,800 --> 01:00:59,560 And there's going to be a lot of hard feelings one way or the other, because like I said, 658 01:00:59,560 --> 01:01:04,560 like in Washington state, they've got those limits set at five thousand. 659 01:01:04,560 --> 01:01:10,840 And if they were going to change those, there would be so much noise in the industry, like 660 01:01:10,840 --> 01:01:12,840 all the processors. 661 01:01:12,840 --> 01:01:15,720 And it's just that's just public policy. 662 01:01:15,720 --> 01:01:16,720 That's what takes place. 663 01:01:16,720 --> 01:01:19,640 And there would just be the deliberative dialogues. 664 01:01:19,640 --> 01:01:23,080 They say, OK, we think we should lower the limits. 665 01:01:23,080 --> 01:01:27,080 The processors are going to say, we don't think you should lower the limits. 666 01:01:27,080 --> 01:01:31,680 And then they'll have their back and forth and they'll settle on something. 667 01:01:31,680 --> 01:01:36,180 And so that's why, as you said, if you say the federal government were going to come 668 01:01:36,180 --> 01:01:41,760 out with residual solvent limits, I think there'd be a big dialogue between all the 669 01:01:41,760 --> 01:01:42,760 parties involved. 670 01:01:42,760 --> 01:01:45,840 That's OK, what are these limits going to be? 671 01:01:45,840 --> 01:01:55,560 Yeah, I wonder if some of these more, I guess, well-off labs are going to start hiring consultants 672 01:01:55,560 --> 01:01:59,040 to go lobby in the various states, right, for their interest. 673 01:01:59,040 --> 01:02:01,360 It's going to be interesting to see what happens. 674 01:02:01,360 --> 01:02:03,360 Well, thank you. 675 01:02:03,360 --> 01:02:04,360 Definitely. 676 01:02:04,360 --> 01:02:07,160 And my my only point there is it's an interesting thing. 677 01:02:07,160 --> 01:02:09,720 So the labs want to test for it. 678 01:02:09,720 --> 01:02:13,840 So the lab says, oh, yes, I think we should test for acetone. 679 01:02:13,840 --> 01:02:20,080 But the lab may not necessarily want a 2 ppm limit on acetone, because if they're having 680 01:02:20,080 --> 01:02:27,680 to fail 30 percent of the samples, then that's a tough conversation you have to have with 681 01:02:27,680 --> 01:02:31,120 the processors. 682 01:02:31,120 --> 01:02:35,520 So I think the labs are in the situation where they probably want to test for it. 683 01:02:35,520 --> 01:02:40,080 But I don't know if they necessarily want the lowest limit possible. 684 01:02:40,080 --> 01:02:45,160 Yeah, as you always say about cost-benefit analysis, right, there's going to be a lot 685 01:02:45,160 --> 01:02:47,640 of that going on, I'm sure. 686 01:02:47,640 --> 01:02:49,920 So anyway, cool stuff. 687 01:02:49,920 --> 01:02:51,440 So interesting topic. 688 01:02:51,440 --> 01:02:52,440 Thanks everyone for coming. 689 01:02:52,440 --> 01:02:54,800 I hope you got something out of it. 690 01:02:54,800 --> 01:02:59,560 And so definitely feel free to shoot any messages throughout the week if you have any ideas 691 01:02:59,560 --> 01:03:02,680 or have any avenues for further research. 692 01:03:02,680 --> 01:03:03,680 Sure. 693 01:03:03,680 --> 01:03:09,240 Just to keep it real quick, I'm shooting to have my full paper completed this weekend. 694 01:03:09,240 --> 01:03:14,600 So if I get that done, I will forward the entire thing over to you this time. 695 01:03:14,600 --> 01:03:15,600 Nice. 696 01:03:15,600 --> 01:03:18,520 And I have a review that owed to you. 697 01:03:18,520 --> 01:03:20,360 And so thanks for bearing with me. 698 01:03:20,360 --> 01:03:22,200 And so yeah, don't worry about it. 699 01:03:22,200 --> 01:03:24,120 Don't kill yourself over that, please. 700 01:03:24,120 --> 01:03:25,120 It's coming. 701 01:03:25,120 --> 01:03:27,240 And so everybody, stay tuned. 702 01:03:27,240 --> 01:03:32,400 I'll try to get the video uploaded so that way you can review it and see anything. 703 01:03:32,400 --> 01:03:35,440 And then, yeah, let's all stay in touch. 704 01:03:35,440 --> 01:03:40,880 And we can pick this back up next weekend and look at some more data. 705 01:03:40,880 --> 01:03:41,880 Take care, everybody. 706 01:03:41,880 --> 01:03:42,880 All right. 707 01:03:42,880 --> 01:03:43,880 Have a productive week. 708 01:03:43,880 --> 01:03:44,880 Bye. 709 01:03:44,880 --> 01:04:09,640 Bye.