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Speaker 1: Heard around the world on the I Heart Radio app,

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Speaker 1: Apple Podcast or wherever you get your podcast. It's Cannabis

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Speaker 1: Talk one on one with Blue and Joe Grande. Hello,

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Speaker 1: walcome to Cannabis Talk one on one, the world's number

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Speaker 1: one source for everything cannabis. My name is Blue. Alongside

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Speaker 1: of is Mr Joe Grande. How are you doing? A

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Speaker 1: body doing great? Christopher right, and thank you guys all

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Speaker 1: for listening to our podcast, Cannabis Talk one on one

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Speaker 1: all around the world. Make sure you check out the

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Speaker 1: website Cannabis Talk one on one dot com, as we

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Speaker 1: are the world's number one source for everything cannabis. We've

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Speaker 1: got so many great articles and blogs on our website.

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Speaker 1: Call us up anytime. Check out our i G pages

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Speaker 1: at Cannabis Talk one oh one. Blue was at the

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Speaker 1: number one, Christopher writes, and I am at Joe Grande

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Speaker 1: fifty two. Go on there and see all my new

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Speaker 1: dog videos and families the Doghouse the Dog, the doghouse videos.

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Speaker 1: But those are actually doghouse videos, right that that old

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Speaker 1: stuff that you see at the beginning, Yes, those are dogs.

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Speaker 1: Love that stuff as much as I love your old

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Speaker 1: videos of Imperial stars. If you have you ever watch,

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Speaker 1: you guys are new videos on YouTube. We have a

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Speaker 1: new intro that Erica put together and it's really highlights

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Speaker 1: old school stuff of Blue and I and Blue mentioned

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Speaker 1: doghouse stuff, but you'll be able to see Blue when

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Speaker 1: he shut down the one on one freeway stars and

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Speaker 1: it just really highlights the O G s that your

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Speaker 1: boy and I really are. So go check it out

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Speaker 1: on YouTube. If you're just listening to this podcast, at

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Speaker 1: least go watch the fucking into yourself favorite spit aside,

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Speaker 1: do yourself a favorite, educate yourself on who one Christopher

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Speaker 1: Right is and then Joe Branda if two really is

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Speaker 1: because you get to see that and you like, okay,

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Speaker 1: and then you know what, while you're doing that, turn

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Speaker 1: your typical into something special and what comes to infuse products?

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Speaker 1: You guys, The flavor you taste should be just as

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Speaker 1: enjoyable as the feeling you experience. What I'm talking about

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Speaker 1: is you need to go check out lorent oils dot

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Speaker 1: com l O R A N N O I l

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Speaker 1: S dot com. On the show today, you guys, this

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Speaker 1: is what I like to call a repercussion of greatness

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Speaker 1: because apparently when we were in Pasadena, at can med

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Speaker 1: we ran across, come a cars off. There were at

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Speaker 1: the house a name by the name of Alex. If

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Speaker 1: you just hear Alex, you get to go. Is Alex

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Speaker 1: Rodriguez the baseball player from the New York Yankees. Maybe

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Speaker 1: a rod Alex, No, but maybe you go. It's Alexandra Harris,

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Speaker 1: otherwise known as Alex on the streets, otherwise known as

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Speaker 1: a cannabis science advisor and consultant chemists at tycoon A

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Speaker 1: lan Usa now taycoon A lan Usa is a cannabis

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Speaker 1: brand that specializes in medical cannabis research and developing award

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Speaker 1: winning flower edibles concentrates as well as topical lotions now

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Speaker 1: takun A lan is also best known for becoming the

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Speaker 1: world's first organizations licensed by a national government to treat

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Speaker 1: pay Shians with medical cannabis. You heard me say, the first,

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Speaker 1: the world's first organization folks Heavily rooted in Israel, tycoon

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Speaker 1: Alan has cur curated and produced specific cannabis based therapies,

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Speaker 1: evaluated individual patient conditions, recorded treatment outcomes, and conducted safety

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Speaker 1: and efficiency trials on the medicines derived from its unique

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Speaker 1: strains with leading Israeli medical institutions. We've always talked about

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Speaker 1: this on this show as Israel is leading the path

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Speaker 1: of this folks with no joke. So to give us

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Speaker 1: further insights about how she and they do this, and

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Speaker 1: I'm not using that as pronouns. I'm saying she and

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Speaker 1: the company that she works for, please put your hands

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Speaker 1: together for our guests and welcome her to the Cannabis

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Speaker 1: Talk one on one campus, Alexandra Harris, everybody give our out.

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Speaker 1: Not only is their hair flowing and blowing because of

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Speaker 1: the fan on her, Like I literally walked into solved

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Speaker 1: do it. It It was all I noticed. He was doing

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Speaker 1: it on perfect alex did I not? I go, hold

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Speaker 1: on out, you look so much prettier. I go, You're

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Speaker 1: already beautiful, but I just looking at you walking in

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Speaker 1: and it's like a pretty woman, Like the fan is

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Speaker 1: blowing on you and your hair is moving. It's just so.

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Speaker 1: But you know, literally I walked into the front and

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Speaker 1: you didn't have you your headphones on, so your hair

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Speaker 1: was blown more. And I literally walked in and it

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Speaker 1: was just like like like a movie was all the

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Speaker 1: air was cool. I felt like I was walking too.

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Speaker 1: I felt the same way. So so go watch the

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Speaker 1: YouTube thing again you can see what Alex is looking

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Speaker 1: like so pretty with her Alex, thank you for coming

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Speaker 1: on the show. Like we said, we crossed paths in

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Speaker 1: Pasadena at one of the most intriguing events Blue and

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Speaker 1: I have ever been to. When I say this, we

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Speaker 1: talk about this fluent least, not claiming that snoop dogs

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Speaker 1: our biggest interview that we want to do. People that

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Speaker 1: we met there in any encounter that we had there.

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Speaker 1: Just to give you some inside info that we were

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Speaker 1: talking about off my in the conference room, they go, Joe,

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Speaker 1: he met her at can Meta go great? Why because

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Speaker 1: every person that I met at ken Med, as I've

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Speaker 1: said on this podcast, was worthy of an interview. Every

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Speaker 1: person that we talked to at that event literally was

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Speaker 1: worth it. So first off, and he met the guy

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Speaker 1: in the restroom and that guy that was we talked

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Speaker 1: that night that the guy was giving us mints and

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Speaker 1: everything exactly. Like, let's just start with that event, Like

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Speaker 1: what brought you to that where we met at um So,

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Speaker 1: I've actually been doing canvas science conferences for the past

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Speaker 1: year UM for my job, so I was working in

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Speaker 1: supercritical CEO two instruments sales and so that led me

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Speaker 1: to go to all kinds of different conferences, some of

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Speaker 1: which were even exclusively pharmaceutical. So it's been really interesting

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Speaker 1: to bring with me my cannabis science knowledge into those realms.

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Speaker 1: But Canabad is really specific and interesting due to the

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Speaker 1: fact that it's based on the medicinal approaches of cannabis

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Speaker 1: in particular. So a lot of the cannabis science conferences

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Speaker 1: are more so focused on like the chemistry behind cannabis

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Speaker 1: and formulation and things like that. Can Meat is really

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Speaker 1: interesting because they're looking at clinical trials, which are super rare. Right,

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Speaker 1: So um to Cune is unique in the fact that

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Speaker 1: we do have so many clinical trials that are based

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Speaker 1: on our patented strains, and so it was really interesting

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Speaker 1: to bring that unique approach to can Mead. It was

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Speaker 1: really appreciated by a lot of the scientists that I met,

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Speaker 1: and so I was really humbled and honored to be

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Speaker 1: representing to kun since the legacy, where do you get

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Speaker 1: that from? I mean, you know, you don't just come

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Speaker 1: in the game and starts speaking like your background, because

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Speaker 1: I mean, you know, just obviously you are to your

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Speaker 1: knowledge your background. Yeah, you articulated that very well, and

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Speaker 1: so what what's your background? Where do you come from? Yeah? So, um,

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Speaker 1: I have a biology degree. Um I got that University

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Speaker 1: of Hawaii. Manoah, that's that's white. Um and uh yeah

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Speaker 1: so Hawai from a little there when I was four yow,

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Speaker 1: so that's why you know what the island. Yeah, and

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Speaker 1: by the way, really strong prevalence of cannabis there as well.

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Speaker 1: But I actually went to court for six months for

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Speaker 1: possession there. So I would love to help Hawaii kind

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Speaker 1: of get up to speed with with cannabis legislation. But

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Speaker 1: that's the convict and everything. Um, I just went to

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Speaker 1: court for six months. I paid a lot of money

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Speaker 1: for a lawyer, and then they finally dropped it. Yeah

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Speaker 1: how much we how much we did I have? Um? God?

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Speaker 1: Maybe an eighth Yeah it's really really cute. And this

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Speaker 1: was in two thousand. Yeah that big a good deal. Okay,

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Speaker 1: So you grew up in Hawaii, went to college in Hawaii?

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Speaker 1: Did you continue anywhere else in college and stuff like that? Um?

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Speaker 1: So I am pursuing my master's now. But a lot

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Speaker 1: happened in between that. So, um, I actually got really

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Speaker 1: sick in high school and I used cannabis to make

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Speaker 1: sure that I got to college. So I owe a

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Speaker 1: lot of my educational and my career to cannabis. Um

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Speaker 1: what do you mean? Yeah? Sure, so, um I was.

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Speaker 1: I lived in Las Vegas for high school. I moved

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Speaker 1: there from Hawaii for high school, and um, I got

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Speaker 1: bit by some kind of spider um and I got

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Speaker 1: really really sick from that. I couldn't walk and I

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Speaker 1: had a stroke and my kidney started to fail. So

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Speaker 1: I missed my whole senior year of high school away

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Speaker 1: from a spider boy. Yeah or something. Let it go

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Speaker 1: longer than you should have. I mean, did you see

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Speaker 1: the bite and go? I immediately went there. I immediately

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Speaker 1: was a bump on your just you know, you get

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Speaker 1: a bite. I had a bite here and about here,

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Speaker 1: and it did thankfully didn't go to cross it because

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Speaker 1: I kept it very sterile. But it went to the

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Speaker 1: stomach instead. So I started to attack my organs a

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Speaker 1: whole year year out. Yeah. Yeah, I couldn't. I couldn't walk,

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Speaker 1: and then I developed like arthritis and asthma, and so

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Speaker 1: I did for a very long time, um, all through college.

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Speaker 1: When I graduated college, I developed shingles, which is only

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Speaker 1: supposed to happen, and people that are over like fifty um,

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Speaker 1: and so they gave a full blood panel at that

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Speaker 1: point and I was tested positive for lyme disease. So

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Speaker 1: from the spider, Yeah, what kind of this spider was

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Speaker 1: runching especially right there all right, like I'm never going

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Speaker 1: back to yeah yeah um so yeah then I mean sorry,

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Speaker 1: but did they discover what kind of actual um? That was?

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Speaker 1: Kind of the issue is if you don't bring the

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Speaker 1: insect that bit you to the hospital, they can't give

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Speaker 1: you any kind of anti venom. Really, they can only

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Speaker 1: give you antibiotics and link wow, so you have to

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Speaker 1: go fight with it. So I just did you know

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Speaker 1: did you see that? Did you try and say, hey,

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Speaker 1: this is what it was? You didn't see? The guy

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Speaker 1: just kept had bumps after. I never steralized where was it?

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Speaker 1: Where was your house? I was at school, at school,

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Speaker 1: at my high school. Yeah. How did cannabis that you

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Speaker 1: got in your shirt or something to treat you? How

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Speaker 1: did you use the cannabis to treat your body that year?

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Speaker 1: So thankfully, um my mom, I'm so sorry you want

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Speaker 1: us to readjust the fan I'm good now, are you sure? Thankfully?

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Speaker 1: My mom was a medical canvabus patient. My whole life.

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Speaker 1: Both my parents were Campas advocates my whole life, so

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Speaker 1: I always had access. Yeah, my too, soars out there,

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Speaker 1: call us up now. Yeah, now they're over twenty one,

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Speaker 1: I can talk about it. But all right, yeah exactly

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Speaker 1: just barely was six when go ahead. Yeah, I was

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Speaker 1: nine when I started smoking. So that's a part of

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Speaker 1: the high five at the end ruined it. Sorry, I'm

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Speaker 1: gonna know your answer. So at your senior year in

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Speaker 1: high school, did they your mom just said use this

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Speaker 1: and at that point did they already have their own

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Speaker 1: remedies like your mom because they used it their whole life.

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Speaker 1: Did they have their own stash of drinks and creams

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Speaker 1: and everything else. We definitely had some primordial tinctures that

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Speaker 1: were really gnarly that I used to use UM. And

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Speaker 1: then I remember I would like go to Vegas and

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Speaker 1: try to get capsules. I could find capsules at some

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Speaker 1: point in time UM that were really concentrated that it

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Speaker 1: would take their hundred milligrams. And I took that in

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Speaker 1: place of my gabapent just because I hated how op

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Speaker 1: it and benzodas beings made me feel, so I replaced

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Speaker 1: it all with cannabis also because I was losing weight

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Speaker 1: very rapidly from not being able to walk, and so

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Speaker 1: eating was really hard for me too. I had a

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Speaker 1: lot of nausea, so cannabis really helped me maintain my weight. Um.

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Speaker 1: But yeah, once I, once I got my diagnosis, I

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Speaker 1: got the correct antibiotics for it, and I went through

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Speaker 1: a few more months of going through really intensive care

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Speaker 1: for that. And then um, I became a substitute teacher

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Speaker 1: because I had a science degree, and I was like,

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Speaker 1: you know, I want to do something that uses my

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Speaker 1: degree that I can do part times I could see

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Speaker 1: you as a teacher. I was a high school teacher

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Speaker 1: I got. I got a full time job after that.

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Speaker 1: I was a high school biology high school. The kids

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Speaker 1: in there, how am I what? What level? Though? Don't

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Speaker 1: let us see. I had software to seniors two and

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Speaker 1: my students were eighteen and I taught sex said twice

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Speaker 1: a year, embarrassing thing for all of them. They were

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Speaker 1: all I got miss alex I got a question mixed Alexandra.

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Speaker 1: What'd they call you? First year? I would have did

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Speaker 1: that would have been the student that called you by

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Speaker 1: your first married Is this a married name? No? No,

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Speaker 1: she's single there it is. Yeah, ship, that's so. That's awesome.

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Speaker 1: So you taught for a while and then keep going

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Speaker 1: that well, I was teaching and I quit teaching like

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Speaker 1: two months before COVID hit, which I don't know how

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Speaker 1: I managed to do that. But I actually went to

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Speaker 1: a what would you call it convention in Palm Springs.

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Speaker 1: I'd never been to a cannabis convention before. It was

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Speaker 1: at the Saguaro it was, yeah, it was. It was

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Speaker 1: in right before Covidad. Yes, it was. Everybody stayed at

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Speaker 1: that hotel and party the whole night. There's a pyramid

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Speaker 1: one down the middle. No, No, it's kind of like

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Speaker 1: an open middle, open middle. There's like pools and stuff

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Speaker 1: kind of there. Yeah, how was that that one? I

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Speaker 1: got interviewed by medmen there, and within two weeks they

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Speaker 1: offered to hire me to take over their analytical chemistry department.

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Speaker 1: Who was that with you? Members name? No, no, what

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Speaker 1: is his name? Burns and something that's lessons like Burns

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Speaker 1: or something like that. I don't know. He was a

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Speaker 1: professor at u C Riverside. I knew that he was

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Speaker 1: from very smart bunch by the way. Yeah, but I

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Speaker 1: was shocked because I was a biology teacher. I didn't

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Speaker 1: have any chemistry experience, and so when I realized that

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Speaker 1: there was this very like strong need for anyone with

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Speaker 1: a science degree in cannabis, I said, I'm out, I'm

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Speaker 1: done with teach and I'm gonna go follow my passion.

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Speaker 1: I'm gonna follow something I've believed in my whole life.

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Speaker 1: And I gave that speech to my students and I

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Speaker 1: was like, I'm gonna go do. Don't let anybody ever

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Speaker 1: stop you, you know, from going to do your passionate

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Speaker 1: about even if it's the middle of the year. Just

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Speaker 1: leave in the middle of the year Halloween. I'm sorry. Yeah,

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Speaker 1: that's it. That's really cool. You know, that's a good

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Speaker 1: moral of the story, and nothing better than those kids

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Speaker 1: that really listened to it and those that are listening

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Speaker 1: to it now, because it's still a real good moral

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Speaker 1: to your story of everyone follow your heart and dreams

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Speaker 1: and path. Yeah, you know, I mean, that's a real

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Speaker 1: good moral to any story of what your life was

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Speaker 1: just become. And now you're leading it working for a

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Speaker 1: fucking company that is so big, that is leading the

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Speaker 1: front of cannabis. In my opinion from an area of Israel,

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Speaker 1: that like, your company is the Tycoon, so to speak.

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Speaker 1: Let alone, that's the name of the company of the

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Speaker 1: industry that's just leading the pack. So how do you

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Speaker 1: even find a company like that? We're gonna take a

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Speaker 1: break right now, we're gonna come back, alex and I

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Speaker 1: want to hear how do you find this company from

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Speaker 1: saying Okay, I'm a biologist, I know this, I know

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Speaker 1: that I'm getting to cannabis, and we're gonna find out

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Speaker 1: how she gets the Tycoon's Cannabis Talk one on one.

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Speaker 1: We'll be right back after this even locks right here,

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Speaker 1: we'll be right back with Cannabis Talk one oh one.

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Speaker 1: Welcome back to Cannabis Talk one oh one. Advanced Nutrients

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Speaker 1: You guys, they got a complete growing system for cannabis

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00:14:54,400 --> 00:14:57,160
Speaker 1: and optimizes all faces and cycles to bring your crops

284
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Speaker 1: and their true genetic potential. You really need to go

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00:14:59,480 --> 00:15:02,320
Speaker 1: check this out discover more advanced new treents dot com.

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Speaker 1: And I really really want to give a big shout

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Speaker 1: out to a big mic over there. Yeah, being one

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Speaker 1: of the top hundred influencers in cannabis, you really know

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Speaker 1: what you're doing out there. And Alexander Harris, when you

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Speaker 1: say so you know, it's funny when you say that,

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Speaker 1: big Mike, you know number one or top half, hud

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Speaker 1: one half, whatever was number But I swear to you

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Speaker 1: do right. I just I was laying in bed last

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Speaker 1: night last night, dude, as you say that, right, And

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Speaker 1: I know that wasn't scripted. I believe I'm understanding. So

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Speaker 1: last night I was just I was just saying, how

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Speaker 1: you know very soon that we're going to be there, right? Yeah? Yeah, no,

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Speaker 1: And it was it's funny that you brought that up

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Speaker 1: today because I was just in my mind and you know,

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Speaker 1: I was just like, damn, you know what, like the

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Speaker 1: the events that we're doing, the influence, Yeah, the movie

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Speaker 1: at the show, and I'm not gonna leak it right now,

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Speaker 1: but I'm real soon, you know, magazine, I say, I'm

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Speaker 1: asking you that what you're talking about clearly? Yeah, yeah, Danny,

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Speaker 1: what do you eat? No, don't put that on there,

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Speaker 1: We can't, but don't don't pull it out yet. Don't

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00:16:08,800 --> 00:16:10,200
Speaker 1: pull it out. So we we've got to put your

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Speaker 1: hair and cover that. Don't. You gotta get that camera

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Speaker 1: off that, dude. But so now that Joe breaks it out,

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Speaker 1: we we do have a we're launching a candidate's talk

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Speaker 1: magazine allegedly, and um, it's gonna be a collector's edition,

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Speaker 1: the first one that comes out. Do you want to

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Speaker 1: see put your hair on that, put that throw on there? Boy? Yeah,

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Speaker 1: that's only a demo so but but it's coming out

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Speaker 1: real soon and it's it's fun to talk about you,

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00:16:40,400 --> 00:16:42,680
Speaker 1: and it is. Yeah. I'm excited to be there, you know.

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Speaker 1: And I'm surprised that you know that. Uh, you know,

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Speaker 1: it's been so long to get you though. Oh, I

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Speaker 1: don't care about me. It's a grand I've been on

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Speaker 1: top one. I likes to be there as smart as

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Speaker 1: she is, Like Andrew Harris, this is She's honest, He's smart, Tycoon.

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Speaker 1: You come into this game as a scientists. Chemists. It's

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Speaker 1: so funny because that's the one class I failed that

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Speaker 1: I had to do. I petitioned to graduate. I have

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Speaker 1: my degree in Radio Television Film, and when I petitioned

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Speaker 1: to graduate, I flunked biology and fucking junior college and

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Speaker 1: that's why I didn't get my degree. Random. But with

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Speaker 1: you being a biology major like that and being now

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Speaker 1: finding this cannabis, this cannabis loved because your family comes

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Speaker 1: from yours. I like to call it like blew, a

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Speaker 1: second generation cannabis. You know, uh family, because your parents

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Speaker 1: taught you as a kid. You came up with a

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Speaker 1: remedy as high school to live and then you figure,

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Speaker 1: I'm quitting's school. I'm gonna go into the industry. You

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Speaker 1: started as this one chemist with Medman and where does

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Speaker 1: it go to get you the tycoon? Because I'm sure

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00:17:46,400 --> 00:17:48,720
Speaker 1: it's a few more stops. So I actually turned down

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Speaker 1: the job with med Men. I had already become privy

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Speaker 1: to what was happening within the industry and I did

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00:17:54,680 --> 00:17:56,760
Speaker 1: not want to work for med Men. I actually ended

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00:17:56,800 --> 00:17:59,520
Speaker 1: up taking a job with cana Safe instead. Um So,

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00:17:59,600 --> 00:18:01,320
Speaker 1: I moved to LA to work with Canna Safe, and

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00:18:01,400 --> 00:18:04,159
Speaker 1: then I worked for one of the competitors, California Cannabis

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Speaker 1: Testing Labs UM. And I realized that that industry has

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00:18:08,280 --> 00:18:12,040
Speaker 1: so much competition, so much inherent lab shopping UM, and

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00:18:12,160 --> 00:18:14,800
Speaker 1: so many issues that in terms of my integrity as

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00:18:14,800 --> 00:18:17,760
Speaker 1: a scientist, we're problems for me. I just couldn't I

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00:18:17,800 --> 00:18:21,720
Speaker 1: couldn't handle the pressure. I guess you should say. Um So,

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00:18:21,800 --> 00:18:23,159
Speaker 1: I worked in that for a bit and then I

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00:18:23,240 --> 00:18:27,080
Speaker 1: left and went into cosmetic chemistry, which is even worse

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00:18:27,359 --> 00:18:33,760
Speaker 1: than even less regulate way less regulated. Um, but you know,

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Speaker 1: I don't know anybody really in that space. I mean

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00:18:35,800 --> 00:18:39,320
Speaker 1: I understand there, but well there's hold on that make

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Speaker 1: I could put some facial sh on my face today. Yeah,

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00:18:42,000 --> 00:18:44,960
Speaker 1: well but it's the least regulated, buddy, That's what I'm saying.

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Speaker 1: A second, I just used some men stuff like you

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00:18:48,960 --> 00:18:50,840
Speaker 1: need to put some moisturizers on your face. I'm like,

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00:18:50,840 --> 00:18:53,119
Speaker 1: I never used that stuff. I always well, you know,

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00:18:53,160 --> 00:18:55,320
Speaker 1: if you get facials one like everyone, well I don't.

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00:18:55,400 --> 00:18:57,360
Speaker 1: People always compliment me and I'm like, what are you using?

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00:18:57,359 --> 00:18:58,760
Speaker 1: And then everybody wants to give me something like dog,

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00:18:58,800 --> 00:19:00,959
Speaker 1: I just use lotion. What to be honest, I use

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Speaker 1: Victoria's secret motion to be honest. I used to make that.

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00:19:03,440 --> 00:19:06,840
Speaker 1: That was what I made good. It's terrible. It's probably

365
00:19:06,880 --> 00:19:12,359
Speaker 1: the word Victoria. It's like half perfume adulthood. I've been

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00:19:12,440 --> 00:19:13,880
Speaker 1: using that, and it's like, what do you have good

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00:19:13,880 --> 00:19:15,560
Speaker 1: school of skin, Joe, I don't know. I use Victoria's

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Speaker 1: Secret logition and you're telling me it's the worst thing ever,

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00:19:18,160 --> 00:19:22,199
Speaker 1: really bad. It's really bad. Yeah. I used to make

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00:19:22,240 --> 00:19:24,920
Speaker 1: Victoria's Secret Everything for Victoria's Secret Bath and Body Works

371
00:19:25,000 --> 00:19:28,680
Speaker 1: go five pg. All the cheap stuff, but even even

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00:19:28,720 --> 00:19:30,720
Speaker 1: the nice stuff, it all comes from a very similar

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Speaker 1: productive facility, a little bit different in quality of raw materials,

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00:19:34,720 --> 00:19:37,400
Speaker 1: but even then vetting those raw materials and keeping those

375
00:19:37,440 --> 00:19:40,360
Speaker 1: raw materials in the correct shelf life and all those

376
00:19:40,400 --> 00:19:42,359
Speaker 1: kinds of things. It's not overlooked by the FDA. That

377
00:19:42,440 --> 00:19:44,800
Speaker 1: kind of stuff is not It's just walked over like

378
00:19:44,880 --> 00:19:48,680
Speaker 1: everybody just puts it on their face. Use I make

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00:19:48,720 --> 00:19:53,600
Speaker 1: my own. I take coconut oil and I put hempseed

380
00:19:53,640 --> 00:19:54,960
Speaker 1: oil in it, and I add a little bit of

381
00:19:55,920 --> 00:19:59,159
Speaker 1: rose hip oil and a little bit tetrie oil for antimicrobial,

382
00:19:59,640 --> 00:20:02,159
Speaker 1: and that all raw stuff that you come up with

383
00:20:02,320 --> 00:20:04,280
Speaker 1: mixed yourself, and do you've add as sent to it?

384
00:20:04,440 --> 00:20:06,240
Speaker 1: I mean the scent really comes with like the rose

385
00:20:06,320 --> 00:20:10,040
Speaker 1: hip and the tea tree and yeah, natural chs. That

386
00:20:10,160 --> 00:20:13,320
Speaker 1: sounds amazing if you ever were dropping off your home. Ye, yeah,

387
00:20:15,040 --> 00:20:18,040
Speaker 1: I don't know if I want the rose though, that

388
00:20:18,160 --> 00:20:22,760
Speaker 1: sounded wonderful. Yeah, just subscribe something because the scent, my

389
00:20:22,800 --> 00:20:25,679
Speaker 1: son smell a little feminine. Well, the te tree actually

390
00:20:25,680 --> 00:20:28,600
Speaker 1: is the strongest. Funny, your thing is is anything feminine

391
00:20:28,600 --> 00:20:31,280
Speaker 1: smelling on a man's body, and my opinion, randomly, I

392
00:20:31,320 --> 00:20:33,000
Speaker 1: sort of got to I believe this, This is my

393
00:20:33,040 --> 00:20:35,600
Speaker 1: whole hearted belief. Just makes us smell differently, and I

394
00:20:35,640 --> 00:20:38,200
Speaker 1: don't think it smells. So I've been using women's products,

395
00:20:38,400 --> 00:20:41,560
Speaker 1: damn your my whole life lotions and creams and oh yeah,

396
00:20:41,760 --> 00:20:44,000
Speaker 1: I mean you know that's that's because you're lazy and

397
00:20:44,080 --> 00:20:47,000
Speaker 1: your girl next to you just like this stuff works. No,

398
00:20:47,080 --> 00:20:49,640
Speaker 1: I'm telling you because you know why my old theory thought.

399
00:20:50,080 --> 00:20:52,720
Speaker 1: If the stripper that smells like that Victoria's Secret got

400
00:20:52,720 --> 00:20:55,840
Speaker 1: me excited, Hey maybe I want to wear that too. Yeah,

401
00:20:55,920 --> 00:20:57,600
Speaker 1: well come on, that's where they used to didn't give me.

402
00:20:57,640 --> 00:21:00,159
Speaker 1: You didn't give me. I'm not even telling you a

403
00:21:00,240 --> 00:21:03,399
Speaker 1: joke though. That's that's where I should think. Where do

404
00:21:03,440 --> 00:21:05,280
Speaker 1: you get that loads your front? Victoria's Secret? That's what

405
00:21:05,480 --> 00:21:07,240
Speaker 1: That's how I found out, which was the worst one,

406
00:21:07,280 --> 00:21:10,000
Speaker 1: of course, and that's the cheapest, so solictit. So so

407
00:21:10,200 --> 00:21:13,000
Speaker 1: you're there now, right, and where do you see this going?

408
00:21:13,080 --> 00:21:14,720
Speaker 1: I mean, you know, I feel like you guys, are

409
00:21:14,880 --> 00:21:17,520
Speaker 1: you know, doing real clinical trials? You said, right, yeah, yeah,

410
00:21:17,640 --> 00:21:19,320
Speaker 1: And so what kind of clinical trials are you guys

411
00:21:19,359 --> 00:21:22,399
Speaker 1: working on to progress the market? So it's actually slowed

412
00:21:22,440 --> 00:21:25,200
Speaker 1: down a little bit due to legislation in Israel, which

413
00:21:25,240 --> 00:21:26,920
Speaker 1: is kind of a side tangent, But I do want

414
00:21:26,920 --> 00:21:29,320
Speaker 1: to answer your question. The most recent study that came

415
00:21:29,320 --> 00:21:32,720
Speaker 1: out from our team was on dementia and cannabin dial

416
00:21:32,960 --> 00:21:35,879
Speaker 1: oil um. So the indications were really good from that

417
00:21:35,960 --> 00:21:39,960
Speaker 1: in reducing the agitation that most dementia patients experienced. UM.

418
00:21:40,000 --> 00:21:43,480
Speaker 1: So yeah, it's it's all been really constructive. Um. But

419
00:21:43,600 --> 00:21:45,520
Speaker 1: like I said, it's kind of slowed down a bit.

420
00:21:45,800 --> 00:21:49,080
Speaker 1: There's a lot of limitations from the government in Israel

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Speaker 1: in terms of what can be used and researched and

422
00:21:51,480 --> 00:21:53,960
Speaker 1: what's legal, especially in comparison to here. So, for instance,

423
00:21:54,160 --> 00:21:58,119
Speaker 1: concentrates are not legal in in in Israel in Israel

424
00:21:58,160 --> 00:22:00,119
Speaker 1: at all. Are the legal here in the States to

425
00:22:00,240 --> 00:22:04,680
Speaker 1: use for research? Umtally we're here over the counter hot well,

426
00:22:04,720 --> 00:22:07,439
Speaker 1: but to use his research though? Are they doing research

427
00:22:07,480 --> 00:22:09,960
Speaker 1: here with it? I mean, yeah, I've seen all kinds

428
00:22:09,960 --> 00:22:13,760
Speaker 1: of research on concentrates here, um. But for some reason,

429
00:22:13,760 --> 00:22:15,879
Speaker 1: I was stuck on the Mississippi farm and just like

430
00:22:15,920 --> 00:22:18,720
Speaker 1: sourcing the plant from there. But yes, there's definitely. Really

431
00:22:19,440 --> 00:22:21,879
Speaker 1: there's definitely research on concentrates as well. I was thinking

432
00:22:21,880 --> 00:22:23,960
Speaker 1: in a limited scope where you know, for the past

433
00:22:24,040 --> 00:22:26,359
Speaker 1: like what forty years that we have actually been trying

434
00:22:26,359 --> 00:22:29,679
Speaker 1: to do any cannabis research coming from one place, and

435
00:22:29,680 --> 00:22:32,320
Speaker 1: it's all mids you know, it's really really low t hcs.

436
00:22:32,560 --> 00:22:34,840
Speaker 1: So they don't really have a great uh you know,

437
00:22:35,920 --> 00:22:38,800
Speaker 1: yeah evidence, They don't have great evidence on on what

438
00:22:38,840 --> 00:22:40,800
Speaker 1: where it's coming from because the cannabis ain't the same.

439
00:22:40,840 --> 00:22:44,000
Speaker 1: It's like you're using it of outdoor farm that probably sucks,

440
00:22:44,200 --> 00:22:46,399
Speaker 1: and and the weather is not as great, and so

441
00:22:46,440 --> 00:22:48,399
Speaker 1: they're probably not getting the high tea it sea yields

442
00:22:48,400 --> 00:22:51,160
Speaker 1: that we are, the same kind of sun that we're using,

443
00:22:51,200 --> 00:22:53,720
Speaker 1: the same soil that we're using, so the product isn't

444
00:22:53,720 --> 00:22:56,520
Speaker 1: coming out as quality. Right. There's a huge disconnect between

445
00:22:56,560 --> 00:23:01,280
Speaker 1: industry and academia for sure, in terms of what's theoretically possible,

446
00:23:01,800 --> 00:23:03,960
Speaker 1: especially when it comes to regulations like coming from the

447
00:23:04,040 --> 00:23:07,200
Speaker 1: d C c UM and also what is actually in

448
00:23:07,240 --> 00:23:09,000
Speaker 1: the market, you know, what is prevalent in the market.

449
00:23:09,080 --> 00:23:11,560
Speaker 1: Those kinds of things are sort of overlooked by a

450
00:23:11,600 --> 00:23:14,120
Speaker 1: lot of academic sources. You know, I wonder why why

451
00:23:14,119 --> 00:23:17,320
Speaker 1: don't Is it still only from Mississippi's as that just

452
00:23:17,440 --> 00:23:19,400
Speaker 1: change is starting to change? Has change now? Is it?

453
00:23:19,480 --> 00:23:23,840
Speaker 1: Is it wide open now? I'm not entirely sure, um,

454
00:23:23,880 --> 00:23:25,919
Speaker 1: but I do know that I've seen a lot of

455
00:23:25,960 --> 00:23:29,120
Speaker 1: good research on concentrates from the American Chemical Society recently,

456
00:23:29,400 --> 00:23:32,880
Speaker 1: especially about dabbing and different different temperatures of dabbing and

457
00:23:32,920 --> 00:23:36,360
Speaker 1: what kind of actions it happens to you. Combustion products

458
00:23:36,440 --> 00:23:39,520
Speaker 1: come from that. So the first thing we can look

459
00:23:39,560 --> 00:23:42,240
Speaker 1: at as chemists is the combustion products of something. Right,

460
00:23:42,520 --> 00:23:43,919
Speaker 1: then you have to take it further and look at

461
00:23:43,920 --> 00:23:46,080
Speaker 1: the farm cokinetics of that and how the body actually

462
00:23:46,080 --> 00:23:48,600
Speaker 1: processes it. And that's how you get the full understanding

463
00:23:48,680 --> 00:23:51,240
Speaker 1: of what's happening. I love when you break down things

464
00:23:51,440 --> 00:23:54,240
Speaker 1: that that can you do that with us please and

465
00:23:54,800 --> 00:23:57,040
Speaker 1: maybe use something that you've already done before, right that

466
00:23:57,119 --> 00:23:59,720
Speaker 1: you know, from beginning to end, how has that process

467
00:23:59,800 --> 00:24:02,000
Speaker 1: done by somebody and your team and smart like you

468
00:24:02,040 --> 00:24:03,920
Speaker 1: guys that go you know, picks up that you've already

469
00:24:03,920 --> 00:24:06,080
Speaker 1: done and an outcome that you can give to us

470
00:24:06,080 --> 00:24:08,360
Speaker 1: and share with us. Sure, So I think the thing

471
00:24:08,359 --> 00:24:10,280
Speaker 1: that I have the most hands on experience with is

472
00:24:10,359 --> 00:24:14,119
Speaker 1: the cannabis testing world. So, UM, there's a lot of

473
00:24:14,119 --> 00:24:16,800
Speaker 1: really important parts to these steps, so I'm definitely have

474
00:24:16,840 --> 00:24:19,760
Speaker 1: to break it down. UM. Sampling is the first one, right,

475
00:24:19,800 --> 00:24:22,679
Speaker 1: So the labs send out samplers UM to the different

476
00:24:22,840 --> 00:24:26,199
Speaker 1: companies that were collecting cannabis from and sampling needs to

477
00:24:26,240 --> 00:24:30,359
Speaker 1: be random as defined by the DCC. But it's not

478
00:24:30,400 --> 00:24:33,480
Speaker 1: really to find how to make it random in this state.

479
00:24:33,920 --> 00:24:36,399
Speaker 1: I was writing some pamphlets for UM, a lab I

480
00:24:36,400 --> 00:24:39,480
Speaker 1: worked for for a while about how to better ensure

481
00:24:39,760 --> 00:24:42,320
Speaker 1: random sampling because we had a lot of complaints about, oh,

482
00:24:42,359 --> 00:24:44,800
Speaker 1: this isn't the th HC we expected, and so I

483
00:24:44,800 --> 00:24:48,440
Speaker 1: wanted to give them ways to mitigate any confounding factors, right,

484
00:24:48,800 --> 00:24:52,600
Speaker 1: So I looked into legislation from Colorado actually to find

485
00:24:52,640 --> 00:24:55,600
Speaker 1: resources on how to set up like an Excel sheet

486
00:24:55,640 --> 00:24:59,160
Speaker 1: and set up a diagram and properly do random sampling

487
00:24:59,200 --> 00:25:01,960
Speaker 1: of a whole batch. So that's one component that's really

488
00:25:02,040 --> 00:25:04,960
Speaker 1: important that's really being overlooked right now. Um, once it

489
00:25:05,000 --> 00:25:07,120
Speaker 1: gets into the lab, the next step is to make

490
00:25:07,119 --> 00:25:09,879
Speaker 1: sure that it's thoroughly homogenized. And there's a lot of

491
00:25:09,880 --> 00:25:12,800
Speaker 1: different methods that can go into homogenization. That also isn't

492
00:25:12,880 --> 00:25:15,880
Speaker 1: very clearly outlined by the d c C, and homogenization

493
00:25:15,880 --> 00:25:18,240
Speaker 1: can make a huge difference in how much th HC

494
00:25:18,480 --> 00:25:22,240
Speaker 1: is actually and how many turpians obviously are actually retained

495
00:25:22,280 --> 00:25:25,679
Speaker 1: in the end product. Um. In particular, you know, you

496
00:25:25,680 --> 00:25:27,800
Speaker 1: want to make sure that you freeze it pretty much immediately.

497
00:25:27,840 --> 00:25:29,359
Speaker 1: That's how I've seen a lot of labs deal with it.

498
00:25:29,400 --> 00:25:32,679
Speaker 1: Is they'll put it straight into like a meat freezer. Um.

499
00:25:32,720 --> 00:25:34,480
Speaker 1: But then there's the confounding factory of oh do I

500
00:25:34,520 --> 00:25:37,520
Speaker 1: put it in plastic because plastic leeches cannabinoids as well,

501
00:25:37,880 --> 00:25:40,159
Speaker 1: and all those sorts of things. So there's many different methods.

502
00:25:40,200 --> 00:25:43,520
Speaker 1: I've worked with coffee grinders, I've worked with rolling pins.

503
00:25:43,880 --> 00:25:47,520
Speaker 1: There's so many different ways that labs homogenized flour, and

504
00:25:47,600 --> 00:25:51,040
Speaker 1: it can directly impact the th HC yield at the end.

505
00:25:51,520 --> 00:25:53,560
Speaker 1: It has there been a way to figure out which

506
00:25:53,560 --> 00:25:56,640
Speaker 1: one is the best that doesn't, so there's testing every lab.

507
00:25:58,200 --> 00:26:01,000
Speaker 1: Flash freezing is great for pres ring tirpins for sure,

508
00:26:01,240 --> 00:26:03,960
Speaker 1: um and for keeping um those tri combs. You know

509
00:26:03,960 --> 00:26:06,040
Speaker 1: what I means, I'm protected, but flash freez it boom,

510
00:26:06,080 --> 00:26:09,040
Speaker 1: it's frozen, and then they put it into I believe,

511
00:26:10,280 --> 00:26:12,040
Speaker 1: I want to say crates, but I don't know if

512
00:26:12,040 --> 00:26:15,040
Speaker 1: that makes say sense. But once they flash freeze it,

513
00:26:15,080 --> 00:26:17,320
Speaker 1: they gotta put it in. But they're put in the plastic.

514
00:26:17,320 --> 00:26:19,040
Speaker 1: They're putting in the plastic what's called you know what

515
00:26:19,040 --> 00:26:21,520
Speaker 1: I mean, they're freezing them, right. But I think that

516
00:26:21,560 --> 00:26:25,240
Speaker 1: if they're the found this is and this is probably wrong,

517
00:26:25,320 --> 00:26:29,280
Speaker 1: but if they were using they're using the plastic containers right,

518
00:26:29,800 --> 00:26:31,760
Speaker 1: versus like a crate, you know what I mean? Like

519
00:26:31,800 --> 00:26:36,760
Speaker 1: the like the plastic crates. The crates are less harmful

520
00:26:37,000 --> 00:26:42,520
Speaker 1: than the containers because the containers have more of I

521
00:26:42,560 --> 00:26:44,880
Speaker 1: don't know whatever and something like that. And I don't

522
00:26:44,880 --> 00:26:46,919
Speaker 1: know that the scientific term of it. This is just

523
00:26:47,000 --> 00:26:49,600
Speaker 1: people and half the people they told me don't know

524
00:26:49,640 --> 00:26:51,879
Speaker 1: half the should they know. But but they had massive

525
00:26:51,880 --> 00:26:53,399
Speaker 1: amounts of it and they had it in creates And

526
00:26:53,400 --> 00:26:55,320
Speaker 1: I was like, whining, crates and doesn't it ruin the bud?

527
00:26:55,320 --> 00:26:56,560
Speaker 1: And they're like, yeah, but we just set it in

528
00:26:56,600 --> 00:26:59,240
Speaker 1: there and creates in the stack. That creates because the

529
00:26:59,240 --> 00:27:01,440
Speaker 1: other kind of plast think that has no breeding room

530
00:27:01,440 --> 00:27:02,840
Speaker 1: in it, and it keeps it all boom and it's

531
00:27:02,880 --> 00:27:05,120
Speaker 1: just frozen I don't know something like that. Yeah, that's

532
00:27:05,160 --> 00:27:07,320
Speaker 1: something that you've probably can particulately. Yeah, but I mean

533
00:27:07,359 --> 00:27:09,800
Speaker 1: that sounds like storage on the larger scale, right, for

534
00:27:10,000 --> 00:27:13,080
Speaker 1: possibly extraction down the line or something like that. UM

535
00:27:13,080 --> 00:27:14,879
Speaker 1: with the lab, you know, we only get a representative

536
00:27:14,920 --> 00:27:16,840
Speaker 1: sample of the batch, so we only have a small amount,

537
00:27:17,040 --> 00:27:18,800
Speaker 1: and then we work with that to homogenize it, and

538
00:27:18,800 --> 00:27:21,320
Speaker 1: then that homogenized sample gets parsed out into the different

539
00:27:21,400 --> 00:27:24,080
Speaker 1: essays where it needs to be tested within the lab. UM.

540
00:27:24,160 --> 00:27:26,880
Speaker 1: So the rail point that I'm trying to drive home

541
00:27:26,920 --> 00:27:28,919
Speaker 1: here is that there's so many different ways to do

542
00:27:29,000 --> 00:27:32,800
Speaker 1: every single step of the process, and labs consider each

543
00:27:32,840 --> 00:27:36,159
Speaker 1: step proprietary and so they don't share that information. They

544
00:27:36,200 --> 00:27:38,400
Speaker 1: see it as their own method that's going to help

545
00:27:38,440 --> 00:27:41,199
Speaker 1: them achieve the results that they're looking for. And in

546
00:27:41,280 --> 00:27:44,000
Speaker 1: terms of science, you know, it's very limiting because we're,

547
00:27:44,040 --> 00:27:45,800
Speaker 1: like you said, you want to do those tests and

548
00:27:45,840 --> 00:27:48,080
Speaker 1: see what's going to absorb the most cannabinoids, what's gonna

549
00:27:48,080 --> 00:27:50,240
Speaker 1: you know, yield the best, But we're not sharing that

550
00:27:50,280 --> 00:27:53,360
Speaker 1: as scientists. Nobody is sharing that information. So we're not

551
00:27:53,520 --> 00:27:57,760
Speaker 1: progressing as an industry because there's these but there Okay,

552
00:27:57,760 --> 00:28:00,159
Speaker 1: so and I remember this that can can mead, right,

553
00:28:00,320 --> 00:28:03,000
Speaker 1: So somebody was talking about it might have been you, guys,

554
00:28:03,400 --> 00:28:06,280
Speaker 1: is putting a platform together, like an open source platform

555
00:28:06,320 --> 00:28:09,160
Speaker 1: where everybody can actually start growing. Isn't that already happening

556
00:28:09,200 --> 00:28:10,800
Speaker 1: with that in that world or is it starting to

557
00:28:11,080 --> 00:28:13,720
Speaker 1: now after can man? Because I remember a lot of

558
00:28:14,040 --> 00:28:16,040
Speaker 1: you know, movement towards something like that. Do you remember that.

559
00:28:16,080 --> 00:28:19,960
Speaker 1: I remember hear some chatter about that too and open source,

560
00:28:20,000 --> 00:28:22,840
Speaker 1: but there should be a certain protocol like everything you're

561
00:28:22,880 --> 00:28:25,240
Speaker 1: describing about what you were going through the beginning. You're

562
00:28:25,320 --> 00:28:27,280
Speaker 1: right because even the different labs that we've heard in

563
00:28:27,280 --> 00:28:29,399
Speaker 1: a different testing. And of course it sucks for the

564
00:28:29,440 --> 00:28:32,879
Speaker 1: grower who wants their ship to come out h C.

565
00:28:33,080 --> 00:28:36,680
Speaker 1: It's a ridiculous number when you get a small butt

566
00:28:36,680 --> 00:28:38,760
Speaker 1: and it comes out bad or it may come out great.

567
00:28:38,800 --> 00:28:40,800
Speaker 1: I think it's kind of hit and miss sometimes so right,

568
00:28:40,800 --> 00:28:43,000
Speaker 1: because they say the top buds are the best, but

569
00:28:43,040 --> 00:28:45,080
Speaker 1: if a good top little bud falls off and that

570
00:28:45,200 --> 00:28:48,480
Speaker 1: tested great, then you won. So it's like a fucking

571
00:28:48,560 --> 00:28:51,200
Speaker 1: hit and miss space anyways, right, Like you know you

572
00:28:51,240 --> 00:28:54,360
Speaker 1: want your top golden nugs, but that's not always going

573
00:28:54,400 --> 00:28:57,480
Speaker 1: to be the tested one. Right, there's the inherent variability

574
00:28:57,520 --> 00:28:59,440
Speaker 1: of the fact that we're working with nature, right, We're

575
00:28:59,440 --> 00:29:03,040
Speaker 1: working with everything changes, everything can change, And we're not

576
00:29:03,120 --> 00:29:07,760
Speaker 1: actually tracking nutrients, we're not tracking growing you know, regiments

577
00:29:07,760 --> 00:29:11,480
Speaker 1: were just tracking seed seed to sales. Sounds crazy, right,

578
00:29:11,760 --> 00:29:14,440
Speaker 1: So a lot of variables that are unchecked here. But

579
00:29:14,440 --> 00:29:16,920
Speaker 1: but they're testing though. But so that kind of tells

580
00:29:16,920 --> 00:29:18,680
Speaker 1: you whether or not if you're using some of the

581
00:29:19,200 --> 00:29:21,960
Speaker 1: you know, um chemical sides, Yeah, that are going to

582
00:29:22,080 --> 00:29:24,360
Speaker 1: ruin me hardeners and stuff like that that are gonna

583
00:29:24,360 --> 00:29:26,280
Speaker 1: screw you up, right, So I mean, at least that's good.

584
00:29:26,320 --> 00:29:28,600
Speaker 1: But you're right, I think it should be it really

585
00:29:28,600 --> 00:29:31,440
Speaker 1: should be coming from you know, not seed to cell.

586
00:29:31,480 --> 00:29:35,040
Speaker 1: It should be seeds, soil, you know, bobo bum down line,

587
00:29:35,200 --> 00:29:38,160
Speaker 1: and then the soil should be checked everything every even

588
00:29:38,240 --> 00:29:41,320
Speaker 1: the water, the water levels and everything exactly. You know,

589
00:29:41,360 --> 00:29:44,000
Speaker 1: everybody's arrowing their water, but they checked that by the

590
00:29:44,000 --> 00:29:48,000
Speaker 1: farmers that are treating us lettuce and tomatoes. That's I

591
00:29:48,000 --> 00:29:49,880
Speaker 1: don't think so. And that's so that's another big thing.

592
00:29:49,880 --> 00:29:51,400
Speaker 1: I have a lot of people kind of argue with

593
00:29:51,440 --> 00:29:53,240
Speaker 1: me on is like why do we need all of this,

594
00:29:53,280 --> 00:29:55,520
Speaker 1: why do we need all this regulation? And I mean,

595
00:29:55,560 --> 00:29:58,280
Speaker 1: when it comes down to is the future of cannabis, right,

596
00:29:58,320 --> 00:30:00,880
Speaker 1: The future of cannabis is quality control because it is

597
00:30:00,880 --> 00:30:03,720
Speaker 1: technically a drug and down the road here it's going

598
00:30:03,800 --> 00:30:05,920
Speaker 1: to people are gonna want to utilize it in a

599
00:30:05,960 --> 00:30:09,920
Speaker 1: way that's reliable, like we do drugs, and so the

600
00:30:09,960 --> 00:30:12,000
Speaker 1: most reliable thing we can think we can do to

601
00:30:12,080 --> 00:30:15,720
Speaker 1: make it as reliable as possible is remove all variables

602
00:30:15,840 --> 00:30:18,640
Speaker 1: and make it as consistent. The one thing that that

603
00:30:18,800 --> 00:30:20,800
Speaker 1: I thoroughly agree with you is it it's medical, right,

604
00:30:20,880 --> 00:30:23,480
Speaker 1: Like I thoroughly thoroughly agree with you, you know, and

605
00:30:23,760 --> 00:30:26,040
Speaker 1: I and I go back to my simple saying is

606
00:30:26,080 --> 00:30:28,200
Speaker 1: that you know, our country is not you would from

607
00:30:28,200 --> 00:30:30,200
Speaker 1: the US, you know what I mean, There's no way

608
00:30:30,200 --> 00:30:33,240
Speaker 1: that we would ever call it medicinal if it wasn't had,

609
00:30:33,360 --> 00:30:35,520
Speaker 1: if it didn't have medicittle value. There's no way, like

610
00:30:35,520 --> 00:30:39,680
Speaker 1: we're not that you know, silly here. Um. But the

611
00:30:39,920 --> 00:30:41,680
Speaker 1: other thought to me is that at least the only

612
00:30:41,760 --> 00:30:45,520
Speaker 1: drug that we've ever had that is also allowed for

613
00:30:45,600 --> 00:30:49,120
Speaker 1: recreational use, right, So I mean, let's think about that, right,

614
00:30:49,160 --> 00:30:54,959
Speaker 1: And maybe cocaine is a good example but it's not

615
00:30:55,000 --> 00:30:58,680
Speaker 1: a well what medicinal value doesn't have? Alcohol was used

616
00:30:58,720 --> 00:31:04,840
Speaker 1: as an antiseptic and pain really okay? And yeahs bacteria out.

617
00:31:04,920 --> 00:31:07,280
Speaker 1: I guess when you're having surgery, they'd rub alcohol on

618
00:31:07,280 --> 00:31:08,680
Speaker 1: it from back in the days. I mean, it's been

619
00:31:08,720 --> 00:31:14,440
Speaker 1: medically used forever. I would agree, Yeah, you're right cocaine,

620
00:31:15,520 --> 00:31:19,440
Speaker 1: but they're not. But they're not a medical rights MDMA

621
00:31:19,560 --> 00:31:22,240
Speaker 1: and mushrooms are all on their way, So I agree

622
00:31:22,280 --> 00:31:25,720
Speaker 1: with you being I guess alcohol would be would be

623
00:31:25,760 --> 00:31:29,400
Speaker 1: the actual, But but cocaine too, because when do you

624
00:31:29,400 --> 00:31:32,840
Speaker 1: get prescribed to alcohol over the counter like you do?

625
00:31:32,920 --> 00:31:35,600
Speaker 1: You can buy aunt other than over the counter. You're

626
00:31:35,640 --> 00:31:38,360
Speaker 1: not you know when do you get prescribed alcohol? Right? Well,

627
00:31:38,400 --> 00:31:41,760
Speaker 1: if you surgery, the medical grade, medical grade alcohol that

628
00:31:41,800 --> 00:31:45,520
Speaker 1: they're going to use to clean, I'm sure they certainly

629
00:31:45,560 --> 00:31:46,880
Speaker 1: do use it at you. You know what I mean.

630
00:31:46,920 --> 00:31:49,680
Speaker 1: I don't know that they give you can go buy

631
00:31:49,800 --> 00:31:51,800
Speaker 1: some medical grade and wipe it on your your knee

632
00:31:51,800 --> 00:31:59,320
Speaker 1: because you heard it about listering listering alcohol. Okay, very scientific,

633
00:32:01,040 --> 00:32:06,200
Speaker 1: feel like it's a good conversation conversation. The reason I

634
00:32:06,280 --> 00:32:08,080
Speaker 1: say that because I sit there and they give it

635
00:32:08,120 --> 00:32:10,680
Speaker 1: like gosh, you know, they're selling cannabis over the counter,

636
00:32:11,040 --> 00:32:13,760
Speaker 1: and it's it is medicinal. I know, anecdotal evidence, right,

637
00:32:13,800 --> 00:32:15,320
Speaker 1: you've lived it, you know, I've seen it in my

638
00:32:15,320 --> 00:32:17,120
Speaker 1: own home. I've seen it in my own you know,

639
00:32:17,400 --> 00:32:20,680
Speaker 1: and tease and drinks and and and and putting on wounds,

640
00:32:20,720 --> 00:32:23,080
Speaker 1: like you said, like alcohol, I guess. But but again

641
00:32:23,160 --> 00:32:25,080
Speaker 1: they never really sold it, like I guess. They sold

642
00:32:25,120 --> 00:32:27,040
Speaker 1: it over the counter, just like alcohol, but it's in

643
00:32:27,080 --> 00:32:31,360
Speaker 1: the stores, so it's alcohol. Is the actual it's the

644
00:32:31,400 --> 00:32:35,760
Speaker 1: exact one, but not very many in the world. Cocoa

645
00:32:35,840 --> 00:32:38,040
Speaker 1: leaf to the cocoa leaf, if I'm not mistaken, is

646
00:32:38,120 --> 00:32:41,200
Speaker 1: used in a lot of medical drugs, altitude sicknesses exactly.

647
00:32:41,240 --> 00:32:47,280
Speaker 1: So the coach gets high and coke, Well leave medicine.

648
00:32:47,360 --> 00:32:49,880
Speaker 1: You know what I'm saying. You used that leaf. So

649
00:32:49,920 --> 00:32:53,320
Speaker 1: my point is that coke. So I'm complete, can't even

650
00:32:53,320 --> 00:32:55,080
Speaker 1: fight the fighting. I mean, I don't want to diminish

651
00:32:55,120 --> 00:32:57,520
Speaker 1: your point. I would say that cannabis definitely has a

652
00:32:57,640 --> 00:33:02,320
Speaker 1: multitude of medicinal applications in comparison to those other drugs.

653
00:33:02,400 --> 00:33:04,240
Speaker 1: So I think that you have a very strong point

654
00:33:04,280 --> 00:33:07,160
Speaker 1: in that regard, because I think the big difference here

655
00:33:07,200 --> 00:33:10,840
Speaker 1: is that cannabis has a stigma and the other drugs don't. Yeah,

656
00:33:10,960 --> 00:33:13,120
Speaker 1: I mean within your context of using cocaine, that's a

657
00:33:13,160 --> 00:33:16,959
Speaker 1: culturally accepted, you know, remedy in that count It might

658
00:33:17,000 --> 00:33:18,720
Speaker 1: be in a fteran, it might be a kinds of

659
00:33:18,800 --> 00:33:20,640
Speaker 1: random things that you know, people are using it in

660
00:33:20,920 --> 00:33:23,880
Speaker 1: like legally across the nation the country, you know, I

661
00:33:23,960 --> 00:33:25,959
Speaker 1: mean not just in our nation. I'm talking about all

662
00:33:26,000 --> 00:33:30,640
Speaker 1: the nations and countries that they utilize that plant for sure. Yeah,

663
00:33:30,680 --> 00:33:33,560
Speaker 1: so the sigma worldwide against cannabis is kind of crazy

664
00:33:34,240 --> 00:33:36,280
Speaker 1: because yeah, there it really is no other plant that's

665
00:33:36,560 --> 00:33:38,920
Speaker 1: has so many medicinal values that has such a stigma

666
00:33:38,960 --> 00:33:40,920
Speaker 1: to it. Right, what is shocked you? You know, when

667
00:33:40,960 --> 00:33:42,480
Speaker 1: we come back and take a breakouts and when we

668
00:33:42,560 --> 00:33:45,880
Speaker 1: come back, I want your thoughts on because you got

669
00:33:45,920 --> 00:33:48,560
Speaker 1: into this game after you became you know, a little

670
00:33:48,560 --> 00:33:50,880
Speaker 1: bit older in your professional career, and as you're studying this,

671
00:33:51,240 --> 00:33:54,720
Speaker 1: has there been anything that surprised you? And when, oh

672
00:33:54,760 --> 00:33:57,760
Speaker 1: my god, this plant does what as you study is

673
00:33:57,840 --> 00:34:00,320
Speaker 1: Cannabis Talk one on one we come back, it's more

674
00:34:00,360 --> 00:34:03,200
Speaker 1: with Alexandra Harris right here on Cannabis Talk one. Oh, one.

675
00:34:03,240 --> 00:34:05,400
Speaker 1: We'll be right back. We'll be right back with Cannabis

676
00:34:05,440 --> 00:34:19,440
Speaker 1: Talk one oh one. Welcome back to Cannabis Talk one

677
00:34:19,440 --> 00:34:23,040
Speaker 1: oh one. What time is it, folks? Do? That's why

678
00:34:23,080 --> 00:34:26,520
Speaker 1: I think higher with Dime Industries. Find them in California, Arizona,

679
00:34:26,520 --> 00:34:29,879
Speaker 1: and Oklahoma. In my pocket. Check out the website Dime

680
00:34:29,920 --> 00:34:34,280
Speaker 1: Industry dot com. You don't know find out one dime

681
00:34:34,400 --> 00:34:39,560
Speaker 1: dot and I need me A came by the other

682
00:34:39,640 --> 00:34:41,600
Speaker 1: day and dropped me off, So she just gave me

683
00:34:41,640 --> 00:34:44,680
Speaker 1: a new one. Hit Skinny Queen for hooking your boy back.

684
00:34:44,760 --> 00:34:47,480
Speaker 1: Said that all that bullshit, it's in my car and

685
00:34:47,520 --> 00:34:50,080
Speaker 1: I don't really have in my pocket to hit it.

686
00:34:50,160 --> 00:34:52,360
Speaker 1: Shout out to everybody on our team, you guys for

687
00:34:52,440 --> 00:34:54,640
Speaker 1: making everything happen. I just said Jena's name out there.

688
00:34:54,719 --> 00:34:57,279
Speaker 1: Jen's doing wonderful things for us and Dime and everybody else.

689
00:34:57,640 --> 00:35:02,760
Speaker 1: Erica Daniel cal Christian a Christian asked Danny Petty, Funk, Connor,

690
00:35:02,880 --> 00:35:08,920
Speaker 1: Gabrielle Sagara, Jessica Cash, Cam Kimberly, Isaiah Solar, Nadia, Ali Pitt,

691
00:35:09,320 --> 00:35:13,759
Speaker 1: Devin Sarah, Alexa Maddie. Those are some new names. I

692
00:35:13,880 --> 00:35:18,240
Speaker 1: like that. Erica Chris Frankino Jennifer, Mark Karnes and Elvis

693
00:35:18,360 --> 00:35:21,080
Speaker 1: and jan still on here. I see you still made

694
00:35:21,080 --> 00:35:23,640
Speaker 1: it on the list. I don't and you know I

695
00:35:23,680 --> 00:35:26,800
Speaker 1: want to. I do want to say, you know, Alexandra Harris,

696
00:35:26,800 --> 00:35:28,560
Speaker 1: we're just gonna bring her in. I think was just

697
00:35:28,800 --> 00:35:31,759
Speaker 1: right for so shook me up do my blood work.

698
00:35:31,760 --> 00:35:33,880
Speaker 1: I don't know, no, no, listen, I've got an idea

699
00:35:34,680 --> 00:35:39,840
Speaker 1: I could tell him so well. I almost think I

700
00:35:39,920 --> 00:35:42,120
Speaker 1: know what it is. I don't know if you do.

701
00:35:42,280 --> 00:35:44,960
Speaker 1: I mean you probably do, actually, but I think I

702
00:35:45,080 --> 00:35:47,360
Speaker 1: do too. I want to do something remote right because

703
00:35:47,360 --> 00:35:48,680
Speaker 1: I know what. I think she could do it, and

704
00:35:48,719 --> 00:35:51,280
Speaker 1: I think she could do everything like I'm so excited

705
00:35:51,320 --> 00:35:55,080
Speaker 1: actually well because I want to work hold on. Before

706
00:35:55,080 --> 00:35:56,600
Speaker 1: we went to break, folks, before we went to break,

707
00:35:56,640 --> 00:35:59,320
Speaker 1: I said to you, what is something studying? Because I

708
00:35:59,440 --> 00:36:01,560
Speaker 1: think there for dominal woman, you can do damn near everything.

709
00:36:01,560 --> 00:36:03,080
Speaker 1: We're going to talk about your podcast too, that you

710
00:36:03,160 --> 00:36:09,520
Speaker 1: do and how did you're so um outgoing and articulate

711
00:36:09,520 --> 00:36:13,960
Speaker 1: intelligence intelligence? Uh, your stories take me down the lane

712
00:36:14,000 --> 00:36:15,840
Speaker 1: that makes me want to listen to That's why I

713
00:36:15,880 --> 00:36:17,839
Speaker 1: know he's I already know where he's going. So that's

714
00:36:17,840 --> 00:36:19,279
Speaker 1: why so I can tell where you're going because you're

715
00:36:19,440 --> 00:36:21,520
Speaker 1: you pull me with a hook. I'm like, let that

716
00:36:21,560 --> 00:36:24,279
Speaker 1: girl out, grab my lip. She grabs me. That being

717
00:36:24,360 --> 00:36:27,360
Speaker 1: said Alex before we went to break as you've got

718
00:36:27,440 --> 00:36:30,080
Speaker 1: into this cannabis game as a young biologist and chemists

719
00:36:30,080 --> 00:36:32,840
Speaker 1: and scientists and becoming everything that you are as we

720
00:36:32,920 --> 00:36:35,680
Speaker 1: read at the beginning, which is a cannabis science advisor

721
00:36:35,760 --> 00:36:39,440
Speaker 1: for God's sakes, consulting chemists. And now you're at tycoon

722
00:36:39,520 --> 00:36:42,520
Speaker 1: a lawn. What have you learned that you went holy ship?

723
00:36:42,640 --> 00:36:45,719
Speaker 1: Where was your first holy ship? When you went cannabis

724
00:36:45,920 --> 00:36:48,880
Speaker 1: can do this? So I would say, actually, my biggest

725
00:36:48,920 --> 00:36:52,759
Speaker 1: holy ship wasn't can med uh speaking up can met Um.

726
00:36:53,560 --> 00:36:57,120
Speaker 1: So I worked in cancer research right before I actually

727
00:36:57,160 --> 00:36:59,280
Speaker 1: I might have still been working at the cancer research

728
00:36:59,360 --> 00:37:01,759
Speaker 1: place when I was at ken med Um. And as

729
00:37:01,840 --> 00:37:03,280
Speaker 1: I was working in that, I would go to different

730
00:37:03,360 --> 00:37:05,560
Speaker 1: places like Stanford and U C. L A. And talked

731
00:37:05,560 --> 00:37:07,040
Speaker 1: to all these researchers. I go, hey, what do you

732
00:37:07,080 --> 00:37:09,360
Speaker 1: think about cannabinoids in this experiment? Do you think that

733
00:37:09,520 --> 00:37:12,520
Speaker 1: exposing these cells to carnabinoids would help? And you know,

734
00:37:12,600 --> 00:37:14,920
Speaker 1: I got some pretty good feedback, but obviously they couldn't.

735
00:37:14,960 --> 00:37:16,840
Speaker 1: They couldn't do it. Um. But then I went to

736
00:37:16,960 --> 00:37:19,320
Speaker 1: can Net and I met Dr Dettie Mary, who was

737
00:37:19,480 --> 00:37:22,640
Speaker 1: the exactly like an idiot where you're talking so intelligent

738
00:37:22,760 --> 00:37:24,040
Speaker 1: right now and I don't know if I want to lap.

739
00:37:24,880 --> 00:37:31,680
Speaker 1: This is why I was a high school teacher. That's

740
00:37:31,680 --> 00:37:36,719
Speaker 1: trying to hit on you right now. Okay, so um,

741
00:37:37,080 --> 00:37:41,200
Speaker 1: Dr Jetty Mary exactly. So there's this like sad, this

742
00:37:41,360 --> 00:37:43,680
Speaker 1: is the coolest stuff ever write. The fad in cancer

743
00:37:43,760 --> 00:37:47,640
Speaker 1: research is um polly pharmacy and personalized medicine. So what

744
00:37:47,760 --> 00:37:49,880
Speaker 1: that means is using more than one drug to attack

745
00:37:49,960 --> 00:37:53,160
Speaker 1: one problem and using drugs that are responding well to

746
00:37:53,239 --> 00:37:56,480
Speaker 1: the individual and tracking that basically. And what Dr Dettie

747
00:37:56,520 --> 00:37:59,800
Speaker 1: Mary is doing is he's doing polly pharmacy but with

748
00:38:00,120 --> 00:38:04,240
Speaker 1: existing Canada's drugs and novel cannabinoids. So he's a novel

749
00:38:04,800 --> 00:38:10,480
Speaker 1: novel old like what I thought, that have never been named?

750
00:38:11,760 --> 00:38:16,800
Speaker 1: So are they just they're already there, they just have

751
00:38:17,040 --> 00:38:20,160
Speaker 1: nobody has. He's running him on a chromatogram like you

752
00:38:20,280 --> 00:38:23,080
Speaker 1: do within cannabis testing, and then he's pulling out those

753
00:38:23,160 --> 00:38:27,640
Speaker 1: peaks that are unlabeled and he's using those to administer

754
00:38:27,760 --> 00:38:29,959
Speaker 1: two different kinds of cancers and the results he's seeing

755
00:38:30,120 --> 00:38:33,920
Speaker 1: is like five times cancer size. Dr Deddie Mary he

756
00:38:34,000 --> 00:38:36,640
Speaker 1: was he was, No, he's at the Techno On Institute

757
00:38:36,680 --> 00:38:39,200
Speaker 1: in Israel. Was was he speaking? He was at Kama.

758
00:38:39,360 --> 00:38:42,000
Speaker 1: He was the keynote speaker at the v I remember

759
00:38:42,080 --> 00:38:46,759
Speaker 1: that one. He's so nice. Yes, remember like yes, no, no, no, no, no,

760
00:38:46,880 --> 00:38:52,399
Speaker 1: he's you're talking about Dr Russo. He was the guy

761
00:38:52,480 --> 00:38:55,279
Speaker 1: that was on the big screen that one. Again. Didn't

762
00:38:55,280 --> 00:38:57,320
Speaker 1: he come on, you guys remember the dinner the v

763
00:38:57,400 --> 00:38:59,560
Speaker 1: I p didn't He was the speaker at the boy

764
00:38:59,760 --> 00:39:01,520
Speaker 1: he was and he had his whole team. There was

765
00:39:01,560 --> 00:39:03,400
Speaker 1: one picture with him, his whole team behind. I remember

766
00:39:03,400 --> 00:39:06,800
Speaker 1: at the end. He was a phenomenal man. His talks

767
00:39:06,840 --> 00:39:10,600
Speaker 1: are so entertaining. It's so funny as you say that, Aletsander,

768
00:39:10,640 --> 00:39:15,600
Speaker 1: because I got away from that event. That's still baffling

769
00:39:15,680 --> 00:39:17,439
Speaker 1: to me that I use when I talked. My wife

770
00:39:17,719 --> 00:39:19,120
Speaker 1: has her doctorate as well. When I say I talked

771
00:39:19,120 --> 00:39:21,920
Speaker 1: to her friends and people in my home life, which

772
00:39:21,960 --> 00:39:24,280
Speaker 1: is quoted a cause where I live in the area

773
00:39:24,280 --> 00:39:26,319
Speaker 1: of people that I live around, and I always say

774
00:39:26,320 --> 00:39:30,399
Speaker 1: to them this, you know what I mean. But these doctors, people, scientists, people,

775
00:39:30,800 --> 00:39:34,160
Speaker 1: which is war higher end. It's more expensive than where

776
00:39:34,160 --> 00:39:38,040
Speaker 1: I lived. That being said, though, the factor that you

777
00:39:38,160 --> 00:39:40,920
Speaker 1: mentioned that, and the key point that I took away

778
00:39:40,960 --> 00:39:45,960
Speaker 1: from can MAD from that statement is that there's still

779
00:39:46,320 --> 00:39:51,480
Speaker 1: things that the can cannabin the camera can, the cannabinoids

780
00:39:51,680 --> 00:39:56,800
Speaker 1: still haven't been found. There's there's still infinite like that.

781
00:39:56,920 --> 00:39:59,920
Speaker 1: We don't have no idea of what it's lots. You don't.

782
00:40:00,239 --> 00:40:02,480
Speaker 1: Sometimes at these events, I'm really high and people ask

783
00:40:02,560 --> 00:40:04,640
Speaker 1: me really technical questions, and I go, you realize, we

784
00:40:04,680 --> 00:40:08,399
Speaker 1: don't know anything about weed, right, Like it's all we've thought.

785
00:40:08,560 --> 00:40:10,440
Speaker 1: We've got some good studies, you know, some good studies

786
00:40:12,160 --> 00:40:14,400
Speaker 1: we've got, so I don't think we'll know in my lifetime.

787
00:40:14,640 --> 00:40:18,520
Speaker 1: Really what what has happening? You're like a big scientist,

788
00:40:18,600 --> 00:40:21,880
Speaker 1: and you know, I just the endocannabinoid system is, it's

789
00:40:21,920 --> 00:40:24,360
Speaker 1: spread so far throughout the body. There's so many implications

790
00:40:24,400 --> 00:40:26,279
Speaker 1: in so many different disease states. And then on top

791
00:40:26,360 --> 00:40:28,960
Speaker 1: of that, the cannabis plant has so many different properties

792
00:40:28,960 --> 00:40:30,960
Speaker 1: and so many different molecules, and then we look at

793
00:40:30,960 --> 00:40:33,480
Speaker 1: all the different roots of administration and how we're actually

794
00:40:33,600 --> 00:40:35,680
Speaker 1: processing that in the body. And then we look at

795
00:40:35,680 --> 00:40:39,560
Speaker 1: all the different genetic predispositions as well as differences based

796
00:40:39,600 --> 00:40:42,840
Speaker 1: on sex and weight and all that kind of So

797
00:40:43,200 --> 00:40:45,359
Speaker 1: there's so many different things that can go into how

798
00:40:45,480 --> 00:40:48,160
Speaker 1: cannabis makes you feel and what medical benefits you can

799
00:40:48,200 --> 00:40:49,880
Speaker 1: derive from it. And you know, Joe and I have

800
00:40:49,960 --> 00:40:52,800
Speaker 1: talked about this and and is simplifying it down to

801
00:40:53,680 --> 00:40:56,400
Speaker 1: and I think in your lifetime do you feel or

802
00:40:56,440 --> 00:40:59,320
Speaker 1: in our lifetime do you feel that we're going to see? Okay,

803
00:40:59,480 --> 00:41:03,279
Speaker 1: you're you know, two d ten pounds, take two of these.

804
00:41:03,520 --> 00:41:06,399
Speaker 1: This is going to help you for them. Yeah, that's

805
00:41:06,440 --> 00:41:08,920
Speaker 1: really what my master's program is doing. So the master's

806
00:41:09,000 --> 00:41:11,839
Speaker 1: program in is a school of pharmacy program, and it's

807
00:41:11,840 --> 00:41:15,120
Speaker 1: all about the pharmacokinetics of cannabis. And so I'm learning

808
00:41:15,120 --> 00:41:18,200
Speaker 1: about dosing based on root of administration, based on indication,

809
00:41:18,280 --> 00:41:20,680
Speaker 1: and based on things like weight, insects and all those

810
00:41:20,760 --> 00:41:23,279
Speaker 1: kinds of things. So, um, you know that side of

811
00:41:23,320 --> 00:41:25,520
Speaker 1: the world, the pharmacists and clinician side of the world,

812
00:41:25,600 --> 00:41:27,359
Speaker 1: is really doing a lot of great work to bring

813
00:41:27,719 --> 00:41:32,040
Speaker 1: cannabis as a legitimate medicine into healthcare facilities, and so

814
00:41:32,160 --> 00:41:34,560
Speaker 1: we will see that. Yeah, I'm raising my hand right now,

815
00:41:35,040 --> 00:41:38,080
Speaker 1: I've got a question, and I love it, and I'm wondering,

816
00:41:38,200 --> 00:41:42,200
Speaker 1: and I'm wondering, does it just go five year big breakground?

817
00:41:42,280 --> 00:41:47,439
Speaker 1: Like say five male female, hundred hundred pound, hundred twenty pound?

818
00:41:48,320 --> 00:41:50,320
Speaker 1: Like what is that dynamic? How does that look like

819
00:41:50,400 --> 00:41:52,799
Speaker 1: from a scientific breakdown? Like what do you guys use?

820
00:41:53,360 --> 00:41:56,239
Speaker 1: Is it five ten pounds? Like from two ten male

821
00:41:56,320 --> 00:42:01,040
Speaker 1: female only? Is it also ten pounds male? Female? Ethnicity?

822
00:42:01,160 --> 00:42:03,800
Speaker 1: Is it Latin blood? Is it African American blood? Is

823
00:42:03,840 --> 00:42:06,120
Speaker 1: it white blood? Like? How does it get broken down?

824
00:42:06,200 --> 00:42:09,279
Speaker 1: And that it? Is it based on fat cells? So

825
00:42:09,560 --> 00:42:14,040
Speaker 1: every study is different? How how how every study sources? Well,

826
00:42:14,080 --> 00:42:16,279
Speaker 1: the fat cells are super important obviously, that's what I

827
00:42:16,960 --> 00:42:19,960
Speaker 1: know what you're alluding to. And that has to do

828
00:42:20,360 --> 00:42:23,719
Speaker 1: with metabolism and extre excretion of cannabinoids and how long

829
00:42:23,800 --> 00:42:26,600
Speaker 1: it takes your body to fully metabolized cannabinoids. And that

830
00:42:26,680 --> 00:42:29,560
Speaker 1: being said real quick, because I don't know if you're heavier,

831
00:42:29,680 --> 00:42:32,960
Speaker 1: does cannabis work differently for your body? Meaning if I'm smoking,

832
00:42:33,040 --> 00:42:35,560
Speaker 1: if I'm if I'm skinnier with fat cells, does a

833
00:42:35,640 --> 00:42:38,719
Speaker 1: cannabinoid system work differently if you're heavier or lighter? If

834
00:42:38,760 --> 00:42:41,920
Speaker 1: you have more out of pose tissue. Theoretically, cannabinoids will

835
00:42:41,960 --> 00:42:44,319
Speaker 1: stay in your body for longer, so you can beer,

836
00:42:44,360 --> 00:42:46,520
Speaker 1: you can get higher. You're higher me last one, not

837
00:42:46,640 --> 00:42:49,400
Speaker 1: necessarily in your blood stream. So the blood stream is

838
00:42:49,440 --> 00:42:50,800
Speaker 1: what's gonna make you feel it, because it's going to

839
00:42:50,840 --> 00:42:52,600
Speaker 1: be in your brain, right, But if it's in your

840
00:42:52,640 --> 00:42:56,160
Speaker 1: fat tissue, that's more so. It's slowly being metabolized by

841
00:42:56,200 --> 00:42:58,440
Speaker 1: your body and excreted, so you can get tested for

842
00:42:58,719 --> 00:43:01,840
Speaker 1: cannabis on a drug tab for longer than someone who's thinnershed.

843
00:43:02,160 --> 00:43:09,400
Speaker 1: So if you're heavier, it will be in your skinny guys,

844
00:43:13,280 --> 00:43:18,399
Speaker 1: but longer it might hang out with Okay, and as

845
00:43:18,480 --> 00:43:21,200
Speaker 1: you see this, this is a random hypothetical you may

846
00:43:21,280 --> 00:43:23,239
Speaker 1: not have an answer for. But I'm just curious with

847
00:43:23,400 --> 00:43:26,120
Speaker 1: your anecdotal evidence of what you've seen and what you think.

848
00:43:26,160 --> 00:43:28,600
Speaker 1: Because you made a statement that said you do not

849
00:43:29,080 --> 00:43:32,040
Speaker 1: believe you'll see it in your lifetime. It's a big statement.

850
00:43:32,360 --> 00:43:35,040
Speaker 1: She's saying everything I know, and I know that, and

851
00:43:35,080 --> 00:43:36,719
Speaker 1: that's what I'm saying to you. Now. I'm gonna make

852
00:43:36,800 --> 00:43:39,120
Speaker 1: this statement for you. If you could see it in

853
00:43:39,200 --> 00:43:44,520
Speaker 1: your lifetime, what would it need to happen? How many scientists,

854
00:43:44,640 --> 00:43:46,839
Speaker 1: how many people would need to work out because you're

855
00:43:46,840 --> 00:43:51,400
Speaker 1: already working with tycoon along the USA. A company at

856
00:43:51,600 --> 00:43:53,640
Speaker 1: Israel that's a big company. And I remember when they

857
00:43:53,680 --> 00:43:55,320
Speaker 1: came here and there and they're no joke, it's a

858
00:43:55,320 --> 00:43:58,400
Speaker 1: big company. Just but but forget the size for a second, right,

859
00:43:59,320 --> 00:44:01,480
Speaker 1: it's the or me, you know. And I say this

860
00:44:01,560 --> 00:44:05,319
Speaker 1: because I've walked through you know, many different facilities. It's

861
00:44:05,400 --> 00:44:08,400
Speaker 1: the way that they carry themselves and and and clearly

862
00:44:08,480 --> 00:44:11,160
Speaker 1: because they have you know, a standard, but but I

863
00:44:11,480 --> 00:44:14,359
Speaker 1: just I've seen the way that they carry themselves at

864
00:44:14,480 --> 00:44:17,480
Speaker 1: the location. So I don't know what their inner workings are,

865
00:44:17,640 --> 00:44:19,680
Speaker 1: you know, how their businesses and all that good stuff.

866
00:44:19,880 --> 00:44:21,480
Speaker 1: But I mean I've been to a lot of facilities,

867
00:44:21,800 --> 00:44:23,799
Speaker 1: and I just like the way they keeping their their house,

868
00:44:24,200 --> 00:44:26,000
Speaker 1: you know. And it's like if you keep your house

869
00:44:26,040 --> 00:44:28,480
Speaker 1: super clean, and and you seem to have very intelligent

870
00:44:28,520 --> 00:44:31,600
Speaker 1: people around you, and the infrastructure seems very well. I

871
00:44:31,960 --> 00:44:33,440
Speaker 1: just appreciate it, you know. I've been to a lot

872
00:44:33,480 --> 00:44:36,800
Speaker 1: of growth and you know, it's questionable whether or not

873
00:44:37,080 --> 00:44:40,680
Speaker 1: they're they're just trying to catch a bag of money

874
00:44:40,840 --> 00:44:46,000
Speaker 1: or some more good high versus you know, progressing versus

875
00:44:46,080 --> 00:44:49,680
Speaker 1: progressing the industry. And I feel from an outside again,

876
00:44:49,719 --> 00:44:52,239
Speaker 1: I'm not in the scientist, nor am I on the

877
00:44:52,280 --> 00:44:54,440
Speaker 1: inside there of their inner workings, but I feel that

878
00:44:54,480 --> 00:44:57,360
Speaker 1: they're really trying to progress in the industry, which to

879
00:44:57,440 --> 00:45:01,520
Speaker 1: me is is where you know, the right everybody should

880
00:45:01,560 --> 00:45:03,759
Speaker 1: be really focused on, versus just like, hey, how do

881
00:45:03,840 --> 00:45:06,200
Speaker 1: we get our bottom down in dollar down, get the

882
00:45:06,280 --> 00:45:09,200
Speaker 1: best quality of weed and get people companies doing the

883
00:45:09,320 --> 00:45:11,239
Speaker 1: right thing. I think they're really trying to, like by

884
00:45:11,320 --> 00:45:13,840
Speaker 1: hiring her, I mean clearly, you know, put research and

885
00:45:13,920 --> 00:45:16,000
Speaker 1: development into the company. There's just a lot of companies

886
00:45:16,000 --> 00:45:18,640
Speaker 1: that don't do any of that, you know, So what

887
00:45:18,840 --> 00:45:20,960
Speaker 1: do you think it would take? So I like to

888
00:45:21,040 --> 00:45:24,800
Speaker 1: be optimistic sometimes about I think that companies like to

889
00:45:24,880 --> 00:45:27,239
Speaker 1: Cune that have good motives that you know, really want

890
00:45:27,280 --> 00:45:31,600
Speaker 1: to get good quality medicine to patients for improving their

891
00:45:31,680 --> 00:45:33,840
Speaker 1: quality of life. I think those companies are going to

892
00:45:33,880 --> 00:45:35,719
Speaker 1: come out on top. And the reason I think that

893
00:45:35,880 --> 00:45:38,720
Speaker 1: is because it's in line with the do no harm,

894
00:45:39,120 --> 00:45:42,160
Speaker 1: you know, goal of healthcare in general. And I think,

895
00:45:42,200 --> 00:45:44,360
Speaker 1: really what it's going to take for the research to

896
00:45:44,400 --> 00:45:46,879
Speaker 1: be expanded to the point where we can understand enough

897
00:45:46,920 --> 00:45:49,920
Speaker 1: to make definitive claims about cannabis. UM is going to

898
00:45:50,000 --> 00:45:54,239
Speaker 1: be removing the stigma, so UM as a student association leader, UM,

899
00:45:54,360 --> 00:45:57,440
Speaker 1: that's really like my big spiel is we do advocacy,

900
00:45:57,640 --> 00:46:00,640
Speaker 1: education and networking, and I think that advocacy in education

901
00:46:00,719 --> 00:46:02,440
Speaker 1: go hand in hand. I think you can't have one

902
00:46:02,480 --> 00:46:06,839
Speaker 1: without the other, because taking the education to the politicians

903
00:46:06,960 --> 00:46:09,320
Speaker 1: and doing that advocacy work and making sure that that

904
00:46:09,440 --> 00:46:13,600
Speaker 1: stigma changes is really the precursor to more research happening. UM.

905
00:46:13,760 --> 00:46:16,160
Speaker 1: You know, we've we've seen all this red tape for

906
00:46:16,239 --> 00:46:19,600
Speaker 1: researchers trying to get funding and approval just to study

907
00:46:19,640 --> 00:46:22,719
Speaker 1: cannabis for so many years. If that stigma went away

908
00:46:22,960 --> 00:46:26,040
Speaker 1: and we actually gave those researchers access to what they need,

909
00:46:26,400 --> 00:46:27,960
Speaker 1: we would be so much farther along right now. And

910
00:46:28,000 --> 00:46:29,799
Speaker 1: that's what we're seeing in countries like Israel, where they've

911
00:46:29,880 --> 00:46:32,279
Speaker 1: kind of embraced it. And I feel like everything you're

912
00:46:32,280 --> 00:46:35,080
Speaker 1: seeing does that happen here though? I mean everything you're

913
00:46:35,080 --> 00:46:38,680
Speaker 1: saying is and it has to happen through education. Now

914
00:46:38,760 --> 00:46:42,160
Speaker 1: we're seeing colleges accept it more. You're in a master's program.

915
00:46:42,239 --> 00:46:44,200
Speaker 1: We heard U c l A is doing something at

916
00:46:44,239 --> 00:46:47,399
Speaker 1: their school with their master's program. You say, you're talking

917
00:46:47,440 --> 00:46:51,120
Speaker 1: to scientists at Stanford. So it's once we educate our

918
00:46:51,680 --> 00:46:55,040
Speaker 1: colleges that are here, that are our universities and they

919
00:46:55,080 --> 00:46:58,719
Speaker 1: accept a cannabis program, which we're seeing more and more

920
00:46:58,840 --> 00:47:02,040
Speaker 1: colleges happen. So is it fair to say that we're

921
00:47:02,080 --> 00:47:06,160
Speaker 1: in the process of it happening because these universities are

922
00:47:06,239 --> 00:47:11,120
Speaker 1: accepting programs that are giving this green thumb of the

923
00:47:11,480 --> 00:47:14,480
Speaker 1: approval of a knowledge of you now getting accepted as

924
00:47:15,120 --> 00:47:20,279
Speaker 1: this as accredited university. So now it's becoming part of

925
00:47:20,320 --> 00:47:22,759
Speaker 1: the process as long as the motives are good. Yes,

926
00:47:23,040 --> 00:47:24,839
Speaker 1: I agree with you. You know, there are some people

927
00:47:24,880 --> 00:47:26,520
Speaker 1: that are just trying to get their bag, like you're saying,

928
00:47:26,600 --> 00:47:28,160
Speaker 1: there are a lot of people that are jumping on this.

929
00:47:29,680 --> 00:47:31,200
Speaker 1: But even if you have so even if you have

930
00:47:31,239 --> 00:47:33,040
Speaker 1: an agree and you're doing it for the cloud, you

931
00:47:33,120 --> 00:47:34,840
Speaker 1: might not be benefiting the cause that much, you know

932
00:47:34,880 --> 00:47:36,680
Speaker 1: what I mean. So that's that's kind of what I'm

933
00:47:36,719 --> 00:47:38,640
Speaker 1: thinking about, is we need more people that have the

934
00:47:38,719 --> 00:47:41,160
Speaker 1: good motives to do the good work and do the

935
00:47:41,200 --> 00:47:43,440
Speaker 1: advocacy and the clarity to actually do it right. So

936
00:47:43,680 --> 00:47:46,320
Speaker 1: I mean a lot of people walk into you know,

937
00:47:46,520 --> 00:47:48,440
Speaker 1: I mean, it's all about having fun. I get it.

938
00:47:48,640 --> 00:47:50,680
Speaker 1: There's all about making money, I get it. But the

939
00:47:50,760 --> 00:47:53,520
Speaker 1: research and development, the research and development is all about

940
00:47:53,560 --> 00:47:56,239
Speaker 1: really helping people. Right. So when you and and there's

941
00:47:56,239 --> 00:47:58,279
Speaker 1: a long term play, and there's a fast term play, right,

942
00:47:58,280 --> 00:48:00,360
Speaker 1: and there's and we've always going about this, like, you know,

943
00:48:00,440 --> 00:48:02,440
Speaker 1: we have a certain culture about us that we why

944
00:48:02,520 --> 00:48:06,080
Speaker 1: we're so successful, why we're able to be somewhat successful?

945
00:48:06,120 --> 00:48:09,319
Speaker 1: How about that? And and but it's it's it's car

946
00:48:09,440 --> 00:48:12,120
Speaker 1: and communicate, it's it's moving forward thinking. It's how to

947
00:48:12,280 --> 00:48:15,160
Speaker 1: how to figure out how to actually deal with people

948
00:48:15,360 --> 00:48:18,000
Speaker 1: and and really deliver for them, right, not really just

949
00:48:18,520 --> 00:48:21,120
Speaker 1: get them something that's fast food. Right, It's like giving

950
00:48:21,120 --> 00:48:22,719
Speaker 1: out bad food all the time. It's like, you know,

951
00:48:22,760 --> 00:48:25,840
Speaker 1: if you just hand out you know, McDonald's to everybody,

952
00:48:25,920 --> 00:48:28,000
Speaker 1: you know, we're all gonna end up dying of cancer

953
00:48:28,200 --> 00:48:31,719
Speaker 1: or obesity, right. But you give them other options and

954
00:48:31,760 --> 00:48:33,480
Speaker 1: then they choose to pick those options. And that's the

955
00:48:33,520 --> 00:48:35,840
Speaker 1: same thing that happened. I think in the cannabis industry.

956
00:48:35,880 --> 00:48:38,279
Speaker 1: There's just other companies that are actually taking more time

957
00:48:38,680 --> 00:48:41,759
Speaker 1: to put their money where their mouth is and would

958
00:48:41,800 --> 00:48:45,239
Speaker 1: probably take losses and probably take losses along the way

959
00:48:45,760 --> 00:48:49,400
Speaker 1: because of the bigger picture, right. And it's like, whereas

960
00:48:49,480 --> 00:48:51,400
Speaker 1: the smaller guys and no offense than any of these

961
00:48:51,480 --> 00:48:54,279
Speaker 1: guys or those companies out there or back dooring selling weed,

962
00:48:54,520 --> 00:48:56,200
Speaker 1: They're doing things behind the back to do what they

963
00:48:56,239 --> 00:48:58,440
Speaker 1: gotta do, and they get it, and I'm not against it.

964
00:48:58,560 --> 00:49:01,359
Speaker 1: I'm I'm but at the same time, I am more

965
00:49:01,520 --> 00:49:07,480
Speaker 1: for the growth. The interview and parency is very key.

966
00:49:08,160 --> 00:49:09,640
Speaker 1: I was actually thinking about that on the way here

967
00:49:09,719 --> 00:49:11,200
Speaker 1: because I was thinking about one thing that I've been

968
00:49:11,200 --> 00:49:13,480
Speaker 1: really passionate about educating people about is checking the s

969
00:49:13,680 --> 00:49:15,680
Speaker 1: base because that's the world I come from. It is

970
00:49:15,680 --> 00:49:18,600
Speaker 1: producing sabase, and sabase can tell you a lot about

971
00:49:18,800 --> 00:49:22,040
Speaker 1: how well a lab vetted that product, especially when it

972
00:49:22,120 --> 00:49:24,160
Speaker 1: comes to the new synthetic products that are coming out,

973
00:49:24,200 --> 00:49:25,719
Speaker 1: which is a whole other tangent that I could go

974
00:49:25,760 --> 00:49:28,520
Speaker 1: on checking them. Do you mean, do you mean really

975
00:49:28,600 --> 00:49:32,719
Speaker 1: like retesting them yourself? No? No, no, no, no, that

976
00:49:32,760 --> 00:49:35,000
Speaker 1: would be quite difficult because you know, there's a lot

977
00:49:35,000 --> 00:49:37,360
Speaker 1: of flim flam with those as well, you know what

978
00:49:37,400 --> 00:49:41,040
Speaker 1: I mean. And often it's like, you know, I hear

979
00:49:41,080 --> 00:49:44,120
Speaker 1: a lot. Right, I'm in the in the in the network,

980
00:49:44,160 --> 00:49:46,760
Speaker 1: if you will, everything, and I'm like, Oh, this guy's

981
00:49:46,760 --> 00:49:48,880
Speaker 1: giving me a test for this, and this guy's testing

982
00:49:48,960 --> 00:49:51,000
Speaker 1: me for that. And I'm like go back and kind

983
00:49:51,040 --> 00:49:52,839
Speaker 1: of like look up those testing labs and they both

984
00:49:52,920 --> 00:49:55,200
Speaker 1: have the same freaking instruments, you know what I mean.

985
00:49:55,239 --> 00:49:57,239
Speaker 1: I'm like, well, how is this possible? Well, there is

986
00:49:57,239 --> 00:49:59,279
Speaker 1: a lot of inherent variability that I was talking about.

987
00:49:59,600 --> 00:50:02,359
Speaker 1: There's a lot that can happen. But um, I guess

988
00:50:02,400 --> 00:50:05,160
Speaker 1: the context I'm referring to is, For instance, I did

989
00:50:05,200 --> 00:50:08,880
Speaker 1: an education session for Los Angeles Normal, a Veterans coalition

990
00:50:09,880 --> 00:50:13,440
Speaker 1: shout out to Normal Love Normal, um, and it was

991
00:50:13,600 --> 00:50:16,080
Speaker 1: on how to read cease because there's so many CBD

992
00:50:16,200 --> 00:50:18,480
Speaker 1: products out there that you can get out of gas station, right,

993
00:50:18,760 --> 00:50:20,759
Speaker 1: And what's the difference between buying a CBD product a

994
00:50:20,840 --> 00:50:22,960
Speaker 1: gas station versus buying one that's a lot more expensive

995
00:50:23,000 --> 00:50:25,200
Speaker 1: at a dispensary. Why would I do that? Right? The

996
00:50:25,280 --> 00:50:27,400
Speaker 1: sea as can be very different. First of all, from

997
00:50:27,400 --> 00:50:29,800
Speaker 1: a gas station, they probably don't have a sea at

998
00:50:29,840 --> 00:50:32,480
Speaker 1: all attached to it. And then secondly, if you do

999
00:50:32,560 --> 00:50:33,920
Speaker 1: look at the s of a and all it has

1000
00:50:34,000 --> 00:50:36,680
Speaker 1: is potency testing. That means that it hasn't been cleared

1001
00:50:36,719 --> 00:50:39,320
Speaker 1: for pesticides, that has been cleared for heavy metals, hasn't

1002
00:50:39,320 --> 00:50:41,439
Speaker 1: been cleared for residual solvents, which are really the health

1003
00:50:41,719 --> 00:50:44,840
Speaker 1: components that we're looking for when we do compliance testing.

1004
00:50:45,320 --> 00:50:48,120
Speaker 1: So um, I was just encouraging, you know, these veterans

1005
00:50:48,200 --> 00:50:49,840
Speaker 1: to make sure that they check their cevase to make

1006
00:50:49,880 --> 00:50:52,000
Speaker 1: sure there's more than potency data if they want to

1007
00:50:52,040 --> 00:50:54,720
Speaker 1: make sure that they're they're sourcing you know, safe medicine.

1008
00:50:55,719 --> 00:50:59,400
Speaker 1: Everybody that's buying it your children. I mean as you

1009
00:50:59,480 --> 00:51:01,640
Speaker 1: say that, I've looked at that for the stuff that

1010
00:51:01,719 --> 00:51:04,000
Speaker 1: I give my kids, right, and that what I give

1011
00:51:04,120 --> 00:51:06,880
Speaker 1: you read the stuff you give your kids exactly what

1012
00:51:07,040 --> 00:51:09,760
Speaker 1: my point is, that's what everybody should do, right, Everybody

1013
00:51:09,800 --> 00:51:14,040
Speaker 1: should look at this because in my opinion, as I

1014
00:51:14,239 --> 00:51:17,560
Speaker 1: look at the only difference between the cannabis I use

1015
00:51:17,640 --> 00:51:20,759
Speaker 1: as a kid from growing up to now and the

1016
00:51:20,880 --> 00:51:23,520
Speaker 1: oils that you're using, are those c oas because you

1017
00:51:23,600 --> 00:51:25,120
Speaker 1: can look at and what you want to look at,

1018
00:51:25,160 --> 00:51:28,520
Speaker 1: in my opinion is pesticides and oils are not oils.

1019
00:51:28,560 --> 00:51:31,320
Speaker 1: Pesticides and metals, folks, those are the heavy ones. And

1020
00:51:31,360 --> 00:51:34,640
Speaker 1: anything else that you read is extra because those are

1021
00:51:34,680 --> 00:51:36,600
Speaker 1: the difference. Why because everything we smoked growing up was

1022
00:51:36,680 --> 00:51:44,520
Speaker 1: the same ship we were smoking coming in tanks when

1023
00:51:44,600 --> 00:51:49,840
Speaker 1: we have the bricks, why with brick read? So my

1024
00:51:50,000 --> 00:51:52,320
Speaker 1: point is, as you look at this the thing that

1025
00:51:52,440 --> 00:51:54,359
Speaker 1: you want to look at our better. Yet you, as

1026
00:51:54,400 --> 00:51:57,640
Speaker 1: a scientist, what would you recommend for people that say

1027
00:51:57,760 --> 00:52:00,600
Speaker 1: this is your best report to read from the best

1028
00:52:00,680 --> 00:52:02,520
Speaker 1: stuff that you can get, Because you're right, if you're

1029
00:52:02,520 --> 00:52:05,319
Speaker 1: looking at potency only, well then you're not looking at

1030
00:52:05,400 --> 00:52:10,520
Speaker 1: medals and my opinion for the safetiest thing in my opinion,

1031
00:52:10,640 --> 00:52:12,359
Speaker 1: and I would love for you to correct me if

1032
00:52:12,400 --> 00:52:15,279
Speaker 1: I'm wrong. I would love for a scientist to say, yes,

1033
00:52:15,600 --> 00:52:18,400
Speaker 1: it's pesticides, medals and you can see turpins. But what

1034
00:52:18,520 --> 00:52:23,320
Speaker 1: are the best vidual solvents? Real solidual solvents, especially for concentrates. Okay,

1035
00:52:23,320 --> 00:52:26,160
Speaker 1: so residual solvents are really important because when you produce

1036
00:52:26,200 --> 00:52:28,480
Speaker 1: a concentrate, but most of the time you will use

1037
00:52:28,560 --> 00:52:31,480
Speaker 1: some kind of organic solvent. And I'm sure you guys

1038
00:52:31,520 --> 00:52:33,520
Speaker 1: have seen big rootov apps. That's how they get all

1039
00:52:33,600 --> 00:52:36,080
Speaker 1: that residual solvent to come off right. But if that

1040
00:52:36,239 --> 00:52:39,560
Speaker 1: isn't done completely. You can be left with some ethanol

1041
00:52:39,719 --> 00:52:42,120
Speaker 1: or some butane in there and combusting that and inhaling

1042
00:52:42,160 --> 00:52:44,239
Speaker 1: that is obviously not going to be fun. Right. Um.

1043
00:52:44,400 --> 00:52:46,840
Speaker 1: So that's a big advancement that I feel like the

1044
00:52:46,880 --> 00:52:50,440
Speaker 1: compliance testing world has brought to cannabis is because you know,

1045
00:52:50,520 --> 00:52:52,719
Speaker 1: back in the day b h O Shatter, it was

1046
00:52:52,840 --> 00:52:55,080
Speaker 1: just like, you know, your neighbor made it, and it's like,

1047
00:52:55,120 --> 00:52:58,160
Speaker 1: hopefully it's okay, I'm an dad, this at six d degrees,

1048
00:52:58,160 --> 00:53:01,120
Speaker 1: it's gonna be great. You know this house literally you know,

1049
00:53:01,400 --> 00:53:04,920
Speaker 1: they caught his whole apartment complex on fire and went

1050
00:53:05,040 --> 00:53:09,239
Speaker 1: to prison for another And now yeah, well not now

1051
00:53:09,280 --> 00:53:10,880
Speaker 1: people aren't buying it no more. I'm just saying, like,

1052
00:53:11,440 --> 00:53:14,160
Speaker 1: like what she's saying is is that where it comes from,

1053
00:53:14,280 --> 00:53:17,040
Speaker 1: where it's now we've evolved quite a bit um and

1054
00:53:17,200 --> 00:53:19,680
Speaker 1: hopefully with over the next ten years with And I

1055
00:53:19,800 --> 00:53:22,759
Speaker 1: think she might be wrong over the fact of, you know,

1056
00:53:23,080 --> 00:53:25,719
Speaker 1: in her lifetime because I say that only because we

1057
00:53:25,800 --> 00:53:30,040
Speaker 1: have you know, forty some or fifty some states already

1058
00:53:30,120 --> 00:53:32,440
Speaker 1: coming on board. But but there's other countries coming on

1059
00:53:32,520 --> 00:53:36,040
Speaker 1: boards and the other countries and she probably have a

1060
00:53:36,080 --> 00:53:38,480
Speaker 1: better scope than I do out so, but there's other

1061
00:53:38,560 --> 00:53:40,759
Speaker 1: countries that are that are that are also coming on board,

1062
00:53:40,800 --> 00:53:42,279
Speaker 1: that are you know, Mexico is going to move the

1063
00:53:42,400 --> 00:53:45,640
Speaker 1: ball very quickly. I'm very sure of um. You know,

1064
00:53:45,840 --> 00:53:47,759
Speaker 1: Israel is gonna come on board. We can have which

1065
00:53:47,880 --> 00:53:49,640
Speaker 1: we need to have a conversation. I had a brief

1066
00:53:49,680 --> 00:53:53,840
Speaker 1: conversation yesterday with um Keith Allen as they're going to Mexico.

1067
00:53:53,960 --> 00:53:55,680
Speaker 1: You know the thing. He wants to have a conversation

1068
00:53:55,680 --> 00:53:58,240
Speaker 1: because the Mexican president, He's like, oh, we gotta get cannabis,

1069
00:53:58,239 --> 00:54:00,080
Speaker 1: talk what out there with him? So you want just

1070
00:54:00,160 --> 00:54:02,440
Speaker 1: to get involved somehow, some way. So we have to

1071
00:54:02,520 --> 00:54:07,920
Speaker 1: jump on a conversations as we do with Alexandra Harris.

1072
00:54:08,960 --> 00:54:12,480
Speaker 1: It's just enjoyable to hear all your scientific vic thoughts

1073
00:54:12,640 --> 00:54:14,439
Speaker 1: in the ways you can go with this, because there's

1074
00:54:14,440 --> 00:54:16,200
Speaker 1: so many different directions. I could still start a new

1075
00:54:16,239 --> 00:54:18,879
Speaker 1: conversation and I didn't forget our other conversation. We'll talk

1076
00:54:18,880 --> 00:54:20,680
Speaker 1: about it off air. Alexander, how old are you the

1077
00:54:20,719 --> 00:54:22,759
Speaker 1: first time you tried cannabis? I know it was nine,

1078
00:54:22,840 --> 00:54:24,360
Speaker 1: But where did you get it from? I got it

1079
00:54:24,440 --> 00:54:28,520
Speaker 1: from my father, who grew my whole life. Thought it

1080
00:54:28,520 --> 00:54:30,440
Speaker 1: would be funny. We were actually in Mexico on a

1081
00:54:30,520 --> 00:54:32,880
Speaker 1: cruise and my parents had smuggled it onto the cruise

1082
00:54:32,960 --> 00:54:34,800
Speaker 1: and we had a coke can and I spoke to

1083
00:54:34,800 --> 00:54:37,800
Speaker 1: about cocaine. He said, why not? And I laughed so

1084
00:54:37,920 --> 00:54:39,680
Speaker 1: hard that when they ordered room service, they had to

1085
00:54:39,719 --> 00:54:42,440
Speaker 1: lock me in the bathroom because I was like crying laugh.

1086
00:54:46,600 --> 00:54:53,640
Speaker 1: He's a daughter's nine. I don't recommend it. Recommendation. WoT

1087
00:54:53,719 --> 00:54:55,960
Speaker 1: we say this? Let me say this back then. The

1088
00:54:56,320 --> 00:54:58,319
Speaker 1: rules were a lot different in the world, are they.

1089
00:54:58,440 --> 00:55:01,680
Speaker 1: It's legal now, you know, but it's it's just what

1090
00:55:02,480 --> 00:55:04,279
Speaker 1: my wife would never get my done. Camp. But I'm

1091
00:55:04,320 --> 00:55:09,840
Speaker 1: just saying, you release a bond, come out down to

1092
00:55:09,920 --> 00:55:12,640
Speaker 1: calm down. But I think that's a knuckle blue song

1093
00:55:12,680 --> 00:55:14,440
Speaker 1: and smoke. Yeah yeah, listen to one of my records

1094
00:55:14,480 --> 00:55:16,239
Speaker 1: and then do that. What is your favorite way to

1095
00:55:16,360 --> 00:55:24,160
Speaker 1: use or smoke cannabis cocaine? Oh yeah, I smoked by

1096
00:55:24,200 --> 00:55:28,400
Speaker 1: the way and ruined many nets on windows. It's a legit.

1097
00:55:28,440 --> 00:55:30,840
Speaker 1: If you have the paper towel roll with the what

1098
00:55:31,040 --> 00:55:33,799
Speaker 1: is it the drier sheet? Yes, yes, and you blow

1099
00:55:33,840 --> 00:55:35,640
Speaker 1: it out. Did you make a car on the side

1100
00:55:35,640 --> 00:55:39,840
Speaker 1: of the can too? So you can oh, yeah, have

1101
00:55:40,040 --> 00:55:42,800
Speaker 1: the car. But I was like, it's a stupid I

1102
00:55:42,840 --> 00:55:45,439
Speaker 1: would say. My favorite way to smoke is my Toro bong.

1103
00:55:45,560 --> 00:55:47,120
Speaker 1: Then one of my best friends gave me it's like

1104
00:55:47,120 --> 00:55:49,959
Speaker 1: a really nice designer. I'm a big bond person. Nice.

1105
00:55:50,640 --> 00:55:52,640
Speaker 1: You know what's crazy? I just I don't even know

1106
00:55:52,640 --> 00:55:53,759
Speaker 1: if I want to stay it on there, I'll stay

1107
00:55:53,760 --> 00:55:55,600
Speaker 1: it off there. I don't want to do it. You

1108
00:55:55,719 --> 00:55:57,759
Speaker 1: got something at home. I know what you showed me, right,

1109
00:55:57,760 --> 00:56:00,200
Speaker 1: you took home. No, dude, I just came with the

1110
00:56:00,200 --> 00:56:02,439
Speaker 1: whole new product. I'm just you know I do. You're

1111
00:56:02,560 --> 00:56:05,399
Speaker 1: very crazy. And he comes up with amazing things. Question

1112
00:56:05,480 --> 00:56:08,560
Speaker 1: number three of the high five Alexander, craziest place you

1113
00:56:08,680 --> 00:56:11,200
Speaker 1: ever used or smoked cannabis um And it's called the

1114
00:56:11,360 --> 00:56:15,000
Speaker 1: Tantalus Overlook and it overlooks all of Waikiki Oahu. And

1115
00:56:15,080 --> 00:56:17,160
Speaker 1: that is where I was caught with wed and which

1116
00:56:17,160 --> 00:56:20,200
Speaker 1: to court for six months. Now, you know, it's the craziest.

1117
00:56:20,840 --> 00:56:24,520
Speaker 1: A beautiful view. It's beautiful. You gotta go to Hawaii

1118
00:56:24,560 --> 00:56:26,919
Speaker 1: because I want to see her vision of it, because

1119
00:56:26,920 --> 00:56:30,040
Speaker 1: she knows the island. You know. Remember that was me

1120
00:56:30,120 --> 00:56:31,799
Speaker 1: and Romeo brought up with that when we were running.

1121
00:56:32,160 --> 00:56:35,359
Speaker 1: We did some cool spots on that see I've been there,

1122
00:56:35,440 --> 00:56:37,080
Speaker 1: but like I said, for me, it was kind of

1123
00:56:37,120 --> 00:56:39,600
Speaker 1: like and I was stuck at the resort. I went

1124
00:56:39,640 --> 00:56:41,640
Speaker 1: to a couple of little places and then it was

1125
00:56:41,719 --> 00:56:44,000
Speaker 1: just like, that's cool. You gotta go with someone that

1126
00:56:44,120 --> 00:56:45,600
Speaker 1: knows what the hell is going on, dud, because I

1127
00:56:45,719 --> 00:56:47,520
Speaker 1: was looking for and I went on to like school,

1128
00:56:47,560 --> 00:56:49,520
Speaker 1: but I paid, I just paid the cost. It was cool,

1129
00:56:49,560 --> 00:56:52,320
Speaker 1: but you gotta hit some spots on the shark diving,

1130
00:56:52,880 --> 00:56:56,359
Speaker 1: shark diving, open cage, open ocean. Yes, some saying we'll

1131
00:56:56,400 --> 00:57:00,800
Speaker 1: do some cool ship. So question number four four, No,

1132
00:57:00,920 --> 00:57:03,200
Speaker 1: you're three, three, you're four. What was your what is

1133
00:57:03,239 --> 00:57:08,200
Speaker 1: your go to munchie after you get home? Del Taco fries.

1134
00:57:08,840 --> 00:57:11,880
Speaker 1: I have a problem with Del Taco Chili cheese. No, no, no, no,

1135
00:57:13,440 --> 00:57:16,200
Speaker 1: it's not funny how Del Taco caters those people too,

1136
00:57:16,320 --> 00:57:18,480
Speaker 1: like they careter you with their commercials and everything you

1137
00:57:18,600 --> 00:57:21,400
Speaker 1: know they know and not and taco bells. We've been

1138
00:57:21,440 --> 00:57:23,000
Speaker 1: trying to reach out to this. People go back to

1139
00:57:23,080 --> 00:57:25,920
Speaker 1: her too, but they know that Stoners love their food.

1140
00:57:26,040 --> 00:57:28,160
Speaker 1: Jack in the Box is really heavy. Started what do

1141
00:57:28,240 --> 00:57:30,480
Speaker 1: you like? What do you like? From Jacko boxes. I don't. Actually,

1142
00:57:30,520 --> 00:57:33,680
Speaker 1: I'm not a big Jack in the box comcommercials. The

1143
00:57:33,800 --> 00:57:36,520
Speaker 1: nasty tacos, man, I'm straight to Del Taco every time.

1144
00:57:36,520 --> 00:57:39,320
Speaker 1: I'm a fan of delt the way I'm not. I'm

1145
00:57:39,360 --> 00:57:42,680
Speaker 1: a I'm a taco bell better no Jack in a box. Oh,

1146
00:57:43,440 --> 00:57:47,840
Speaker 1: I'm a Jacko crack. Honestly, I probably eat more Del Taco,

1147
00:57:48,040 --> 00:57:51,920
Speaker 1: but I will jump into you know, the tacos and

1148
00:57:51,960 --> 00:57:57,920
Speaker 1: their nastiest hell I get time. I'm mad that, like,

1149
00:57:57,960 --> 00:58:00,360
Speaker 1: can you put extra cheese in that taco? It's like

1150
00:58:00,440 --> 00:58:04,120
Speaker 1: the worst taco in the world. Dude, I'm gonna have

1151
00:58:04,160 --> 00:58:05,640
Speaker 1: to get one of those nasty ones right now, and

1152
00:58:05,640 --> 00:58:07,120
Speaker 1: I'm gonna go to Jack in a crack if I

1153
00:58:07,200 --> 00:58:09,880
Speaker 1: get one box down the street and the De'll Taco

1154
00:58:10,000 --> 00:58:11,840
Speaker 1: by the way, and I do like that, like the

1155
00:58:11,920 --> 00:58:14,720
Speaker 1: case a Dias Dey'll Talco way better with the green

1156
00:58:14,800 --> 00:58:16,720
Speaker 1: sau I don't know why I'm hungry for something crazy

1157
00:58:16,800 --> 00:58:18,919
Speaker 1: like that, right A fan of it, I'm not even there,

1158
00:58:20,560 --> 00:58:23,640
Speaker 1: And I think the best thing there is the the

1159
00:58:24,120 --> 00:58:28,600
Speaker 1: Dell cheeseburger. Yeah, the Double Dells. I mean they've got everything.

1160
00:58:28,640 --> 00:58:30,160
Speaker 1: We got everything you need when you're hiding. It's the

1161
00:58:30,240 --> 00:58:32,000
Speaker 1: best thing. Can you guys go meet for dinner at

1162
00:58:32,040 --> 00:58:35,000
Speaker 1: del Taco? Question number five with the high five. If

1163
00:58:35,040 --> 00:58:38,480
Speaker 1: you could smoke cannabis alex with anyone dead or alive,

1164
00:58:39,080 --> 00:58:41,720
Speaker 1: who would it be and why? And it better not

1165
00:58:41,800 --> 00:58:45,200
Speaker 1: be the owner of Delle Taco? So hard, this one's

1166
00:58:45,240 --> 00:58:48,240
Speaker 1: so hard. Like if I could get if I could

1167
00:58:48,280 --> 00:58:50,920
Speaker 1: get like a group of people from Canada, those researchers

1168
00:58:50,960 --> 00:58:53,200
Speaker 1: like Ethan Russo, maybe get the Schulem in there and

1169
00:58:53,320 --> 00:58:55,720
Speaker 1: Deddie Marie and have like a little hot box session,

1170
00:58:55,880 --> 00:58:58,320
Speaker 1: I would love that. Um I would like to be

1171
00:58:58,560 --> 00:59:01,760
Speaker 1: they're all alive so we can make that happen. Yeah,

1172
00:59:01,960 --> 00:59:04,880
Speaker 1: we can know that. Like we said, we've said this

1173
00:59:05,000 --> 00:59:10,240
Speaker 1: to people, can needs to be as big as um M. Yeah.

1174
00:59:10,880 --> 00:59:12,640
Speaker 1: And if it was as big as that, people would

1175
00:59:12,640 --> 00:59:15,440
Speaker 1: be so intrigued like we were, because it's it's that

1176
00:59:15,760 --> 00:59:17,840
Speaker 1: it's that intriguing, you know, I think it isn't and

1177
00:59:17,960 --> 00:59:20,439
Speaker 1: istant right, So there's there's two times. There's two times.

1178
00:59:20,640 --> 00:59:22,840
Speaker 1: So we're the messengers, right, So it's easier for us

1179
00:59:22,920 --> 00:59:26,800
Speaker 1: to fall in love with like all the messages. Right,

1180
00:59:27,160 --> 00:59:29,600
Speaker 1: So for us we get to see, you know, everybody

1181
00:59:29,640 --> 00:59:32,000
Speaker 1: sells pits. What they're trying to you know, their goal

1182
00:59:32,120 --> 00:59:34,800
Speaker 1: is their messages, right, So so it's as for us,

1183
00:59:35,240 --> 00:59:36,960
Speaker 1: it's gegegy for us because we're like, oh my god,

1184
00:59:37,080 --> 00:59:40,000
Speaker 1: that actually know what is going on. That's the mesa,

1185
00:59:41,040 --> 00:59:44,160
Speaker 1: that's what we're trying to push, that's what we believe in. Yeah,

1186
00:59:44,280 --> 00:59:46,800
Speaker 1: and I think there's there's uh, there's the other the

1187
00:59:47,000 --> 00:59:50,360
Speaker 1: other side that that doesn't have that business and and

1188
00:59:50,440 --> 00:59:52,360
Speaker 1: it's it's great, Like I said that we need them,

1189
00:59:52,960 --> 00:59:54,560
Speaker 1: we need them all. And I think there's more people

1190
00:59:54,640 --> 00:59:58,520
Speaker 1: trying to break into the industry versus break the code

1191
00:59:58,640 --> 01:00:00,600
Speaker 1: of how to fix people, you know what I mean.

1192
01:00:00,720 --> 01:00:02,800
Speaker 1: And that's that's where that comes when you bring together.

1193
01:00:02,880 --> 01:00:05,160
Speaker 1: There's a lot of hierarchy within research. You know, it's

1194
01:00:05,360 --> 01:00:07,880
Speaker 1: very closed off to people who aren't from academia and

1195
01:00:07,920 --> 01:00:11,120
Speaker 1: who aren't from that world. So you know, having pharmaceutical

1196
01:00:11,200 --> 01:00:13,120
Speaker 1: credits is like a big part of being able to

1197
01:00:13,200 --> 01:00:16,000
Speaker 1: be taken seriously within that whole realm. So it was

1198
01:00:16,040 --> 01:00:18,240
Speaker 1: a lot harder. Yeah, you come up there trying to

1199
01:00:18,280 --> 01:00:22,439
Speaker 1: give some some anecdotal evidence like, bro, listen, you're absolutely wrong.

1200
01:00:22,600 --> 01:00:25,080
Speaker 1: I know this for a million percent because of my

1201
01:00:25,120 --> 01:00:27,960
Speaker 1: bibology degree, and I worked with this company and that company,

1202
01:00:28,040 --> 01:00:30,800
Speaker 1: and you know it makes sense. And Johnson and Johnson,

1203
01:00:30,880 --> 01:00:32,160
Speaker 1: by the way, they were a gland of mine for

1204
01:00:32,160 --> 01:00:39,920
Speaker 1: a long time. But were they Advisor as well? Who

1205
01:00:40,040 --> 01:00:44,240
Speaker 1: just bought Marina? Who is doing connabinoid research? Advisor is looking?

1206
01:00:44,400 --> 01:00:48,000
Speaker 1: That's all I'm saying, what is those companies? Yeah? What

1207
01:00:48,360 --> 01:00:50,280
Speaker 1: is your inside on those? So I just used to

1208
01:00:50,320 --> 01:00:53,320
Speaker 1: work with researchers there to help optimize cancer and immunology

1209
01:00:53,640 --> 01:00:56,800
Speaker 1: UM experiments through I had. I was working in like

1210
01:00:56,840 --> 01:00:59,600
Speaker 1: a personalized medicine platform type company and I was there

1211
01:00:59,600 --> 01:01:03,160
Speaker 1: filled up vacation scientists. So um yeah, I mean it

1212
01:01:03,200 --> 01:01:05,360
Speaker 1: wasn't It wasn't cannabis related at all. But of course

1213
01:01:05,400 --> 01:01:07,240
Speaker 1: with my passion, I was always trying to push for it.

1214
01:01:07,280 --> 01:01:08,400
Speaker 1: I was like, Hey, what do you think about this?

1215
01:01:09,080 --> 01:01:10,400
Speaker 1: What if I just drop a little bit of this

1216
01:01:10,520 --> 01:01:14,760
Speaker 1: and then yeah the microscope? And is that what you do?

1217
01:01:14,880 --> 01:01:16,840
Speaker 1: Or you under the microscope and just putting dabs of

1218
01:01:16,920 --> 01:01:18,440
Speaker 1: this and dab of that. Is that kind of your

1219
01:01:18,520 --> 01:01:20,640
Speaker 1: research style? Are you mixing it with something or what

1220
01:01:20,800 --> 01:01:24,240
Speaker 1: is within that job? There was a lot of microscope work. Yes,

1221
01:01:24,520 --> 01:01:27,960
Speaker 1: within analytical chemistry it's all done within l c MS

1222
01:01:28,080 --> 01:01:31,520
Speaker 1: g CMS, which is like Agilant and Thermo Fisher and

1223
01:01:31,600 --> 01:01:34,200
Speaker 1: Shimadzu instruments. I'm sure you guys have seen those companies

1224
01:01:34,280 --> 01:01:37,520
Speaker 1: at the conventions. Um, that's all based on like someone

1225
01:01:37,640 --> 01:01:40,000
Speaker 1: listening that doesn't know the little glass explaining a little

1226
01:01:40,000 --> 01:01:42,360
Speaker 1: bit more for what that those are though. Um So,

1227
01:01:42,600 --> 01:01:45,680
Speaker 1: l c MUS and GCMs are chromo chromatography methods that

1228
01:01:45,800 --> 01:01:49,680
Speaker 1: are paired with mass spectrometry. So basically, you use a

1229
01:01:50,040 --> 01:01:52,200
Speaker 1: column and you run a solvent through it, and that

1230
01:01:52,320 --> 01:01:54,440
Speaker 1: solvent has the molecules that you want to look at

1231
01:01:54,600 --> 01:01:57,360
Speaker 1: dissolved in it, and as the solvent goes through the column,

1232
01:01:57,400 --> 01:02:00,680
Speaker 1: it separates based on polarity and affinity for that column,

1233
01:02:01,080 --> 01:02:05,479
Speaker 1: and then that is transcribed basically into software. I'm really

1234
01:02:05,560 --> 01:02:08,920
Speaker 1: simplizing simplifying it right now, but um yeah, they just

1235
01:02:09,080 --> 01:02:12,360
Speaker 1: look at how it's spread apart based on those properties,

1236
01:02:12,360 --> 01:02:14,680
Speaker 1: and then you can identify what molecules are in there

1237
01:02:15,120 --> 01:02:17,400
Speaker 1: um and quantify them as well. And it keeps you

1238
01:02:17,480 --> 01:02:20,800
Speaker 1: there all day. Every day never ends. Oh yeah, I've

1239
01:02:20,880 --> 01:02:23,640
Speaker 1: done yeah, way too many hours. I loves. I'm sure

1240
01:02:23,680 --> 01:02:26,640
Speaker 1: because like I said, it's just it's just it never ends.

1241
01:02:26,880 --> 01:02:29,200
Speaker 1: So if you can never find out, you can stay

1242
01:02:29,240 --> 01:02:32,680
Speaker 1: there all day every day. Yeah, well listen, is there

1243
01:02:32,680 --> 01:02:34,760
Speaker 1: anything else that that we didn't cover that you'd like

1244
01:02:34,840 --> 01:02:38,680
Speaker 1: to go over? Um? You know, I'm just I'm just

1245
01:02:38,760 --> 01:02:41,080
Speaker 1: really proud to be able to represent a company like

1246
01:02:41,160 --> 01:02:42,920
Speaker 1: to Coon, so, UM, you know, I want to I

1247
01:02:43,000 --> 01:02:44,840
Speaker 1: want to thank that that company if we're doing all

1248
01:02:44,880 --> 01:02:47,440
Speaker 1: the work that they've been doing. And um, everybody who

1249
01:02:47,640 --> 01:02:51,520
Speaker 1: does tune into my weekly education videos that I produce

1250
01:02:51,600 --> 01:02:55,240
Speaker 1: for them on Instagram, on Instagram and as well as LinkedIn.

1251
01:02:55,280 --> 01:02:56,760
Speaker 1: We've been sharing them on LinkedIn as well, such a

1252
01:02:56,840 --> 01:03:01,000
Speaker 1: cunelam USC on Instagram and just to con on LinkedIn. Um,

1253
01:03:01,240 --> 01:03:03,600
Speaker 1: so I put on a video every week with education

1254
01:03:03,640 --> 01:03:06,280
Speaker 1: about cannabis, and um, everybody that's been watching it has

1255
01:03:06,280 --> 01:03:09,080
Speaker 1: been really supportive and the community that has grown from

1256
01:03:09,120 --> 01:03:11,080
Speaker 1: it has been amazing for me. So I just want

1257
01:03:11,120 --> 01:03:13,840
Speaker 1: to thank everybody who's tuned into that. Yeah, that's awesome.

1258
01:03:13,920 --> 01:03:15,600
Speaker 1: I can't wait to see you. Well there it is, guys.

1259
01:03:15,640 --> 01:03:17,760
Speaker 1: It's Cannabis Talk one on one. And remember this, if

1260
01:03:17,840 --> 01:03:20,480
Speaker 1: no one else lives you, we knew. Thank you for

1261
01:03:20,640 --> 01:03:22,600
Speaker 1: listening to Cannabis Talk one on one on the I

1262
01:03:22,760 --> 01:03:26,760
Speaker 1: Heart Radio app, Apple podcast or wherever you get your podcasts.