Yale Psychiatry Grand Rounds: November 11, 2022

Transcript

• 00:00Thank you. Very much.
• 00:01Thanks so much for that Nice introduction.
• 00:05It's really an honor to be here.
• 00:06And I was just talking to
• 00:08some folks before the talk.
• 00:09I've known folks from Yale
• 00:11since I was a graduate student,
• 00:13and I've always admired them.
• 00:14So it's nice to be here giving my own talk.
• 00:17So I'm going to cover a lot today.
• 00:21I just to give you an outline
• 00:22of what I'd like to talk about.
• 00:24I'd like to talk about some background
• 00:26about cannabis and the brain and how
• 00:29the landscape of cannabis and cannabis
• 00:31itself is changing and just rapidly changing.
• 00:33The product types, the the the,
• 00:36the characteristics of people
• 00:37using it are are,
• 00:38are dramatically changing.
• 00:39Then I'd like to talk about some of
• 00:42my work on cannabis and cognition and
• 00:44adolescent adolescents and young adults
• 00:46and talk about a super cool clinical
• 00:48trial that we did with adolescence.
• 00:51Then I'd like to talk about.
• 00:52Umm.
• 00:53The medicinal aspects of cannabis,
• 00:56which a lot of my work focuses on now
• 00:59because it's just such a hot topic right
• 01:01now about whether cannabis is a medicine,
• 01:04how it can be conceptualized as a medicine,
• 01:06does it work as a medicine?
• 01:08And then finally,
• 01:09I want to talk about some of my
• 01:12acute THC administration paradigms
• 01:15where we're looking at the problem
• 01:17of cannabis impaired driving and
• 01:19whether we can detect cannabis
• 01:20impairment from brain imaging.
• 01:22So it's sort of a.
• 01:24A lot to cover, so I'll get right into it.
• 01:27So what is cannabis?
• 01:29So, so cannabis is simply a plant.
• 01:32It is a dry shredded mix of leaves,
• 01:35flower stems and seeds from the
• 01:37cannabis sativa or indica plant.
• 01:39These are common subspecies of the hemp
• 01:40plant which is common throughout the world.
• 01:42And cannabis contains over
• 01:44400 chemical compounds.
• 01:46So when we talk about cannabis and
• 01:48cannabis derived products and the
• 01:50landscape of cannabis products
• 01:51in the United States,
• 01:52I think it's important to keep in mind.
• 01:55Sort of that that this is all basically
• 01:58originating from this hemp plant.
• 02:00Cannabis is the most commonly used quote
• 02:04illicit drug in the United States.
• 02:07You have to put quotes around
• 02:08it because as we all know,
• 02:10the legality of cannabis is
• 02:12constantly changing.
• 02:13I think in the election this week
• 02:15two more states legalized cannabis,
• 02:18so I have this map.
• 02:20I have to update it about every 10
• 02:22minutes about sort of the legal
• 02:23landscape throughout the United States.
• 02:25But the point of this is that
• 02:27cannabis use is, is,
• 02:28is incredibly common over 100.
• 02:30Million Americans have tried cannabis.
• 02:34And millions more people use it
• 02:35for the first time every year.
• 02:37And this is this is increasing dramatically.
• 02:40And a lot of the reasons for its
• 02:42increase has to do with sort of
• 02:44societal tolerance of cannabis that's
• 02:45really increased in the past decade.
• 02:51OK. So how does cannabis affect the brain?
• 02:55So when cannabis is smoked,
• 02:58THC, which is the the main
• 03:00psychoactive compound in cannabis,
• 03:01passes from the lungs into the bloodstream.
• 03:04Bloodstream carries the chemical to the
• 03:06brain and other organs throughout the body.
• 03:08When cannabis is orally ingested,
• 03:11it's absorbed more slowly,
• 03:12so it takes more time to reach the brain.
• 03:14But basically,
• 03:15THC acts on molecular targets and brain
• 03:18cells called cannabinoid receptors.
• 03:21These are these are endogenous receptors
• 03:25that are ordinarily activated by natural
• 03:28chemicals that are very similar to THC.
• 03:31And the one I have here is called
• 03:33anandamide that are part of a
• 03:35neural communication network that is
• 03:36called the endocannabinoid system.
• 03:38And this is an incredibly important
• 03:40system in and plays a role in normal
• 03:43brain development and function.
• 03:44So what happens is that THC's
• 03:46chemical structure is quite similar
• 03:48to anandamide and that is how
• 03:50it is recognized by the brain.
• 03:52And it can alter normal brain communication.
• 03:55So the endocannabinoid system is
• 03:57often thought of as the neurons
• 04:00volume control system.
• 04:02It dials down activity when
• 04:03neuronal activity is too strong,
• 04:05and it regulates neurotransmitters that
• 04:07affect things like pleasure and mood
• 04:09and appetite and motivation and memory.
• 04:11So a wide variety of of functions are
• 04:15affected by the endocannabinoid system.
• 04:18The endocannabinoid system is also
• 04:20incredibly important in brain development.
• 04:22It guides neurons to grow in the right place.
• 04:25It controls neuronal activity.
• 04:26We say neurons that that fire
• 04:29together wire together.
• 04:30So it it plays a role in making
• 04:32sure these neurons reach the the
• 04:33correct targets and destinations.
• 04:35And it supports myelin growth on neurons.
• 04:37So again,
• 04:38it's an incredibly important
• 04:40system in the brain.
• 04:41So thinking about THC versus anandamide,
• 04:43they have a very similar chemical
• 04:45structure and both dial down
• 04:47neuronal activity and change.
• 04:48Neurotransmitter release.
• 04:49But THC has this much stronger and
• 04:53longer effect compared to an end of mind.
• 04:55And what it does is it interferes
• 04:57with an and amide functions.
• 04:59So you have this distribution of THC
• 05:02binding sites throughout the brain.
• 05:04Whoops.
• 05:05Sorry.
• 05:06And throughout the prefrontal cortex,
• 05:09throughout somatosensory cortex, cortex,
• 05:11the cerebellum, thalamus, hippocampus,
• 05:13basically throughout the brain.
• 05:16And because the the binding sites are
• 05:20very dispersed throughout the brain,
• 05:23the functions that it affects
• 05:25our quite dispersed.
• 05:26So THC will affect everything from
• 05:30motor control to memory to anxiety,
• 05:33emotion, fear and it has some.
• 05:36Really important implications for
• 05:38pain processing and other functions
• 05:42underlying these brain regions.
• 05:45So let's talk about cannabis, the product.
• 05:48So cannabis from basically the
• 05:50beginning of time, this is you know,
• 05:53pictures from the 1960 to 2000s,
• 05:54canvas was this plant that
• 05:56I talked about before.
• 05:57People would smoke it in a joint,
• 05:59people would sometimes vape it,
• 06:01but it's THC content was quite low.
• 06:03So 1 to 3% was was fairly common
• 06:06for the amount of THC in cannabis
• 06:08that was used on the street.
• 06:12What's happened lately and this is really
• 06:15been in the past decade is that THC
• 06:17potency has has gone up dramatically.
• 06:19This has happened in plant based
• 06:21THC and they're they've done some
• 06:23studies looking at police seizures
• 06:24of THC and they've of cannabis and
• 06:27they've measured THC concentration.
• 06:28So even the the plant based cannabis
• 06:31growers have worked to make it more potent.
• 06:33But now even in addition to that
• 06:35we have all these new products,
• 06:38these derivatives which contain up
• 06:40to 98% THC. So you have hash oil.
• 06:42Shatter, butter,
• 06:44wax and these are incredibly potent products.
• 06:49You have novel forms of THC delivery
• 06:52such as you can put THC oil in
• 06:54a jewel pod and this is use is
• 06:56very difficult to detect.
• 06:58So something that we have seen in
• 07:00our adolescent studies is that.
• 07:03People's kids will use this
• 07:04in school all day long.
• 07:05They'll put this, this jewel pod under their
• 07:07shirt and they can just use it all day.
• 07:09So it wasn't like, you know,
• 07:10when I was in high school,
• 07:11of course kids used pot,
• 07:12but you had to sneak out.
• 07:13You had to sneak out to the corner
• 07:15or the bathroom or something.
• 07:16Now they can basically do
• 07:17this in class all day.
• 07:19And you have kids who are high.
• 07:20There's no odor.
• 07:22You can't,
• 07:23there's no smoke that's emitted.
• 07:26And oftentimes the kids don't
• 07:28get the bloodshot eyes,
• 07:29so you would just have no idea.
• 07:32This is to say nothing of the new
• 07:35market of edibles that is now prevalent.
• 07:38There are edibles,
• 07:39particularly in states with legal cannabis.
• 07:42These shops are everywhere.
• 07:43I was just in Portland last week and I was
• 07:46trying to get a cup of coffee and all I,
• 07:48you know,
• 07:48I couldn't even find a coffee
• 07:50shop shop because there were all
• 07:52these recreational pot shops and
• 07:53this was just in the windows.
• 07:54Just every, every edible you could think of.
• 07:57These products simply didn't
• 07:58exist 10 years ago.
• 07:59This is a product of of commercial.
• 08:02Location of cannabis.
• 08:04Now you know manufacturers are
• 08:06working to to sort of create this
• 08:08emerging commercial market of
• 08:10products and a lot of them are
• 08:12appealing to children because you
• 08:14know a lot of adults don't eat pop
• 08:16tarts and fruit loops and things like that,
• 08:18but kids do and then instead
• 08:20of your pop tarts you have pop
• 08:22tarts and things like that.
• 08:23So this we've seen increases in ER visits
• 08:26of kids getting a hold of these products.
• 08:29This is not uncommon and these
• 08:32products again are are are.
• 08:34Super potent, a lot of them.
• 08:36You know, a cookie will be,
• 08:37you know, 10 servings of THC.
• 08:40But who eats 1/10 of a cookie?
• 08:41Nobody eats 1/10 of a cookie.
• 08:42So oftentimes people do have negative
• 08:45side effects from these edibles
• 08:46because they're just not used to it.
• 08:51So we know that. That the brain is
• 08:55developing throughout adolescence.
• 08:57This is very well known and this is research
• 08:59that that's now you know 30 years old.
• 09:01We know that the brain has developmental
• 09:04changes into the third decade of life
• 09:06and we know that these changes take
• 09:08place you know in multi domain changes
• 09:10in connectivity and brain chemistry,
• 09:12in in brain morphology and the prefrontal
• 09:15cortex which is up here is the last
• 09:18to develop and that's part of the
• 09:21theories of adolescent development
• 09:22is that this prefrontal cortex.
• 09:24Develops later,
• 09:25and that's why teenagers are often,
• 09:29often make risky decisions,
• 09:31more so than than adults do.
• 09:33But the other thing about the
• 09:35prefrontal cortex is it's densely
• 09:36populated with cannabinoid receptors.
• 09:38So these prefrontal regions
• 09:40critically underlie higher order
• 09:42cognitive decision making.
• 09:43And they're also densely populated
• 09:46with cannabinoid receptors.
• 09:47And that means that adolescent cannabis
• 09:51use is particularly detrimental.
• 09:53So I'm going to there's been,
• 09:55you know,
• 09:55tons and tons of of studies showing
• 09:57that animal studies and to human
• 09:59studies showing that effects
• 10:01of cannabis are just worse in
• 10:02teenagers than they are in adults.
• 10:04And there's a lot of controversy
• 10:06in the cannabis field.
• 10:08But I would say that that's one of the
• 10:10least controversial statements I can make,
• 10:12that that cannabis is worse
• 10:15for kids than adults.
• 10:17And this is just a study that I
• 10:19did a few years ago now where
• 10:21we brought people into the lab.
• 10:23For all cannabis users.
• 10:24And we gave them a memory task and it
• 10:27was called the CVLT California verbal test.
• 10:29And we let we read them a list of words
• 10:32and they had to recall them back to us.
• 10:34And this is just the number
• 10:36of words recalled.
• 10:37And then you read them the list again
• 10:38and they read it back to you again and
• 10:40then you do it again for five trials.
• 10:42So what we did was everyone,
• 10:43these were college students,
• 10:44so they were all ages 21 to 25
• 10:47and some of them had started using
• 10:49cannabis before the age of 16.
• 10:50Some of them had been using,
• 10:52started using cannabis.
• 10:53After the age of 18,
• 10:54so we had these early onset users
• 10:57and these later onset users and
• 11:00what we found was that.
• 11:01Learning improved in both groups,
• 11:04all three groups actually.
• 11:05We had a control group also.
• 11:06So learning improved over time,
• 11:08which you would expect.
• 11:10The slopes were absolutely identical.
• 11:12The rate of learning was identical
• 11:14but these early onset users which
• 11:17are shown in the red.
• 11:18Had trouble with encoding.
• 11:20They had trouble with initial learning,
• 11:22they just didn't learn the
• 11:24information as efficiently.
• 11:25So these weren't even
• 11:26really memory differences.
• 11:28So this is trial 5,
• 11:29and then there's a delay and they call they.
• 11:31They basically you do something
• 11:32else with them and then you ask
• 11:34them to recall the words again.
• 11:35And what we found is that they
• 11:37remembered everything they learned
• 11:39the same as the controls of
• 11:40the late onset
• 11:41users, but they just never
• 11:42learned it in the 1st place.
• 11:44And that was really the first
• 11:45demonstration that I know of
• 11:47of really parsing the learning.
• 11:49Process and understanding that it
• 11:51was the initial encoding that was
• 11:54really affected by the cannabis
• 11:55and this was cross-sectional.
• 11:57So there's caveats to this
• 11:59study showing that.
• 12:00You know, you can say that
• 12:02maybe these people had poorer
• 12:03memory being begin with,
• 12:05but I thought this was a powerful
• 12:07illustration that that the age of onset is,
• 12:10is quite important and this is
• 12:12specific to encoding strategies.
• 12:16We find that this is even worse in
• 12:18people with psychiatric diagnosis and
• 12:20this has also been shown a few times
• 12:23and this was a study where we looked at
• 12:25people with depression and cannabis use.
• 12:29So again this is the same test
• 12:30and this is total number of words
• 12:33recalled across all trials.
• 12:35So you see the control participants
• 12:37did the best and then the cannabis
• 12:40users had a significant decrease.
• 12:42The the participants with depression
• 12:44had even more of a decrease and
• 12:48they participants with both
• 12:50depression and cannabis use showed
• 12:53the worst decrements in learning.
• 12:55And if you look at the memory component,
• 12:58so this is the learning component,
• 13:00this is the memory component component,
• 13:01the free recall after delay and you can do
• 13:04this with a short delay or a long delay,
• 13:06then you really see this.
• 13:07You really see this additive effect of of
• 13:10depression and cannabis use we also saw.
• 13:13To break brain imaging on all
• 13:15these people and we also saw not
• 13:17only did their performance suffer,
• 13:18but they had reduced cortical thickness
• 13:20in the middle middle temporal gyrus,
• 13:22which is also important in memory
• 13:24in this group.
• 13:28So something that comes up quite
• 13:29often is the question of whether
• 13:32cognitive deficits are reversible.
• 13:33So we we've shown that that you know,
• 13:36when when people are acutely
• 13:38intoxicated from cannabis,
• 13:40they have memory weaknesses.
• 13:41And we've shown that chronic
• 13:43users have memory weaknesses.
• 13:45But these are all people who
• 13:46are still using cannabis.
• 13:47What happens if people stop using cannabis?
• 13:52So we did a trial, and this was led
• 13:54by my colleague Randy Schuster.
• 13:57Where we use something called contingency
• 14:00management to pay kids to stop using
• 14:03cannabis for a specific period of time.
• 14:05Contingency management is is widely
• 14:07used in the substance use field.
• 14:10And basically it's it's what it's it
• 14:12sounds like you pay people for negative
• 14:15drug screens and you have escalating
• 14:17payments over time so that they're
• 14:19invested in in stopping use, you know,
• 14:22for longer periods of time because
• 14:24they keep making more and more money.
• 14:25The reason why we we we chose to
• 14:27do this contingency management
• 14:29study is that you cannot randomize
• 14:31kids to use or not use cannabis.
• 14:34That's unethical,
• 14:34but it was not considered unethical
• 14:37to pay some kids for stopping.
• 14:39So what we did was we did this,
• 14:40this randomized trial where
• 14:41we paid some kids to stop.
• 14:44Other kids, we did not pay to stop.
• 14:45They were called a monitoring condition.
• 14:47We said you can stop if you'd like,
• 14:48but we're not going to pay you to do so.
• 14:50And you can imagine how many stopped.
• 14:52And we looked at changes in
• 14:56cognition with abstinence.
• 14:58So these were high school
• 14:59and college students.
• 15:00They used cannabis weekly or more.
• 15:02They were not seeking treatment.
• 15:03And as I mentioned after baseline,
• 15:07the kids who are abstained to cannabis
• 15:09were asked to stop using cannabis for
• 15:11a month and there was urine samples
• 15:13to verify this and those assigned to
• 15:15monitoring were not asked to change
• 15:18their patterns of cannabis use.
• 15:20And we we assess cognition with
• 15:22the cantab battery and and and
• 15:24the two domains we were interested
• 15:26were attention and memory.
• 15:27So we had a series of of cognitive
• 15:30tasks in each of these domains.
• 15:33OK.
• 15:33So.
• 15:34The first thing we found was that
• 15:37kids will abstain for money.
• 15:39So this study worked beautifully.
• 15:41So this is the group that was randomized
• 15:44to CM and this is their carboxy THC levels.
• 15:47And you could see they just plummeted and
• 15:50stayed really low throughout the study.
• 15:52I think we had something like
• 15:54a 90% abstinence rate.
• 15:55And then this was the group that
• 15:56continued to use and of course there
• 15:58was a lot more variation in their
• 16:00carboxyl levels because we had, you know,
• 16:02kids with different use patterns,
• 16:03but the randomization worked quite well.
• 16:07And this is what we found.
• 16:09So for attention, they improved over time.
• 16:12They're given the same tests
• 16:14throughout four weeks.
• 16:15So as you can imagine,
• 16:16there's learning that occurs.
• 16:19So attention,
• 16:20you saw no difference between the kids
• 16:21who stopped and the kids who continued.
• 16:23But something really interesting
• 16:25happened with memory.
• 16:26So the kids, this is a monitoring group.
• 16:28This is the kids who didn't
• 16:30change their cannabis use.
• 16:31They just didn't improve
• 16:32from week zero to week four.
• 16:35We're giving them the same test four times.
• 16:36They showed no improvement.
• 16:38The kids who were abstinent showed
• 16:41dramatic improvement in week one,
• 16:43and then they sort of.
• 16:45Stayed the same.
• 16:47So a week of abstinence was enough
• 16:50to really improve the amount
• 16:52that they that they learned,
• 16:54which was quite interesting because
• 16:55you think about kids who, you know,
• 16:57smoke pot on the weekends and then
• 16:59they go to school on the weekdays
• 17:00and there are not learning as well,
• 17:02is what this study indicates.
• 17:04So what we found in this study
• 17:06is that memory improved among
• 17:08adolescents who abstained,
• 17:10but not among those who continue to use.
• 17:12We didn't see this for attention.
• 17:13So this really seems specific
• 17:15to learning and memory.
• 17:16Um, this finding is consistent
• 17:18with other studies that show that
• 17:20neurocognitive dysfunction persists
• 17:21after several days of abstinence.
• 17:23And the improvement occurred within
• 17:26one week of continuous abstinence,
• 17:28which was super interesting.
• 17:29So we thought that this study provides
• 17:31evidence that adolescents and young
• 17:33adults may experience improvements in
• 17:35their ability to learn information
• 17:36when they stop using cannabis,
• 17:38which has a lot of implications for,
• 17:41you know,
• 17:41for for adolescent cannabis use,
• 17:43which we know is increasing steadily,
• 17:45particularly among 12th graders.
• 17:46And I think I'm going to show you that data.
• 17:51So now I'd like to change gears
• 17:54and talk a little bit about.
• 17:56Cannabis is a medicine.
• 17:58So is cannabis and medicine right?
• 18:01Is there anything to this?
• 18:03So my answer to this is it's not simple.
• 18:06So cannabis is a medicine for some
• 18:10and there have been components of
• 18:12cannabis that have been FDA approved
• 18:15for different medicinal purposes.
• 18:17So Epidiolex is,
• 18:18is a CBD medication that's FDA approved
• 18:20for children and adults with epilepsy
• 18:23and we're studying that in one of our
• 18:25trials now journal is a synthetic THC.
• 18:28That's approved for AIDS
• 18:30patients with severe weight loss.
• 18:31But the thing to keep in mind is for
• 18:34all other indications other than
• 18:36the epilepsy for Epidiolex and the
• 18:39severe weight loss for dronabinol,
• 18:42there are too few studies and
• 18:44poor data quality to really know.
• 18:48And I think effective regulation
• 18:49using a public health framework
• 18:51is really key to mitigating risk.
• 18:52And people ask me sometimes,
• 18:54well are you for or against legalization?
• 18:56And I say, well it's not that simple.
• 18:58It's it's.
• 18:59You know, it's it's how are you?
• 19:00How are you legalizing?
• 19:03I think, you know,
• 19:04at the Center for Addiction Medicine,
• 19:06we we believe in treatment, not punishment.
• 19:07Nobody needs to go to jail,
• 19:09but there is a way to regulate safely,
• 19:13and I'm going to talk about that a
• 19:15little bit in the next few minutes.
• 19:17So medical cannabis products from
• 19:19dispensaries are not FDA approved.
• 19:22And FDA approval is important.
• 19:24It assures that medicines are effective
• 19:26and safe and properly labeled.
• 19:28The FDA can't really evaluate medical
• 19:30cannabis as a drug since it's a plant,
• 19:32it's not a standardized medical
• 19:34formulation and it's quite different
• 19:35depending on how it's bred,
• 19:37the conditions that it's grown
• 19:39and a million other variables.
• 19:41So when we say medical cannabis,
• 19:42we're not talking about one drug,
• 19:44we're talking about you know, this, this.
• 19:47Wide variety of of dispensary products.
• 19:51Umm.
• 19:51Commercial cannabis that you buy
• 19:53at dispensaries just has not been
• 19:55tested to medicinal standards.
• 19:57I don't think that's a
• 19:58controversial statement,
• 19:58I think everyone would agree with that.
• 20:01The gold standard in medicine are these
• 20:03double-blind placebo-controlled trials and
• 20:05few exist for these cannabis products.
• 20:07And clinical trials unfortunately
• 20:10have been quite mixed,
• 20:12particularly for chronic pain which
• 20:14is the indication that people use
• 20:17medical cannabis for most frequently.
• 20:19There have been a lot of systematic
• 20:21reviews and meta analysis.
• 20:22And and the the evidence just isn't strong.
• 20:26Some find small effects,
• 20:27some find no effect,
• 20:28so it's really up in the air.
• 20:31So I'd like to talk to you about a
• 20:34clinical trial that we conducted
• 20:35in my lab of medical marijuana.
• 20:37And this was, this was my first R1.
• 20:40It was an RCT of medical
• 20:42marijuana card holders.
• 20:43And what we did was we wanted to
• 20:45test the products that people
• 20:46were using in the real world.
• 20:48So we randomized people to either an
• 20:51active study group and and we told them
• 20:54to go out and get a medical cannabis card.
• 20:57We didn't provide the cards for them,
• 20:59but we said go out and get a card.
• 21:01Here are some resources and the other
• 21:03group agreed to be in a weightless
• 21:05control and we said will you wait
• 21:07three months before getting a medical
• 21:09cannabis card and they had to agree to
• 21:11wait before randomization and then we
• 21:13would randomize them to the two groups.
• 21:16So we had a baseline of two week
• 21:17or one month and a three month
• 21:20visit during the randomized phase
• 21:21and then after the three months
• 21:23they could do whatever they want.
• 21:25Because I didn't think about 12
• 21:27month wave was controls feasible
• 21:28even though we were interested in,
• 21:30you know the the.
• 21:32The development of of cannabis
• 21:35use over a year and everybody was
• 21:37followed up at 6 and 12 months.
• 21:40So the patients were between
• 21:4218 and 55 years old.
• 21:43They were seeking medical
• 21:44marijuana cards for pain,
• 21:45insomnia or or depression and anxiety.
• 21:48The reason we chose those conditions was
• 21:50those are the most common conditions
• 21:51that people seek medical cannabis for,
• 21:53and they're often comorbid.
• 21:56And we also did brain imaging
• 21:57at baseline and at 12 months.
• 22:02So the interesting thing about this
• 22:04trial is our exclusion criteria was
• 22:05daily cannabis use because we didn't
• 22:07want people who were using already.
• 22:09We wanted people were interested
• 22:10in using and cannabis use disorder
• 22:12or at screening or baseline.
• 22:14Also things like current psychosis
• 22:16and other substance use disorders.
• 22:17The patients were responsible for
• 22:19arranging for and paying for the cost of
• 22:22obtaining their cards and their products.
• 22:24We didn't provide the products,
• 22:25we didn't pay for the products,
• 22:26but we paid them for their
• 22:28for their participation.
• 22:30Our outcome measures.
• 22:33Where cannabis use disorder and then
• 22:35the changes in the symptoms that they
• 22:37were seeking the medical marijuana for.
• 22:39So depression, anxiety, pain and sleep.
• 22:43This is our concert diagram.
• 22:45So the the the reason I'm showing
• 22:46this the most interesting thing here,
• 22:48we randomized 2 to one to the
• 22:49cannabis card or the control group,
• 22:51because this is the group
• 22:54we really cared about more.
• 22:56And about 50 of them didn't even end
• 22:58up getting a medical marijuana card.
• 23:00So they were interested in the study.
• 23:01They passed the screen, they got
• 23:03randomized and they changed their minds.
• 23:05And a lot of that had to do with
• 23:06the process for getting the card.
• 23:08A lot of the cannabis doctors
• 23:11were really sketchy.
• 23:12We can talk about that in the Q&A.
• 23:15I can, I can write a book on some of
• 23:16the stories I heard and a lot of people
• 23:18were quite turned off to the system.
• 23:20But in the end we had 100,
• 23:23we had about 100 in the medical cannabis
• 23:26group and about 75 in the wait list
• 23:28control group that we could compare.
• 23:31We also did an analysis of
• 23:33their urine because, again,
• 23:35we're not giving the cannabis.
• 23:37We don't know what's in it.
• 23:38So we sent off their Urnes to a lab
• 23:40in Colorado and we got measures
• 23:42of THC and the metabolites of THC
• 23:45and CBD and other cannabinoids,
• 23:46which was kind of Nice.
• 23:49OK.
• 23:50So the first thing we found was
• 23:52that the randomization worked.
• 23:55The group that got the card increased
• 23:58their use basically right away to
• 24:00about three to four days per week.
• 24:03We had some daily users,
• 24:05we had some people who used less,
• 24:06and the delayed acquisition group was
• 24:08basically from less than once a week to,
• 24:11you know,
• 24:11less than once or twice a month.
• 24:14We did not tell them they
• 24:16couldn't use cannabis,
• 24:18but we said please don't get a card because.
• 24:20A lot of these people were were very
• 24:23light cannabis users in the beginning
• 24:25of the study and then we didn't want
• 24:27to introduce another intervention.
• 24:28We thought,
• 24:29oh should we do CM and pay them not to use.
• 24:31But it got too complicated.
• 24:32But as you can see there is a
• 24:35nice separation and use patterns.
• 24:37OK,
• 24:37so the biggest finding from this
• 24:40trial was that people in the
• 24:42medical marijuana card group
• 24:44developed cannabis use disorder.
• 24:46So again,
• 24:47cannabis use disorder was
• 24:49exclusionary at baseline.
• 24:51And what we saw was that in the 12 weeks,
• 24:54there was almost 20% of
• 24:57people who developed CVD,
• 24:59particularly in the depression
• 25:00and Anxiety group,
• 25:02in the pain and insomnia group,
• 25:03very little CD,
• 25:04not any different than the
• 25:06weightless control group.
• 25:07Um, but the pain,
• 25:08the Depression anxiety group.
• 25:09We saw this increase in
• 25:11cannabis use disorder symptoms.
• 25:13Now I will say most of it was mild.
• 25:15Most of it was was.
• 25:16I mean you need two or more symptoms of
• 25:18of cannabis use disorder for diagnosis.
• 25:21And people have asked me,
• 25:22well,
• 25:23you know,
• 25:23are these appropriate this is UD scale
• 25:26appropriate for medical cannabis users.
• 25:28And I think there's there
• 25:29there are things that we
• 25:31could do better in assessing
• 25:32cannabis use disorder.
• 25:33But people were developing tolerance.
• 25:37They were using despite negative consequences
• 25:39they were using in risky situations,
• 25:42which I'll talk about a
• 25:43little bit in a few minutes.
• 25:44So we definitely did see people were
• 25:48developing some problematic use.
• 25:50What about symptoms?
• 25:51So we found no effect of medical cannabis
• 25:55compared to the way it was control on pain,
• 25:58on depression or anxiety.
• 26:01There was just nothing.
• 26:03We found worsening OCD symptoms,
• 26:05which I just told you in
• 26:07the medical cannabis group,
• 26:08and we saw improvement in insomnia symptoms.
• 26:11So it helped people sleep better and
• 26:13that was a pretty robust finding,
• 26:15a large effect size,
• 26:16but no effect on pain or depression
• 26:18or anxiety, which was.
• 26:20Um, surprising to some people?
• 26:24We also saw no effect on cognition.
• 26:26So we did this nice cognitive battery
• 26:28throughout the trial and we saw
• 26:30that cognition didn't change in the
• 26:32medical marijuana group group versus
• 26:34the way it was controlled group.
• 26:37And we also saw no significant brain changes.
• 26:39So this was an end back task that we did.
• 26:41This was a 2 back versus 0 back
• 26:44condition at baseline and this is at
• 26:45one year in the Medical cannabis group.
• 26:48And there were no significant differences,
• 26:49which is really good news and not
• 26:51surprising because a lot of the
• 26:53brain changes that we've seen with
• 26:54cannabis have been in adolescence.
• 26:56So these were generally older adults
• 26:59and these were generally people who
• 27:03weren't using heavily somewhere,
• 27:05but we didn't, we didn't see changes
• 27:07in cognition or the brain.
• 27:09After one year of use in in these patients.
• 27:13We also looked at patterns
• 27:15of use post randomization,
• 27:17so this is month 4 to 12.
• 27:18And we did a trajectory analysis where
• 27:21we looked at sort of their naturalistic
• 27:23patterns of use and we found that
• 27:25most people were pretty stable.
• 27:27So this is our low use category,
• 27:31this is our moderate use category,
• 27:33this is our high use category.
• 27:35And most of the participants
• 27:36were in one of these three.
• 27:38And then we had two smaller groups that
• 27:40either went from low to high or high to low.
• 27:43But most people were pretty stable.
• 27:45Which is important to know.
• 27:48But what we found was that, and I'm sorry,
• 27:51these categories are not very descriptive,
• 27:54but this is our low stable use category and
• 27:57this is CD diagnosis and it was quite low.
• 28:00And as the patterns emerge
• 28:02emerged for more cannabis use,
• 28:04you had greater CD likelihood,
• 28:07which is not surprising,
• 28:08but it was an interesting
• 28:10proof of concept that you know,
• 28:11medical cannabis users can
• 28:14develop CD people thought,
• 28:16you know, well,
• 28:17they're not using to get high.
• 28:19They're using because you know,
• 28:20they have pain.
• 28:21They're not going to develop CD and
• 28:22we've shown that some people do.
• 28:25Also, I'm just going to read
• 28:27this to you because this was
• 28:28something that really struck me.
• 28:30This is what a patient said.
• 28:32I was taking what I thought was CBD oil and
• 28:34apparently it wasn't what I thought it was.
• 28:36I started feeling the effects when I
• 28:37was driving, which was really scary.
• 28:39I got home as quickly as I could.
• 28:41I felt so high I didn't know where I
• 28:43was and could have focused and the only
• 28:45way I got home was the noises from GPS.
• 28:48I was paranoid that I might
• 28:49have hit someone or something,
• 28:51but I checked my car and there was no damage.
• 28:53So I call this the downside
• 28:55of poor regulation. So.
• 28:57These products are not very well regulated.
• 29:00So this person was not an
• 29:02experienced cannabis user.
• 29:03They thought they were taking CBD
• 29:06and obviously it had THC in it.
• 29:08They took it before going somewhere
• 29:10and it they they could have,
• 29:12they could have really injured
• 29:14themselves or somebody else.
• 29:15So I think it's,
• 29:16it's just going forward and thinking
• 29:18about how we deal with this new
• 29:20system of medical cannabis products.
• 29:22I think you know education and proper
• 29:24labeling is just critically important.
• 29:29So from this trial, what we found
• 29:31was that medical marijuana cards were
• 29:33associated with developing CD symptoms
• 29:34and no significant improvement in pain,
• 29:37anxiety or depression.
• 29:38So you think about risk reward.
• 29:40And people talk to me a lot about, well,
• 29:43isn't cannabis better than opioids?
• 29:45Well, yes, of course nobody's
• 29:47dying from cannabis.
• 29:48People are dying from from opioids,
• 29:50from overdoses.
• 29:51But even though it has to have a benefit too.
• 29:55So what we found here is that it really
• 29:57didn't have any benefit on pain and.
• 29:59And and you know the effect of
• 30:01cannabis on opioid reduction is a
• 30:02really hot topic right now and I
• 30:04have another grant to assess that
• 30:06and it really remains to be seen.
• 30:09We did see that the medical marijuana
• 30:10cards were associated with improved,
• 30:12improved sleep quality in the short term.
• 30:15And the nice thing about this trial,
• 30:17the reassuring thing was that there
• 30:18were no adverse events related
• 30:20to psychotic symptoms.
• 30:21Mania, hypomania,
• 30:22suicidal ideation didn't differ
• 30:24between the groups.
• 30:25So that was all reassuring.
• 30:28And I think the results warrant
• 30:30further investigation of benefits
• 30:32of cannabis for insomnia and also
• 30:35understanding the risk for CVD.
• 30:40OK. So in the last 10 or 15 minutes,
• 30:44I want to talk to you about
• 30:46something a little bit separate,
• 30:48but I think we'll be interesting
• 30:49to some people here who are
• 30:51working on similar projects,
• 30:52looking at THC impairment using
• 30:55functional brain imaging.
• 30:57I know there's some people here,
• 30:59Godfrey Pearlson and and Cyril Disa who
• 31:01are doing work very similar to this,
• 31:03so I wanted to include this so.
• 31:06Driving while high is not good.
• 31:09Despite what anyone will tell you,
• 31:11cannabis does not make you a better driver.
• 31:14I have heard this in talks,
• 31:16it is just not true.
• 31:17But the true rate crash risk of
• 31:19THC is actually quite challenging.
• 31:22We know that cannabis impairs
• 31:24psychomotor skills, divided attention,
• 31:26lane tracking, things like that.
• 31:28But the epidemiological literature
• 31:30is really quite divided and
• 31:32knits this crash risk study.
• 31:34They found the unadjusted odds
• 31:35ratio for THC in.
• 31:37In crashes was 1.25,
• 31:38which is a 25% increase.
• 31:40But when they adjusted this
• 31:42for other demographics,
• 31:44they did not find an effect.
• 31:45And a lot of the epidemiological
• 31:48research is similarly mixed.
• 31:50I would like to argue that part of the
• 31:53reason why the the literature is mixed is
• 31:55we're not getting people at the right time,
• 31:57we're we're measuring carboxy THC,
• 31:59which I'm going to talk about in a minute,
• 32:01sticks around for quite some time.
• 32:03So if you measure somebody in an
• 32:06accident and you look at carboxy THC.
• 32:09You know,
• 32:09they're,
• 32:10they're that doesn't mean they were
• 32:12high when they when they crashed.
• 32:14So US state THC driving impairment laws are,
• 32:18excuse the pun all over the map.
• 32:21So some states have 0 tolerance,
• 32:23so if you have any THC you're
• 32:25considered to be THC impaired.
• 32:28Some states have THC per se laws,
• 32:30which it just means a specific
• 32:31amount and it's usually two to
• 32:33five nanograms per milliliter,
• 32:34which I don't think makes much sense
• 32:36and I'll talk about that in a minute.
• 32:38And most states don't have anything,
• 32:40although Gray states,
• 32:40they don't have any laws on the books.
• 32:42It's sort of up to the the cop.
• 32:44To determine whether they're
• 32:46impaired from THC.
• 32:47And this is a really challenging problem.
• 32:51The model for alcohol is breath
• 32:53alcohol concentration that
• 32:54you blow into a breathalyzer.
• 32:56We've decided as a society that
• 32:58.08 BAC is the legal limit.
• 32:59We decided that based on,
• 33:03you know,
• 33:04an exponentially rising curve
• 33:05of BAC and crash risk.
• 33:07This does not exist for cannabis.
• 33:09We don't have this nice curve,
• 33:10and a lot of it is because
• 33:12cannabis is unique in its
• 33:14pharmacokinetics and pharmacodynamics.
• 33:15It's not as easy as alcohol.
• 33:18THC peaks in about 10 minutes
• 33:21post smoking or vaping,
• 33:23as you can see here it in
• 33:26breath and in blood.
• 33:27Your THC levels are quite
• 33:28high right after you use,
• 33:30and they return to baseline quite quickly.
• 33:34And carboxy THC,
• 33:35which is what THC is metabolized into
• 33:38and this is probably what if you,
• 33:40if you're given a drug test or a
• 33:41clinical drug test,
• 33:42that this is what these tests detect sticks
• 33:45around for a very long period of time.
• 33:48So this is detection window of
• 33:50marijuana drug tests in breath,
• 33:52in saliva, this is urine. It can.
• 33:56You can test positive for a month.
• 33:59If you're a heavy cannabis user
• 34:01and you stop so so carboxy THC is
• 34:03not water soluble, lipid soluble.
• 34:05It's stored in fat cells,
• 34:07it stays in the system for a long
• 34:09time and therefore it's not a very
• 34:11good test of impairment. And then?
• 34:13So we have THC is too quick,
• 34:16carboxy THC is too long.
• 34:17Well, how long are people
• 34:19actually reporting impairment?
• 34:20And this also varies dramatically.
• 34:23So this was a smoking study and you
• 34:25can see in after an hour about 50%.
• 34:28We're still impaired after three hours.
• 34:3310% were still impaired.
• 34:35So there's just and it also
• 34:37depends how much you use.
• 34:39So impairment can last for for four hours,
• 34:42particularly for oral THC,
• 34:43which I'm going to talk about in this study,
• 34:45impairment lasts for a
• 34:47very long period of time.
• 34:50The other thing we know is that people
• 34:51have poor insight to their own impairment.
• 34:53This was a super cool paper that just
• 34:56came out where they did this driving task
• 34:59and people pre smoking did very well.
• 35:02After they smoked,
• 35:0230 minutes later they did a
• 35:04lot worse and they knew this
• 35:06was their perceived impairment.
• 35:08They knew they weren't doing very well.
• 35:09This is how impaired are you,
• 35:10but that in an hour and 30 minutes
• 35:13something interesting happened.
• 35:14So there's still quite impaired,
• 35:16not as impaired at 30 minutes,
• 35:17but they're still quite impaired.
• 35:19But now sorry, I'm I did that backwards.
• 35:22This is their composite Dr score.
• 35:24So there's still quite impaired from driving,
• 35:26but they're perceived impairment
• 35:28is quite low.
• 35:29So you have this gap where
• 35:30people are still impaired,
• 35:31but they don't think they are.
• 35:33So that's not good for when
• 35:35you're deciding to drive a car.
• 35:38Dozens of studies have now shown
• 35:40that there's no association between
• 35:42THC biomarkers and impairment there.
• 35:44It's just really hard to detect THC
• 35:46impairment using a blood or a breath level.
• 35:49These are three papers.
• 35:50There are dozens more.
• 35:53So our idea was, is there a test that
• 35:55can go to the source of impairment
• 35:57so when you break a bone you
• 36:00take an X-ray if you're impaired,
• 36:01the affected organ is actually the brain.
• 36:04These other methods all look for body
• 36:05fluids which replicates the alcohol model,
• 36:07but as I mentioned that doesn't work for THC.
• 36:10So we wanted to use F near as
• 36:12functional near infrared spectroscopy.
• 36:14Not many people haven't heard of Fnirs,
• 36:16it's not as popular as F MRI,
• 36:18but it it's an optical imaging
• 36:21technique that's non invasive.
• 36:22It'll it'll allows measurement of
• 36:25brain tissue concentration changes or
• 36:27HBO following neuronal activation.
• 36:29It uses light to measure brain activity.
• 36:32Same principles of F MRI.
• 36:33F MRI uses magnets, FNIRS uses light.
• 36:36And the cool thing about F nears
• 36:38is it's non invasive.
• 36:39It's safe, it's inexpensive,
• 36:40it's portable, it's wireless,
• 36:42it can be used in natural environments
• 36:44without restraints without sedation.
• 36:47F MRI will never be useful on the roadside,
• 36:49obviously for obvious reasons,
• 36:50but you can imagine that.
• 36:53If news is a good indicator
• 36:54of impairment that you know,
• 36:56someday it might be useful,
• 36:58like the breathalyzer.
• 37:00And just if anyone's curious
• 37:02about how F nears works,
• 37:05basically brain activation could be inferred
• 37:07by this oxygenated hemoglobin concentration.
• 37:09So you have your neuronal activation,
• 37:11metabolic demand, increased blood flow
• 37:13and then you have this increase in,
• 37:15in,
• 37:16in,
• 37:16in oxyhemoglobin and wash out of
• 37:18D deoxyhemoglobin and you can
• 37:20measure that with light.
• 37:24This is the first breathalyzer.
• 37:26It took up a whole desktop and
• 37:28now it's smaller than your iPhone.
• 37:30And I think a similar thing is happening
• 37:32with Fnirs where these things are big
• 37:34and bulky and have wires sticking out,
• 37:36but I think they are just becoming smaller
• 37:38and smaller and more user friendly.
• 37:41So. For our study,
• 37:44what we did was we had 169 participants
• 37:47who were weekly or more cannabis users.
• 37:49They had two visits a week apart.
• 37:51They got placebo one day
• 37:52and THC and other day.
• 37:54And we did Fnirs recording during an
• 37:56in back task before they received
• 37:58THC or placebo at 100 minutes when
• 38:01peak effects were expected and at
• 38:03200 minutes and we got actual cops to
• 38:05come in and do and do assessments.
• 38:08They're called Dre drug drug recognition
• 38:10experts. We didn't train CRC's.
• 38:12To do this, we wanted,
• 38:13we wanted the real cops to come in.
• 38:15We told them don't worry your uniforms,
• 38:16we don't want to scare people,
• 38:17but they did their whole field sobriety test.
• 38:21And we did something in this
• 38:23study that was controversial,
• 38:24but we thought it was necessary
• 38:27is we did individualize dosing
• 38:29of THC to achieve impairment.
• 38:31So how much THC does it take
• 38:33to get somebody impaired?
• 38:35We have no idea.
• 38:36We have no idea.
• 38:37So what we did was we took a a very
• 38:41detailed medical history of their
• 38:43cannabis use and we looked at age
• 38:45and gender and tolerance and BMI
• 38:47and their patterns of cannabis
• 38:49use and determined the dose.
• 38:51That we thought would achieve impairment
• 38:52and that was different for everybody.
• 38:54So some people we gave them
• 38:5610 milligrams of THC,
• 38:57some people we gave up to
• 38:5980 milligrams of THC,
• 39:00some people who we gave 80 milligrams
• 39:02of THC didn't even get impaired.
• 39:04Dosing is really difficult.
• 39:05We couldn't figure out a dose
• 39:07for everybody and particularly
• 39:09after commercialization,
• 39:10people are using these, you know,
• 39:12high potency products.
• 39:15So we estimate that a little
• 39:16over half got impaired,
• 39:17even though we tried our darn
• 39:19hardest to get everybody impaired.
• 39:23How? How do we know who's impaired?
• 39:25So we're like, oh,
• 39:26we'll let the cops tell us, you know,
• 39:28this is what they do for a living.
• 39:30We found that the cops weren't very
• 39:31good at telling us were impaired.
• 39:33About 20% of those who received
• 39:35placebo were judged as impaired,
• 39:37which was kind of disturbing.
• 39:39And then the DRE's were really inconsistent.
• 39:42One of them was fantastic
• 39:44and had a 92% accuracy.
• 39:46One was 5050.
• 39:47So we didn't want to use the DRES
• 39:50as our ground truth of impairment.
• 39:52So what we did was we had this sort of,
• 39:55I don't know this this cumbersome but very
• 39:58thorough assessment of impairment where
• 40:00we had a clinical assessment, we, we,
• 40:03we decided this was me and my colleague,
• 40:05we looked at all the indications
• 40:07during the study visit,
• 40:09how they were acting, you know the
• 40:11blinded study nurse her her assessment,
• 40:14if they said they were high,
• 40:15if they said they felt the drug effect.
• 40:17And then we had a computer based
• 40:19algorithm of of heart rate change
• 40:21and self reported high and both
• 40:23methods needed agreement for us
• 40:24to consider that person impaired.
• 40:26So the clinical consensus we have to
• 40:27say yeah, I think they were impaired,
• 40:29it was like a chart review and then
• 40:31the computer algorithm had to say yes,
• 40:32this was indicative of impairment.
• 40:35And this is just an example of our
• 40:39time course and this is a person
• 40:42self reported high and this is a
• 40:44person's heart rate change in red.
• 40:46And you can see this person had a
• 40:48dramatic increase in heart rate.
• 40:49This is on the THC day, on the placebo day.
• 40:52We didn't see anything on this person.
• 40:54And then this is an example of
• 40:55somebody who we just did not give
• 40:57them a high enough dose.
• 40:58They had very minimal,
• 41:00minimal,
• 41:00minimal heart rate change and
• 41:02they reported zeros all day and
• 41:04they both got 30 milligrams of.
• 41:06HC. So that's just an example.
• 41:09And then what we found was that
• 41:12subjective and physiological responses
• 41:14clearly distinguish the two groups.
• 41:16So this is the impaired group,
• 41:19this is their self reported high,
• 41:21this is the non impaired group.
• 41:23So they got a little impaired but not
• 41:24dramatically and this is our placebo group,
• 41:26this is heart rate.
• 41:27This is you know the the heart
• 41:29rate change or the impaired group,
• 41:30the heart rate change of the unimpaired
• 41:33group and placebo and this shading is
• 41:36this was our pre pre dose effner scan,
• 41:39this was our post dose EFFNER
• 41:41scan and that was the second one.
• 41:43So we did get sort of at the
• 41:46peak of using the ether scan.
• 41:48So that was nice.
• 41:49Now the important thing for me to
• 41:51point out here no dose difference.
• 41:52So the the people who got high,
• 41:54the people who did not get clearly high,
• 41:57there was no significant dose
• 41:59in difference in dose in THC.
• 42:01OK.
• 42:02So question is do impaired
• 42:03and non impaired groups
• 42:05differ on effner's measures.
• 42:06So again this is our end back task,
• 42:10this is our, our prefrontal probe.
• 42:12We looked at these different ROI.
• 42:15And what we found was that
• 42:16there was increased activation
• 42:18throughout the prefrontal cortex
• 42:19only in those who were impaired.
• 42:21So this is the scan at baseline is in blue,
• 42:26the scan after the drug is
• 42:28administered is in red.
• 42:30And we had significant differences in
• 42:32every ROI in the people who are impaired,
• 42:34people who are not impaired.
• 42:35We didn't see any significant
• 42:37differences and we didn't see
• 42:39any differences on placebo.
• 42:41And again, no dose difference.
• 42:45So, you know, looking at this group
• 42:48difference, this is super interesting.
• 42:49You could get a good publication out of it,
• 42:51but it's not very useful.
• 42:52So group level impairment data
• 42:53is not useful in the real world.
• 42:55And psychiatry has really struggled with
• 42:57the ability to diagnose an individual with
• 43:00a condition based on functional brain data.
• 43:02So could we do this with impairment?
• 43:04Maybe impairment is such a global
• 43:06change that it would work.
• 43:07So we, we basically,
• 43:08we broke this etnier signal into
• 43:11features and gave them to our machine.
• 43:14Morning colleagues and said could you
• 43:16use a machine learning algorithm to
• 43:18determine who was impaired and who
• 43:20was not based on fnirs data alone?
• 43:26And yes, So what this graph shows
• 43:29is our machine learning results.
• 43:33And in the blue we have the Dre,
• 43:36so this is the cop.
• 43:37So the cop was about 72% accurate
• 43:39in judging people who are impaired.
• 43:42The positive predictive value of
• 43:43of those who are called impaired,
• 43:45how many were really impaired
• 43:46using our ground truth method
• 43:48and then a false positive rate.
• 43:49So what we found with Fnirs
• 43:51is we were a little better.
• 43:54From the cop about equal,
• 43:55a little better than the cop,
• 43:56much better in positive predictive
• 43:58value and we had half of
• 44:00the false positive rate.
• 44:01So that was kind of exciting.
• 44:05Umm. Something that came up is, you know,
• 44:08you're giving people an end back task.
• 44:09How realistic is that?
• 44:10And we thought, well,
• 44:11what if it was just a resting state scan.
• 44:13So we looked at resting state connectivity,
• 44:16which is a measure of how regions of
• 44:18the brain interact with each other
• 44:19without need for a cognitive task.
• 44:21And basically with that,
• 44:23with functional connectivity,
• 44:24you're looking for patterns of
• 44:26temporally correlated but face but
• 44:28spatially distinct brain activity.
• 44:30And again what we found is that the
• 44:33people who are impaired after THC,
• 44:37they had this reduction in
• 44:39functional connectivity.
• 44:40The people who are not impaired,
• 44:41you see no difference between
• 44:44pre and post Drug Administration.
• 44:46Another way of looking at that
• 44:48is placebo and THC.
• 44:49So on placebo and THC,
• 44:53if you were not impaired from THC,
• 44:55there was no significant
• 44:56difference in brain connectivity.
• 44:58But for the people who are impaired,
• 44:59they had this dramatic decrease
• 45:01in brain connectivity.
• 45:02The groups are matched with placebo,
• 45:04which indicates to us that
• 45:05we're measuring the state level
• 45:07and not trade level effect,
• 45:08which was exciting.
• 45:11And then finally,
• 45:12as part of this, the study,
• 45:14we gave some people some alcohol,
• 45:16a subset of participants, 20 of them,
• 45:18also received an alcoholic beverage.
• 45:20So we had this nice two by two design
• 45:22THC and placebo, alcohol, placebo,
• 45:24THC, real alcohol, THC and alcohol,
• 45:26and then double placebo to see if
• 45:29alcohol interferes with our ability to
• 45:33detect THC intoxication using F nears.
• 45:35And we found that even with alcohol
• 45:37on board we could still decrease
• 45:39detect this decreased functional
• 45:41connectivity in people who are impaired.
• 45:43And this is different channels in the
• 45:45brain that I showed you and this is
• 45:48pre dose before they got anything and
• 45:50this is after both THC and alcohol.
• 45:52So you have this reduction in connectivity.
• 45:55So I think this is real and
• 45:56I think this is robust.
• 45:59So what can we say?
• 46:00So prefrontal cortical activation
• 46:02collected with portable fnirs
• 46:04appears to be a biomarker of THC
• 46:06impairment and not exposure that could
• 46:08potentially be collected in the field.
• 46:11It's different only in
• 46:12people who are impaired.
• 46:14It's the first biomarker that
• 46:15we know of impairment from THC,
• 46:17not just THC exposure.
• 46:18This biomarker can be detected when people
• 46:21are doing a task or at risk at rest.
• 46:24And what we're doing now is we're
• 46:26writing a grant with folks from MIT
• 46:28to incorporate a driving simulator.
• 46:30So we'll have.
• 46:30People do the fears getting the
• 46:32driving simulator and see how
• 46:33they actually drive because again,
• 46:35you know,
• 46:35F nears task doesn't really have
• 46:37a lot of ecological validity.
• 46:41So just to wrap up,
• 46:45I hope I've convinced you that
• 46:46this is a really active area of
• 46:48research with so many more questions,
• 46:50so studies that we're working on now,
• 46:53we have an RO one looking at medical
• 46:55marijuana pain and opioid use in
• 46:57patients on chronic opioid therapy.
• 46:58And we want to see if medical cannabis does
• 47:01in fact help people taper their opioid dose.
• 47:03There's a lot of speculation out there.
• 47:05This hasn't really been shown very well.
• 47:07So we're doing,
• 47:08we're doing a trial to see if that's true.
• 47:10And something else that I thought of
• 47:12might might be interested interesting to
• 47:14this group is we're also doing PET scans.
• 47:17We're we're evaluating CBD for
• 47:19reduction of brain neuroinflammation.
• 47:21There's a a pet marker called PBR
• 47:2328 that's a a marker of microglial
• 47:25activation and we want to see if
• 47:28CBD reduces neural glial activation
• 47:30in patients with chronic pain.
• 47:34So with that, I just need to
• 47:36acknowledge everyone in my group
• 47:38who helped with this research.
• 47:40My the director of our center.
• 47:42You didn't Evans,
• 47:43our project manager Gladys Patches,
• 47:45Randy Schuster,
• 47:45who did the the adolescent studies,
• 47:47Kevin, our statistician, Michael,
• 47:48our programmer Nissan who did
• 47:50a lot of the Effner's analysis,
• 47:52and all of the CRC's who did
• 47:54fantastic work in collecting
• 47:55all this data and of course,
• 47:57funding sources.
• 48:01So thank you. Thank you so much,
• 48:04Jody. That was a wonderful talk.