TL neuro

December 9, 2016

Vaccination against the effects of MDPV (“bathsalts”) and alpha-PVP (“flakka”)

Filed under: alpha-PVP, Cathinones, MDPV, Vaccines — mtaffe @ 10:10 am

The substituted cathinone stimulants 3,4-methylenedioxypyrovalerone (MDPV) and alpha-pyrrolidinopentiophenone(alpha-PVP) have emerged as significant public health concerns in recent years. These drugs turned out to be monoamine transporter inhibitors with high selectivity for the dopamine transporter. These two compounds lack the monoamine releasing properties of methamphetamine, MDMA and other recently popular cathinone derivatives such as mephedrone and methylone. As we’ve shown, both MDPV and alpha-PVP are highly reinforcing in the rat self-administration paradigm and increase locomotor behavior when injected non-contingently or inhaled with e-cig technology. Although these drugs are still in the early stages of market penetration, the data from our lab as well as several other labs suggest that these will have high abuse liability. Effective countermeasures are therefore likely to be needed in the future.

One method to counteract effects of psychoactive drugs that has been attempted is vaccination; an explainer video from NIDA is available here. In this strategy a drug-like chemical structure is attached to a large protein that generates an immune response. When successful, this immune response creates antibodies that circulate in the blood with the capacity to recognize and bind to the target drug molecule. If this is done to effective levels, the administration of a given dose of drug leads to a reduced response, due to part of the drug dose being bound to antibodies in the bloodstream which prevents from entering the brain.

A paper describing an initial effort to develop a vaccine to provide protection against the effects of MDPV and alpha-PVP has recently been accepted for publication. As with all of our vaccine work to date, this was conducted in collaboration with the Janda laboratory at TSRI.

Nguyen, J.D., Bremer, P.T., Ducime, Creehan, K.M., Kisby, B.R., Taffe, M.A. and Janda, K.D. Active vaccination attenuates the psychostimulant effects of α-PVP and MDPV in rats, Neuropharmacology, 2017, 116:1-8. [PubMed][Publisher Site]

In this study, Paul Bremer and Alex Ducime created vaccine candidates designed to generate antibodies against MDPV and alpha-PVP, respectively. Initially, three groups of male rats were vaccinated to evaluate the MDPV-specific, alpha-PVP-specific vaccines against a group vaccinated with the immunogenic protein (keyhole limpet hemocyanin; KLH). The antibodies in the MDPV-vaccinated group showed high affinity for MDPV but not for alpha-PVP or methamphetamine. Likewise, the antibodies in the alpha-PVP group were selective for alpha-PVP over MDPV or methampetamine.

Brent Kisby, an undergraduate on an extended internship, in combination with Kevin Creehan and Jacques Nguyen first determined if these rats would exhibit functional protection against drug exposure. We selected a wheel-activity response to drug injection (see Huang et al, 2012) because this had proved effective at screening anti-methamphetamine candidate vaccines in our prior study (Miller et al, 2013).
nguyen17-alphavaccfig3-wheel This figure (click to enlarge) shows wheel activity (quarter revolutions) in the four hours following injection with four doses of alpha-PVP (Panels A, B) or four doses of MDPV (Panels C, D). The left hand panels depict the effects of drug in the KLH-only control groups while the right hand panels depict the effects of drug in the respective alpha-PVP-KLH and MDPV-KLH vaccine groups. The asterix indicates a significant change of activity relative to the vehicle (saline) injection condition. The takeaway message here is that doses of alpha-PVP (0.5, 1.0 mg/kg, i.p.) and MDPV (1.0 mg/kg, i.p.) which increase wheel activity in the control group do not do so in the respective vaccine group. The vaccine can be partially surmounted since the 5 mg/kg dose of each drug increased activity in the vaccinated rats, although this increase was numerically lower and lasted less long in the MDPV-KLH and alpha-PVP-KLH animals compared with the control group.

This promising result led to the design of an intravenous self-administration study to test the ability of alpha-PVP-KLH vaccination to alter the course of self-administration. Jacques Nguyen and Kevin Creehan headed up this study.
A group of rats were first trained to self-administer alpha-PVP, prior to any vaccination. This is only the second study to publish the acquisition of alpha-PVP self-administration in an animal model (see Aarde et al, 2015) and we found that a 0.1 mg/kg/infusion dose was required to produce good acquisition in Sprague-Dawley male rats. Thereafter the rats were placed on hiatus from drug self-administration and given a 5 week protocol of three immunizations, divided into two groups- one receiving KLH only and the other receiving alpha-PVP-KLH vaccine. We showed first that on return to self-administration at a reduced per-infusion dose of 0.025 mg/kg/infusion the alpha-PVP-KLH vaccinated animals self-administered more drug. This result is consistent with the circulating antibodies producing partial reduction of the dose as it was self-administered and the corresponding behavioral compensation to produce similar brain levels of drug.
nguyen17-fig7-prepostAfter three weeks the animals were given a booster immunization which resulted in about a doubling of the circulating antibody level (titer). This resulted in no change in the KLH-only animals’ drug intake, however the alpha-PVP-KLH animals changed from a mean of 17-20 infusions per session to a mean of about 4-5 infusions per session, a significant reduction in self administration. This lasted for 15 sessions and is depicted in the figure (click to enlarge) as Post4-Post8 bins of three sequential sessions.

As discussed in the paper this is an initial feasibility study but it shows the potential of the anti-drug immunotherapy strategy to be effective against the effects of both MDPV and alpha-PVP. This should encourage additional work to determine the extent and nature of the protection against these substituted cathinone stimulants that can be achieved with vaccines.

These studies were funded by USPHS grants DA024705, DA042211 and DA037709.
Additional Reading: A list of our cathinone-related publications can be found here.

December 3, 2016

New Chapter on Entactogen Self-Administration

Filed under: 4-MMC/Mephedrone, alpha-PVP, Cathinones, MDPV, Methylone — mtaffe @ 2:48 pm

We have recently published a short review on the self-administration of entactogen psychostimulants.

Aarde, S.M. and Taffe, M.A. Predicting the Abuse Liability of Entactogen-Class, New and Emerging Psychoactive Substances via Preclinical Models of Drug Self-administration. Curr Top Behav Neurosci. 2016 Dec 2. [Epub ahead of print] [PubMed][Publisher Site]

This is part of a Current Topics in Behavioral Neuroscience book on New and Emerging Psychoactive Substances organized by Mike Baumann of the NIDA IRP who has been publishing a lot of work on synthetic cathinones lately. Eventually the Chapters will be collected into a book and assigned unique pagination.

For now you can look chronologically in the pre-publication OnlineFirst list.

The first chapter of the series that was published was:
Schifano et al “NPS: Medical Consequences Associated with Their Intake” [link]

The cannabinoids are covered:
Wiley, Marusich and Thomas Combination Chemistry: Structure–Activity Relationships of Novel Psychoactive Cannabinoids [link]

All told there will be around a dozen chapters, I think most of them are on the pre-print list already. Happy reading!

November 3, 2016

Thoughts on Proposition 64 to Legalize Recreational Marijuana in California

Filed under: Cannabis — mtaffe @ 10:41 am

I wrote a brief note on Facebook the other day to outline what I thought were several points that come up when people in the community ask me about the upcoming vote on recreational marijuana (link to ballotpedia summary of Prop 64). This was picked up in a post at Forbes by David Kroll (a handy summary video is here)

This piece was noticed by Sasha Foo at KUSI and she was kind enough to film a news segment which aired on 2 November, 2016. This links to the 6 pm broadcast version.

My Facebook remarks (with a few key links to data sources added):

I’m in California which will be voting on Proposition 64 which legalizes recreational marijuana. As many of my friends, neighbors and acquaintances are aware that I work in the substance-abuse fields of science, they have questions. So I thought I would put some of my usual responses/points down on a Fb post.

First, some background on my opinions. I work for you, the taxpayer of the US. This is because my work is funded by grants from the National Institutes of Health. Because these are primarily from the National Institute on Drug Abuse, my role is to investigate the effects of recreational drugs on the brain (and the rest of the body) with some attention paid to how this might affect the health of humans.

This is most emphatically not a policy role. I have no special expertise on public policy and my comments are not meant in that way. I do hope that science can be used to inform policy and, frankly, I wish that public policy across the board paid a lot more attention to facts and data. This is not to say, however, that I believe that the facts necessarily lead all interested people to the same *policy* decision. Because policy requires the weighing of factors and pitting positives and negatives of various kinds against each other.

As far as legalizing recreational marijuana goes, I do think that the epidemiological, human laboratory and animal laboratory data has some relevance to the Prop 64 issues. So, I’m going to list a few facts.

1) Marijuana is addictive. Full stop. The conditional probability of dependence is about 9% where like-to-like comparisons put cocaine and methamphetamine at 15%, heroin at 25-45% (data are terrible) and alcohol at 4%. Alcohol is a huge problem because 85%+ of people consume it at least annually. In contrast, less than 1% of people have ever tried heroin, 0.4% in the past year. Marijuana comes in at about 32% annual prevalence for ages 19-28. The scope of the addiction issue depends on how many people are using it, obviously. This will go up with legalization- but we don’t have any idea how much.

2) 5-6% of high-school seniors use Marijuana daily. Daily. That’s the US average. I don’t have numbers for California.

3) Marijuana addiction is as “real” as any other. Frequency of withdrawal symptoms and severity of those symptoms were compared between marijuana and tobacco smokers and the data were nearly indistinguishable. Most people are much more familiar with nicotine dependency (which is a higher rate, btw, probably 33%+) since it is more common, not embarrassing to discuss in public and is conventionally recognized. A lack of personal familiarity with the scope of withdrawal in the people who are marijuana dependent doesn’t mean that it doesn’t exist.

4) There is no such thing as “psychological” versus “physical” dependence since the brain is part of the body and the mind is the functioning of the brain. Keep in mind that people can be months to years out from their last use of any drug and still relapse severely. This is not being driven by the withdrawal symptoms that most everyone recognizes when they talk about “physical” dependence.

5) Marijuana acutely impairs cognitive and other behavioral functions.

6) Behavioral tolerance with chronic exposure is substantial. Blood levels of THC in animals or humans are a poorer proxy for impairment (versus other drugs) if you do not know anything about the prior exposure history.

7) THC is detectable in the body for a very long time compared with many other drugs of abuse. One study found detectable THC, or one of the main metabolites, for 30 days of in patient study (chronic users).

8) Trying to make specific predictions about an individual who uses marijuana from general findings (there is always a central tendency or average around which the distribution of data points or individual outcomes varies) is a fools’ errand. We can only predict general trends. Conversely, and this is important for your personal introspection, the evidence from one given data point or individual doesn’t tell us much that is informative about the average trend. The fact that it is your personal experience does not make it more valid.

Finally, there is much we simply don’t know. Any given scientific study or data set is limited by how it was generated. This doesn’t mean we throw up our hands and say it is all bunk or uninterpretable but it means one does have to think about it a bit.

I would invite you to read over the Prop 64 provisions. Personally, I see a fair bit of investment of the tax revenue in state sponsored activities to answer some of these issues better, to address some of the obvious concerns, etc. To me this is a positive. The extent to which this will happen, the extent to which actionable information will result, the extent to which activities intended to head off or ameliorate obvious negatives is, however, an unknown.

September 20, 2016

Just. Keep. Swimming.

Filed under: 4-MMC/Mephedrone, Cathinones, MDPV, NIH — mtaffe @ 1:07 pm

In the prior post I tried to give some flavor of the sort of grant submission effort that it has taken for me to keep my lab afloat to this point in time. That description gave an overview of my rough success rates which hovers somewhere in the high teens, not too far away from the aggregate NIH success rate over a similar interval of time.

As I point out to trainees now and again, there is no reason for any of us to think we are somehow special in securing grant funding. The NIH system of extramural funding has been under high stress in the past 10-15 years and there are far more deserving proposals being submitted than can be funded.

In this post, I want to outline the course of a particular research program of mine.

In early 2010 I became aware of a new recreational drug called mephedrone, (aka meow-meow or plant-food) which was very popular in the UK. It was not legally controlled and it seemed to emerge in a bit of a MDMA drought in that country. I soon found that 4-methylmethcathinone was the drug of interest, that the core molecule of cathinone was very similar to amphetamine and that it appeared to be only one of several substituted cathinones which were circulating. I did a bit of searching on PubMed and rapidly concluded that very little science had been published with any of the cathinones after a brief interest in methcathinone and cathinone in the 80s. From what little pharmacological evidence was available, combined with human subjective trip reports I could find online, it was pretty clear that we were facing a reboot of the substituted amphetamine era of the 1980s.

Mephedrone had first come to media attention around 2008 with an overdose in Sweden and had gradually grown in popularity through 2009 and into 2010. The UK government was alerted, trying to complete legal controls and had to rely on very imprecise reviews of the available knowledge.

I found this professionally embarrassing that so little was known. We spent so much effort on methamphetamine and MDMA and here, one to two years into a novel drug phenomenon we knew nothing. Nobody was presenting data at the scientific meetings I was attending, either.

I was also very interested scientifically precisely because of my interest in that prior episode of substituted amphetamine popularity and in the clear “winner”, i.e., MDMA or Ecstasy. This highly popular new drug, mephedrone, was being used by MDMA type populations in the MDMA type environment with many of them explicitly saying they were looking for a MDMA substitute. This drew my attention. There was also a very clear under-current that this mephedrone stuff was like a poor echo of MDMA but watch out for the compulsive use risk. Users were suggesting that this compound was perhaps more like a traditional psychostimulant than MDMA is.

This realization came as I was working on a final revision of an R01 proposal I was submitting on the topic of the abuse liability of MDMA, why it differs from a traditional psychostimulant like methamphetamine and how various situational or experiential factors may make MDMA more compulsively abused. The A1 had received a 21 %ile with pretty minor criticisms so of course there was no way I was going to start dragging in new drugs for the A2 (which I submitted in April of 2010).

Instead I started plotting an assault on specific funding for these novel cathinone drugs. I contacted my Program Officer who, having driven some funding opportunities for MDMA back in the day, was of course interested. But this was 2010. And there was about zero enthusiasm down in the NIDA trenches for anything that wasn’t already on NIDA Director Volkow’s current priority list. In emails and eventually in person at CPDD that year, I bounced around from one NIDA person to another and came up with a similar story. Nobody was enthusiastic about generating any special interest. “Get a fundable score and we’ll talk” was the size of it. There was even a hilarious (not really) standoff between DEA who were demanding data from NIDA (for their intent to Schedule some of these drugs) and the latter’s demand that DEA pay for it and sure, they’d see what they could do.

I got friendly with some DEA scientists to find out what was being seen in the US since law enforcement detection usually runs far ahead of any epidemiology in the peer reviewed literature. From this I deduced that mephedrone was actually pretty rare in the US but that MDPV was going to be a thing.

As we all know, Preliminary Data was going to be required to get a grant funded. But that requires….the drugs!

NIDA drug supply wouldn’t provide any of these new drugs. The usual commercial suppliers didn’t have them either.

Luckily, I was working with a couple of investigators in the department of Chemistry. One of them, Tobin Dickerson, took a look at what I needed and said “Looks pretty simple, how’s next Thursday?”. Boom! We were in business.

Our first grant proposal on this topic was submitted in October of 2010 and focused on mephedrone/4-MMC. It included self-administration data, thermoregulation and activity data, metabolism and PK data from Karen Houseknecht at UNE, microdialysis data on dopamine and serotonin responses generated with Larry Parsons’ lab and receptor/transporter screening from Bryan Roth’s Psychoactive Drug Screening Program at UNC. We proposed self-administration investigations, physiological endpoints and PK. In recognition that there were going to be many other substituted cathinone derivatives of interest we proposed a bit of structure-activity manipulation to start looking at whether specific chemical alterations conferred enhanced/decreased risk for adverse outcomes. In retrospect, putting all this together in the early days of this drug trend was probably one of the best things I’ve ever done in terms of a scientific program.

It was triaged. The app went to MNPS study section instead of BRLE (which we had requested) or even NMB, probably because of all the PK and the structure/activity content. Even though the focus was really on the novelty and the abuse liability/risks. We got 4-6s on the Innovation and 5s on the approach. But really, reading on and between the lines of the critiques it was all about “Problem? What problem?“. This could have occurred at any study section.

One has to be a bit sanguine about the inherent conservatism of the NIH grant process. It was absolutely true that there was not as yet overwhelming evidence of broad use of substituted cathinones, no evidence of large numbers of addicted people in serious life crisis and no evidence of weird/unique dangers akin to the serotonergic neurotoxicity that attends high-dose repeated MDMA exposure to drive enthusiasm.

But still. We weren’t the only ones who could see the importance of this. And as I started to present our data at meetings, I would run into colleagues who were also interested in studying these drugs. And their efforts at grant funding were to sound very familiar over the coming years.

The A1 for this initial proposal was submitted July of 2011 and likewise triaged by MNPS. There was still a lot of kvetching about “Problem? What problem?” but also some typical grant stuff. “Too descriptive”. “What’s the hypothesis”. Etc. This is always a problem for how I look at science, of course, but in this case it was kind of annoying since very little was known about any of these drugs yet, and we did have a clear hypothesis under investigation. [Related papers: Huang et al, 2012; Wright, Angrish et al, 2012; Miller et al, 2013; Aarde, Angrish et al, 2013]

I next incorporated cathinone studies on a competing continuation application for a prior MDMA-focused project that admittedly had issues with its chance of being renewed, even before I added cathinones. The first one went in July 2011 and was triaged by BRLE. The A1 went in March 2012 and got a 42 %ile. As far as the inclusion of substituted cathiones goes, it was mixed. Some reviewers saw this as a positive but some also made comments to the effect of “Problem? What problem?” and “Why don’t you have clearer hypotheses?”. Seeing a pattern? [Related paper: Wright, Vandewater et al, 2012]

I had been doing some work on methamphetamine vaccines with the Janda lab, where my collaborator on the cathinones had done his doctoral studies. As a newish PI, he’d been trying to get away from that area of work (successfully) but here I was dragging him back into work on drug abuse. So it seemed natural for us to put in a vaccine proposal in October, 2012. This time we were focused on MDPV because it was becoming clear in our ongoing studies that this was much more like a traditional psychostimulant with a high potential for addiction in humans. Triaged. With reviewers throwing 6s and a 7 and an 8! Ouch. Well, it certainly wasn’t my strongest proposal but, more to the point, there wasn’t much complaint about the drug choice. Maybe because the rest of it drew so much fire, I couldn’t say. [Related paper: Aarde, Huang et al, 2013]

[Updated: I forgot about this one] I tried a slightly different strategy at this point, submitting a new proposal in October 2012 that wasn’t focused on the cathinones, per se. Instead, this was a proposal about another topic in substance abuse research (one which had background, we’d been working a little bit on it, had a pub, etc, etc) where we just used MDPV self-administration as the drug model. Our most recent Preliminary Data were from this so why not, right? The PMDA study section triaged it- one reviewer threw a 9 for approach and a 7 for significance but the other three reviewers were throwing 3s and 4s mostly. Leaving aside the hater reviewer who went off hilariously on ad hominem attacks and thoroughly unjustified complaints (going by my rather considerable collection of grant reviews testifying to my minimal competence level), the remaining three reviewers ranged from slightly skeptical (insufficient justification for selecting MDPV as the model) to out and out objecting (“…should be examined using a drug that has well characterized patterns of self-administration in the laboratory“). Needless to say when I put the revision in it did not include a cathinone as the model. [Related papers: Aarde, Huang et al, 2015; Aarde, Miller et al, 2015]

In Feb 2013 we submitted a new approach to the cathinones, now with the take on Hypothesis B, as opposed to the Hypothesis A that underlay most of our arguments up to this point. Triaged by NMB. Things were improving slightly, however. A little bit of kvetching over methodology but for the most part no complaining about the relevance of studying these emerging drugs. A fascinating new all-reviewers complaint was included about our structure-activity studies somehow informing clandestine chemists how to make better (or worse from another point of view) drugs. [Related paper: Aarde, Creehan et al, 2015]

Of course by this point we had started publishing papers on cathinone-related topics. Our first ones must have appeared online in early 2012 with print versions issued in fall of 2012. I think we had 6 papers published by the end of 2013. I’ve added citations to the above to indicate the approximate stage of Preliminary Data that were available and relevant at each grant submission- obviously the papers appeared later in most cases.

I’m not entirely sure I remember why but we submitted a different take to the question in November 2013. This one backed off of Hypothesis B and struck out on a tack that tried to address what was now a diverse set of substituted cathinones on the open market. This was promptly triaged by BRLE. One reviewer was convinced that we’d never publish many papers. Most of the rest was the usual ticky tack stuff about “why didn’t you do it this way?” and questions that really can only be resolved by getting in there and doing the work. In a word, empirical. By this point, reviewers were viewing the attention to these novel drugs as a strength, no more comments about demonstrating the scope of the real world problem.

In February of 2014, NIDA posted a new funding opportunity announcement on synthetic drugs, the R01 version was PAR-14-106. Actually, it was initially posted as a PA, withdrawn and reposted as a PAR “to allow a Special Emphasis Panel to provide peer review of the applications”. Why? Who knows. But as soon as the original PA was posted I sent an email to the Program Officer in charge that included my summary statements to that point in time and an observation that throwing these apps into regular study sections was unlikely to produce fundable scores. If you are keeping track, nearly everything I had submitted was triaged, except the A1 for my competing continuation (which you might view as a sympathy scoring/discussion).

Up to that point in time, if you search RePORTER for funded grant projects on “mdpv, methylone, mephedrone or cathinone” for fiscal years 2010-2014 you would first find 2 pre-doc fellowships and one post-doc fellowship. Next you would notice that one R01 was funded in FY2012 via a conflict special emphasis panel for a study section chair, one R01 was funded in FY2014 on human epidemiology through a regular standing study section and one R21 was funded through BRLE for FY2012. In addition, five NIDA intramural labs started mentioning these key words and are located by this search.

The point here is that clearly my colleagues who were also submitting grants on cathinone-related topics were having a similar lack of success. We talk at meetings so, trust me, there were several quite accomplished PIs who were applying during this interval of time as well.

We submitted a new version of the Hypothesis B proposal in June 2014 for this new PAR. It got a 25%ile so we resubmitted it in March 2015 again to the PAR. It got a 24%ile. No movement. The resume of discussion for the first version complained about minor technical issues, interdependence of Aims (this is grantsmithing stuff) and “sloppy constructed, lacking clarity and consistency”. This latter bit was interesting since one of the prior reviews of this Hypothesis B lauded it for clarity and fantastic grantsmithing. It happens. Oh, and by now we were trying to get out ahead of the looming SABV initiative and mentioned including female and male rats. Got killed for “design concerns”. The resume of discussion for the second one was a classic case of “we don’t have any real complaints but there are one or more grants better than yours in the list so we have to find something”. Very frustrating. Oh, and we were offered the opportunity to propose a R56 Bridge on the last version of this (yay!) to focus on the sex-differences and improve our hypotheses…..but it wasn’t selected for funding. Another half-submission in late 2015.

In between these submission we put in an R21 on vapor inhalation of cathinones in Jun of 2015 to be reviewed by the SEP. It received a 39 impact score with concerns mostly focused on the novel inhalation model. So no real issues with the cathinone topic itself, after all it was a synthetic drugs SEP! [Related paper: Nguyen, Aarde et al, 2016]

By this time, the MDMA-related grant I mentioned at the top was due for a competing continuation application, which went in November 2015. You may be wondering by now how we were able to sustain the effort to generate new preliminary data and such for all of these applications and, ultimately, papers. Well, our MDMA grant was funded pretty soon after we got really interested in the cathinones. There was a lot of dovetailing of the topic domains, as I mentioned, the mephedrone compound was originally reported as being sort of MDMA-like, but with enhanced abuse liability. Methylone eventually emerged as the direct cathinone cousin of MDMA. So it actually made a lot of sense to draw these together for the competing continuation. It got a 27%ile from BRLE and the reviewers were totally on board with the inclusion of new cathinone experiments as well as the harmony of what we’ve been doing over the past 4 years with the original MDMA proposal (which was originally designed before these designer cathinones appeared in user groups). This put us up to something like 4 straight applications discussed after our initial run of 6 7 triages interrupted only by one kiss-your-sister score of a -06A1 application. Progress! [Related papers: Creehan et al, 2015; Vandewater et al, 2015; Nguyen, Grant et al, 2016]

The stalling of the Hypothesis B proposal at an unfundable 24-25/%ile was frustrating, but what can you do? The ideas seemed to have legs and the complaints were not substantial. We put it back in as new application in October 2015, for the SEP once more. It got an 18%ile. Definitely outside the likely payline for the year*. So I revised and resubmitted it in August 2016. Sixth time (honestly I’m losing track at this point) is the charm for Hypothesis B?

So here we are in September of 2016. We’ve been working on this topic for over 5 years and submitting grants for almost 5 years. We’ve had thirteen papers and I’ve submitted thirteen fourteen grant applications (my collaborator has put in a few more during this interval as well).

NIDA eventually created a FOA for synthetic drugs (not just cathinones, includes cannabinoids and opioids as well). The degree to which this was influenced by our advocacy and publications, I don’t know but it had to have helped. Certainly our early triaged summary statement results were key to getting a SEP convened for this purpose. They’ve funded, by my count, two R15s, one R21 and one R03 via regular study sections and one R21 via SEP for a more general funding opportunity announcement. The PAR on synthetic drugs resulted in the funding of an R21 and four R01s on synthetic cathinones since being issued, that is 6 possible funding rounds to this date*.

We recently received word that the aforementioned October 2015 submission of the Hypothesis B proposal will be funded.

Time to REALLY get to work!



Addendum: We never work alone on these projects and it has been a large team effort. Deepshikha Angrish synthesized compounds in the Dickerson lab in the early days. Deborah Barlow in the Houseknecht lab was essential for the PK work. Matt Buczynski jumped right on a key early neuropharmacology experiment in the Parsons laboratory. Jerry Wright, Shawn Aarde (in particular), Michelle Miller and Jacques Nguyen are postdocs that did heavy lifting on this topic in my group. My laboratory’s incredible technicians Sophia Vandewater, Kevin Creehan and former technician PK Huang (now a graduate student elsewhere) likewise did great work.


*There is an interesting vignette in here about the effectiveness of convening SEPs for PARs. My three scores for Hypothesis B in this SEP (which doesn’t have standing members but is convened per-round) ranged from 31-36. At one point the PO seemed to let slip that my 31 was the top score in that round for the SEP. Going from the PO’s general demeanor in discussing how the FOA was going, and the rather thin list of funded grants (not many cannabinoid or opioid ones emerged either), I conclude that reviewers are not issuing clearly-fundable scores in every round. And not many fundable scores all together over 6 rounds. This is somewhat puzzling**.


**In FY2014 alone, NIDA funded 37 new R01s that included cocaine as a keyword and 13 with heroin. Eighteen competing continuation R01s with either heroin or cocaine referenced. Of course there would be far more that were in the middle of non-competing intervals of funding.

August 30, 2016

What it takes to survive the NIH Game

Filed under: Careerism, Postdoctoral — mtaffe @ 11:07 am

I recently dusted off some old slides on the academic science career arc to prepare for a presentation to our postdoctoral trainees who are supported on the training grant that has been housed in our department for much of its 35 years. I am the new PI of this NIH award and it falls to me to serve in an overseer role for the training and education the postdocs receive. No small responsibility, this.

Of course, we will eventually cover career paths that veer outside the NIH-funded grant-supported research laboratory in which these trainees are working. But to start with, I presented a very superficial overview of the NIH extramural system. As a NIH Training Grant, the first assumption is that we are training the next generation of Principal Investigators to lead their own independent research projects, so this frames our starting point.

One of the elements which I stress repeatedly is for individual trainees to do their own research about how the NIH’s (or other agency’s) grant game might work for them. Individually. Part of that was an exhortation to see how it has worked, or is working, for the scientists that they know (NIH’s RePORTER is helpful) …if nothing else to educate themselves on the world of the possible. The experiences of scientists change over time and with academic generations but it is a good idea to take a look at the career paths of those PIs who are most like you (the trainee) imagine yours will be.

I also recently had a peer scientist who provides me with a lot of career and grant related sounding board type advice remark “you work at this harder than anyone I have ever heard of”. I do not know if that is true or false when compared to people in my field at my approximate career age (I was appointed Assistant Professor in mid-2000) and in my approximate employment type (soft money, i.e., essentially all of my time is spent on grant-funded research activities).

But this resonated with my advice to the Training Grant postdocs to do some research on the career arc of the scientists in their fields. So, here’s a summary of how hard I work at it. YMMV, of course.

Starting in early 2000, I have submitted approximately (I may have lost track of one or two here and there) the following number of grant applications to the NIH as a Principal Investigator, including participation as a component head on P-mechanism.

Thirty two new (including revisions) R01 applications, 6 of which were funded.

Seven competing continuation R01 applications, one of which was funded.

[Note that my 18% hit rate for R01 submissions is (roughly, roughly) right about where the aggregate success rate for NIH submissions is, if you amortize over this interval of time with a very broad brush.]

Component head within a P (Center) application included 4 total submission rounds, one of which (the second) was funded.

One U01 application, which was not funded.

Eleven R21 applications, one of which was funded.

One R25 application, not funded.

I’ve also contributed substantially to three SBIR applications in the sense of being the scientific subcontract for those proposals; one of these was funded.

It is important to note that many of these submissions were in fact re-submission of amended versions of proposals that had been previously reviewed. There are also many of my submissions that were highly similar to other proposals even if not direct revisions. This might be due to the NIH rules not allowing further revisions or by alterations in our ideas or plans.

As far as my funded R01 awards go, two were funded un-amended, two on the A1 version and three on the A2; but this only tells a part of the story. Each “un-amended” app had been reviewed previously as part of a different grant mechanism.

Two of these awards were clearly saved by Program Officers deciding to pick up a grant that otherwise might not have funded.

Two received 1-2%ile scores (you can’t do much better than that).

One followed an R21 award (funded on A1) and one followed a component of a funded P20 Center (components are ~R21 size) in terms of topic and direction. These might therefore be considered more in line with a competing continuation rather than a new award/new project although they were not technically competing continuation applications.

I have also been the PI of three major awards that were originally reviewed with a different person as the PI (two of which I contributed to as the postdoc in the laboratory of the PI).

Obviously the question of how hard one has to work at maintaining a given level of research funding is a moving target at best. I have a colleague of my approximate generation that has received funding for over 80% of submissions. I have colleagues of various generations beyond Assistant Professor stage that have been very spottily funded over many years to decades. Some of this depends on personal choice of research topics, grant submission behavior, choice of laboratory size and other factors. Some, no doubt, is just variation in how successful one happens to be within this highly competitive grant-award system. And some probably depends on how hard you work at it. For that you would have to ask the individual PI in question how many unsuccessful grants they have submitted.



Update 05/17/17: I recently found reference to this paper.  It emphasizes that grant success is a function of grant application effort.

June 3, 2016

Inhalation delivery of psychostimulants to rats using e-vape technology

Filed under: 4-MMC/Mephedrone, Cathinones, E-cigarettes, MDPV, Methamphetamine — mtaffe @ 4:03 pm

Although inhaled exposure of drugs is a prevalent route of administration for human substance abusers, animal models of inhaled exposure to psychomotor stimulants (cocaine, methamphetamine, synthetic cathinones, etc) are not commonly available. Inhaled use of methamphetamine is more common than other routes of administration in habitual and dependent users (Das-Douglas et al. 2008; Heinzerling et al. 2010; Wood et al. 2008) and the SAMHSA/TEDS treatment admission database for 2012 shows 4.7% of treatment seekers in the USA were admitted for smoked cocaine vs 2.2% for other routes of cocaine administration. There is limited evidence that people are using e-cigarettes for inhalation of methamphetamine (Evans 2014; Rass et al. 2015), “bath salts” (Johnson and Johnson 2014; Rass et al. 2015) and “flakka” (presumptively α-pyrrolidinopentiophenone; alpha-PVP) as reported (Anderson 2015).

We have therefore developed a method for the delivery of psychostimulant drugs to rats and evaluated the impact of methamphetamine (MA), 3,4-methylenedioxypyrovalerone (MDPV; “bath salts”) and 4-methylmethcathinone (4-MMC; mephedrone). The following paper describing our initial studies has been recently accepted for publication in Neuropsychopharmacology:

Locomotor stimulant and rewarding effects of inhaling methamphetamine, MDPV and mephedrone via electronic cigarette-type technology. Jacques D. Nguyen1, Shawn M. Aarde1, Maury Cole2, Sophia A. Vandewater1, Yanabel Grant1 and Michael A. Taffe1
1Committee on the Neurobiology of Addictive Disorders; The Scripps Research Institute; La Jolla, CA, USA
2La Jolla Alcohol Research, Inc, La Jolla, CA, USA

Schematic of the inhalation chamber

Schematic of the inhalation chamber

Our exposure model for this study involved a standard sized rat housing chamber with a sealed lid- these are commercially available for a variety of purposes. The chamber was plumbed for regulated airflow and incorporated the ability to deliver and exhaust the vapor from an e-cigarette type device. The overall approach for delivery to rodents is under patent to La Jolla Alcohol Research, Inc which has been instrumental in developing the equipment for our studies. This collaboration has resulted in a number of studies so far, this one is the second one to be published. The first paper described the effects of THC inhalation (blogpost). The company has also recently been awarded an SBIR Phase II Grant (R44 DA041967) to further develop and enhance commercialization of the device.

Control of the dose administered to the rat in this system is a key initial topic of investigation. We determined in this paper whether the dose can be altered with the manipulation of a number of variables. The concentration off the drug may be altered in the propylene glycol (PG) vehicle (aka “e-juice”)- our standard condition for this study was 100 mg/mL but effects from 12.5-200 mg/mL were also explored for different drugs. For the most part this study found concentration-dependent effects only across drugs (4-MMC was much less potent than MA or MDPV) when the puffing and inhalation duration was held constant. The puffing regimen and duration of inhalation exposure can be altered as well. In most of our studies we delivered 10-s vapor puffs with 2-s intervals between them every 5 minutes for durations of 10-40 min (approximately 0.125 ml was used in a 40 min exposure session). Varying the total duration from 10 to 30 min resulted in dose dependent effects of inhaling MA (12.5 mg/mL) or MA (12.5 mg/mL).

Vape decreases ICSS thresholds

A decrease in ICSS threshold was produced by inhalation exposure to 4MMC (200 mg/mL), MA (100 mg/mL) and MDPV (100 mg/mL). Similar effects were produced by i.p. administration of 4MMC (1.0mg/kg), MA (0.5 mg/kg) or MDPV (0.5 mg/kg). Significant differences from the respective Vehicle condition are indicated by *.

We present data on the intracranial self-stimulation reward paradigm in this paper. This is a model in which electrodes are implanted into the medial forebrain bundle of the rat and it is trained to respond for small deliveries of electrical current which has a rewarding or reinforcing effect. The procedure used for this study ramps the stimulation up and down during a session until the threshold necessary for the individual to experience a reinforcing effect is determined. Once the animals are trained to generate stable thresholds, they can be tested by administering drugs before the session. If a drug has a rewarding or reinforcing effect, it tends to lower the threshold below the baseline level. Here we show that all three drugs decrease reward thresholds in male rats. The reduction in the reward threshold was of a similar magnitude when drug was administered by injection or by vapor inhalation. This is a key indication that this procedure can generate reinforcing or rewarding levels of drug in the rats.

Activity rates after inhalation of  3,4-methylenedioxypyrovalerone (MDPV; 25,50,100mg/mL) or 4-methylmethcathinone (4MMC/mephedrone; 100, 200mg/mL).

Mean (N=13; + SEM) activity rates after inhalation of 3,4-methylenedioxypyrovalerone (MDPV; 25,50,100mg/mL) or 4-methylmethcathinone (4MMC/mephedrone; 100, 200mg/mL). Gray shaded symbols indicate a significant difference from PG vehicle at the corresponding time point. Base = pre-inhalation baseline.

Locomotor activity was measured after vapor inhalation using a radiotelemetry system that generates activity rates as counts per minute. In this figure we show the activity before and after inhalation of the PG vehicle and then three concentrations of MDPV and two concentrations of 4-methylmethcathinone (4-MMC, mephedrone) for 40 min. Locomotor activity was increased for 2-3 h after the initation of vapor for all three MDPV concentrations and for the 200 mg/mL concentration of 4-MMC. Similar effects were observed for MA and we went on to show that the dopamine D1-like receptor antagonist SCH23390 (10 ug/kg, i.p., prior to inhalation) blocked locomotor increases caused by inhalation of each drug. This is as would be expected, similar to the effect of SCH23390 on locomotor stimulant effects of these drugs when injected in rodents.

Wheel Activity after MDPV or MA

Mean (N=7; ± SEM) wheel activity of male rats after inhalation of methamphetamine (100 mg/mL in PG), MDPV (100 mg/mL in PG) or the PG alone for 40 minutes. Gray shaded symbols indicate a significant difference from PG. A significant difference from the 30 min time point within an inhalation condition is indicated with *, and a difference from MA with #, for corresponding time points.

Another study in the paper investigated effects of vapor inhalation of the MA and MDPV on wheel activity. Under vehicle treatment, rats run more on the wheel in the first 30 minutes and then run significantly less for the subsequent 90 min of a 2 h session. When allowed to use the wheel after vapor exposure to MA or MDPV, activity is initially suppressed and then rebounds as the session continues. Presumably, the initial suppression of wheel activity is related to the increase in chamber locomotor activity found in the radiotelemetry study- if the rats were running around the cage they might be unlikely to enter the wheels. In the study depicted, MDPV caused significantly more activity than vehicle inhalation 60-90 min after finishing the vapor inhalation. MA in this experiment did not increase activity compared with vehicle, however activity was significantly higher in the last thirty minutes than the first 30 min after MA inhalation. Additional data found no significant effects of 40 min of inhalation of either MDPV or MA at a 25 mg/mL concentration and a third study found elevations of wheel activity 90-120 min after a 20 min inhalation of MA (100 mg/mL). In total, the wheel activity data confirm dose-dependent effects on a second measure of locomotion.

Overall, this study is the first to demonstrate behavioral effects of e-cigarette type inhalation delivery of psychostimulants to rats. This further validates our model and encourages additional study of the risks of e-cigarette delivery of psychoactive substances in laboratory animal models.
J. D. Nguyen, S. M. Aarde, M. Cole, S. A. Vandewater, Y. Grant and M. A. Taffe. Locomotor stimulant and rewarding effects of inhaling methamphetamine, MDPV and mephedrone via electronic cigarette-type technology, 2016, accepted article preview 9 June 2016; doi: 10.1038/npp.2016.88 [ PublisherSite ][ PubMed ]

Funding and Disclosures for this paper: This work was funded by support from the United States Public Health Service National Institutes of Health (R01 DA024105, R01 DA024705, R01 DA035281 and R44 DA041967) which had no direct input on the design, conduct, analysis or publication of the findings. Subsets of these data were first presented at the Experimental Biology meeting in 2015 and the Annual Meeting of the Society for Neuroscience 2015. Development of the apparatus was supported by La Jolla Alcohol Research, Inc and MC is inventor on a patent for this device. SAV consults for La Jolla Alcohol Research, Inc.

May 31, 2016

Inhalation model for evaluation of e-cigarette based delivery of THC

Filed under: Cannabis, E-cigarettes, Vape inhalation — mtaffe @ 11:13 am

Our interest in developing inhalation techniques for delivering cannabinoids, most especially the primary active constituent Δ9-tetrahydrocannabinol (THC), to rats arose from the realization that increasing numbers of people were using non-combusted methods for inhalation. When we started this project there were no studies using a Volcano type or e-cigarette type of system to deliver THC to rodents. Of course the majority of cannabis consumption has always been via smoke inhalation and there have been a few prior studies in laboratory models, primarily from the Lichtman laboratory. Our focus was therefore on the non-combustible techniques stemming from the evidence of personal acquaintance reports, a plethora of Web sites advertising methods, an emerging literature showing human practices (Giroud et al, 2015, Morean et al, 2015) and from suggestions that e-cigarette delivery may offer a safer alternative for medical cannabis consumers (Varlet et al, 2016).

The following has been recently accepted for publication in Neuropharmacology.
Inhaled delivery of Δ9-tetrahydrocannabinol (THC) to rats by e-cigarette vapor technology. Jacques D. Nguyen1, Shawn M. Aarde1, Sophia A. Vandewater1, Yanabel Grant1, David G. Stouffer1, Loren H. Parsons1, Maury Cole2 and Michael A. Taffe1
1Committee on the Neurobiology of Addictive Disorders; The Scripps Research Institute; La Jolla, CA, USA
2La Jolla Alcohol Research, Inc; La Jolla CA, USA

Schematic of the inhalation chamber

Schematic of the inhalation chamber

Our exposure model for this study involved a standard sized rat housing chamber with a sealed lid- these are commercially available for a variety of purposes. The chamber was plumbed for regulated airflow and incorporated the ability to deliver and exhaust the vapor from an e-cigarette type device. We tried a number of commercial tanks in this study, one specific example is the Protank 3 Atomizer by Kanger Tech. The overall approach for delivery to rodents is under patent to La Jolla Alcohol Research, Inc which has been instrumental in developing the equipment for our studies. This collaboration has resulted in a number of studies so far, this one is the first to be published. The company has also recently been awarded an SBIR Phase II Grant (R44 DA041967) to further develop and enhance commercialization of the device.

Dosing control was managed in this system with the manipulation of a number of variables. One of the major goals of this study was to determine how the dose delivered to the animal might be regulated by altering these vaping parameters. The concentration off the drug (in this case Δ9-tetrahydrocannabinol (THC) may be altered in the propylene glycol (PG) vehicle (aka “e-juice”)- our standard condition for this study was 200 mg/mL but effects from 25-100 mg/mL were also explored and showed a concentration-dependent effect when the puffing and inhalation duration was held constant. The puffing regimen and duration of inhalation exposure can be altered as well. In most of our studies we delivered 10-s vapor puffs with 2-s intervals between them every 5 minutes for durations of 10-40 min (approximately 0.125 ml was used in a 40 min exposure session). This study established that for a given THC concentration in the vehicle, the duration over which animals were exposed could produce graded effects consistent with a dose-dependent pattern.

Mean (N=8; ±SEM) temperature response to THC inhalation for 10, 20 or 30 min in 5 min intervals. A significant difference from both the baseline and the other exposure conditions is indicated by the open symbols and from the 10 min condition by the shaded symbols.

Mean (N=8; ±SEM) temperature response to THC vapor inhalation for 10, 20 or 30 min in 5 min intervals. A significant difference from both the baseline and the other exposure conditions is indicated by the open symbols and from the 10 min condition by shaded symbols.

This first figure depicts THC-induced reductions in body temperature produced by THC inhalation for 10-30 minutes in male rats, using a radiotelemetry system for reporting temperature every 5 minutes. The figure depicting this experiment in the paper depicts 30 min averages but I really like this version so I’m including it here. [For those concerned with statistics, see below.] The points to the left indicate a pre-inhalation baseline interval in the telemetry recording chambers. There is a break in the series because we didn’t record them during vapor inhalation (see our SFN 2014 poster presentation for a pilot study recording during inhalation). The main point here is that 10 min of inhalation doesn’t change body temperature, 30 min has a major hypothermic effect and 20 min produces an intermediate effect. Thus, this system is able to produce dose-dependent effects that are so helpful for interpretation of behavioral pharmacology studies. We show in the paper that i.p. injection of 10-20 mg/kg THC produces a temperature nadir similar to that produced by 20-30 min of inhalation (see a blog post on our 2015 paper on temperature responses to injected THC for comparison). Our telemetry measure of locomotion did not show any suppression in this experiment but we do show a suppression of activity in both males and females in Figure 2 of the paper. There was some evidence that female rats are more sensitive to the hypothermia induced by, e.g., THC 50 mg/mL for 30 min in this study, likely because of their lower bodyweight compared with the male rats.

Mean tail-flick latency measured following 20 min of exposure with pre-treatment with SR141716 (SR; 4 mg/kg, i.p.) or Vehicle (N=8). Significant differences compared with respective vehicle condition are indicated by *, differences from SR+THC vapor by #.

Mean tail-flick latency measured following 20 min of exposure with pre-treatment with SR141716 (SR; 4 mg/kg, i.p.) or Vehicle (N=8). Significant differences compared with respective vehicle condition are indicated by *, differences from SR+THC vapor by #.

One of the major tests of cannabinoid activity in a rodent is a decrease in nociception. The ability to sense a noxious stimulus was tested by placing the tail in a 52°C water bath and timing the latency for it to flick it out. The experiment in the figure depicts a study in which the animals were exposed to PG or 200 mg/mL THC for 20 min with and without prior treatment with the cannabinoid 1 receptor antagonist SR141716 (Rimonabant; 4 mg/kg, i.p.). This shows that THC inhalation extends the time for the animal to flick its tail out of the warm water and that this effect is blocked with the antagonist pre-treatment. Although not shown here, the magnitude of the latency change caused by vapor inhalation of THC was the same as that produced by a 10 mg/kg THC i.p. injection. This comparability of the effect of inhaled versus injected THC was also highly consistent with data we generated showing that blood concentrations of THC were very similar when observed 30 min after THC (200 mg/mL) inhalation or 30 min after 10 mg/kg, i.p. injection.

In summary, we’ve created a new model for evaluating inhaled delivery of THC to rats via an e-cigarette type of method. We’ve found significant effects on three of the four traditional measures (Tetrad Test) of cannabinoid activity in a rodent- hypothermia, hypolocomotion and antinociception (the fourth, catalepsy, was not assessed). Effects were of comparable magnitude to those produced by intraperitoneal injection, allowing these data to be placed in context with prior studies using injection delivery of THC. There are several advantages of this model, most pertinently the more rapid timecourse of effects compared to what is produced with an i.p. injection.

Jacques D. Nguyen, Shawn M. Aarde, Sophia A. Vandewater, Yanabel Grant, David G. Stouffer, Loren H. Parsons, Maury Cole and Michael A. Taffe. Inhaled delivery of Δ9-tetrahydrocannabinol (THC) to rats by e-cigarette vapor technology, 2016, Neuropharmacology, in press. DOI: 10.1016/j.neuropharm.2016.05.021 [PubMed]

Funding and Disclosures for this paper: This work was funded by support from the United States Public Health Service National Institutes of Health (R01 DA024105, R01 DA035281 and R44 DA041967) which had no direct input on the design, conduct, analysis or publication of the findings. Development of the apparatus was supported by La Jolla Alcohol Research, Inc and MC is inventor on a patent for this device. SAV consults for La Jolla Alcohol Research, Inc.

[Stats for body temperature figure: The ANOVA of the five minute temperature intervals (including three baseline samples, -15 to -5, and 40-180 min following initiation of vapor) confirmed main effects of Time post-initiation [F (32, 224) = 38.36; P < 0.0001], Duration of vapor exposure [F (2, 14) = 38.66; P < 0.0001] and the interaction of factors [F (64, 448) = 16.64; P < 0.0001].
The Tukey post-hoc test confirmed significant temperature reductions after 20 (40-70 min post-vapor initiation) or 30 min (40-155 min post-vapor initiation) of vapor exposure to THC compared with each of three baseline samples. Furthermore, the post-hoc test confirmed that temperature after all three exposure durations differed significantly from each other from 40-150 and 160-165 min following vapor initiation. Significant differences in temperature between 10 and 30 min vapor exposures were confirmed for the entire post-vapor duration.]

April 10, 2016

Caffeine and Cathinones

Filed under: Cathinones, MDPV — mtaffe @ 3:06 pm

An interesting presentation at the recent 2016 annual meeting of ASPET (part of Experimental Biology) from Gregory Collins reported on the interactive effects of caffeine with other stimulant drugs, including MDPV. It appears that Dr. Collins has recently been funded by the NIH to work on just such interactions of caffeine with MDPV and methylone.

I was interested about the premise here, due to to a longstanding interest in MDMA and its effects on people. In a short summary, the street “Ecstasy” supply has been notoriously contaminated with all sorts of psychoactive compounds other than MDMA. The testing site was set up in part as a warning/surveillance system. At present, if you go to advanced search and identify materials they have tested that return MDMA and nothing else you find 1281 (105 in 2016 to date) entries. If you search for items they have found positive for MDMA and at least one other psychoactive constituent you find 659 (17 in 2016 to date) items. This is 34% of the total number of MDMA-positive samples. Undoubtedly this has ebbed and flowed over the years but my recollection in doing similar searches now and again is that it has generally been the case that at least half of the tested items have been pure MDMA. [As always, do note that there is a selection factor for who bothers to send samples in to ecstasydata for testing. Likely to be non-random in terms of users (I would expect repeat submissions from afficionados or other highly interested and aware parties) and in terms of chances of non-MDMA constituents (I am making an assumption here that items of suspicious subjective effects/experiences are more likely to be submitted.).]

Returning to the caffeine story, I note that ecstasydata returns 347 items containing both MDMA and caffeine, representing 18% of the total MDMA-positive population or 53% of the contaminated subset.

Moving on, we can searched for MDPV only (9 items), MDPV plus some other psychoactive (28 items, 76% of MDPV -containing) and MDPV plus caffeine (17 items, 46% of all MDPV -containing, 61% of MDPV +other). Wondering if this was a function of MDPV really not being very Ecstasy-like and therefore being unlikely to turn up by itself in the population who are sending samples to ecstasydata, I looked at alpha-PVP (14 pure, 3 alpha-PVP+other and 0 with caffeine). Hmmm.

I also searched for methylone only (64 items), methylone plus some other psychoactive (30 items, 32% of methylone-containing) and methylone plus caffeine (7 items, 7.4% of all methylone-containing, 23% of methylone+other).

So the rationale for looking at caffeine interactions for methylone (and MDMA for that matter) is pretty good, even if we must recognize that the majority (going by this particular measure of epidemiology) of the street Ecstasy / Molly / methylone is probably pure MDMA or pure methylone.

The MDPV supply looks highly contaminated with caffeine (46%) but there is, to my view, a slightly bigger problem with assuming submissions reflect the drug that is available on the street. Going by media reports, MDPV (and alpha-PVP) seem to be very common in people that fit the profile of (or are reported to be) those who use prototypical stimulant drugs such as methamphetamine and cocaine. They seem less similar to the clubbing/raving Ecstasy using consumer. On average. This would, potentially, mean that is getting submissions from a much less representative part of those people exposed to MDPV versus methylone.

This is, of course, barely better than speculation and it will require information from other sources, such as DEA legal seizure activities, to further explore this issue.

Still, I think we can conclude that caffeine interaction with cathiones are of interest, even if they are not perhaps the first order of business (i.e., the effects of each drug by itself).

It was in the session in the afternoon of Mon the 4th of April. It was organized by Li and Gerak and titled “Division for Behavioral Pharmacology Symposium: Quantitative Pharmacological Analysis of In Vivo Data and Its Implications in CNS Drug Discovery”.

Predicting Additivity: Abuse—Related Effects of “Bath-Salt” Mixtures
Gregory Collins—South Texas Veterans Hlth. Care Syst.—Audie L. Murphy VA Hosp.

March 2, 2016

Escalation of mephedrone IVSA under long-access conditions

Filed under: 4-MMC/Mephedrone, Cathinones, Methylone — mtaffe @ 10:41 am

StructureFig-MDMA-Methylone-MephedroneWe continue to be interested in assessing the relative abuse liability of new synthetic cathinone stimulants that pop up in recreational users. The most established entities such as mephedrone (4-methylmethcathinone; 4-MMC) and methylone (3,4-methylenedioxymethcathinone) are of particular interest to our research because they share some pharmacological properties with MDMA (Ecstasy), constituting a class of stimulants sometimes called entactogens. As you can see from the structures at the left, methylone is the direct cathinone cousin of MDMA– the ketone group on the beta carbon is the element that differentiates a cathinone from an amphetamine.

The 2013 and 2014 NFLIS showed that methylone may be more common than MDMA in the US and mephedrone continues to be popular in the UK. Our recent papers (Vandewater et al, 2015 and Creehan et al, 2015) compared the intravenous self-administration (IVSA) of methylone, mephedrone and MDMA within relatively short (2 h) daily training sessions in male and female rats, respectively. We found that rats will IVSA greater amounts of mephedrone compared with MDMA with methylone falling in between the other two. One prior study had found that rats will IVSA methylone at very high rates, more like a traditional stimulant than like MDMA, thus we were curious to further examine potential differences.

It has been shown that relatively long (6 h) daily sessions of access to cocaine (Ahmed and Koob, 1998; Larson et al., 2007) or methamphetamine (Kitamura et al., 2006; Schwendt et al., 2009) IVSA results in both higher daily drug intake and a progressive increase across sessions (termed “escalation”) relative to animals trained only in 1-2 h sessions. This has been conceptualize as a better rat model of the state of human stimulant addiction, as opposed to the interpretation of mere drug liking. In contrast, a prior study found no difference in total session intake of the entactogen class stimulant MDMA between long (6 h) and short (2 h) access groups over the first 11 sessions (Schenk et al., 2003). This seemed a little unusual to us and we showed in Vandewater et al (2015) that when run in the dark cycle (the rats’ active period of the day), male rat IVSA of MDMA
Fig1-LgA-ShA-MethyloneMMC-Revunder 6 h daily access conditions is higher than under 2 h access conditions. So we conducted a new study to determine how the rat IVSA of the two entactogen (MDMA-like) cathinones would fare under 6 h access conditions. The following has been recently accepted for publication:

Nguyen, J.D., Grant, Y., Creehan, K.M., Vandewater, S.A. and Taffe, M.A. Escalation of intravenous self-administration of methylone and mephedrone under extended access conditions., Addict Biol, 2016, in press. [ Publisher Site ][ PubMed ]

This study was conducted in male rats, trained to intravenously self-administer methylone or mephedrone in Short Access (ShA; 2 h) or Long Access (LgA; 6 h) sessions. The training dose was 0.5 mg/kg per infusion for each drug. The mean (SEM) number of infusions obtained by the four different groups is depicted in the first figure from the paper, reproduced here. There are two takeaway messages. First, the total daily intake is higher for the LgA groups for both drugs. Secondly the mephedrone LgA group obtained more infusions than did the methylone LgA group. [Significant differences from the first three sessions within group are indicated by shaded symbols. Significant differences between Access groups within a drug are indicated by * and differences between drugs, within Access condition, by †.] This further confirms, as did our MDMA LgA study, that there is nothing weird about entactogen IVSA under LgA vs ShA conditions- rats take more drug in 6 h than in 2 h. It also emphasizes that rats will take more mephedrone than methylone.

First 2 h intake of LgA groups

First 2 h intake of LgA groups Significant differences from the first three sessions within group are indicated by shaded symbols. Significant differences from MDMA are indicated by * and from methylone by †.

In some senses that is a trivial observation and one of the key measures of rats having achieved a state more similar to the addicted human is whether the LgA animals gradually take more drug in the time interval commensurate with the ShA animals- in our case the initial two hours of their 6 h session. This graph depicts the first 2 h infusions for the mephedrone (4-MMC) and methylone trained animals from this new study as well as the similar data for the MDMA 6 h animals from* Vandewater et al (2015). As you can see in this graph, the three drugs are clearly distinguished from each other on this key measure of “escalated” drug seeking behavior. First 2 h intake of MDMA is relatively stable across this training interval, first 2 h methylone intake increases across sessions and first 2 h mephedrone intake increases even more. The conclusion we reach from this is that both methylone and mephedrone have enhanced abuse liability compared with MDMA and they are more likely to lead to patterns of relatively uncontrolled or compulsive drug use in humans.

We also took this new study one step farther by asking how hard the four groups would work for a given magnitude of drug infusion. We do this by using a Progressive Ratio procedure. In the normal training the animals have a Fixed Ratio (as it is called) of lever presses to infusions. In this study, it was FR1 meaning they had only to make one press on the drug-associated lever to get an infusion of drug. In the PR procedure, the number of responses required for each successive drug infusion is progressively increased throughout the session (e.g., 1, 2, 4, 8, 16….). Eventually the rats will stop obtaining drug infusions. The last ratio they completed for a drug infusion is called the “breakpoint”, indicating how many lever presses they made for that final infusion. We also varied the available drug dose per infusion in a random order across session. Thus, we obtain an estimate of how hard each group will work for a given dose of drug. In order to directly compare liability for stimulant drug seeking across the groups we used the same two test drugs, methamphetamine (MA) and mephedrone/4-MMC.

The top panels contrast breakpoints during methamphetamine (MA) substitution in A) ShA and B) LgA groups. The bottom panels contrast breakpoints reached during mephedrone (4-MMC) dose substitution in C) ShA and D) LgA groups. Significant differences from vehicle control within-group are indicated by *, from the 0.125 dose by # and from all other dose conditions by %. Significant differences from all other groups, within a dose condition, are indicated by †.

The top panels contrast breakpoints during methamphetamine (MA) substitution in A) ShA and B) LgA groups. The bottom panels contrast breakpoints reached during mephedrone (4-MMC) dose substitution in C) ShA and D) LgA groups. Significant differences from vehicle control within-group are indicated by *, from the 0.125 dose by # and from all other dose conditions by %. Significant differences from all other groups, within a dose condition, are indicated by †.

This direct comparison study found that the rats trained to IVSA mephedrone under LgA conditions worked harder for either their training drug mephedrone or MA than did any other the other groups. There was no similar LgA/ShA difference for methylone-trained rats. This further emphasizes the substantial abuse liability of mephedrone/4-MMC. This drug appears to be quite similar to classical stimulants like methamphetamine and cocaine in this respect.

It continues, therefore, to be a mystery why a drug which releases serotonin in the nucleus accumbens to a greater degree than it releases dopamine would be such an effective reinforcer in the rat IVSA assay. There is considerable evidence, beyond just the fact that rats are pretty reluctant to IVSA MDMA compared with methamphetamine, that increasing serotonergic over dopaminergic effects of drugs is going to decrease the effectiveness as a reinforcer. And therefore decrease the liability for repeated use patterns. One of the scientific benefits of looking into the rewarding properties of some of these new cathinone stimulants is precisely this. It can suggest places where the existing dogma, based on the amphetamines in large part, may need some reconsideration.

*We originally submitted this paper including a comparison with the prior MDMA group, cited and referenced so that there was no confusion as to where the data came from. First, a reviewer mentioned that this may be inappropriate. Second, the handling Editor noted that this was against journal policy. After a bit of back and forth with the Editor over the reasons for making this comparison we had to cave and remove the direct (i.e. including statistical comparisons) contrast with those prior data.

December 17, 2015

Daily Marijuana Use In Adolescents

Filed under: Cannabis — mtaffe @ 9:38 am

The Monitoring the Future Study of longitudinal drug trends releases the latest updates in December each year. The website has links to the updated tables and a few selected Figures.
2015-DailyPot-MtFThis graph depicts the percentage of 8th, 10th and 12th grade students in the US who indicate that they have used marijuana at least 25 days out of the past 30 (their definition of “Daily” in the survey). For those who want precision, the 2015 numbers are 1.1% for 8th graders, 3.0% for 10th graders and 6% for 12th graders. You may be inclined to view single digit percentages as no big deal. It seems like a small number. One percent? Hardly worth talking about, right?

Except if, as I do, you have children in one or more of these age ranges. And you go so far as to become acquainted with some of your children’s friends and schoolmates. And acquainted with some of their parents. What you quickly realize is that you know at least 50 kids within your child’s circle at least a little bit. Enough to know their name and something about them. Maybe 100. And your kid probably knows at least 200 fairly well.

So look around? Which 1 of these kids is already smoking pot every day in 8th grade? Which 6 are at the end of high school?

EVERY day. Smoking pot. And the odds are very good that this kid is smoking multiple times a day. Staying high for extended periods.

Remember this when you think dismissively to yourself that “that 7th grader looks stoned, hahaha” as I once did before catching myself. I should know better. And even I don’t really think specific kids are the ones smoking pot every day. Until I think about it.

But the stats say they are. Some of them.



It is also the case that 6.5% of 8th graders, 15% of 10th graders and 21% of 12th graders have used marijuana at least once in the past month. 35% of 12th graders in the past year. This means the daily use rate is 17% of 12th graders who have tried marijuana at least once in the past year.

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