There was a press release issued by NIDA today, trumpeting a report of a Phase III trial of medication for methamphetamine use disorders. As a very brief recap, we have no approved medications to assist with methamphetamine (or any psychostimulant) use disorder and the distressing health consequences for addiction to cocaine, methamphetamine and some other related drugs are very severe. According to 2019 data from SAMHSA (Table 5.14A), some 534,000 folks over age 25 were in treatment for cocaine use disorder, 566,000 for methamphetamine and this contrasts with 594,000 for heroin, 552,000 for marijuana and 1,957,000 for alcohol. Table 5.1A points out that some 756,000 of folks in this range probably had a cocaine use disorder, 904,000 had a methamphetamine use disorder and 10,959,000 had an alcohol use disorder.

Not everyone who needs treatment gets it. Not even close.

Hunter Biden, the President’s second (and still living) son has recently published a memoir detailing his struggles with addiction to cocaine and alcohol. Joe Biden, the President, issued a recent press release calling for a $6.5 billion launch of an Advanced Research Projects Agency for Health (ARPA-H) within the National Institutes of Health.

With an initial focus on cancer and other diseases such as diabetes and Alzheimer’s, this major investment in federal research and development will drive transformational innovation in health research and speed application and implementation of health breakthroughs.

Notably missing is any prominent mention of substance use disorder in ARPA-H.

On the relative scale of progress in treating cancer and diabetes, and yes even Alzheimer’s, I would argue that treatments for substance use disorders have been woefully under researched. Funding has lagged for the development of treatments and medications both in the public and private sectors. This means novel discovery, of course, but the real glaring deficit is in the routine churning of clinical trial after clinical trial for evaluating pretty run of the mill stuff. As they did in this recent Phase III trial.

Methamphetamine, as they say, is a helluva drug. From Brecht and Herbeck, 2014, we see the following relapse survival curve for a sample of methamphetamine users admitted to the Los Angeles County substance use treatment system. the followup period ranged from 22-90 months over which 23% maintained abstinence from methamphetamine. That means 77% relapsed, with a range of 0-79 months until relapse. As you can see from the below, 36% returned to methamphetamine use immediately upon discharge (Nb, this is not a sample selected for desire to quit), 14% more relapsed by 6 months and a total of 61% had relapsed within a year of entry. The good news, if there is any, is that this should be low hanging fruit. Anything, anything at all, that seems to work will be a huge gain versus the situation at present.

The new trial conducted by Trivedi et al. found that depot injection of naltrexone combined with daily oral buproprion (a cathinone-derivative, aka “bathsalt”) was effective, versus placebo control, in treating methamphetamine use disorder.


Meaning that within a population of methamphetamine users with “moderate to severe” use disorder who intended to quit, 11.4% responded. Where a response was 3 out of four urine samples negative for methamphetamine during weeks 11-12. Only 1.8% in the placebo group had this “response”. Let’s round that out to 10% efficacy.

Now, the glass is most emphatically half full. Ten percent is not very impressive sounding but it is something. It is some improvement for some folks. Ten percent of the ~904,000 estimated with a methamphetamine use disorder is a lot of people and their families that have improved lives. We are moved by the stories of single individuals- like Hunter Biden, and Nic Sheff and William C. Moyers. Let us apply that same empathy we feel for these men and their relative success at recover to each and every other person with a stimulant use disorder.

And we have nowhere to go but up, with discovery of any additional strategies that, btw, likely will also help with cocaine use disorder.

Do we need DARPA-like innovation? of course. Anti-drug vaccines (something I’ve worked on, for disclosure) have been languishing in a twilight of basic biological efficacy but need a big kick in the pants to advance to real-world efficacy. Wearable technology has several immediately imaginable future uses. Deep brain stimulation. TMS. Individualized therapy based on genotyping. There is no reason to think that we could not go big with ARPA-H for substance use.

It is more than a little bothersome that Joe Biden, who so explicitly ties his interest in Cancer Moonshots and the like to the fate of his older son, does not exhibit the same motivations for the trials of his younger son. Who, btw, is not dead and is at continual risk of relapse given his history.

Trivedi MH, et al. Trial of Bupropion and Naltrexone in Methamphetamine Use Disorder. New England Journal of Medicine. January 14, 2020.

If I’m going to bash a journalist when she writes something horrible about drug abuse, I must take pains to congratulate her when she writes something pretty good.

Maia Szalavitz’ latest “Of course Marijuana addiction exists and it’s (almost) all in your head” is actually not bad.
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Ok, ok, I have no actual data on this. But if I had to pick one thing in substance abuse science that has been most replicated it is this.

If you surgically implant a group of rats with intravenous catheters, hook them up to a pump which can deliver small infusions of saline adulterated with cocaine HCl and make these infusions contingent upon the rat pressing a lever…

Rats will intravenously self-administer (IVSA) cocaine.

This has been replicated ad nauseum.

If you want to pass a fairly low bar to demonstrate you can do a behavioral study with accepted relevance to drug abuse, you conduct a cocaine IVSA study [Wikipedia] in rats. Period.

And yet. There are sooooo many ways to screw it up and fail to replicate the expected finding.

Note that I say “expected finding” because we must include significant quantitative changes along with the qualitative ones.

Off the top of my head, the types of factors that can reduce your “effect” to a null effect, change the outcome to the extent even a statistically significant result isn’t really the effect you are looking for, etc

  • Catheter diameter or length
  • Cocaine dose available in each infusion
  • Rate of infusion/concentration of drug
  • Sex of the rats
  • Age of rats
  • Strain of the rats
  • Vendor source (of the same nominal strain)
  • Time of day in which rats are run (not just light/dark* either)
  • Food restriction status
  • Time of last food availability
  • Pair vs single housing
  • “Enrichment” that is called-for in default guidelines for laboratory animal care and needs special exception under protocol to prevent.
  • Experimenter choice of smelly personal care products
  • Dirty/clean labcoat (I kid you not)
  • Handling of the rats on arrival from vendor
  • Fire-alarm
  • Cage-change day
  • Minor rat illness
  • Location of operant box in the room (floor vs ceiling, near door or away)
  • Ambient temperature of vivarium or test room
  • Schedule- weekends off? seven days a week?
  • Schedule- 1 hr? 2hr? 6 hr? access sessions
  • Schedule- are reinforcer deliveries contingent upon one lever press? five? does the requirement progressively increase with each successive infusion?
  • Animal loss from the study for various reasons

As you might expect, these factors interact with each other in the real world of conducting science. Some factors you can eliminate, some you have to work around and some you just have to accept as contributions to variability. Your choices depend, in many ways, on your scientific goals beyond merely establishing the IVSA of cocaine.

Up to this point I’m in seeming agreement with that anti-replication yahoo, am I not? Jason Mitchell definitely agrees with me that there are a multitude of ways to come up with a null result.

I am not agreeing with his larger point. In fact, quite the contrary.

The point I am making is that we only know this stuff because of attempts to replicate! Many of these attempts were null and/or might be viewed as a failure to replicate some study that existed prior to the discovery that Factor X was actually pretty important.

Replication attempts taught the field more about the model, which allowed investigators of diverse interests to learn more about cocaine abuse and, indeed, drug abuse generally.

The heavy lifting in discovering the variables and outcomes related to rat IVSA of cocaine took place long before I entered graduate school. Consequently, I really can’t speak to whether investigators felt that their integrity was impugned when another study seemed to question their own work. I can’t speak to how many “failure to replicate” studies were discussed at conferences and less formal interactions. But given what I do know about science, I am confident that there was a little bit of everything. Probably some accusations of faking data popped up now and again. Some investigators no doubt were considered generally incompetent and others were revered (sometimes unjustifiably). No doubt. Some failures to replicate were based on ignorance or incompetence…and some were valid findings which altered the way the field looked upon prior results.

Ultimately the result was a good one. The rat IVSA model of cocaine use has proved useful to understand the neurobiology of addiction.

The incremental, halting, back and forth methodological steps along the path of scientific exploration were necessary for lasting advance. Such processes continue to be necessary in many, many other aspects of science.

Replication is not an insult. It is not worthless or a-scientific.

Replication is the very lifeblood of science.

*rats are nocturnal. check out how many studies**, including behavioral ones, are run in the light cycle of the animal.

**yes to this very day, although they are certainly less common now

The recent fax (yes, they still call it this despite it arriving via email attachment) from CESAR (Vol 21, Issue 40; October 09, 2012) puts us back on an occasional theme of this blog.
They have adapted data from the latest update from SAMHSA’s National Household Survey on Drug Abuse. This figure shows the number of past year users of selected illicit/recreational drugs.
Interestingly, marijuana use continues to trend up from the approximate plateau of 2002-2007, while use of cocaine is trending downward. Even the nonmedical use of prescription drugs (which has been a big problem overdose-wise) is relatively flat. Rounding slightly, we’re looking at some 30 million past year users of marijuana compared with 4 million past year users of cocaine.

So why is this interesting? Well, as we’ve covered in the past the notion of conditional probability of dependence is a key issue for parents and policy makers and yet we have really poor estimates on that. Direct studies are usually limited in scope and the big-scale epidemiological stuff is too imprecise- i.e., rarely are there good diagnostics of dependence. So we sometimes have to infer things based on, e.g., daily use rates versus annual rates. Something like that. Fortunately the more precise studies and the broader interpretive efforts tend to agree.

Roughly speaking the conditional probability of alcohol dependence is on the order of 4%, for cannabis on the order of 8-10% and for stimulants, including cocaine, on the order of 15%.

So, applying these rough estimates to the past-year data above, we end up with something on the order of 600,000 dependent on cocaine and 2,400,000 dependent on marijuana. If you dropped the estimate of conditional probability for marijuana to the 4% of alcohol, you still end up with 1.2M people dependent on marijuana.

My point, as always, is that the definition and scope of a “drug dependence problem” is going to depend on frame of reference. One important frame of reference in my view is the number of people who are affected. This, btw, is why we think of alcohol dependence as such a huge problem even though just about every estimate suggests the conditional probability of dependence is one of the lowest. Because the percentage of the entire population exposed to alcohol on a regular basis is so large, the number of people who are dependent is relatively large.

In a Twittersation today we arrived at the possibility that being a heroin user is a unique lyrical stimulus. The specific assertion is that while a lot of so-called ‘crack rap’ discusses *selling* crack cocaine, there are no lyrics about being a crack *user*.

So let’s broaden the call…can you think of songs that are about using drugs other than heroin? Let’s leave alcohol aside for the moment, there are a bajillion songs about drinking.

Is Exercise Addictive?

September 7, 2010

Athletes, particularly those that engage in the sustained-activity aerobic sports such as running, cycling and Nordic skiiing, are occasionally to be found describing their chosen physical activity as addictive. Some of them talk about symptoms of anxiety and depression and discomfort when not permitted to engage in their usual level of activity due to injury or other life circumstances. These can sound suspiciously like syndromes associated with addictive drugs, to those of us who are familiar with the type and aware that drug “withdrawal” is not limited to the dramatic symptoms associated with withdrawal from a substantial intravenous heroin addiction.

Is this real, though? Is there something neurobiologically similar to drug addiction about what can happen to the brain in the course of a sustained aerobic exercise habit? To answer these questions it helps, of course, to have an animal model, preferably one that has a lot of similarity to our drug-abuse models.

ResearchBlogging.orgEikelboom and Lattanzio published two papers in 2003 that proposed a possible model of exercise-dependence using activity wheels in rats. You will be familiar with the notion that hamsters, rats and mice  will run on a treadwheel under single-housed conditions from your local pet store. Drop by one on your way home today if you don’t know what I mean. There is also an older behavioral literature that shows that wheel access can act as a reinforcer in laboratory rats- they will press a lever to get a brief interval of wheel running. Manipulating the length of time they can run on the wheel acts, to a first approximation, like manipulating the number of food pellets delivered in a traditional setup.

But just because something is chosen voluntarily and acts as a reinforcer does not necessarily mean that it can model compulsive, repetitive behavioral patterns. It does not necessarily mean that it will tap into the disruption of brain reward pathways and mechanisms that is the hallmark of substance dependency. For this we need a little more evidence, starting with behavior and moving into neurobiology as the evidence mounts.

The background for the Lattanzio and Eikelboom work is  the Ahmed and Koob 1998 paper which has become hugely influential in substance abuse models. The short version was that instead of permitting rats an hour of access to intravenous cocaine each day, they permitted the animals 6 hours of access per day. They observed that the 6-hr (termed “Long Access”) group took more cocaine than animals run in the traditional 1-hour sessions, perhaps unsurprisingly given the increased opportunity. More importantly, as the sessions of longer access continued, the rats took an ever increasing amount including in the first hour of access. Not only that, but the Long Access group took more cocaine in the very first 10 minutes of the session.  This seminal paper has been followed by a lot of additional evidence that this change in the Long Access group is brought about by lasting disruptions of common reward mechanisms.

[Sidebar: You will recall from my posts trying to work out the conditional probability of dependence, that I am not a fan of simple, drug-feels-good models of drug reinforcement; even though they have a place. The short version of my thinking is that we already know from the human epidemiology that a large fraction of the individuals who find that drugs make them feel good do not go on to develop dependence, addiction or what we might term a drug problem. Animal models that move on from the simple feels-good stage of drug taking resonate more strongly with me.]

Lattanzio and Eikelboom set out to provide rats with longer and shorter access to wheel running and see if there was behavioral evidence of the sort of “escalation” that was reported by Ahmed and Koob.

In the first paper the authors compared wheel running in rats who had 24/7 access to the wheel to rats who had only a two hours of access for 24 days. As depicted in the first figure, wheel activity gradually increased in the 24/7 group across the three weeks of study. This is pretty consistent with my reading of the circadian literature and has some interesting implications with respect to the development of aerobic fitness. Activity in the 2-hour group remained stable.

So far so good. They also show that the 24/7 animals ran more in a comparable 2-hr interval, reminiscent of the key first-hour comparison in the drug self-administration paradigm.

Or, they sort of show that.

When they selected the same two-hour interval of the day in which the 2-hr group was exposed to the wheel, the 24-hr animals ran less. A lot less. Because. they. ran. the. 2-hr. group. in. the. light. cycle. Rats are nocturnal and more active in the dark. So when the authors (cherry) picked the most-active 2-hr interval in the 24/7 access group, then yes, it looked like an escalation across the days of training.

Frustrating. A hint of an escalation type of effect with longer access to the wheel but confounded by an inexplicable choice to run the short-access group in the light part of the cycle. Luckily, the authors did not leave off at this one study.

The second paper is more interesting because they run both the longer and shorter sessions in the dark, when rats are most active. In addition they are pitting 1 hr access against only 4 hours of wheel access, instead of a full 24 hrs. So it makes it a little more comparable to the typical drug self-administration experiment. These results are again consistent with escalation of wheel running. In Figure 2B they show that the 4-hour group’s wheel running in the first two hours of access increased substantially more with sequential training sessions in comparison with the 1-hour group’s running.

These papers are, to my eye, a good first attempt at a model. This is not the answer to whether exercise is addictive or becomes a compulsive behavior similar to drug self-administration. However it shows that we can now go on to ask additional questions which might answer the question. Are the brains of the longer-access rats changing in the same way that the long-access to cocaine rats’ brains change? Are they in a state of reward deficit (disrupted allostasis in the Ahmed/Koob handwaving) that generalizes across reinforcers?

If evidence develops for this, we can only then move on to the larger issues. Does a substantial history of exercise leave individuals at risk for reward-related disorders when they stop exercising? Are they at increased liability for compulsive eating or drug abuse? If so, what is the threshold? Etc. Really, there is a lot of fascinating research ahead on this topic.

I have a few current questions about the exercise physiology angle because I know there is a blogger or two around and about that might have some information. Are the physiological changes brought about by wheel running in laboratory rats similar to those we might expect from a human in aerobic conditioning training? The circadian literature shows pretty consistently, to my eye, that daily running in rats given 24/7 access to wheels increases over a several week interval to reach a sustained plateau of daily activity. This suggests that there are perhaps cardiovascular and muscular adaptations at play, in a word “fitness”. But then again the sort of exercise that results in human conditioning is sort of aversive at the start, isn’t it? We force ourselves to do it because we want to be fit or to race or whatever. We don’t do it because every step of the 6 mi run is pure bliss right off the couch, right? So why would rats voluntarily run themselves into this sort of conditioning effect?

Those of us who are looking at this from a perspective of reward mechanisms will eventually need to show that wheel “escalation” is not just a result of a conditioning effect which permits the rats to run for longer distances. Or for that matter a motor skill effect which permits them to tread the wheel bars more efficiently.

Disclaimer: See the Disclaimer page for the usual about my conflicts when it comes to drug abuse research topics. Also, I am professionally acquainted with some of the authors of the work under discussion in this post.

Literature Cited:
Ahmed SH, & Koob GF (1998). Transition from moderate to excessive drug intake: change in hedonic set point. Science (New York, N.Y.), 282 (5387), 298-300 PMID: 9765157
Lattanzio SB, & Eikelboom R (2003). Wheel access duration in rats: I. Effects on feeding and running. Behavioral neuroscience, 117 (3), 496-504 PMID: 12802878
Eikelboom R, & Lattanzio SB (2003). Wheel access duration in rats: II. Day-night and within-session changes. Behavioral neuroscience, 117 (4), 825-32 PMID: 12931966

I last broached the topic of immunization against drug use some time ago and I concentrated more on the ethical implications of vaccinating. I was being ever so slightly disingenuous because the current state of progress is not such that we need to consider such questions as:

Would you recommend it broad-spectrum for all children much like MMR?
Would you recommend parents be permitted to subject their drug abusing teen against his or her will?
Allow the courts to mandate inoculation?
Suppose it were made a condition of employment? This post was chosen as an Editor's Selection for ResearchBlogging.orgA recent paper by Martell and colleagues provides a nice opportunity to review the promise and limitations of immunopharmacotherapy for drugs of abuse. The rationale for such studies is pretty easy to grasp, although at present the results fall short of the lasting immunity you associate with childhood vaccines and even the seasonal flu shot. Drugs of abuse are molecules that do not generate any immune response because they are too small. The starting rationale is that if you create a drug mimic and attach it to something that will attract the attention of the immune system you might be able to generate antibodies that recognize the target drug.

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I read a Re-Twitt from our good blog friend Abel Pharmboy of Terra Sigillata which pointed to a most amazing bit of online drug information. The originator was @mjrobbins of The Lay Scientist blog*. The answer to “What are the most addictive drugs” on some Q/A site called blurtit. And dude, do they have answers! For example, the “addiction likelihood” of cocaine is 78%, of heroin is 87.5% and of crystal meth is 89.5%. Wow, what precision! And they cite some science-y sounding dudes including some that I recognize as being experts. Great stuff, all kinds of people want to know the objective addictiveness of different drugs right? From parents to policy makers, users to scientists.
…but what’s all this? The “addiction likelihood” of cannabis is 42%, of LSD is 32% and of psilocybin and mescaline are 16-18%? Hmm…..

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Nicholas Kristoff of the NYT has an Op-Ed Column up which questions the Drug War. When it comes to asking about the cost of incarceration and interdiction, I have no bloggable opinion. As my readers know, I don’t really delve into policy issues on this front.
My main problem is when Kristoff trots out the usual dismissal of the public health costs of de-criminalization and, in particular, resorts to an argument which is so disconnected from any logical reality it is laughable. Or it would be, if I couldn’t see otherwise intelligent people nodding along in agreement.

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2Figure 15b: Advanced emphysema in a
relatively young (36-year-old) woman with
a history of heavy cocaine abuse and unrelated
mitral valve disease. Chest CT scan reveals
diffuse advanced emphysema.

The latest news in the celebrity drug-abuse world is that Amy Winehouse’s dad has informed the press that she has early stage emphysema. Her publicist has also confirmed the report.

Although health problems related to drug abuse are nothing novel in the world of musical entertainment, emphysema in a 24-year old is unusual, to say the least.

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Perennial Playboy Magazine Top-Ten Party School San Diego State University is in the news following the arrest of some of its students on allegations of illicit drug dealing and drug possession. The San Diego Union Tribune is reporting:

Federal agents and SDSU police culminated a yearlong investigation into drug dealing around campus yesterday, …Ninety-six suspects, including 75 SDSU students, have been arrested on drug-related charges…The SDSU Police Department approached the DEA and county narcotics task-force officials for assistance in December, when it became clear that the trafficking was more widespread than it could handle.
Investigation seizures by the numbers (sidebar; SOURCE: SD County District Attorney’s Office)

  • 50: Pounds of marijuana
  • 4: Pounds of cocaine
  • 3: Semiautomatic handguns
  • 1: Shotgun
  • 48: Marijuana plants
  • 350: Ecstasy pills
  • 30: Vials of hash oil
  • $60,000: Cash

Sadly, the investigation was sparked by a drug-overdose fatality, albeit of an anonymous undergraduate rather than someone as famous as Heath Ledger or Len Bias. There is also another drug-overdose fatality caught up in this story.
I want to talk about Jennifer Poliakoff and Kurt Baker today.

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This week’s fax from the Center for Substance Abuse Research at the University of Maryland touches on an issue of continual interest, namely the determination of “how addictive” different drugs of abuse may be. As I have mentioned a time or two (or three) before, I believe this is an area where the scientific research tends to skirt a key issue. From my perspective, this is one of the hardest questions to answer on the basis of the available human data and the animal models tend to drive right over the essential concepts.
This week’s CESAR fax (sign up here) reports rates of discontinuation, continued use without dependence and dependence for most major drugs of abuse. These data can help us to answer the question of “how addictive” are various recreational drugs.

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I’m following up on some blogging resulting from a recent post of mine on the effect Len Bias’ death (apparently) had on population level perception of the riskiness of trying cocaine. This will verge on the type of link-vomitus that is much despised by the PhysioProf, so consider yourself warned!

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I have a tendency to refer to data from the Monitoring the Future study with some frequency. Unfortunately I’ve been too lazy to post the critical data figures for your entertainment. Until today DearReader.
One example of which I am particularly fond, is what I call the “Len Bias effect” on the public perception of “risk” associated with casual use of cocaine. I refer to this so often because of the casual sneering response I (and others of my approximate generation) retain for the “Just Say No” program championed by Nancy Reagan in the mid-80s. The MtF data suggest to me at any rate that our “gut feeling” that these types of programs are stupid should be more nuanced.

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