Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2016 Oct 1.
Published in final edited form as: Drug Alcohol Depend. 2015 Sep 2;155:16–23. doi: 10.1016/j.drugalcdep.2015.08.022

Effects of 7-day continuous d-amphetamine, methylphenidate, and cocaine treatment on choice between methamphetamine and food in male rhesus monkeys*

Kathryn L Schwienteck 1, Matthew L Banks 1,2,*
PMCID: PMC4582002  NIHMSID: NIHMS720556  PMID: 26361713

Abstract

Background

Methamphetamine addiction is a significant public health problem for which no Food and Drug Administration-approved pharmacotherapies exist. Preclinical drug vs. food choice procedures have been predictive of clinical medication efficacy in the treatment of opioid and cocaine addiction. Whether preclinical choice procedures are predictive of candidate medication effects for other abused drugs, such as methamphetamine, remains unclear. The present study aim was to determine continuous 7-day treatment effects with the monoamine releaser d-amphetamine and the monoamine uptake inhibitor methylphenidate on methamphetamine vs. food choice.In addition, 7-day cocaine treatment effects were also examined.

Methods

Behavior was maintained under a concurrent schedule of food delivery (1-g pellets, fixed-ratio 100 schedule) and methamphetamine injections (0-0.32 mg/kg/injection, fixed-ratio 10 schedule) in male rhesus monkeys (n=4). Methamphetamine choice dose-effect functions were determined daily before and during 7-day periods of continuous intravenous treatment with d-amphetamine (0.01-0.1 mg/kg/h), methylphenidate (0.032-0.32 mg/kg/h), or cocaine (0.1-0.32 mg/kg/h).

Results

During saline treatment, increasing methamphetamine doses resulted in a corresponding increase in methamphetamine vs. food choice. Continuous 7-day treatments with d-amphetamine, methylphenidate or cocaine did not significantly attenuate methamphetamine vs. food choice up to doses that decreased rates of operant responding. However, 0.1 mg/kg/h d-amphetamine did eliminate methamphetamine choice in two monkeys.

Conclusions

The present subchronic treatment resultssupport the utility of preclinical methamphetamine choice to evaluate candidate medications for methamphetamine addiction. Furthermore, these results confirm and extend previous results demonstrating differential pharmacological mechanisms between cocaine choice and methamphetamine choice.

Keywords: methamphetamine, choice, methylphenidate, cocaine, amphetamine

1. Introduction

Methamphetamine addiction is a significant and global public health problem. For example, methamphetamine was the most frequently identified phenethylamine and the most frequently reported compound by federal Drug Enforcement Agency laboratories (2014). In addition, the 2013 National Survey on Drug Use and Health, revealed that the number of individuals aged 12 or older who were current users of methamphetamine in 2013 was 595,000 and this number has remained relatively stable over the past decade (SAMHSA, 2014). Currently, there is no Food and Drug Administration (FDA)-approved pharmacotherapy for the treatment of methamphetamine addiction (Brensilver et al., 2013; Carson and Taylor, 2014; Karila et al., 2010). In summary, the prevalence of methamphetamine abuse and absence of effective treatment strategies for methamphetamine addiction suggests a need for preclinical studies in the development and evaluation of potential pharmacotherapies.

One method of preclinical model validation is a reverse translational or “bedside-to-bench” approach where candidate medications have been first evaluated in either human laboratory drug self-administration studies or clinical trials and then subsequently tested in preclinical models to determine concordance of results. The most evident example of this approach in the drug addiction literature has been methadone treatment for heroin addiction (Dole et al., 1966; Griffiths et al., 1975; Negus, 2006). A more recent example of this reverse translation approach might be the demonstration of amphetamine treatment efficacy for cocaine addiction (Grabowski et al., 2001; Negus, 2003). Overall, the good concordance between candidate medication efficacy in clinical trials and subchronic candidate medications treatment effects in preclinical drug vs. food choice procedures for opioids (Haney and Spealman, 2008; Negus and Banks, 2013) and cocaine (Banks et al., 2015; Haney and Spealman, 2008) support the potential extension of this approach to other abused drugs, such as methamphetamine.

Because of the relative success of agonist-based pharmacotherapy approaches for opioids and cocaine, agonist-based approaches for methamphetamine addiction have been the most extensively examined (Brensilver et al., 2013; Karila et al., 2010). In particular, the monoamine uptake inhibitor methylphenidate and the monoamine releaser d-amphetamine have been two of the most extensively evaluated candidate medications in clinical trials outside of bupropion. Methylphenidate treatment effects have been equivocal with three clinical trials (Konstenius et al., 2014; Rezaei et al., 2015; Tiihonen et al., 2007) demonstrating a reduction in amphetamine/methamphetamine use and three clinical trials (Konstenius et al., 2010; Ling et al., 2014; Miles et al., 2013) demonstrating no effect on amphetamine/methamphetamine use. Furthermore, d-amphetamine treatment efficacy has not been significant in either clinical trials (Galloway et al., 2011; Longo et al., 2010) or a human laboratory methamphetamine self-administration study (Pike et al., 2014). However, there are two potential reasons for these equivocal or negative clinical results. First, some of these clinical trials did not distinguish between enrolled amphetamine-dependent and methamphetamine-dependent individuals. Given potential differences between amphetamine and methamphetamine interactions at the dopamine transporter (Goodwin et al., 2009), there may also be differential treatment sensitivity between these two drug-dependent populations. Second, candidate medication dosing regimens in clinical trials may be restricted for safety reasons. For example, the largest methylphenidate dose (180 mg/day; ∼ 0.11 mg/kg/h) (Konstenius et al., 2014) examined was also a clinical trial that reported a treatment effect.

Given that preclinical studies have both greater control over drug exposure and are able to evaluate both a broader dose range and larger doses than in human drug self-administration studies or clinical trials, the present studies were designed to address these two potential reasons for the equivocal clinical trial results. A concurrent schedule of methamphetamine and food pellet presentation was utilized because preclinical choice procedures have been predictive of candidate medication effects for cocaine (Banks et al., 2015) and heroin (Negus and Banks, 2013). Subchronic 7-day d-amphetamine and methylphenidate treatment effects were determined to model treatment regimens in human laboratory drug self-administration studies and clinical trials. Moreover, to the best of our knowledge, subchronic d-amphetamine or methylphenidate treatment effects on preclinical methamphetamine self-administration have not been previously reported. Furthermore, there are reported differences between cocaine choice and methamphetamine choice in monkeys (John et al., 2015) and the degree to which amphetamine treatment differentially alters cocaine choice vs. methamphetamine choice remains unknown. In addition, we also determined continuous 7-day cocaine treatment effects on methamphetamine choice. Previous studies have demonstrated that methamphetamine treatment reduced cocaine use in a clinical trial (Mooney et al., 2009) and reduced cocaine choice in monkeys(Banks et al., 2011). If cocaine treatment did not attenuate methamphetamine choice, this result would further support dissociation of cocaine choice and methamphetamine choice pharmacological mechanisms.

2. Methods

2.1 Subjects

Studies were conducted in total of five adult male rhesus monkeys (Macaca mulatta) surgically implanted with a double-lumen catheter (0.76 mm ID × 2.36 mm OD, STI Flow, Morrisville, NC) inserted into a femoral or jugular vein and had an experimental history(Banks and Blough, 2015). Monkeys were maintained on a diet of fresh fruit and food biscuits (Lab Diet High Protein Monkey Biscuits #5045, PMI Nutrition Inc., St. Louis, MO) delivered in the afternoon post-operant behavioral session. Water was continuously available in the housing chamber and a 12 h light-dark cycle was in effect. Monkeys had visual, auditory and olfactory contact with other monkeys throughout the study. Operant procedures and foraging toys were provided for environmental manipulation and enrichment. Videos or music was also played daily in animal housing rooms to provide additional environmental enrichment. Animal research and maintenance were conducted according to the 2011 Guide for the Care and Use of Laboratory Animals (8th edition) as adopted and promulgated by the National Institutes of Health. Animal facilities were licensed by the United States Department of Agriculture and accredited by the Association for Assessment and Accreditation of Laboratory Animal Care. The Institutional Animal Care and Use Committee approved the research and environmental enrichment protocol.

2.2 Apparatus

The housing chamber served as the experimental chamber and was equipped with a custom operant panel, a pellet dispenser (Med Associates, Model ENV-203-1000, St. Albans, VT), and two syringe pumps (Model PHM-108, Med Associates). One “self-administration” pump delivered contingent methamphetamine injections through one lumen of the catheter. The second “treatment” pump delivered a 0.1 mL saline, d-amphetamine, methylphenidate, or cocaine noncontingent infusion through the second lumen of the catheter at a programmed rate of every 20 minutes from 12:00 p.m. each day until 11:00 a.m. the following morning. The intravenous catheter was protected by a customized stainless steel tether and jacket system (Lomir Biomedical, Malone, NY) that permitted monkeys to move freely in the home chamber. Catheter patency was periodically evaluated by intravenous ketamine (5 mg/kg) administration through one lumen of the double-lumen catheter and after any pharmacological manipulation that produced a decrease in methamphetamine vs. food choice. The catheter was considered patent if intravenous ketamine administration produced muscle tone loss within 10 s.

2.3 Methamphetamine Versus Food Choice Procedure

Daily experimental sessions were conducted from 0900 to 1100 h in each monkey's home chamber as described previously (Banks and Blough, 2015). The terminal choice procedure consisted of five 20-min components, with a different unit methamphetamine dose available during each successive component (0, 0.01, 0.032, 0.1, and 0.32 mg/kg/injection during components 1-5, respectively). Manipulating the injection volume controlled the methamphetamine dose (0, 0.03, 0.1, 0.3, and 1.0 mL/injection, respectively).Components were separated by 5-min timeout periods. During each component, the left, food-associated key was transilluminated red, and completion of the FR requirement (FR100) resulted in 1-g food pellet delivery. The right, methamphetamine-associated key was transilluminated green, and completion of the FR requirement (FR10) resulted in delivery of the intravenous unit methamphetamine dose available during that component. Stimulus lights for the methamphetamine-associated key were flashed on and off in 3s cycles, and longer flashes were associated with higher methamphetamine doses. Monkeys could complete up to a total of 10 ratio requirements on both the food- and methamphetamine-associated keys. Responding on either key reset the ratio requirement on the other key. Completion of each ratio requirement initiated a 30-s timeout, during which all stimulus lights were turned off, and responding had no programmed consequences. Choice behavior was considered stable when the lowest unit methamphetamine dose maintaining greater than 80% methamphetamine vs. food choice varied by ≤ 0.5 log units for 3 consecutive days.

Once methamphetamine vs. food choice was stable, test sessions were conducted to determine continuous 7-day d-amphetamine (0.01-0.1 mg/kg/h), methylphenidate (0.032-0.32 mg/kg/h), or cocaine (0.1-0.32 mg/kg/h) treatment effects on methamphetamine vs. food choice. d-Amphetamine and methylphenidate treatments were tested up to doses that either decreased methamphetamine choice or rates of operant responding primarily during components when food was chosen. The 3-day period of saline infusions before each test drug treatment was used as the baseline “+saline.” At the conclusion of each 7-day treatment periods, saline infusions were reinstituted for at least 4 days and until methamphetamine vs. food choice had returned to pretreatment levels. d-Amphetamine, methylphenidate, and cocaine doses were counterbalanced across subjects, but all drug doses were tested before proceeding to testing of a different drug.

2.4 Data Analysis

The primary dependent measures were (1) percent methamphetamine choice, defined as (number of ratios completed on the methamphetamine-associated key ÷ total number of ratios completed)*100 and (2) number of ratio requirements (hereafter referred to as “choices”) completed. The mean of the last 3 days of each experimental condition for each monkey for each of the measures were then plotted as a function of unit methamphetamine dose during the behavioral session. Results were analyzed using a linear mixed-effects analysis with unit methamphetamine dose and treatment drug dose as the fixed main effects and subjects as the random effect. Additional dependent measures collected were total choices, food choices, and methamphetamine choices for the entire behavioral session. The mean of the last 3 days of each experimental condition for each monkey for each of these measures were then plotted as a function of each dependent measure. These results were analyzed using two-way repeated-measures analysis of variance with experimental manipulation and dependent measures as the main factor. Post-hoc comparisons against baseline “+saline” conditions within a given methamphetamine dose were performed using the Dunnett's test following a significant main effect of experimental manipulation or methamphetamine dose × experimental manipulation interaction as appropriate. The criterion for significance was set a priori at the 95% confidence level (p< 0.05). All analyses were conducted using JMP Pro 11.1.1, SAS, Cary, NC.

2.5 Drugs

(+)-methamphetamine HCl, (−)-cocaine HCl, and (±)-methylphenidate HCl were provided by the National Institute on Drug Abuse Drug Supply Program (Bethesda, MD). d-Amphetamine hemisulfate was purchased from a commercial supplier (Sigma Aldrich, St. Louis, MO). All drug doses are expressed as the salt forms listed above. All drug solutions were passed through a sterile 0.2 μm filter (Millipore, Billerica, MA) before administration.

3. Results

3.1 Stability of baseline methamphetamine vs. food choice

Under baseline “+ saline” conditions when saline was infused through the ‘treatment’ lumen of the double-lumen catheter, methamphetamine maintained a dose-dependent increase in preference over an alternative food reinforcer. When no (0) or small(0.01 and 0.032 mg/kg/injection) methamphetamine doses (Figure 1A and 2A, 3A, 4A) were available as the alternative, monkeys primarily responded on the food-associated key. As the unit methamphetamine dose increased, monkeys reallocated their behavior away from the food-associated key such that at a unit methamphetamine dose of 0.1 mg/kg/injection dose, behavior was 50% preference for methamphetamine. A larger unit methamphetamine dose (0.32 mg/kg/injection) maintained almost exclusive methamphetamine preference. Figure 1C and Supplemental Figures 1C, 2C, and 3C1 show total choices, food choices, and methamphetamine choices completed during the behavioral session during saline treatments. On average, monkeys completed 41 of the 50 available total choices with a distribution of approximately 31 food choices and 10 methamphetamine choices.

Figure 1.

Figure 1

Open in a new tab

Stability of baseline methamphetamine vs. food choice during continuous saline treatment over the experimental testing period in rhesus monkeys (n=4). (A and B) Abscissa: unit dose methamphetamine in mg/kg/injection (log scale). (A) Left ordinate: percent methamphetamine choice. Right ordinate: percent food choice. (B) Ordinate: choices completed per component. (C) Ordinate: number of choices per session. Abscissa: experiment end point. Panel shows summary data for total choices, food choices, and methamphetamine choices summed across all methamphetamine doses. All points and bars represent mean ± SEM obtained during the 3 days preceding each 7-day experimental testing period.

Figure 2.

Figure 2

Open in a new tab

Effects of continuous 7-day d-amphetamine (0.01-0.1 mg/kg/h) treatment on choice between methamphetamine and food in four rhesus monkeys. Abscissa: unit dose methamphetamine in mg/kg/injection. Left ordinate: percent methamphetamine choice. Right ordinate: percent food choice. All points represent mean ± SEM obtained during days 5-7 of each 7-day treatment period. Missing points indicate that the monkey failed to respond during that component.

Figure 3.

Figure 3

Open in a new tab

Effects of continuous 7-day (±)-methylphenidate (0.032-0.32 mg/kg/h) treatment on choice between methamphetamine and food in four rhesus monkeys. Abscissa: unit dose methamphetamine in mg/kg/injection. Left ordinate: percent methamphetamine choice. Right ordinate: percent food choice. All points represent mean ± SEM obtained during days 5-7 of each 7-day treatment period. Missing points indicate that the monkey failed to respond during that component.

Figure 4.

Figure 4

Open in a new tab

Effects of continuous 7-day (–)-cocaine (0.1-0.32 mg/kg/h) treatment on choice between methamphetamine and food in four rhesus monkeys. Abscissa: unit dose methamphetamine in mg/kg/injection. Left ordinate: percent methamphetamine choice. Right ordinate: percent food choice. All points represent mean ± SEM obtained during days 5-7 of each 7-day treatment period.

3.2 Effects of d-amphetamineon methamphetamine vs. food choice

Figure 2 shows continuous 7-day d-amphetamine treatment effects on methamphetamine versus food choice in individual monkeys (n=4) and group mean results are shown in Supplemental Figure 1A2. In general, small (0.01 mg/kg/h) and intermediate (0.032 mg/kg/h) d-amphetamine treatment doses tended to increase methamphetamine vs. food choice and produce leftward shifts in the methamphetamine choice dose-effect function. The largest d-amphetamine treatment dose (0.1 mg/kg/h) eliminated methamphetamine choice in two (M1515, M1523) out of four monkeys and increased methamphetamine choice in the two other monkeys (M1514, M1516). Supplemental Figure 1B shows 0.1 mg/kg/h d-amphetamine treatment significantly decreased choices in components when 0.032 and 0.1 mg/kg/injection methamphetamine was available(methamphetamine dose × d-amphetamine dose: F9,48 = 2.33, p = 0.0288). Supplemental Figure 2C3 shows that 0.1 mg/kg/h d-amphetamine treatment decreased the total number of choices completed per session and indicative of a general reinforcement-independent rate-altering drug effect (d-amphetamine dose: F3,12=4.36, p=0.0269).

3.3 Effects of methylphenidate on methamphetamine vs. food choice

Figure 3 shows continuous 7-day methylphenidate treatment effects on methamphetamine versus food choice in individual monkeys and group mean data are shown in Supplemental Figure 2A4. In general, small (0.032 mg/kg/h) and intermediate (0.1 mg/kg/h) methylphenidate treatment doses tended to increase methamphetamine vs. food choice. Treatment with 0.32 mg/kg/h methylphenidate did not alter methamphetamine preference. Supplemental figure 2B5shows 0.32 mg/kg/h methylphenidate treatment significantly decreased choices per component(methylphenidate dose: F3, 45 = 8.53, p = 0.0001).Supplemental Figure 2C6 also shows that 0.32 mg/kg/h methylphenidate treatment significantly decreased both total choices(methylphenidate dose: F3,12=6.55,p=0.0072) and food choices completed for the entire session (methylphenidate dose: F3,12 =5.31, p=0.0147).

3.4 Effects of cocaine on methamphetamine vs. food choice

Figure 4 shows continuous 7-day cocaine treatment effects on methamphetamine versus food choice in individual monkeys and group mean data are shown in Supplemental Figure 3A7. In general, 0.1 mg/kg/h cocaine treatment did not alter methamphetamine choice. When the cocaine treatment dose was increased to 0.32 mg/kg/h, methamphetamine preference was increased in two monkeys (M1515 and M1509) and decreased in another monkey (M1516).Supplemental Figure 3B8and Supplemental Figure 3C9shows cocaine treatment did not significantly alter choices completed per component or total, food, or methamphetamine choices completed for the entire session.

4. Discussion

The present study was designed to determine the utility of subchronic candidate medication treatments and a preclinical methamphetamine vs. food choice procedure to produce concordant results with human laboratory methamphetamine self-administration studies and clinical trials. There were two main findings. First, individual differences were observed during subchronic d-amphetamine treatment with two monkeys showing complete elimination of methamphetamine choice. These results suggest that larger d-amphetamine treatment than those previous utilized may be efficacious in a subset of methamphetamine-addicted individuals. Second, subchronic methylphenidate and cocaine treatment did not attenuate methamphetamine choice. Overall, these results confirm and extend previous findings demonstrating different pharmacological mechanisms of cocaine and methamphetamine reinforcement under a concurrent schedule.

4.1 Baseline methamphetamine choice

Consistent with previous methamphetamine self-administration studies in nonhuman primates (Banks and Blough, 2015; John et al., 2014, 2015) and humans (Kirkpatrick et al., 2012; Pike et al., 2014), increasing methamphetamine doses resulted in an increased preference over an alternative, nondrug reinforcer. In contrast, the present study was inconsistent with two previous rat methamphetamine choice studies (Caprioli et al., 2015; Ping and Kruzich, 2008). Similar inconsistencies of dose-dependent cocaine choice between nonhuman primates (Banks and Negus, 2010) and rats(Cantin et al., 2010) have also been reported. Whether these differences represent potential procedural or species differences in drug vs. nondrug choice remains to be empirically established. However, the dose dependence of methamphetamine choice in monkeys provides an empirical foundation upon which to determine the predictive validity of preclinical methamphetamine choice results to human laboratory and clinical trial results.

4.2 d-Amphetamine treatment effects onmethamphetamine choice

Although continuous d-amphetamine treatment did not significantly attenuate methamphetamine vs. food choice, d-amphetamine treatment did eliminate methamphetamine choice in two out of four monkeys. The present results, from a group analysis perspective, are consistent with previous human laboratory (Pike et al., 2014) and clinical trials (Galloway et al., 2011; Longo et al., 2010) demonstrating no robust, significant d-amphetamine treatment effect. However, there is a published case report of oral amphetamine substitution treatment reducing illicit methamphetamine use in four out of ten patients (Sherman, 1990). Furthermore, there are other published case reports of oral amphetamine substitution treatment reducing illicit amphetamine use (Charnaud and Griffiths, 1998; Fleming and Roberts, 1994; White, 2000). Although the environmental and genetic determinants remain to be fully elucidated, the present d-amphetamine results in conjunction with the literature suggest amphetamine substitution treatment may have efficacy in a subset of methamphetamine users and that larger amphetamine doses than those previously published in humans may be necessary to unmask an amphetamine treatment effect on methamphetamine use.

Previous preclinical studies have determined treatment effects with monoamine releasers other than d-amphetamine on methamphetamine self-administration. For example, acute methamphetamine (Munzar et al., 1999; Schindler et al., 2011) or phentermine (Munzar et al., 1999) pretreatment attenuated methamphetamine self-administration. Timecourse analysis of d-amphetamine treatment effects did not reveal a significant attenuation of methamphetamine choice on day 1 and d-amphetamine treatment efficacy increased over subsequent treatment days with complete elimination of methamphetamine choice by days 3-4 that was sustained through the seven treatment days. Furthermore, this d-amphetamine treatment effect was greater in magnitude on methamphetamine choice than seven days of saline substitution for one of these monkeys (Banks and Blough, 2015). Individual differences in lifetime methamphetamine intake or experimental history do not readily explain the differential d-amphetamine treatment effects. Future preclinical studies correlating peripheral or central biomarkers with pharmacological treatment efficacy may unmask potential mechanisms regarding the individual subject sensitivity to d-amphetamine treatment.

4.3 Methylphenidatetreatment effects on methamphetamine choice

Subchronic treatment with the monoamine uptake inhibitor methylphenidate also failed to significantly attenuate methamphetamine choice in both group and single subject analyses. These methylphenidate treatment results are consistent with a previous acute methylphenidate pretreatment results on methamphetamine self-administration in monkeys (Schindler et al., 2011) and methylphenidate treatment results in clinical trials (Konstenius et al., 2010; Ling et al., 2014; Miles et al., 2013). However, the presents results are inconsistent with other clinical trials demonstrating methylphenidate treatment reduced amphetamine-type stimulant addiction (Konstenius et al., 2014; Rezaei et al., 2015; Tiihonen et al., 2007). One potential explanation could be these three clinical trials (Konstenius et al., 2014; Rezaei et al., 2015; Tiihonen et al., 2007) did not differentiate between amphetamine- and methamphetamine-dependent individuals as only amphetamine-positive urines were assessed. Consistent with this hypothesis of differential methylphenidate treatment effects on amphetamine vs. methamphetamine use, a subsequent larger clinical trial (Miles et al., 2013) that included predominant amphetamine users from Finland and methamphetamine users from New Zealand showed no methylphenidate treatment efficacy whereas the previous study from predominantly amphetamine users in Finland (Tiihonen et al., 2007) did show methylphenidate treatment efficacy. Furthermore, in the methylphenidate trial that did directly measure methamphetamine in the urine, methylphenidate was without treatment efficacy (Ling et al., 2014). In summary, the present results are consistent with and extend previous preclinical and clinical results demonstrating a lack of methylphenidate treatment efficacy for methamphetamine addiction.

4.4 Implications for methamphetamine addiction medication development research

The absence of a positive medication effect in either human laboratory methamphetamine self-administration studies or methamphetamine clinical trials hinders preclinical model validation. Despite this lack of a positive control, the present results and the broader scientific literature support two methodologies that may enhance the translational predictive validity of preclinical results to clinical outcomes. First, consistent with other preclinical drug vs. food choice studies (Banks and Negus, 2012), a methamphetamine vs. food choice procedure allows for the assessment of both reinforcement-dependent (behavioral allocation) and reinforcement-independent (rate of behavior) treatment effects. Second, the use of subchronic treatment regimens, compared to acute, single dose experiments, also appears to enhance preclinical predictive validity (Banks et al., 2015; Comer et al., 2008; Haney and Spealman, 2008). Overall, given the accumulative evidence of different pharmacological mechanisms between cocaine choice and methamphetamine choice (John et al., 2015), there is a need for preclinical research to developnovel pharmacotherapeutic strategies to treat methamphetamine addiction.

Supplementary Material

supplement

Highlights.

  • Subchronic d-amphetamine treatment decreased methamphetamine choice in two of four monkeys

  • Subchronic methylphenidate and cocaine treatment mostly decreased rates of operant behavior

  • Preclinical choice results suggest differential behavioral pharmacological mechanisms for methamphetamine choice versus cocaine choice.

Acknowledgments

We appreciate the technical assistance of Jennifer Gough. We also acknowledge Kevin Costa for writing the original versions of the behavioral programs.

Role of Funding Source: Research reported in this publication was supported by National Institutes of Heath grant R01DA031718. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.

Footnotes

*

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

1

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

2

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

3

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

4

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

5

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

6

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

7

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

8

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

9

Supplementary material can be found by accessing the online version of this paper at http://dx.doi.org and by entering doi:….

Conflict of Interest: There are no existing or perceived conflicts of interest for any author.

Contributors: Banks designed the study. Schwienteck conducted the experiments. Schwienteck and Banks analyzed the data. Schwienteck and Banks wrote the manuscript. All authors have contributed to and have approved the final manuscript.

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

References

  1. Banks ML, Blough BE. Effects of environmental maniuplations and bupropion and risperidone treatments on choice between methamphetamine and food in rhesus monkeys. Neuropsychoharmacology. 2015;40:2198–2206. doi: 10.1038/npp.2015.63. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Banks ML, Blough BE, Negus SS. Effects of monoamine releasers with varying selectivity for releasing dopamine/norepinephrine versus serotonin on choice between cocaine and food in rhesus monkeys. Behav Pharmacol. 2011;22:824–836. doi: 10.1097/FBP.0b013e32834d63ac. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Banks ML, Hutsell BA, Schwienteck KL, Negus SS. Use of preclinical drug vs. food choice procedures to evaluate candidate medications for cocaine addiction. Curr Treat Options Psychol. 2015;2:136–150. doi: 10.1007/s40501-015-0042-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Banks ML, Negus SS. Effects of extended cocaine access and cocaine withdrawal on choice between cocaine and food in rhesus monkeys. Neuropsychopharmacology. 2010;35:493–504. doi: 10.1038/npp.2009.154. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Banks ML, Negus SS. Preclinical determinants of drug choice under concurrent schedules of drug self-administration. Adv Pharmacol Sci. 2012;2012:281768. doi: 10.1155/2012/281768. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Brensilver M, Heinzerling KG, Shoptaw S. Pharmacotherapy of amphetamine-type stimulant dependence: an update. Drug Alcohol Rev. 2013;32:449–460. doi: 10.1111/dar.12048. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Cantin L, Lenoir M, Augier E, Vanhille N, Dubreucq S, Serre F, Vouillac C, Ahmed SH. Cocaine is low on the value ladder of rats: possible evidence for resilience to Addiction. PLoS One. 2010;5:e11592. doi: 10.1371/journal.pone.0011592. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Caprioli D, Zeric T, Thorndike EB, Venniro M. Persistent palatable food preference in rats with a history of limited and extended access to methamphetamine self-administration. Addict Biol. 2015 doi: 10.1111/adb.12220.. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Carson DS, Taylor ER. Commentary on Heinzerling et al. (2014): a growing methamphetamine dependence therapeutics graveyard. Addiction. 2014;109:1887–1888. doi: 10.1111/add.12709. [DOI] [PubMed] [Google Scholar]
  10. Charnaud B, Griffiths V. Levels of intravenous drug misuse among clients prescribed oral dexamphetamine or oral methadone: a comparison. Drug Alcohol Depend. 1998;52:79–84. doi: 10.1016/s0376-8716(98)00052-0. [DOI] [PubMed] [Google Scholar]
  11. Comer SD, Ashworth JB, Foltin RW, Johanson CE, Zacny JP, Walsh SL. The role of human drug self-administration procedures in the development of medications. Drug Alcohol Depend. 2008;96:1–15. doi: 10.1016/j.drugalcdep.2008.03.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Dole VP, Nyswander ME, Kreek M. Narcotic blockade. Arch Intern Med. 1966;118:304–309. [PubMed] [Google Scholar]
  13. Office of Diversion Control, Department of Justice, editor. Drug Enforcement Administration. National Forensic Laboratory Information System Special Report: Synthetic cannabinoids and synthetic cathinones reported in NFLIS, 2010-2013. Drug Enforcement Administration; Springfield, VA: 2014. [Google Scholar]
  14. Fleming PM, Roberts D. Is the prescription of amphetamine justified as a harm reduction measure? J R Soc Health. 1994;114:127–131. doi: 10.1177/146642409411400303. [DOI] [PubMed] [Google Scholar]
  15. Galloway GP, Buscemi R, Coyle JR, Flower K, Siegrist JD, Fiske LA, Baggott MJ, Li L, Polcin D, Chen CYA, Mendelson J. A randomized, placebo-controlled trial of sustained-release dextroamphetamine for treatment of methamphetamine addiction. Clin Pharmacol Ther. 2011;89:276–282. doi: 10.1038/clpt.2010.307. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Goodwin JS, Larson GA, Swant J, Sen N, Javitch JA, Zahniser NR, De Felice LJ, Khoshbouei H. Amphetamine and methamphetamine differentially affect dopamine transporters in vitro and in vivo. J Biol Chem. 2009;284:2978–2989. doi: 10.1074/jbc.M805298200. [DOI] [PMC free article] [PubMed] [Google Scholar]
  17. Grabowski J, Rhoades H, Schmitz J, Stotts A, Daruzska LA, Creson D, Moeller FG. Dextroamphetamine for cocaine-dependence treatment: a double-blind randomized clinical trial. J Clin Psychopharmacol. 2001;21:522–526. doi: 10.1097/00004714-200110000-00010. [DOI] [PubMed] [Google Scholar]
  18. Griffiths RR, Wurster RM, Brady JV. Discrete-trial choice procedure: Effects of naloxone and methadone on choice between food and heroin. Pharmacol Rev. 1975;27:357–365. [PubMed] [Google Scholar]
  19. Haney M, Spealman R. Controversies in translational research: drug self-administration. Psychopharmacology. 2008;199:403–419. doi: 10.1007/s00213-008-1079-x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. John WS, Banala AK, Newman AH, Nader MA. Effects of buspirone and the dopamine D3 receptor compound PG619 on cocaine and methamphetamine self-administration in rhesus monkeys using a food-drug choice paradigm. Psychopharmacology. 2014;232:1279–1289. doi: 10.1007/s00213-014-3760-6. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. John WS, Newman AH, Nader MA. Differential effects of the dopamine D3 receptor antagonist PG01037 on cocaine and methamphetamine self-administration in rhesus monkeys. Neuropharmacology. 2015;92:34–43. doi: 10.1016/j.neuropharm.2014.12.024. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Karila L, Weinstein A, Aubin HJ, Benyamina A, Reynaud M, Batki SL. Pharmacological approaches to methamphetamine dependence: a focused review. Br J Clin Pharmacol. 2010;69:578–592. doi: 10.1111/j.1365-2125.2010.03639.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Kirkpatrick MG, Gunderson EW, Johanson CE, Levin FR, Foltin RW, Hart CL. Comparison of intranasal methamphetamine and d-amphetamine self-administration by humans. Addiction. 2012;107:783–791. doi: 10.1111/j.1360-0443.2011.03706.x. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Konstenius M, Jayaram-Lindström N, Beck O, Franck J. Sustained release methylphenidate for the treatment of ADHD in amphetamine abusers: a pilot study. Drug Alcohol Depend. 2010;108:130–133. doi: 10.1016/j.drugalcdep.2009.11.006. [DOI] [PubMed] [Google Scholar]
  25. Konstenius M, Jayaram-Lindström N, Guterstam J, Beck O, Philips B, Franck J. Methylphenidate for attention deficit hyperactivity disorder and drug relapse in criminal offenders with substance dependence: a 24-week randomized placebo-controlled trial. Addiction. 2014;109:440–449. doi: 10.1111/add.12369. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Ling W, Chang L, Hillhouse M, Ang A, Striebel J, Jenkins J, Hernandez J, Olaer M, Mooney L, Reed S, Fukaya E, Kogachi S, Alicata D, Holmes N, Esagoff A. Sustained-release methylphenidate in a randomized trial of treatment of methamphetamine use disorder. Addiction. 2014;109:1489–1500. doi: 10.1111/add.12608. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Longo M, Wickes W, Smout M, Harrison S, Cahill S, White JM. Randomized controlled trial of dexamphetamine maintenance for the treatment of methamphetamine dependence. Addiction. 2010;105:146–154. doi: 10.1111/j.1360-0443.2009.02717.x. [DOI] [PubMed] [Google Scholar]
  28. Miles SW, Sheridan J, Russell B, Kydd R, Wheeler A, Walters C, Gamble G, Hardley P, Jensen M, Kuoppasalmi K, Tuomola P, Föhr J, Kuikanmäki O, Vorma H, Salokangas R, Mikkonen A, Kallio M, Kauhanen J, Kiviniemi V, Tiihonen J. Extended-release methylphenidate for treatment of amphetamine/methamphetamine dependence: a randomized, double-blind, placebo-controlled trial. Addiction. 2013;108:1279–1286. doi: 10.1111/add.12109. [DOI] [PubMed] [Google Scholar]
  29. Mooney ME, Herin DV, Schmitz JM, Moukaddam N, Green CE, Grabowski J. Effects of oral methamphetamine on cocaine use: a randomized, double-blind, placebo-controlled trial. Drug Alcohol Depend. 2009;101:34–41. doi: 10.1016/j.drugalcdep.2008.10.016. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Munzar P, Baumann MH, Shoaib M, Goldberg SR. Effects of dopamine and serotonin-releasing agents on methamphetamine discrimination and self-administration in rats. Psychopharmacology. 1999;141:287. doi: 10.1007/s002130050836. [DOI] [PubMed] [Google Scholar]
  31. Negus SS. Rapid assessment of choice between cocaine and food in rhesus monkeys: Effects of environmental manipulations and treatment with d-amphetamine and flupenthixol. Neuropsychopharmacology. 2003;28:919–931. doi: 10.1038/sj.npp.1300096. [DOI] [PubMed] [Google Scholar]
  32. Negus SS. Choice between heroin and food in nondependent and heroin-dependent rhesus monkeys: effects of naloxone, buprenorphine, and methadone. J Pharmacol Exp Ther. 2006;317:711–723. doi: 10.1124/jpet.105.095380. [DOI] [PubMed] [Google Scholar]
  33. Negus SS, Banks ML. Medications development for opioid abuse. Cold Spring Harb Perspect Med. 2013;3 doi: 10.1101/cshperspect.a012104. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Pike E, Stoops WW, Hays LR, Glaser PE, Rush CR. Methamphetamine self-administration in humans during D-amphetamine maintenance. J Clin Psychopharmacol. 2014;34:675–681. doi: 10.1097/JCP.0000000000000207. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Ping A, Kruzich PJ. Concurrent access to sucrose pellets decreases methamphetamine-seeking behavior in Lewis rats. Pharmacol Biochem Behav. 2008;90:492–496. doi: 10.1016/j.pbb.2008.04.009. [DOI] [PubMed] [Google Scholar]
  36. Rezaei F, Emami M, Zahed S, Morabbi MJ, Farahzadi M, Akhondzadeh S. Sustained-release methylphenidate in methamphetamine dependence treatment: a double-blind and placebo-controlled trial. Daru. 2015;23:2. doi: 10.1186/s40199-015-0092-y. [DOI] [PMC free article] [PubMed] [Google Scholar]
  37. SAMHSA, editor. SAMHSA. Results from the 2013 National Survey on Drug Use and Health: Summary of National Findings. Rockville, MD: 2014. [Google Scholar]
  38. Schindler CW, Gilman JP, Panlilio LV, McCann DJ, Goldberg SR. Comparison of the effects of methamphetamine, bupropion, and methylphenidate on the self-administration of methamphetamine by rhesus monkeys. Exp Clin Psychopharmacol. 2011;19:1–10. doi: 10.1037/a0022432. [DOI] [PMC free article] [PubMed] [Google Scholar]
  39. Sherman JP. Dexamphetamine for “speed” addiction. Med J Aust. 1990;153:306. doi: 10.5694/j.1326-5377.1990.tb136930.x. [DOI] [PubMed] [Google Scholar]
  40. Tiihonen J, Kuoppasalmi K, Fohr J, Tuomola P, Kuikanmaki O, Vorma H, Sokero P, Haukka J, Meririnne E. A comparison of aripiprazole, methylphenidate, and placebo for amphetamine dependence. Am J Psychiatry. 2007;164:160–162. doi: 10.1176/ajp.2007.164.1.160. [DOI] [PubMed] [Google Scholar]
  41. White R. Dexamphetamine substitution in the treatment of amphetamine abuse: an initial investigation. Addiction. 2000;95:229–238. doi: 10.1046/j.1360-0443.2000.9522299.x. [DOI] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

supplement
NIHMS720556-supplement-Supplemental.docx (1.1MB, docx)

RESOURCES