A novel open-source drug-delivery system that allows for first-of-kind simulation of nonadherence to pharmacological interventions in animal disease models

doi:10.1016/j.jneumeth.2014.09.019

Journal of Neuroscience Methods

Volume 238, 30 December 2014, Pages 105-111

https://doi.org/10.1016/j.jneumeth.2014.09.019 Get rights and content

Highlights

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Novel model of nonadherence which uses drug-in-food to treat animals chronically.
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Future studies will examine the consequences of nonadherence in epileptic rats.
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Utility extends to nonadherence in any etiologically-relevant animal disease model.
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Open-source method allows for implementation of a system for modeling nonadherence.

Abstract

Background

Nonadherence to a physician-prescribed therapeutic intervention is a costly, dangerous, and sometimes fatal concern in healthcare. To date, the study of nonadherence has been constrained to clinical studies. The novel approach described herein allows for the preclinical study of nonadherence in etiologically relevant disease animal model systems.

New method

The method herein describes a novel computer-automated pellet delivery system which allows for the study of nonadherence in animals. This system described herein allows for tight experimenter control of treatment using a drug-in-food protocol. Food-restricted animals receive either medicated or unmedicated pellets, designed to mimic either “taking” or “missing” a drug.

Results

The system described permits the distribution of medicated or unmedicated food pellets on an experimenter-defined feeding schedule. The flexibility of this system permits the delivery of drug according to the known pharmacokinetics of investigational drugs.

Comparison with other methods

Current clinical adherence research relies on medication-event monitoring system (MEMS) tracking caps, which allows clinicians to directly monitor patient adherence. However, correlating the effects of nonadherence to efficacy still relies on the accuracy of patient journals.

Conclusion

This system allows for the design of studies to address the impact of nonadherence in an etiologically relevant animal model. Given methodological and ethical concerns of designing clinical studies of nonadherence, animal studies are critical to better understand medication adherence. While the system described was designed to measure the impact of nonadherence on seizure control, it is clear that the utility of this system extends beyond epilepsy to include other disease states.

Graphical abstract

Introduction

Patient nonadherence to a doctor-prescribed therapeutic regimen is a widespread problem across all prescribed pharmaceutical treatments and is often associated with expensive and sometimes fatal consequences. It is estimated that one-half to one-third of patients practice imperfect adherence across almost all disease categories (Osterberg and Blaschke, 2005). In the United States alone, it is estimated that nonadherence is responsible for as many as 125,000 preventable deaths per year (McCarthy, 1998) and $290 billion in preventable health care spending per year (Cutler and Everett, 2010). This makes nonadherence a major disease category on its own.

In the field of neurological diseases, patients practicing proper adherence has been linked to more positive outcomes. Improved adherence to cholinesterase inhibitors has demonstrated a marked improvement in quality-of-life for Alzheimer's patients (Brady and Weinman, 2013). Patients with Parkinson's disease have a reduction in motor deficits when practicing proper adherence to levodopa treatments (Grosset et al., 2009). Post-mortem toxicology has suggested that better anti-depressant adherence could reduce suicide rates (Isacsson et al., 1994). For the treatment of epilepsy, near-perfect adherence may result in nearly two-thirds fewer pharmacoresistant patients (Modi et al., 2014). However, the study of nonadherence has previously been limited to clinical research.

Clinical studies of nonadherence are confounded by poor patient and/or guardian reporting of adherence (Modi et al., 2011a). Newer technologies, such as electronic medication event monitoring system (MEMS) caps (Cramer et al., 1989), have increased the fidelity of patient adherence data. It has is widely appreciated that patient adherence is highly irregular (Buelow and Smith, 2004, Grosset et al., 2009). However, only one clinical report thus far has demonstrated actual patient patterns of nonadherence following prescription (Modi et al., 2011b). Additionally, clinical results often group patients without regards to which pharmacotherapy they are prescribed, thus confounding the results. Finally, patient reporting may still be unreliable in these systems, as well as adequate descriptions of symptoms and adverse events (Buelow and Smith, 2004, Hoppe et al., 2007). This, in turn, increases the error when attempting to correlate nonadherence to specific disease state outcomes; e.g. efficacy and adverse events (Faught, 2012). A novel system that can directly measure the impact of nonadherence in an etiologically relevant animal disease model would begin to address these concerns.

Simulating daily patterns of nonadherence is possible without use of an automated system. However, it would require a substantial commitment of resources (i.e. 24 h a day, 7 days a week), in order to deliver drugs on a fixed schedule; thus, it is not feasible for a long-term chronic experiment. To make the study of nonadherence feasible requires an automated system that can reliably deliver a fixed dose of drug for a protracted period of time. One method to deliver drugs to animals is through the use of food pellets that are formulated with a specific quantity of a given drug (Grabenstatter et al., 2007). Thus, adherence can be simulated by administering medicated pellets for a single meal to simulate “taking” a dose, and administering unmedicated placebo control food pellets to simulate “missing” a dose.

Having the drug-in-food pellets available still requires a means to deliver them to the animal at a schedule that meets the needs of the individual investigator. This need led to the design and creation of the system described herein; i.e. an automated pellet delivery system capable of delivering medicated or unmedicated food pellets 24/7 according to an experimenter defined feeding schedule. The proof-of-principle experiments that were conducted to demonstrate the feasibility of the approach employed epileptic rats housed individually in a cage that was equipped with two feeders, thereby allowing each animal to have independent levels of experimenter-defined nonadherence. Section 2 describes the design and implementation of this system. While the system is integrated with video-EEG so that the delivery and consumption of anti-seizure drugs could be correlated with seizure control, the implementation of this system without video-EEG would certainly permit the study of nonadherence in a variety of animal disease models. Moreover, it would also allow for chronic delivery of drug for the purpose of conducting pharmacokinetic/pharmacodynamic studies.

Section snippets

System architecture overview

The system is able to administer medicated and non-medicated pellets to up to twelve individual epileptic rats in an effort to simulate clinically relevant patterns of nonadherence (Modi et al., 2011b). Additionally, the system coordinates the recording of EEG and video so that the resulting impact of nonadherence in an animal model of epilepsy can be assessed. The overall system design contains 24 automated feeders (Fig. 1A), a Feeder Control System, a BioPac MP150 EEG recording system, and a

Results and discussion

The result of this work is the design of a flexible system that provides the ability to chronically administer medicated and unmedicated food to 12 animals 24 h a day, seven 7 days a week, with minimal investment of staff labor and an elimination of the handling-induced stress associated with chronic manual delivery of a drug. The system described herein allows for a large variety of chronic studies to be performed in different disease models.

Conclusion

This system is the first of its kind and was designed to optimize preclinical adherence models for more relevant translation for bench-to-bedside research. The automated drug-in-pellet delivery system described herein permits the delivery of drugs according to a feeding schedule based on the individual pharmacokinetics of a given drug; i.e. the rate of metabolism and elimination of the drug. Any pharmaceutical intervention that can be integrated into food pellets, and is sufficiently palatable

Acknowledgements

The authors wish to thank Carlos Rueda, D.V.M., Barry Evans, and Thomas G. Newell for the outstanding technical assistance. This work was supported by NINDS, NIH Contract #HHSN271201100029C. HSW is a scientific co-founder of NeuroAdjuvants, Inc. Salt Lake City, UT.

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A novel open-source drug-delivery system that allows for first-of-kind simulation of nonadherence to pharmacological interventions in animal disease models

Highlights

Abstract

Background

New method

Results

Comparison with other methods

Conclusion

Graphical abstract

Introduction

Section snippets

System architecture overview

Results and discussion

Conclusion

Acknowledgements

Epilepsy Behav

Neurosci Biobehav Rev

Epilepsy Behav

J Affect Disord

Adherence to cholinesterase inhibitors in Alzheimer's disease: a review

Dement Geriatr Cogn Disord

How often is medication taken as prescribed? A novel assessment technique

JAMA

Thinking outside the pillbox—medication adherence as a priority for health care reform

N Engl J Med

Longitudinal analysis of patterns and predictors of changes in self-reported adherence to antiretroviral therapy: Swiss HIV Cohort Study

J Acquir Immune Defic Syndr

Anticonvulsant effects of carbamazepine on spontaneous seizures in rats with kainate-induced epilepsy: comparison of intraperitoneal injections with drug-in-food protocols

Epilepsia