Modeling and simulation of adherence: approaches and applications in therapeutics

How to handle a delayed or missed dose of edoxaban in patients with non-valvular atrial fibrillation? A model-informed remedial strategy

AIM

Edoxaban is a non-vitamin K antagonist oral anticoagulant (NOAC) widely used for the long-term prevention of stroke in patients with non-valvular atrial fibrillation (NVAF). Adherence to NOAC therapy has been unsatisfactory and decreases over time. Remedial strategies are currently used to address the non-adherence events. Current recommendations, however, are generic and not well supported by evidence. The aim of this study was to explore appropriate remedial dosing regimens for non-adherent edoxaban-treated NVAF patients through the Monte Carlo simulation.

METHODS

Six regimens were compared with the current recommendations of the European Heart Rhythm Association (EHRA) guide based on total deviation time. Both edoxaban plasma concentration and intrinsic Factor Xa activity were considered. Monte Carlo simulations were performed using RxODE based on a published population pharmacokinetics/pharmacodynamics (PK/PD) model.

RESULTS

The proposed remedial strategies were different than the EHRA recommendations and were related to the delay time. However, it was found that the missed dose can be administered immediately if the delay time is within 11 h. When the delay is between 12 and 19 h, a half dose followed by a regular dosing schedule is recommended. When the delay time exceeds 19 h, a full dose followed by a half dose is preferred.

CONCLUSION

PK/PD modelling and simulation are effective in developing and evaluating the remedial strategies of edoxaban, which can help maximise its therapeutic effect.

Solving the Evidence Interpretability Crisis in Health Technology Assessment: A Role for Mechanistic Models?

Health technology assessment (HTA) aims to be a systematic, transparent, unbiased synthesis of clinical efficacy, safety, and value of medical products (MPs) to help policymakers, payers, clinicians, and industry to make informed decisions. The evidence available for HTA has gaps-impeding timely prediction of the individual long-term effect in real clinical practice. Also, appraisal of an MP needs cross-stakeholder communication and engagement. Both aspects may benefit from extended use of modeling and simulation. Modeling is used in HTA for data-synthesis and health-economic projections. In parallel, regulatory consideration of model informed drug development (MIDD) has brought attention to mechanistic modeling techniques that could in fact be relevant for HTA. The ability to extrapolate and generate personalized predictions renders the mechanistic MIDD approaches suitable to support translation between clinical trial data into real-world evidence. In this perspective, we therefore discuss concrete examples of how mechanistic models could address HTA-related questions. We shed light on different stakeholder's contributions and needs in the appraisal phase and suggest how mechanistic modeling strategies and reporting can contribute to this effort. There are still barriers dissecting the HTA space and the clinical development space with regard to modeling: lack of an adapted model validation framework for decision-making process, inconsistent and unclear support by stakeholders, limited generalizable use cases, and absence of appropriate incentives. To address this challenge, we suggest to intensify the collaboration between competent authorities, drug developers and modelers with the aim to implement mechanistic models central in the evidence generation, synthesis, and appraisal of HTA so that the totality of mechanistic and clinical evidence can be leveraged by all relevant stakeholders.

Study protocol for iSIPsmarter: A randomized-controlled trial to evaluate the efficacy, reach, and engagement of a technology-based behavioral intervention to reduce sugary beverages among rural Appalachian adults

Sugar-sweetened beverage (SSB) consumption is disproportionately high among rural Appalachian adults, with intakes double the national average and nearly four times the recommended amount. This trial targets this major dietary risk factor and addresses notable gaps in the rural digital health intervention literature. iSIPsmarter is a technology-based behavior and health literacy intervention aimed at improving SSB behaviors. It is comprised of six Internet-delivered, interactive Cores delivered weekly, an integrated short message service (SMS) strategy to engage users in tracking and reporting SSB behaviors, and a cellular-enabled scale for in-home weighing. iSIPsmarter is adapted from an evidence-based intervention and is grounded by the Theory of Planned Behavior and health literacy, numeracy, and media literacy concepts. The RCT is guided by the RE-AIM framework and targets 244 rural Appalachian adults. The goal is to examine the efficacy of iSIPsmarter to reduce SSB in a two-group design [iSIPsmarter vs. static Participant Education website] with four assessment points. Changes in secondary outcomes (e.g., diet quality, weight, quality of life) and maintenance of outcomes will also be evaluated. Additional secondary aims are to examine reach and representativeness, patterns of user engagement, and cost. Two tertiary aims are exploratory mediation analyses and a systems-level, participatory evaluation to understand context for future organizational-level adoption of iSIPsmarter. The long-term goal is to sustain an effective, scalable, and high reach behavioral intervention to reduce SSB-related health inequities and related chronic conditions (i.e., obesity, diabetes, some obesity-related cancers, heart disease, hypertension, dental decay) in rural Appalachia and beyond. ClinicalTrial registry: NCT05030753.

Statistical analysis of one-compartment pharmacokinetic models with drug adherence

Pharmacokinetics is a scientific branch of pharmacology that describes the time course of drug concentration within a living organism and helps the scientific decision-making of potential drug candidates. However, the classical pharmacokinetic models with the eliminations of zero-order, first-order and saturated Michaelis-Menten processes, assume that patients perfectly follow drug regimens during drug treatment, and the significant factor of patients' drug adherence is not taken into account. In this study, therefore, considering the random change of dosage at the fixed dosing time interval, we reformulate the classical deterministic one-compartment pharmacokinetic models to the framework of stochastic, and analyze their qualitative properties including the expectation and variance of the drug concentration, existence of limit drug distribution, and the stochastic properties such as transience and recurrence. In addition, we carry out sensitivity analysis of drug adherence-related parameters to the key values like expectation and variance, especially for the impact on the lowest and highest steady state drug concentrations (i.e. the therapeutic window). Our findings can provide an important theoretical guidance for the variability of drug concentration and help the optimal design of medication regimens. Moreover, The developed models in this paper can support for the potential study of the impact of drug adherence on long-term treatment for chronic diseases like HIV, by integrating disease models and the stochastic PK models.

Approaches to handling missing or "problematic" pharmacology data: Pharmacokinetics

Missing or erroneous information is a common problem in the analysis of pharmacokinetic (PK) data. This may present as missing or inaccurate dose level or dose time, drug concentrations below the analytical limit of quantification, missing sample times, or missing or incorrect covariate information. Several methods to handle problematic data have been evaluated, although no single, broad set of recommendations for commonly occurring errors has been published. In this tutorial, we review the existing literature and present the results of our simulation studies that evaluated common methods to handle known data errors to bridge the remaining gaps and expand on the existing knowledge. This tutorial is intended for any scientist analyzing a PK data set with missing or apparently erroneous data. The approaches described herein may also be useful for the analysis of nonclinical PK data.

Temporal Factors and Missed Doses of Tuberculosis Treatment. A Causal Associations Approach to Analyses of Digital Adherence Data

Rationale: Tuberculosis treatment lasts for 6 months or more. Treatment adherence is critical; regimen length, among other factors, makes this challenging. Globally, analyses mapping common types of nonadherence are lacking. For example, is there a greater challenge resulting from early treatment cessation (discontinuation) or intermittent missed doses (suboptimal dosing implementation)? This is essential knowledge for the development of effective interventions and more “forgiving” regimens, as well as to direct national tuberculosis programs.

Objectives: To granularly describe how patients take their tuberculosis medication and the temporal factors associated with missed doses.

Methods: The present study included patients with pulmonary tuberculosis enrolled in the control arm of a pragmatic, cluster-randomized trial in China of electronic reminders to improve treatment adherence. Treatment was the standard 6-month course (180 d), dosed every other day (90 doses). Medication monitor boxes recorded adherence (box opening) without prompting reminders. Patterns of adherence were visualized and described. Mixed-effects logistic regression models examined the temporal factors associated with per-dose suboptimal dosing implementation, adjusting for clustering within a participant. Cox regression models were used to examine the association between early suboptimal dosing implementation and permanent discontinuation.

Results: Across 780 patients, 16,794 (23.9%) of 70,200 doses were missed, 9,487 of which were from suboptimal dosing implementation (56.5%). By 60 days, 5.1% of participants had discontinued, and 14.4% had discontinued by 120 days. Most participants (95.9%) missed at least one dose. The majority of gaps were of a single dose (71.4%), although 22.6% of participants had at least one gap of 2 weeks or more. In adjusted models, the initiation–continuation phase transition (odds ratio, 3.07 [95% confidence interval, 2.68–3.51]) and national holidays (1.52 [1.39–1.65]) were associated with increased odds of suboptimal dosing implementation. Early-stage suboptimal dosing implementation was associated with increased discontinuation rates.

Conclusions: Digital tools provide an unprecedented step change in describing and addressing nonadherence. In our setting, nonadherence was common; patients displayed a complex range of patterns. Dividing nonadherence into suboptimal dosing implementation and discontinuation, we found that both increased over time. Discontinuation was associated with early suboptimal dosing implementation. These apparent causal associations between temporal factors and nonadherence present opportunities for targeted interventions.

Clinical trial registered with the ISRCTN Registry (ISRCTN46846388).

When Multiple Objective Measures of Medication Adherence Indicate Incongruent Adherence Results: An Example with Pediatric Cancer

Previous research suggests that children and adolescents with acute lymphoblastic leukemia (ALL) and lymphoblastic lymphoma (LBL) often have difficulty adhering to complex treatment regimens during the maintenance phase of therapy. Measurement of treatment adherence can be done via objective (e.g., electronic monitoring (EM), pharmacological assays) or subjective methods (patient, parent, or physician reports). This paper provides an illustration of recommended strategies for comparing discrepancies between two objective measures of medication adherence (e.g., behavioral adherence using electronic monitoring versus pharmacological adherence using 6-mercaptopurine (6MP) metabolite data) within a relatively large cohort of pediatric patients with ALL or LBL (N = 139) who had longitudinal data for both measures of medication adherence over a 15-month period. Additionally, individual- and family-level factors such as gender, socioeconomic status, household environment, and dose intensity will be examined to identify possible sources of discrepancies between adherence measures. This information will provide practical advice for physicians, healthcare providers, and psychologists in identifying nonadherence and the caveats therein so patients achieve the best possible health outcomes.

Assessment of tacrolimus intrapatient variability in stable adherent transplant recipients: Establishing baseline values

The purpose of this study was to determine the intrapatient (within the same patient) variability of tacrolimus in adherent patients. Daily tacrolimus trough levels were obtained at home using dried blood spot technology in kidney and liver transplant recipients. Patients were randomized to receive 3 formulations of tacrolimus, each for two 1-week periods. Adherence was monitored by patient diary, pill counts, and use of the Medication Event Monitoring System (MEMS). Variability was quantified as the coefficient of variation (CV). Comparison of CV between groups was by independent t test or one-way ANOVA as appropriate. The population was found to be adherent with a rate of 99.9% with a mean interval between the evening and morning dose of tacrolimus of 11.86 hours. The median CV for the entire population was 15.2% (range 4.8%-110%). There were no differences in CV by allograft type or tacrolimus formulation. The multivariate analysis did not identify any demographic characteristics associated with a CV > 30%. In a highly adherent population, tacrolimus did not display high intrapatient variability. Given the association between IPV and poor allograft outcomes, future studies are needed to quantitate the influence of adherence and establish target IPV goals.

A Systematic Evaluation of Effect of Adherence Patterns on the Sample Size and Power of a Clinical Study

The objective of our study was to evaluate the effect of adherence patterns on the sample size and power of a clinical trial. Simulations from a population pharmacokinetic/pharmacodynamic (PK/PD) model linked to an adherence model were used. Four types of drug characteristics, such as long (~35 hours) and short (~12 hours) half-life in combination with earlier or delayed time to reach steady-state PD end points were studied. Adherence patterns were simulated using Markov chains. Our results clearly demonstrate the significant impact of varying levels and patterns of nonadherence on the sample size and power of a study. For drugs with short half-lives the evidence to support efficacy could be diluted by various patterns of nonadherence that would make its efficacy indistinguishable from the response to placebo. Prospectively utilizing clinical trial simulations with thorough incorporation of various adherence patterns would provide valuable information when designing a trial.

Measuring Medication Adherence in Pediatric Cancer: An Approach to Validation

Objective

This study described the prospective relationship between pharmacological and behavioral measures of 6-mercaptopurine (6MP) medication adherence in a multisite cohort of pediatric patients diagnosed with cancer ( N  = 139).

Methods

Pharmacological measures (i.e., metabolite concentrations) assessed 6MP intake. Behavioral measures (e.g., electronic monitoring) described adherence patterns over time.

Results

Three metabolite profiles were identified across 15 months: one group demonstrated low levels of both metabolites (40.8%) consistent with nonadherence and/or suboptimal therapy; two other groups demonstrated metabolite clusters indicative of adequate adherence (59.2%). Those patients whose metabolite profile demonstrated low levels of both metabolites had consistently lower behavioral adherence rates.

Conclusions

To our knowledge, this was the first study to prospectively validate a pharmacological measure of medication adherence with a behavioral adherence measure in a relatively large sample of pediatric patients with cancer. Using multiple methods of adherence measurement could inform clinical care and target patients in need of intervention.

Impact of disease, drug and patient adherence on the effectiveness of antiviral therapy in pediatric HIV

INTRODUCTION

Maintaining effective antiretroviral treatment for life is a major problem in both resource-limited and resource-rich countries. Despite the progress observed in paediatric antiretroviral therapy, approximately 12% of children still experience treatment failure due to drug resistance, inadequate dosing and poor adherence. We explore the current status of antiretroviral therapy in children with focus on the interaction between disease, drug pharmacokinetics and patient behavior, all of which are strongly interconnected and determine treatment outcome. Areas covered: An overview is provided of the viral characteristics and available drug combinations aimed at the prevention of resistance. In this context, the role of patient adherence is scrutinized. A detailed assessment of factors affecting adherence is presented together with the main strategies to enhance treatment response in children. Expert opinion: Using modeling and simulation, a framework for characterizing the forgiveness of non-adherence for specific antiretroviral drugs in children is proposed in which information on pharmacokinetics, pharmacokinetic-pharmacodynamic relationships and viral dynamics is integrated. This approach represents an opportunity for the simplification of dosing regimens taking into account the interaction between these factors. Based on clinical trial simulation scenarios, we envisage the possibility of assessing the impact of variable adherence to antiretroviral drug combinations in HIV-infected children.

Bayesian population modeling of drug dosing adherence

Adherence is a frequent contributing factor to variations in drug concentrations and efficacy. The purpose of this work was to develop an integrated population model to describe variation in adherence, dose-timing deviations, overdosing and persistence to dosing regimens. The hybrid Markov chain-von Mises method for modeling adherence in individual subjects was extended to the population setting using a Bayesian approach. Four integrated population models for overall adherence, the two-state Markov chain transition parameters, dose-timing deviations, overdosing and persistence were formulated and critically compared. The Markov chain-Monte Carlo algorithm was used for identifying distribution parameters and for simulations. The model was challenged with medication event monitoring system data for 207 hypertension patients. The four Bayesian models demonstrated good mixing and convergence characteristics. The distributions of adherence, dose-timing deviations, overdosing and persistence were markedly non-normal and diverse. The models varied in complexity and the method used to incorporate inter-dependence with the preceding dose in the two-state Markov chain. The model that incorporated a cooperativity term for inter-dependence and a hyperbolic parameterization of the transition matrix probabilities was identified as the preferred model over the alternatives. The simulated probability densities from the model satisfactorily fit the observed probability distributions of adherence, dose-timing deviations, overdosing and persistence parameters in the sample patients. The model also adequately described the median and observed quartiles for these parameters. The Bayesian model for adherence provides a parsimonious, yet integrated, description of adherence in populations. It may find potential applications in clinical trial simulations and pharmacokinetic-pharmacodynamic modeling.

How to handle missed or delayed doses of tacrolimus in renal transplant recipients? A pharmacokinetic investigation

Every transplant patient will, at least occasionally, miss immunosuppressive drug doses or take them outside the prescribed times. This study aims at quantifying the impact of poor execution on tacrolimus exposure in renal transplant patients. Validated pharmacokinetic tools applied in clinical setting were used to simulate the steady-state pharmacokinetic profiles of the drug when given as the immediate-release formulation to renal transplant patients, being CYP3A5 expressors or not, and who have reached either a standard or a minimized exposure. Situations of interruption due to a missed or delayed dose were simulated and the impact on drug exposure was explored. In case of a missed dose, it was observed that: (i) a single forgotten dose can greatly impact exposure: up to 49% decrease for tacrolimus trough concentration and 70% for AUC0-12 h in patients with the highest clearance values; (ii) patients with a minimized exposure are the most affected by a missed dose; and (iii) a dose of 1.5 times the usual dose may be recommended after a total dose oversight. Considering that intra-patient exposure variability is a predictive factor of poor graft outcome, these modeling results may serve as recommendations for patients, both preventively and in response to their questions.

Defining medication adherence in individual patients

BACKGROUND

The classification of patients as adherent or non-adherent to medications is typically based on an arbitrary threshold for the proportion of prescribed doses taken. Here, we define a patient as pharmacokinetically adherent if the serum drug levels resulting from his/her pattern of medication-taking behavior remained within the therapeutic range.

METHODS

We used pharmacokinetic modeling to calculate serum drug levels in patients whose patterns of dosing were recorded by a medication event monitoring system. Medication event monitoring system data were from a previously published study of seven psoriasis patients prescribed 40 mg subcutaneous adalimumab at 14-day intervals for 1 year. Daily serum concentrations of adalimumab were calculated and compared with a known therapeutic threshold.

RESULTS

None of the seven patients took adalimumab precisely every 14 days. Three patients who took adalimumab at intervals of 6-26 days could be classified as pharmacokinetically adherent, because their daily adalimumab serum concentration never fell below the therapeutic threshold. The four other patients, who took adalimumab at intervals of 7-93 days, could be classified as pharmacokinetically non-adherent, because their adalimumab serum concentration fell below the therapeutic threshold on 3.5%-71.3% of days.

CONCLUSION

Patients with varying patterns of adalimumab dosing could be classified as pharmacokinetically adherent or non-adherent according to whether or not their serum drug concentrations remained within the therapeutic range.

Measuring adherence by visual inspection of returned empty gel applicators in the CAPRISA 004 microbicide trial

In the CAPRISA 004 trial, adherence was estimated as the proportion of reported sex acts covered by two gel doses, which was assessed by counting returned empty gel applicators. The returned empty applicators were inspected visually in a standardized manner for residue on the outside of the applicator, as an indicator of vaginal insertion. Over 15 months, spanning 11,839 study visits by 838 women, a total of 59,800 returned empty applicators were inspected. By visual assessment, 77.5 % of these applicators appeared to have been inserted. To test the accuracy of the assessment we fitted a Cox model and found that the risk for HIV infection was doubled when less than half of the returned empty applicators had been assessed as not inserted in the vagina. Visual inspection enhanced both the accuracy of the adherence measurement and aided identification of mechanical problems with applicator use experienced by women in the trial.

Electronic monitoring of medication adherence in a 1-year clinical study of 2 dosing regimens of mesalazine for adults in remission with ulcerative colitis

BACKGROUND

Adherence to medication is an issue of great importance for patients with ulcerative colitis. Once daily mesalazine seems to be no worse than divided doses in preventing relapse in remitting patients. Although this has been attributed to improved adherence, detailed measures of adherence have been lacking from previous studies.

METHODS

A 1-year substudy was conducted alongside a trial that compared 2 different dosing regimens (once daily versus three times daily) of mesalazine for patients in remission with ulcerative colitis. Participants in the substudy had their adherence monitored electronically using the medication event monitoring system, self-report, and tablet counts. We compared measures, determined factors associated with adherence and associations between adherence and relapse, modeled adherence over time, and explored behavioral aspects.

RESULTS

We included 58 participants. Adherence was high across all measures (89.3% self-report, 96.7% tablet counts, and 89.2% medication event monitoring system). Agreement between the measures was poor at times. Adherence according to the medication event monitoring system best distinguished between the participants who relapsed (71.4%) and those who remained in remission (93.4%), although this difference was not statistically discernible at the 5% level. Adherence deteriorated over the study period, with three times daily participants generally less adherent than once-daily participants (odds ratio, 0.03; 95% confidence interval, 0.01-0.08). Adherence was higher on weekdays (odds ratio, 1.47; 95% confidence interval, 1.31-1.65) and around clinic visit dates (odds ratio, 1.43; 95% confidence interval, 1.18-1.72).

CONCLUSIONS

Simple dosing regimens are preferable to multiple daily dosing regimens. Electronic monitoring of adherence should be used more often in clinical studies. Self-reported adherence and tablet counts may underestimate adherence. Adherence declined over time, and adherence was generally lower and more varied for those allocated to the three times daily regimen.

Electronic monitoring of medication adherence in early maintenance phase treatment for pediatric leukemia and lymphoma: identifying patterns of nonadherence

OBJECTIVE

To describe patterns of treatment adherence to early maintenance phase therapy for acute lymphoblastic leukemia (ALL) and lymphoblastic lymphoma (LBL).

METHODS

Using an objective observational method (electronic monitoring), adherence was examined for 139 patients aged 7-19 years diagnosed with ALL or LBL across 6 centers.

RESULTS

The mean adherence percentage was 86.2%. Adherence rates declined over the 1-month of follow-up to 83%. 3 linear trajectories of 6-mercaptopurine adherence were identified: (1) exemplary adherence (n = 99): Averaging nearly 100%; (2) deteriorating (n = 23): Adherence decreased from 100 to 60%; and (3) chronically poor adherence (n = 9): Averaging 40%.

CONCLUSIONS

Adherence promotion interventions might be tailored to subgroups of patients who demonstrated problematic patterns of treatment adherence that could place them at risk for relapse. This research demonstrates the importance of using objective real-time measures of medication adherence for measuring and documenting adherence patterns.

A model of HIV drug resistance driven by heterogeneities in host immunity and adherence patterns

Background

Population transmission models of antiretroviral therapy (ART) and pre-exposure prophylaxis (PrEP) use simplistic assumptions – typically constant, homogeneous rates – to represent the short-term risk and long-term effects of drug resistance. In contrast, within-host models of drug resistance allow for more detailed dynamics of host immunity, latent reservoirs of virus, and drug PK/PD. Bridging these two levels of modeling detail requires an understanding of the “levers” – model parameters or combinations thereof – that change only one independent observable at a time. Using the example of accidental tenofovir-based pre-exposure prophyaxis (PrEP) use during HIV infection, we will explore methods of implementing host heterogeneities and their long-term effects on drug resistance.

Results

We combined and extended existing models of virus dynamics by incorporating pharmacokinetics, pharmacodynamics, and adherence behavior. We identified two “levers” associated with the host immune pressure against the virus, which can be used to independently modify the setpoint viral load and the shape of the acute phase viral load peak. We propose parameter relationships that can explain differences in acute and setpoint viral load among hosts, and demonstrate their influence on the rates of emergence and reversion of drug resistance. The importance of these dynamics is illustrated by modeling long-lived latent reservoirs of virus, through which past intervals of drug resistance can lead to failure of suppressive drug regimens. Finally, we analyze assumptions about temporal patterns of drug adherence and their impact on resistance dynamics, finding that with the same overall level of adherence, the dwell times in drug-adherent versus not-adherent states can alter the levels of drug-resistant virus incorporated into latent reservoirs.

Conclusions

We have shown how a diverse range of observable viral load trajectories can be produced from a basic model of virus dynamics using immunity-related “levers”. Immune pressure, in turn, influences the dynamics of drug resistance, with increased immune activity delaying drug resistance and driving more rapid return to dominance of drug-susceptible virus after drug cessation. Both immune pressure and patterns of drug adherence influence the long-term risk of drug resistance. In the case of accidental PrEP use during infection, rapid transitions between adherence states and/or weak immunity fortifies the “memory” of previous PrEP exposure, increasing the risk of future drug resistance. This model framework provides a means for analyzing individual-level risks of drug resistance and implementing heterogeneities among hosts, thereby achieving a crucial prerequisite for improving population-level models of drug resistance.

Reminder packaging for improving adherence to self-administered long-term medications

BACKGROUND

Current methods of improving medication adherence for health problems are mostly complex, labour-intensive, and not reliably effective. Medication 'reminder packaging', which incorporates a date or time for a medication to be taken in the packaging, can act as a reminder to improve adherence. This review of reminder packaging is an update of our 2006 Cochrane review.

OBJECTIVES

The objective of this review was to determine the effects of reminder packaging aids for self-administered medication/s taken for at least one month, on adherence and other outcomes.

SEARCH STRATEGY

We updated searches of the Cochrane Central Register of Controlled Trials (CENTRAL) and the Database of Abstracts of Reviews of Effects (DARE) (The Cochrane Library Issue 9, 2010), MEDLINE, EMBASE, CINAHL and PsycINFO from the database start dates to September 2010. We searched Current Controlled Trials to identify trials in progress. We performed a cited reference search on the Science Citation Index to identify papers that had cited the original systematic review.We also searched the Internet, contacted packaging manufacturers, and checked abstracts from the Pharm-line database and reference lists from relevant articles. We did not apply any language restrictions.

SELECTION CRITERIA

We selected randomised controlled trials with at least 80% follow up. We intended to do a sensitivity analysis of those studies that analysed their data on an intention-to-treat basis. Included studies compared a reminder packaging device with no device, for participants taking self-administered medications for at least one month.

DATA COLLECTION AND ANALYSIS

Three review authors independently assessed studies for inclusion, assessed quality, and extracted data from included studies. Where considered appropriate, data were combined for meta-analysis, or were reported and discussed in a narrative.

MAIN RESULTS

We included twelve studies containing data on 2196 participants; four of these studies were newly included in this 2011 update of our 2006 Cochrane review.Six intervention groups in four trials provided data on the percentage of pills taken. Reminder packaging increased the percentage of pills taken (mean difference (MD) 11% (95% confidence interval (CI) 6% to 17%)). Notable heterogeneity occurred among these trials (I(2) = 96.3%). Two trials provided data for the proportion of self-reported adherent patients, reporting a reduction in the intervention group which was not statistically significant (odds ratio = 0.89 (95% CI 0.56 to 1.40)). We conducted meta-analysis on data from two trials assessing the effect of reminder packaging on blood pressure measurements. We found that reminder packaging significantly decreased diastolic blood pressure (MD = -5.89 mmHg (95% CI -6.70 to -5.09; P < 0.00001; I(2) = 0%). No effect was seen on systolic blood pressure (mean change -1.01, 95% CI -2.22 to 0.20; P = 0.1, I(2) = 0%). We also conducted meta-analysis on extracted data from two trials that looked at change in glycated haemoglobin. We found that reminder packaging significantly reduced glycated haemoglobin levels (MD -0.72; 95% CI -0.83 to -0.60; P < 0.00001; I(2) = 92%), although there was considerable heterogeneity.No appropriate data were available for meta-analysis of remaining clinical outcomes, which included serum vitamin C and E levels, and self-reported psychological symptoms (one trial each). We reported remaining data narratively. In one study the presence of a reminder packaging aid was found to be preferred by patients with low literacy levels.

AUTHORS' CONCLUSIONS

Reminder packing may represent a simple method for improving adherence for patients with selected conditions. Further research is warranted to improve the design and targeting of these devices.

Quantifying the impact of nonadherence patterns on exposure to oral immunosuppressants

Background and objectives:

Nonadherence to oral immunosuppressive drugs in renal transplant patients remains a major challenge. The objective of this study was to develop an adherence-exposure model that 1) quantifies the impact of nonadherence patterns on cyclosporine levels and 2) identifies nonadherence patterns that are associated with unfavorable transplantation outcomes.

Design, setting, participants, and measurements:

This model quantified variability in drug exposure, expressed as the coefficient of variation (CV%), for time-averaged and trough cyclosporine levels (C_avg and C_min, respectively), and percentage of days spent below the therapeutic C_min target. Simulated patterns of nonadherence closely matched those observed in clinical practice for four nonadherence clusters and an “Others” category.

Results:

Patients in simulated nonadherence clusters 1–3 spent a mean (standard deviation) 5.8% (4.9), 9.0% (5.0), and 6.5% (3.4) of days below the C_min target, compared with 76.8% (6.5) for cluster 4 and 38.3% (6.4) for the “Others” category. Mean (standard deviation) CV% values for C_min were 24.1 (7.9), 35.4 (11.7), and 34.1 (10.6) for clusters 1–3, compared with 136.4 (23.6) for cluster 4 and 64.8 (10.3) for the “Others” category. Findings for C_avg were similar.

Conclusion:

Based on nonadherence patterns and known relationships between CV% for C_min and C_avg, and transplantation outcomes, patients in cluster 4 and the “Others” category are expected to be at high risk of allograft rejection. The proposed drug adherence-exposure model is useful to identify high-risk patients who can be targeted for interventions aimed at enhancing drug adherence to optimize clinical long-term outcomes.

Concepts and challenges in quantitative pharmacology and model-based drug development

Model-based drug development (MBDD) has been recognized as a concept to improve the efficiency of drug development. The acceptance of MBDD from regulatory agencies, industry, and academia has been growing, yet today's drug development practice is still distinctly distant from MBDD. This manuscript is aimed at clarifying the concept of MBDD and proposing practical approaches for implementing MBDD in the pharmaceutical industry. The following concepts are defined and distinguished: PK-PD modeling, exposure-response modeling, pharmacometrics, quantitative pharmacology, and MBDD. MBDD is viewed as a paradigm and a mindset in which models constitute the instruments and aims of drug development efforts. MBDD covers the whole spectrum of the drug development process instead of being limited to a certain type of modeling technique or application area. The implementation of MBDD requires pharmaceutical companies to foster innovation and make changes at three levels: (1) to establish mindsets that are willing to get acquainted with MBDD, (2) to align processes that are adaptive to the requirements of MBDD, and (3) to create a closely collaborating organization in which all members play a role in MBDD. Pharmaceutical companies that are able to embrace the changes MBDD poses will likely be able to improve their success rate in drug development, and the beneficiaries will ultimately be the patients in need.

Attitudes toward attention-deficit hyperactivity disorder (ADHD) treatment: parents' and children's perspectives

Attitudes toward pharmacological treatment may be a major factor contributing to adherence to such treatment. In the current study, attitudes toward methylphenidate treatment among 50 children diagnosed with attention-deficit hyperactivity disorder (ADHD) and their parents were assessed. Authors of this study have found that the study population is concerned and suspicious toward methylphenidate treatment. Most participants were exposed to negative information even before treatment initiation, which caused many participants to consult other sources and postpone the treatment initiation. Although experiencing methylphenidate as safe and effective (after 23.5 months of treatment), the leading cause of negative attitudes is the concern regarding long-term effects. The single most effective factor regarding the attitude toward methylphenidate treatment is the neurologist's explanation. It is concluded that the pediatric neurologist has a crucial role in affecting attitudes of children and parents toward methylphenidate treatment.

Estimation of the impact of noncompliance on pharmacokinetics: an analysis of the influence of dosing regimens

WHAT IS ALREADY KNOWN ABOUT THIS SUBJECT

Patient compliance is better with formulations that require less frequent dosing than with formulations that require more frequent dosing. Intramuscular risperidone and long-acting oxybutynin are two examples of medicines reformulated for less frequent dosing. However, it is not clear whether better compliance with less frequent dosing regimens translates to improved therapeutic outcome.

WHAT THIS STUDY ADDS

At equivalent daily doses and typical patterns of compliance, fortnightly intramuscular depot administrations of risperidone provide better pharmacokinetic coverage than once-daily oral dosing. Once-daily dosing of oxybutynin is no better at maintaining pharmacokinetic exposure than twice-daily dosing at half strength. The use of simulated compliance data as input to pharmacokinetic models is useful to assess the impact of noncompliance on internal drug exposure.

AIMS

To determine whether, for oxybutynin and risperidone, drug exposure is better with less frequent dosing regimens than with regimens that require more frequent dosing.

METHODS

Pharmacokinetic models of oxybutynin (5 mg twice-daily and 10 mg once-daily) and risperidone (2 mg once-daily orally and 25 mg fortnightly intramuscular injection) were developed. Simulations of multiple doses were performed by use of stochastic models of dose-taking compliance and clinic visit attendance.

RESULTS

At therapeutic concentrations and with typical patterns of noncompliance, intramuscular injections of risperidone resulted in a 41% (SD 12%) greater pharmacokinetic coverage than the oral dose, 76% (SD 10%) vs. 35% (SD 7%). No discernable differences were evident between once- and twice-daily formulations of oxybutynin, 29.2% (SD 10%) vs. 29.0% (SD 13%).

CONCLUSIONS

For equivalent doses for each drug, the longer acting preparation of risperidone, but not oxybutynin, is pharmacokinetically more forgiving of noncompliance than the shorter acting counterparts. Further analysis is required to confirm whether these observations are valid clinically.

An alternative method for population pharmacokinetic data analysis under noncompliance

Noncompliance presents a persistent problem while analyzing PK data from outpatient clinical studies. Ignoring dose omission or making uninformed assumptions about patient drug intake history can prove detrimental to the objectives of the analysis (e.g. determining the PK model parameters or identifying covariates) and ultimately compromise the interpretation of the data. In order to overcome this problem, an alternative method of handling noncompliant data is evaluated in this report. The proposed approach is based on the principle of superposition and works by separating the estimation of the elimination rate from the model based steady-state PK concentration. Simulations implementing this method under different scenarios of noncompliance demonstrate that it performs better than the conventional method of analyzing population PK data when compared on the basis of bias and imprecision in parameter estimation and power (and type I error) for covariate detection. Overall, the new method exhibits great potential to address the issue of uncertain/unreliable dosing histories frequently encountered in clinical trials.

A measurement model of medication adherence to highly active antiretroviral therapy and its relation to viral load in HIV-positive adults

This study compared a multiple method measurement model of highly active antiretroviral therapy (HAART) adherence with single-method models to determine optimal validity in predicting HIV viral load. Repeated measures of antiretroviral adherence were collected over a 15-month period using three different measurement methods: a self-report questionnaire, an adherence interview item, and electronic medication monitoring. The participants included HIV-positive men and women (n = 323) who were currently prescribed HAART. Single-factor models composed of multiple measurements over time were developed for each adherence method and HIV viral load. The three adherence methods were then combined in a second order factor measurement model. Structural equation modeling was used to test the models. Mean adherence, defined as percent of doses taken, was 92%, 90%, and 57% by self-report, interview, and electronic monitoring, respectively. Reliability of individual measurements of adherence was low. Four or seven assessments were needed to attain acceptable stability, depending on the method. The second-order factor model of adherence fit the data and explained 45% of the variability in HIV viral load. Models including only one method of assessing adherence explained between 20% and 24% of the variability. Models that included both self-report and electronic monitoring optimized predictive validity. Using at least two different methods of adherence measurement, each assessed at multiple times is recommended to derive reliable and valid measurement of medication adherence, which is predictive of biological outcomes such as HIV viral load.