Dashboard systems: implementing pharmacometrics from bench to bedside

"Getting the Dose Right"-Revisiting the Topic With Focus on Biologic Agents

Nearly two decades after the Peck and Cross article '"Getting the dose right: facts, a blueprint, and encouragements" was published, a review of dose recommendations for biologics shows that the success in getting the dose right appears to have improved given the relatively low incidence of drug withdrawals and dosing/label changes. However, the clinical experience with monoclonal antibodies (MAbs) following approval has been less than perfect. In inflammatory diseases, the disease burden changes with time and high treatment failure rates have been reported. In addition, the use of concomitant steroids and immunosuppressant drugs with MAbs is common. These concomitant agents have their own safety issues and many immunosuppressant agents are not well-tolerated although they have been shown to reduce the incidence of anti-drug antibodies (ADA). This same complexity is seen in MAbs used in oncology as well, although with these agents the doses appear to be higher than needed, which results in high treatment costs and incidence of adverse events. Given the complexity of MAb pharmacokinetics, which makes providing a detailed description of dose options difficult, product labeling should include the options for alternative dose strategies and potentially include the use of therapeutic drug monitoring with dose individualization which have been shown to improve clinical response and reduce the incidence of ADA. So, while the recommended dosing for biologics seems improved over the issues noted 17 years ago, we still have some work to do.

Personalized Dosing of Infliximab in Patients With Inflammatory Bowel Disease Using a Bayesian Approach: A Next Step in Therapeutic Drug Monitoring

Although biological agents have revolutionized the management of inflammatory bowel diseases (IBDs), a significant proportion of patients show primary non-response or develop secondary loss of response. Therapeutic drug monitoring (TDM) is advocated to maintain the efficacy of biologic agents. Reactive TDM can rationalize the management of primary non-response and secondary loss of response and has shown to be more cost-effective compared with empiric dose escalation. Proactive TDM is shown to increase clinical remission and the durability of the response to a biologic agent. However, the efficacy of proactive and reactive TDM has been questioned in recent studies and meta-analyses. Hence, we need a different approach to TDM, which addresses inflammatory burden, the individual patient, and disease factors. Bayesian approaches, which use population pharmacokinetic models, enable clinicians to make better use of TDM for dose adjustment. With rapid improvement in computer technology, these Bayesian model-based software packages are now available for clinical use. Bayesian dashboard systems allow clinicians to apply model-based dosing to understand an individual's pharmacokinetics and achieve a target serum drug concentration. The model is updated using previously measured drug concentrations and relevant patient factors, such as body weight, C-reactive protein, and serum albumin concentration, to maintain effective drug concentrations in the serum. Initial studies have found utility for the Bayesian approach in induction and maintenance, in adult and pediatric patients, in clinical trials, and in real-life situations for patients with IBD treated with infliximab. This needs confirmation in larger studies. This article reviews the Bayesian approach to therapeutic drug monitoring in IBD.

Recent advancements in clearance monitoring of monoclonal antibodies in patients with inflammatory bowel diseases

INTRODUCTION

Less than 50% of patients with inflammatory bowel diseases (IBD) receiving monoclonal antibody (mAb) therapy achieve endoscopic remission. Poor outcomes may indicate a need for dose optimization. During therapeutic drug monitoring (TDM), drug concentrations are measured, and when found too low, dosage regimen escalations are performed. To date, benefits of TDM of mAbs in patients with IBD are uncertain.

AREAS COVERED

This review presents an overview of what clearance monitoring is, how it can be performed, and why and when it may be valuable in treating patients with IBD. Virtual patients were used for illustration. A literature search was performed to summarize current evidence for clearance monitoring in IBD and other disease settings.

EXPERT OPINION

During clearance monitoring, mAb clearance is calculated and monitored over time. Higher mAb clearance in patients with IBD has been associated with higher target load (target-mediated drug disposition), protein-losing enteropathy (fecal drug loss), and immunogenicity. Although not prospectively confirmed, clearance monitoring might facilitate identification of (yet) asymptomatic disease flares or presence of (yet) undetectable anti-drug antibodies. Furthermore, clearance monitoring may be used to predict treatment outcomes. Whether dosage regimen adjustments can modify the clearance time course and the treatment outcome is to be determined.

The effect of electronic audits and feedback in primary care and factors that contribute to their effectiveness: a systematic review

PURPOSE

The aim of this systematic review was (i) to assess whether electronic audit and feedback (A&F) is effective in primary care and (ii) to evaluate important features concerning content and delivery of the feedback in primary care, including the use of benchmarks, the frequency of feedback, the cognitive load of feedback and the evidence-based aspects of the feedback.

DATA SOURCES

The MEDLINE, Embase, CINAHL and CENTRAL databases were searched for articles published since 2010 by replicating the search strategy used in the last Cochrane review on A&F.

STUDY SELECTION

Two independent reviewers assessed the records for their eligibility, performed the data extraction and evaluated the risk of bias. Our search resulted in 8744 records, including the 140 randomized controlled trials (RCTs) from the last Cochrane Review. The full texts of 431 articles were assessed to determine their eligibility. Finally, 29 articles were included.

DATA EXTRACTION

Two independent reviewers extracted standard data, data on the effectiveness and outcomes of the interventions, data on the kind of electronic feedback (static versus interactive) and data on the aforementioned feedback features.

RESULTS OF DATA SYNTHESIS

Twenty-two studies (76%) showed that electronic A&F was effective. All interventions targeting medication safety, preventive medicine, cholesterol management and depression showed an effect. Approximately 70% of the included studies used benchmarks and high-quality evidence in the content of the feedback. In almost half of the studies, the cognitive load of feedback was not reported. Due to high heterogeneity in the results, no meta-analysis was performed.

CONCLUSION

This systematic review included 29 articles examining electronic A&F interventions in primary care, and 76% of the interventions were effective. Our findings suggest electronic A&F is effective in primary care for different conditions such as medication safety and preventive medicine. Some of the benefits of electronic A&F include its scalability and the potential to be cost effective. The use of benchmarks as comparators and feedback based on high-quality evidence are widely used and important features of electronic feedback in primary care. However, other important features such as the cognitive load of feedback and the frequency of feedback provision are poorly described in the design of many electronic A&F intervention, indicating that a better description or implementation of these features is needed. Developing a framework or methodology for automated A&F interventions in primary care could be useful for future research.

Status Toward the Implementation of Precision Dosing in Children

Precision dosing is progressing beyond the conceptual and proof-of-concept stages toward implementation. As the availability of dosing algorithms, tools, and platforms increases, so do the investment in technology services and actual implementation of clinical services offering these solutions to patients. Nowhere is this needed more than in pediatric populations, which are still reliant on adult drug development and bridging strategies to support dosing, often in the absence of actual dose-finding studies in the target pediatric population. Still, there is more work to be done to ensure that proper governance of these services is maintained, and that sustainability of these early implementations is guided by new science as it evolves and meaningful outcome data to confirm that such services deliver on both clinical and economic return on investment. In addition, the field should ensure that all approaches beyond a therapeutic drug monitoring-driven, pharmacokinetic-centric approach should be considered as the tools and services evolve, especially when pediatric-specific pharmacokinetic/pharmacodyamic and pharmacogenetic data are available and shown to be useful to guide dosing. This review evaluates current pediatric precision dosing efforts, highlighting their utility, longevity, and sustainability and assesses the current process for implementing such approaches examining current barriers that stand in the way of broader implementation and the stakeholders that must engage to ensure its ultimate success.

Efficacy of dashboard driven dosing of infliximab in inflammatory bowel disease patients; a randomized controlled trial

OBJECTIVES

Loss of response (LOR) to infliximab (IFX) remains a challenge in the management of inflammatory bowel diseases (IBD). Proactive dosing strategies to achieve and maintain predefined IFX trough levels (TL) may prevent LOR. We aimed to investigate the efficacy of dashboard driven IFX dosing compared to standard dosing in a prospective trial in IBD patients.

METHODS

In this multicentre 1:1 'PRECISION' trial, we randomized IBD patients in clinical remission (Harvey Bradshaw Index ≤4 for Crohn's disease (CD) or a partial Mayo score ≤2 for ulcerative colitis (UC)) receiving IFX maintenance treatment. The precision group (PG) received IFX dosing guided by a Bayesian pharmacokinetic model, aiming to achieve and maintain a TL of 3 µg/ml by treatment (de)escalation as indicated by the dashboard. Patients in the control group (CG) continued treatment without dose adaptations. The primary endpoint was the proportion of patients in sustained clinical remission after 1 year.

RESULTS

Eighty patients were enrolled (66 CD, 14 UC), and the median [interquartile range] age was 37 years [27-51]). After one year, 28/32 (88%) of patients in the PG were in sustained clinical remission versus 25/39 (64%) in the CG (p = .017). PG patients had lower median faecal calprotectin levels after 1 year (p = .031), whereas no significant differences in median CRP levels were found.

CONCLUSION

We demonstrated that the use of a Bayesian dashboard for IFX dosing in maintenance treatment for IBD reduced the incidence of LOR compared to standard dosing. Precision dosing also resulted in lower FCP levels.

CLINICALTRIALS.GOV NUMBER

NCT02453776.

A Model Averaging/Selection Approach Improves the Predictive Performance of Model-Informed Precision Dosing: Vancomycin as a Case Study

Many important drugs exhibit substantial variability in pharmacokinetics and pharmacodynamics leading to a loss of the desired clinical outcomes or significant adverse effects. Forecasting drug exposures using pharmacometric models can improve individual target attainment when compared with conventional therapeutic drug monitoring (TDM). However, selecting the "correct" model for this model-informed precision dosing (MIPD) is challenging. We derived and evaluated a model selection algorithm (MSA) and a model averaging algorithm (MAA), which automates model selection and finds the best model or combination of models for each patient using vancomycin as a case study, and implemented both algorithms in the MIPD software "TDMx." The predictive performance (based on accuracy and precision) of the two algorithms was assessed in (i) a simulation study of six distinct populations and (ii) a clinical dataset of 180 patients undergoing TDM during vancomycin treatment and compared with the performance obtained using a single model. Throughout the six virtual populations the MSA and MAA (imprecision: 9.9-24.2%, inaccuracy: less than ± 8.2%) displayed more accurate predictions than the single models (imprecision: 8.9-51.1%; inaccuracy: up to 28.9%). In the clinical dataset, the predictive performance of the single models applying at least one plasma concentration varied substantially (imprecision: 28-62%, inaccuracy: -16 to 25%), whereas the MSA or MAA utilizing these models simultaneously resulted in unbiased and precise predictions (imprecision: 29% and 30%, inaccuracy: -5% and 0%, respectively). MSA and MAA approaches implemented in TDMx might thereby lower the burden of fit-for-purpose validation of individual models and streamline MIPD.

Therapeutic drug monitoring of β-lactam antibiotics in the ICU

INTRODUCTION

Individualizing antibiotic therapy is paramount to improve clinical outcomes while minimizing the risk of toxicity and antimicrobial therapy. β-lactam antibiotics are amongst the drugs most commonly prescribed in the Intensive Care Unit (ICU). The pharmacokinetics of β-lactam antibiotics are profoundly altered in critically ill patients, leading to the failure of standard drug dosing regimens to result in adequate drug concentrations. Therapeutic Drug Monitoring (TDM) of β-lactam antibiotics is a promising tool to help optimize β-lactam antibiotic therapy.

AREAS COVERED

The rationale behind TDM for β-lactam antibiotics is explained, as well as some more practical aspects such as when to sample, what concentrations to strive for and how to use it in clinical practice. We also discuss microbiological and analytical considerations, knowledge gaps, and future perspectives of β-lactam antibiotics TDM in ICU patients.

EXPERT OPINION

TDM of β-lactam antibiotics has been studied intensively in recent years. While TDM may not yet be widely available, and targets need to be further refined, TDM of β-lactam antibiotics will help to optimize antibiotic therapy in the critically ill patient, as an integrated part of an antimicrobial stewardship program.

Improved Population Pharmacokinetic Model for Predicting Optimized Infliximab Exposure in Pediatric Inflammatory Bowel Disease

BACKGROUND

Many pediatric patients with inflammatory bowel disease (IBD) lose response to infliximab (IFX) within the first year, and achieving a minimal target IFX trough concentration is associated with higher remission rates and longer durability. Population pharmacokinetic (PK) modeling can predict trough concentrations for individualized dosing. The object of this study was to refine a population PK model that accurately predicts individual IFX exposure during maintenance therapy using longitudinal real-practice data.

METHODS

We exported data from the electronic health records of pediatric patients with IBD treated with originator IFX at a single center between January 2011 and March 2017. Subjects were divided into discovery and validation cohorts. A population PK model was built and then validated.

RESULTS

We identified 228 pediatric patients with IBD who received IFX and had at least 1 drug concentration measured, including 135 and 93 patients in the discovery and validation cohorts, respectively. Weight, albumin, antibodies to IFX (ATI) detected by a drug-tolerant assay, and erythrocyte sedimentation rate (ESR) were identified as covariates significantly associated with IFX clearance and incorporated into the model. The model exhibited high accuracy for predicting target IFX trough concentrations with an area under the receiver operating characteristic curve (AUROC) of 0.86 (95% confidence interval [CI], 0.81-0.91) for population-based predictions without prior drug-level input. Accuracy increased further for individual-based predictions when prior drug levels were known, with an AUROC of 0.93 (95% CI, 0.90-0.97).

CONCLUSIONS

A population PK model utilizing weight, albumin, ordinal drug-tolerant ATI, and ESR accurately predicts IFX trough concentrations during maintenance therapy in real-practice pediatric patients with IBD. This model, which incorporates dynamic clinical information, could be used for individualized dosing decisions to increase response durability.

Clinical Pharmacokinetic and Pharmacodynamic Considerations in the Treatment of Ulcerative Colitis

Ulcerative colitis (UC) is an inflammatory bowel disease (IBD) of unknown etiology, probably caused by a combination of genetic and environmental factors. The treatment of patients with active UC depends on the severity, localization and history of IBD medication. According to the classic step-up approach, treatment with 5-aminosalicylic acid compounds is the first step in the treatment of mild to moderately active UC. Corticosteroids, such as prednisolone are used in UC patients with moderate to severe disease activity, but only for remission induction therapy because of side effects associated with long-term use. Thiopurines are the next step in the treatment of active UC but monotherapy during induction therapy in UC patients is not preferred because of their slow onset. Therapeutic drug monitoring (TDM) of the pharmacologically active metabolites of thiopurines, 6-thioguanine nucleotide (6-TGN), has proven to be beneficial. Thiopurine S-methyltransferase (TMPT) plays a role in the metabolic conversion pathway of thiopurines and exhibits genetic polymorphism; however, the clinical benefit and relevance of TPMT genotyping is not well established. In patients with severely active UC refractory to corticosteroids, calcineurin inhibitors such as ciclosporin A (CsA) and tacrolimus are potential therapeutic options. These agents usually have a rather rapid onset of action. Monoclonal antibodies (anti-tumor necrosis factor [TNF] agents, vedolizumab) are the last pharmacotherapeutic option for UC patients before surgery becomes inevitable. Body weight, albumin status and antidrug antibodies contribute to the variability in the pharmacokinetics of anti-TNF agents. Additionally, the use of concomitant immunomodulators (thiopurines/methotrexate) lowers the rate of immunogenicity, and therefore the concomitant use of anti-TNF therapy with an immunomodulator may confer some advantage compared with monotherapy in certain patients. TDM of anti-TNF agents could be beneficial in patients with primary nonresponse and secondary loss of response. The potential benefit of applying TDM during vedolizumab treatment has yet to be determined.

Using Real-World Data to Guide Ustekinumab Dosing Strategies for Psoriasis: A Prospective Pharmacokinetic-Pharmacodynamic Study

Variation in response to biologic therapy for inflammatory diseases, such as psoriasis, is partly driven by variation in drug exposure. Real‐world psoriasis data were used to develop a pharmacokinetic/pharmacodynamic (PK/PD) model for the first‐line therapeutic antibody ustekinumab. The impact of differing dosing strategies on response was explored. Data were collected from a UK prospective multicenter observational cohort (491 patients on ustekinumab monotherapy, drug levels, and anti‐drug antibody measurements on 797 serum samples, 1,590 measurements of Psoriasis Area Severity Index (PASI)). Ustekinumab PKs were described with a linear one‐compartment model. A maximum effect (E_max) model inhibited progression of psoriatic skin lesions in the turnover PD mechanism describing PASI evolution while on treatment. A mixture model on half‐maximal effective concentration identified a potential nonresponder group, with simulations suggesting that, in future, the model could be incorporated into a Bayesian therapeutic drug monitoring “dashboard” to individualize dosing and improve treatment outcomes.

Therapeutic drug monitoring-based dosing of TNF inhibitors in inflammatory bowel disease: the way forward?

Introduction: Secondary loss of response to anti-tumor necrosis factor (TNF) therapy remains a challenge in the clinical management of inflammatory bowel disease (IBD) patients. A frequently observed reason for secondary loss of response to TNF blockers is inadequate drug exposure and sub-therapeutic serum drug concentrations. Areas covered: This review presents an overview of recent research on therapeutic drug monitoring (TDM)-based dosing with anti-TNF agents in IBD. The role of reactive and proactive TDM and different approaches on how to optimize anti-TNF treatment are discussed. Expert opinion: Due to variations within and between patients, the 'one size fits all' theory does not apply to all IBD patients receiving anti-TNF agents. Timing of TDM (i.e. reactive versus proactive) is a matter of debate. Both strategies might optimize anti-TNF treatment, although most trials did not show a clinical benefit compared to conventional dosing up to now. So-called dashboard systems might have an additive value in the optimization of anti-TNF treatment, since these tools enable clinicians to really personalize anti-TNF treatment.

Innovative Study Designs Optimizing Clinical Pharmacology Research in Infants and Children

Almost half of recent pediatric trials failed to achieve labeling indications, in large part because of inadequate study design. Therefore, innovative study methods are crucial to optimizing trial design while also reducing the potential harms inherent with drug investigation. Several methods exist to optimize the amount of pharmacokinetic data collected from the smallest possible volume and with the fewest number of procedures, including the use of opportunistic and sparse sampling, alternative and noninvasive matrices, and microvolume assays. In addition, large research networks using master protocols promote collaboration, reduce regulatory burden, and increase trial efficiency for both early- and late-phase trials. Large pragmatic trials that leverage electronic health records can capitalize on central management strategies to reduce costs, enroll patients with rare diseases on a large scale, and augment study generalizability. Further, trial efficiency and safety can be optimized through Bayesian adaptive techniques that permit planned protocol changes based on analyses of prior and accumulated data. In addition to these trial design features, advances in modeling and simulation have paved the way for systems-based and physiologically based models that individualize pediatric dosing recommendations and support drug approval. Last, given the low prevalence of many pediatric diseases, collecting deidentified genetic and clinical data on a large scale is a potentially transformative way to augment clinical pharmacology research in children.

Call for action: how to improve use of patient-reported outcomes to guide clinical decision making in rheumatoid arthritis

Current guidelines for the management of rheumatoid arthritis (RA) recommend early treatment and a treat-to-target goal of remission or low disease activity. Over the past decade, this approach has been extremely successful in reducing disease activity and joint damage in patients with RA. At the same time, however, overall patient perception of well-being appears to have decreased with respect to outcome measures considered important by patients themselves, such as pain, fatigue, physical function and quality of life. The timely and effective use of patient-reported outcomes (PROs) could encourage physicians to focus more on the impact of RA on patients and how patients are feeling. This in turn would facilitate shared decision making between patients and physicians, ultimately leading to a more patient-centered approach and improved patient care. Indeed, PROs provide information about individual patients that complements information provided by physical assessment and composite scores, and can also be used to guide patient care, such as determining whether a clinic visit is needed or whether treatment modifications are necessary. This is particularly important for patients who do not achieve the aspirational target of remission or low disease activity with pharmacological treatment. A number of validated PRO questionnaires are available, but how and which PROs should be incorporated into rheumatology clinical practice as part of the decision-making process is still controversial. Combining PROs with technology, such as computer adaptive tests, electronic PRO systems, web-based platforms and patient dashboards, could further aid PRO integration into daily rheumatology clinical practice.

Assessing Decline: Visualising Progression in Huntington's Disease using a Clinical Dashboard with Enroll-HD Data

BACKGROUND

In Huntington's disease (HD), it remains unclear how symptom severity and rate of symptomatic change relates to age and CAG repeat number (CAGn). It is often difficult for clinicians to assess whether an affected individual's symptoms are progressing at a similar rate to their affected peers, limiting their ability to intervene at the most appropriate time.

OBJECTIVE

To develop a clinical dashboard that compares an individual's total motor score (TMS), total functional capacity (TFC) and symbol digit modality test (SDMT) scores against a global cohort, controlling for age and CAGn. The dashboard could then be used by clinicians to identify individuals progressing at a disproportionate rate to his or her peers.

METHODS

Annualised longitudinal clinical assessment scores from the Enroll-HD dataset were used to generate decline trajectories of the global cohort, allowing cross-sectional (TMS n = 734; TFC n = 734; SDMT n = 694) and longitudinal (TMS n = 270; TFC n = 270; SDMT n = 247) comparison with individual clinical symptom rating scores, to assess decline relative to affected peers.

RESULTS

An electronic dashboard with a dynamic output display was created that rapidly compares clinical symptom rating scores of a specific individual against affected peers from a global cohort of comparable CAGn.

CONCLUSIONS

This study shows the potential for use of multi-centre trial data in allowing comparison of the individual to a larger group to facilitate improved decision-making for individual patients. Visualisation of these metrics via a clinical dashboard demonstrates how it may aid identification of those with disproportionate decline, offering potential for intervention at specific critical points in the disease course.

Prediction of Individual Serum Infliximab Concentrations in Inflammatory Bowel Disease by a Bayesian Dashboard System

Despite a robust exposure-response relationship of infliximab in inflammatory bowel disease (IBD), attempts to adjust dosing to individually predicted serum concentrations of infliximab (SICs) are lacking. Compared with labor-intensive conventional software for pharmacokinetic (PK) modeling (eg, NONMEM) dashboards are easy-to-use programs incorporating complex Bayesian statistics to determine individual pharmacokinetics. We evaluated various infliximab detection assays and the number of samples needed to precisely forecast individual SICs using a Bayesian dashboard. We assessed long-term infliximab retention in patients being dosed concordantly versus discordantly with Bayesian dashboard recommendations. Three hundred eighty-two serum samples from 117 adult IBD patients on infliximab maintenance therapy were analyzed by 3 commercially available assays. Data from each assay was modeled using NONMEM and a Bayesian dashboard. PK parameter precision and residual variability were assessed. Forecast concentrations from both systems were compared with observed concentrations. Infliximab retention was assessed by prediction for dose intensification via Bayesian dashboard versus real-life practice. Forecast precision of SICs varied between detection assays. At least 3 SICs from a reliable assay are needed for an accurate forecast. The Bayesian dashboard performed similarly to NONMEM to predict SICs. Patients dosed concordantly with Bayesian dashboard recommendations had a significantly longer median drug survival than those dosed discordantly (51.5 versus 4.6 months, P < .0001). The Bayesian dashboard helps to assess the diagnostic performance of infliximab detection assays. Three, not single, SICs provide sufficient information for individualized dose adjustment when incorporated into the Bayesian dashboard. Treatment adjusted to forecasted SICs is associated with longer drug retention of infliximab.

Therapeutic Drug Monitoring During Induction of Anti-Tumor Necrosis Factor Therapy in Inflammatory Bowel Disease: Defining a Therapeutic Drug Window

Anti-tumor necrosis factor (TNF) therapy has revolutionized the treatment of inflammatory bowel disease (IBD). However, up to 30% of patients with IBD show no clinical benefit and are defined as having a primary nonresponse. Primary nonresponse to a biologic can be attributed to either pharmacokinetic or pharmacodynamic issues, such as those involved in secondary loss of response. Pharmacokinetic issues are linked to undetectable or subtherapeutic drug concentrations because of either an accelerated non-immune-mediated clearance or immunogenicity and the development of antidrug antibodies, whereas pharmacodynamic issues are likely related to "non-TNF driven" disease. Therapeutic drug monitoring (TDM), defined as the evaluation of drug concentrations and antidrug antibodies, has been proven effective for optimizing anti-TNF therapy in IBD. Nevertheless, most of the data for TDM relate to patients losing response during maintenance therapy, whereas much less is known about the therapeutic drug window and use of TDM during anti-TNF induction therapy. Recent exposure-response relationship studies, though, demonstrate that high serum anti-TNF drug concentrations during and early after induction therapy are associated with favorable therapeutic outcomes in IBD. This suggests that early optimization of anti-TNF therapy may prevent some of the primary nonresponse related to pharmacokinetic issues (low drug concentrations) and lead to better short- and long-term outcomes. This review will focus on the role of TDM during the induction phase of anti-TNF therapy.

A systematic review of electronic audit and feedback: intervention effectiveness and use of behaviour change theory

BACKGROUND

Audit and feedback is a common intervention for supporting clinical behaviour change. Increasingly, health data are available in electronic format. Yet, little is known regarding if and how electronic audit and feedback (e-A&F) improves quality of care in practice.

OBJECTIVE

The study aimed to assess the effectiveness of e-A&F interventions in a primary care and hospital context and to identify theoretical mechanisms of behaviour change underlying these interventions.

METHODS

In August 2016, we searched five electronic databases, including MEDLINE and EMBASE via Ovid, and the Cochrane Central Register of Controlled Trials for published randomised controlled trials. We included studies that evaluated e-A&F interventions, defined as a summary of clinical performance delivered through an interactive computer interface to healthcare providers. Data on feedback characteristics, underlying theoretical domains, effect size and risk of bias were extracted by two independent review authors, who determined the domains within the Theoretical Domains Framework (TDF). We performed a meta-analysis of e-A&F effectiveness, and a narrative analysis of the nature and patterns of TDF domains and potential links with the intervention effect.

RESULTS

We included seven studies comprising of 81,700 patients being cared for by 329 healthcare professionals/primary care facilities. Given the extremely high heterogeneity of the e-A&F interventions and five studies having a medium or high risk of bias, the average effect was deemed unreliable. Only two studies explicitly used theory to guide intervention design. The most frequent theoretical domains targeted by the e-A&F interventions included 'knowledge', 'social influences', 'goals' and 'behaviour regulation', with each intervention targeting a combination of at least three. None of the interventions addressed the domains 'social/professional role and identity' or 'emotion'. Analyses identified the number of different domains coded in control arm to have the biggest role in heterogeneity in e-A&F effect size.

CONCLUSIONS

Given the high heterogeneity of identified studies, the effects of e-A&F were found to be highly variable. Additionally, e-A&F interventions tend to implicitly target only a fraction of known theoretical domains, even after omitting domains presumed not to be linked to e-A&F. Also, little evaluation of comparative effectiveness across trial arms was conducted. Future research should seek to further unpack the theoretical domains essential for effective e-A&F in order to better support strategic individual and team goals.

Clinical Pharmacokinetics and Pharmacodynamics of Biologic Therapeutics for Treatment of Systemic Lupus Erythematosus

Systemic lupus erythematosus (SLE) is a multifactorial autoimmune disease with potentially severe clinical manifestation that mainly affects women of child-bearing age. Patients who do not respond to standard-of-care therapies, such as corticosteroids and immunosuppressants, require biologic therapeutics that specifically target a single or multiple SLE pathogenesis pathways. This review summarizes the clinical pharmacokinetic and pharmacodynamic characteristics of biologic agents that are approved, used off-label, or in the active pipeline of drug development for SLE patients. Depending on the type of target, the interacting biologics may exhibit linear (non-specific) or non-linear (target-mediated) disposition profiles, with terminal half-lives varying from approximately 1 week to 1 month. Biologics given by subcutaneous administration, which offers dosing flexibility over intravenous administration, demonstrated a relatively slow absorption with a time to maximum concentration of approximately 1 day to 2 weeks and a variable bioavailability of 30-82 %. The population pharmacokinetics of monoclonal antibodies were best described by a two-compartment model with central clearance and steady-state volume of distribution ranging from 0.176 to 0.215 L/day and 3.60-5.29 L, respectively. The between-subject variability in pharmacokinetic parameters were moderate (20-79 %) and could be partially explained by body size. The development of linked pharmacokinetic-pharmacodynamic models incorporating SLE disease biomarkers are an attractive strategy for use in dosing regimen simulation and optimization. The relationship between efficacy/adverse events and biologic concentration should be evaluated to improve clinical trial outcomes, especially for biologics in the advanced phase of drug development. New strategies, such as model-based precision dosing dashboards, could be utilized to incorporate information collected from therapeutic drug monitoring into pharmacokinetic/pharmacodynamic models to enable individualized dosing in real time.

Personalized Drug Dosage - Closing the Loop

A brief account is given of various approaches to the individualization of drug dosage, including the use of pharmacodynamic markers, therapeutic monitoring of plasma drug concentrations, genotyping, computer-guided dosage using ‘dashboards’, and automatic closed-loop control of pharmacological action. The potential for linking the real patient to his or her ‘virtual twin’ through the application of physiologically-based pharmacokinetic modeling is also discussed.

Clinical Decision Support Tools: The Evolution of a Revolution

Dashboard systems for clinical decision support integrate data from multiple sources. These systems, the newest in a long line of dose calculators and other decision support tools, utilize Bayesian approaches to fully individualize dosing using information gathered through therapeutic drug monitoring. In the treatment of inflammatory bowel disease patients with infliximab, dashboards may reduce therapeutic failures and treatment costs. The history and future development of modern Bayesian dashboard systems is described.

A model-based evaluation of single metrics for discriminating changes in rheumatoid arthritis disease activity

AIMS

Composite indices for quantifying rheumatoid arthritis (RA) disease activity such as the 28-joint disease activity score (DAS28) are comprised of single parameters ('metrics') in various combinations. Population modelling methods were used to evaluate single metrics for their ability to reflect changes in disease activity with a view to understanding and improving composite indices.

METHODS

A total of 11 single metrics of RA disease activity (tender and swollen joint counts, acute phase reactants and global health, pain and physical function assessments) were obtained from 203 patients with recent onset RA. Participants received combination disease-modifying anti-rheumatic drugs (DMARDs) according to a treat-to-target approach with a pre-defined protocol for treatment intensification. Models describing each metric's magnitude and variability of change from baseline to a single 'treated' state in the population were developed using nonmem(®) . Measures that displayed uniformly large changes between states across the population were ranked higher in terms of discriminatory capacity.

RESULTS

Joint counts demonstrated a greater ability to discriminate changes in RA disease activity than others. Correlations between metrics demonstrated that erythrocyte sedimentation rate (ESR) had limited relationships with others for baseline scores and changes in RA disease activity (r generally < 0.2). However it appeared to be important in describing changes for those individuals where ESR levels were initially elevated.

CONCLUSION

It appears unlikely that a single group of metrics may be suitable to capture disease activity changes across all RA patients and defining the most appropriate metric(s) for individual patients will be an important area of future research.

Use of Modeling and Simulation in the Design and Conduct of Pediatric Clinical Trials and the Optimization of Individualized Dosing Regimens

Mathematical models of drug action and disease progression can inform pediatric pharmacotherapy. In this tutorial, we explore the key issues that differentiate pediatric from adult pharmacokinetic (PK) / pharmacodynamic (PD) studies, describe methods to calculate the number of participants to be enrolled and the optimal times at which blood samples should be collected, and therapeutic drug monitoring methods for individualizing pharmacotherapy. The development of pediatric-specific drug dosing dashboards is also highlighted, with an emphasis on clinical-relevance and ease of use.

Modeling and simulation in pediatric drug therapy: Application of pharmacometrics to define the right dose for children

During the past decades significant progress has been made in our understanding of the importance of age-appropriate development of new drug therapies in children. Importantly, several regulatory initiatives in Europe and the US have provided a framework for a rationale. In the US, most notably the enactment of the Best Pharmaceuticals for Children Act (BPCA) and Product Research and Equity Act (PREA) has facilitated the studying of on-patent and off-patent drugs in children. The biggest challenge in pediatric studies is defining a safe and effective dose or dose range in a patient population that can span from premature neonates to adolescents. From a mechanism-based perspective, advances in the science of quantitative pharmacology and pharmacometrics have resulted in the development of model-based approaches to better describe and understand important age-related factors influencing drug disposition and response in pediatric patients. The application of modeling and simulation has been shown to result in better estimates of pediatric doses as evidenced by several studies, although the optimal approach is still being debated. The extrapolation of efficacy findings from adults to the pediatric population has streamlined the development process especially for studies in older children. However, a focus on developmental changes in neonates and infants as well as further developing a paradigm for conducting pharmacodynamic studies in neonates, infants, and children remain important unmet needs. In this overview we will review current approaches for age-appropriate dose selection and highlight ongoing efforts to define exposure-response and clinical outcome relationships across the pediatric age spectrum.

Pharmacokinetic modeling of therapies for systemic lupus erythematosus

With the increasing use of different types of therapies in treating autoimmune diseases such as systemic lupus erythematosus (SLE), there is a need to utilize pharmacokinetic (PK) strategies to optimize the clinical outcome of these treatments. Various PK analysis approaches, including population PK modeling and physiologically based PK modeling, have been used to evaluate drug PK characteristics and population variability or to predict drug PK profiles in a mechanistic manner. This review outlines the PK modeling of major SLE therapies including immunosuppressants (methotrexate, azathioprine, mycophenolate and cyclophosphamide, among others) and immunomodulators (intravenous immunoglobulin). It summarizes the population PK modeling, physiologically based PK modeling and model-based individualized dosing strategies to improve the therapeutic outcomes in SLE patients.

Review article: applying pharmacokinetics to optimise dosing of anti-TNF biologics in acute severe ulcerative colitis

BACKGROUND

Acute severe ulcerative colitis (ASUC), the most aggressive presentation of ulcerative colitis (UC), occurs in 15% of adults and children with UC. First line therapy with intravenous corticosteroids is ineffective in half of adults and one-third of children. Therapeutic monoclonal antibodies against TNF (anti-TNF therapy) are emerging as a common treatment for ASUC due to their similar efficacy to calcineurin inhibitors and more favourable adverse effect profile.

AIM

To comprehensively review the evidence for anti-TNF therapy for ASUC in children and adults with regard to outcomes and pharmacokinetics.

METHODS

PubMed and recent conference proceedings were searched using the terms 'ulcerative colitis', 'acute severe ulcerative colitis', 'anti-TNF', 'pharmacokinetics' and the generic names of specific anti-TNF agents.

RESULTS

Outcomes after anti-TNF therapy for ASUC remain suboptimal with about one half of children and adults undergoing colectomy. While several randomised controlled trials have demonstrated the efficacy of anti-TNF therapy for ambulatory patients with moderate to severely active UC, patients in these studies were less ill than those with ASUC. Patients with ASUC may exhibit more rapid clearance of anti-TNF biologics due to pharmacokinetic mechanisms influenced by disease severity.

CONCLUSIONS

Conventional weight-based dosing effective in patients with moderately to severely active UC, may not be equally effective in those with acute severe ulcerative colitis. Personalised anti-TNF dosing strategies, which integrate patient factors and early measures of pharmacokinetics and response, hold promise for ensuring sustained drug exposure and maximising early mucosal healing in patients with acute severe ulcerative colitis.