Hollow-fibre system model of tuberculosis reproducibility and performance specifications for best practice in drug and combination therapy development.

BACKGROUND: The hollow-fibre system model of tuberculosis (HFS-TB) has been endorsed by regulators; however, application of HFS-TB requires a thorough understanding of intra- and inter-team variability, statistical power and quality controls. METHODS: Three teams evaluated regimens matching those in the Rapid Evaluation of Moxifloxacin in Tuberculosis (REMoxTB) study, plus two high-dose rifampicin/pyrazinamide/moxifloxacin regimens, administered daily for up to 28 or 56 days against Mycobacterium tuberculosis (Mtb) under log-phase growth, intracellular growth or semidormant growth under acidic conditions. Target inoculum and pharmacokinetic parameters were pre-specified, and the accuracy and bias at achieving these calculated using percent coefficient of variation (%CV) at each sampling point and two-way analysis of variance (ANOVA). RESULTS: A total of 10 530 individual drug concentrations, and 1026 individual cfu counts were measured. The accuracy in achieving intended inoculum was >98%, and >88% for pharmacokinetic exposures. The 95% CI for the bias crossed zero in all cases. ANOVA revealed that the team effect accounted for <1% of variation in log10 cfu/mL at each timepoint. The %CV in kill slopes for each regimen and different Mtb metabolic populations was 5.10% (95% CI: 3.36%-6.85%). All REMoxTB arms exhibited nearly identical kill slopes whereas high dose regimens were 33% faster. Sample size analysis revealed that at least three replicate HFS-TB units are needed to identify >20% difference in slope, with a power of >99%. CONCLUSIONS: HFS-TB is a highly tractable tool for choosing combination regimens with little variability between teams, and between replicates.

Target product profiles: tests for tuberculosis treatment monitoring and optimization.

The World Health Organization has developed target product profiles containing minimum and optimum targets for key characteristics for tests for tuberculosis treatment monitoring and optimization. Tuberculosis treatment optimization refers to initiating or switching to an effective tuberculosis treatment regimen that results in a high likelihood of a good treatment outcome. The target product profiles also cover tests of cure conducted at the end of treatment. The development of the target product profiles was informed by a stakeholder survey, a cost-effectiveness analysis and a patient-care pathway analysis. Additional feedback from stakeholders was obtained by means of a Delphi-like process, a technical consultation and a call for public comment on a draft document. A scientific development group agreed on the final targets in a consensus meeting. For characteristics rated of highest importance, the document lists: (i) high diagnostic accuracy (sensitivity and specificity); (ii) time to result of optimally ≤ 2 hours and no more than 1 day; (iii) required sample type to be minimally invasive, easily obtainable, such as urine, breath, or capillary blood, or a respiratory sample that goes beyond sputum; (iv) ideally the test could be placed at a peripheral-level health facility without a laboratory; and (v) the test should be affordable to low- and middle-income countries, and allow wide and equitable access and scale-up. Use of these target product profiles should facilitate the development of new tuberculosis treatment monitoring and optimization tests that are accurate and accessible for all people being treated for tuberculosis.

L'Organisation mondiale de la santé a élaboré des profils de produits cibles contenant des cibles minimales et optimales pour les caractéristiques principales des essais destinés au suivi et à l'optimisation du traitement de la tuberculose. L'optimisation du traitement de la tuberculose fait référence à l'instauration d'un régime de traitement efficace de la tuberculose ou à l'adoption d'un tel régime, avec une probabilité élevée d'obtenir de bons résultats thérapeutiques. Les profils de produits cibles couvrent également les essais de guérison effectués à l'issue du traitement. Les profils de produits cibles ont été élaborés sur la base d'un sondage auprès des parties prenantes, d'une analyse coût-efficacité et d'une analyse du parcours de soins du patient. Des retours supplémentaires des parties prenantes ont été obtenus au moyen d'un processus créé selon la méthode Delphi, d'une consultation technique et d'un appel à commentaires publics sur un projet de document. Un groupe d'élaboration scientifique s'est mis d'accord sur les objectifs finaux lors d'une réunion de concertation. En ce qui concerne les caractéristiques jugées les plus importantes, le document énumère ce qui suit: (i) une grande précision diagnostique (sensibilité et spécificité); (ii) un délai idéal d'obtention des résultats ≤ 2 heures et au maximum de 1 jour; (iii) le type d'échantillon requis doit être peu invasif et facile à obtenir, comme l'urine, l'haleine ou le sang capillaire, ou bien un échantillon respiratoire au-delà des expectorations; (iv) idéalement, l'essai pourrait avoir lieu dans un établissement de santé périphérique sans laboratoire ; et (v) l'essai devrait être abordable pour les pays à revenu faible et intermédiaire et permettre un accès large et équitable ainsi qu'une mise à l'échelle. L'utilisation de ces profils de produits cibles devrait faciliter la mise au point de nouveaux essais de surveillance et d'optimisation du traitement de la tuberculose qui soient précis et accessibles à toutes les personnes suivant un traitement pour la tuberculose.

La Organización Mundial de la Salud ha elaborado perfiles de productos objetivo que contienen objetivos mínimos y óptimos para las características principales de las pruebas de seguimiento y optimización del tratamiento de la tuberculosis. La optimización del tratamiento de la tuberculosis consiste en iniciar o cambiar a un régimen eficaz de tratamiento de la tuberculosis que ofrezca una alta probabilidad de un buen resultado terapéutico. Los perfiles de productos objetivo también abarcan las pruebas de curación realizadas al final del tratamiento. La elaboración de los perfiles de los productos objetivo se basó en una encuesta a las partes interesadas, un análisis de rentabilidad y un análisis de la vía de atención al paciente. Se obtuvo información adicional de las partes interesadas mediante un proceso tipo Delphi, una consulta técnica y una convocatoria de comentarios públicos sobre un borrador del documento. Un grupo de desarrollo científico acordó los objetivos finales en una reunión de consenso. Para las características clasificadas de mayor importancia, el documento enumera: (i) alta precisión diagnóstica (sensibilidad y especificidad); (ii) tiempo hasta el resultado de óptimamente ≤ 2 horas y no más de 1 día; (iii) el tipo de muestra requerida debe ser mínimamente invasiva, fácil de obtener, como orina, aliento o sangre capilar, o una muestra respiratoria que vaya más allá del esputo; (iv) idealmente la prueba podría realizarse en un centro sanitario periférico sin laboratorio; y (v) la prueba debe ser asequible para los países de ingresos bajos y medios y permitir un acceso amplio y equitativo y su expansión. El uso de estos perfiles de producto objetivo debería facilitar el desarrollo de pruebas nuevas de seguimiento y optimización del tratamiento de la tuberculosis que sean precisas y accesibles para todas las personas que reciben tratamiento antituberculoso.

Model-Based Meta-Analysis of Relapsing Mouse Model Studies from the Critical Path to Tuberculosis Drug Regimens Initiative Database.

Tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb), remains a leading infectious disease-related cause of death worldwide, necessitating the development of new and improved treatment regimens. Nonclinical evaluation of candidate drug combinations via the relapsing mouse model (RMM) is an important step in regimen development, through which candidate regimens that provide the greatest decrease in the probability of relapse following treatment in mice may be identified for further development. Although RMM studies are a critical tool to evaluate regimen efficacy, making comprehensive "apples to apples" comparisons of regimen performance in the RMM has been a challenge in large part due to the need to evaluate and adjust for variability across studies arising from differences in design and execution. To address this knowledge gap, we performed a model-based meta-analysis on data for 17 unique regimens obtained from a total of 1592 mice across 28 RMM studies. Specifically, a mixed-effects logistic regression model was developed that described the treatment duration-dependent probability of relapse for each regimen and identified relevant covariates contributing to interstudy variability. Using the model, covariate-normalized metrics of interest, namely, treatment duration required to reach 50% and 10% relapse probability, were derived and used to compare relative regimen performance. Overall, the model-based meta-analysis approach presented herein enabled cross-study comparison of efficacy in the RMM and provided a framework whereby data from emerging studies may be analyzed in the context of historical data to aid in selecting candidate drug combinations for clinical evaluation as TB drug regimens.

Sputum lipoarabinomannan (LAM) as a biomarker to determine sputum mycobacterial load: exploratory and model-based analyses of integrated data from four cohorts.

BACKGROUND: Despite the high global disease burden of tuberculosis (TB), the disease caused by Mycobacterium tuberculosis (Mtb) infection, novel treatments remain an urgent medical need. Development efforts continue to be hampered by the reliance on culture-based methods, which often take weeks to obtain due to the slow growth rate of Mtb. The availability of a "real-time" measure of treatment efficacy could accelerate TB drug development. Sputum lipoarabinomannan (LAM; an Mtb cell wall glycolipid) has promise as a pharmacodynamic biomarker of mycobacterial sputum load. METHODS: The present analysis evaluates LAM as a surrogate for Mtb burden in the sputum samples from 4 cohorts of a total of 776 participants. These include those from 2 cohorts of 558 non-TB and TB participants prior to the initiation of treatment (558 sputum samples), 1 cohort of 178 TB patients under a 14-day bactericidal activity trial with various mono- or multi-TB drug therapies, and 1 cohort of 40 TB patients with data from the first 56-day treatment of a standard 4-drug regimen. RESULTS: Regression analysis demonstrated that LAM was a predictor of colony-forming unit (CFU)/mL values obtained from the 14-day treatment cohort, with well-estimated model parameters (relative standard error ≤ 22.2%). Moreover, no changes in the relationship between LAM and CFU/mL were observed across the different treatments, suggesting that sputum LAM can be used to reasonably estimate the CFU/mL in the presence of treatment. The integrated analysis showed that sputum LAM also appears to be as good a predictor of time to Mycobacteria Growth Incubator Tube (MGIT) positivity as CFU/mL. As a binary readout, sputum LAM positivity is a strong predictor of solid media or MGIT culture positivity with an area-under-the-curve value of 0.979 and 0.976, respectively, from receiver-operator curve analysis. CONCLUSIONS: Our results indicate that sputum LAM performs as a pharmacodynamic biomarker for rapid measurement of Mtb burden in sputum, and thereby may enable more efficient early phase clinical trial designs (e.g., adaptive designs) to compare candidate anti-TB regimens and streamline dose selection for use in pivotal trials. Trial registration NexGen EBA study (NCT02371681).

Duration of pretomanid/moxifloxacin/pyrazinamide therapy compared with standard therapy based on time-to-extinction mathematics.

OBJECTIVES: Animal models have suggested that the combination of pretomanid with pyrazinamide and moxifloxacin (PaMZ) may shorten TB therapy duration to 3-4 months. Here, we tested that in the hollow-fibre system model of TB (HFS-TB). METHODS: A series of HFS-TB experiments were performed to compare the kill rates of the PaMZ regimen with the standard three-drug combination therapy. HFS-TB experiments were performed with bacilli in log-phase growth treated for 28 days, intracellular bacilli treated daily for 28 days and semi-dormant Mycobacterium tuberculosis treated with daily therapy for 56 days for sterilizing effect. Next, time-to-extinction equations were employed, followed by morphism transformation and Latin hypercube sampling, to determine the proportion of patients who achieved a time to extinction of 3, 4 or 6 months with each regimen. RESULTS: Using linear regression, the HFS-TB sterilizing effect rates of the PaMZ regimen versus the standard-therapy regimen during the 56 days were 0.18 (95% credible interval=0.13-0.23) versus 0.15 (95% credible interval=0.08-0.21) log10 cfu/mL/day, compared with 0.16 (95% credible interval=0.13-0.18) versus 0.11 (95% credible interval=0.09-0.13) log10 cfu/mL/day in the Phase II clinical trial, respectively. Using time-to-extinction and Latin hypercube sampling modelling, the expected percentages of patients in which the PaMZ regimen would achieve sterilization were 40.37% (95% credible interval=39.1-41.34) and 72.30% (95% credible interval=71.41-73.17) at 3 and 4 months duration of therapy, respectively, versus 93.67% (95% credible interval=93.18-94.13) at 6 months for standard therapy. CONCLUSIONS: The kill rates of the PaMZ regimen were predicted to be insufficient to achieve cure in less than 6 months in most patients.

Using Motion Picture Films to Teach Nursing Theory in Graduate Nursing Education.

Teaching strategies that use pedagogy of inquiry and contextualization are needed to ensure that nursing students will be well prepared to manage increasingly complex patient information. The rationale for using motion pictures to teach theoretical thinking is explained, and an assignment that uses motion pictures is described. Film scene assignments facilitate learning theoretical thinking skills, reading clinical situations, and understanding how theory can be useful to problem-solve ambiguous clinical situations. Motion pictures present a text-in-motion that can be studied and analyzed in a repeatable, objective, and collaborative way.

Quantitative approach for cardiac risk assessment and interpretation in tuberculosis drug development.

Cardiotoxicity is among the top drug safety concerns, and is of specific interest in tuberculosis, where this is a known or potential adverse event of current and emerging treatment regimens. As there is a need for a tool, beyond the QT interval, to quantify cardiotoxicity early in drug development, an empirical decision tree based classifier was developed to predict the risk of Torsades de pointes (TdP). The cardiac risk algorithm was developed using pseudo-electrocardiogram (ECG) outputs derived from cardiac myocyte electromechanical model simulations of increasing concentrations of 96 reference compounds which represented a range of clinical TdP risk. The algorithm correctly classified 89% of reference compounds with moderate sensitivity and high specificity (71 and 96%, respectively) as well as 10 out of 12 external validation compounds and the anti-TB drugs moxifloxacin and bedaquiline. The cardiac risk algorithm is suitable to help inform early drug development decisions in TB and will evolve with the addition of emerging data.

A standardised method for interpreting the association between mutations and phenotypic drug resistance in Mycobacterium tuberculosis.

A clear understanding of the genetic basis of antibiotic resistance in Mycobacterium tuberculosis is required to accelerate the development of rapid drug susceptibility testing methods based on genetic sequence.Raw genotype-phenotype correlation data were extracted as part of a comprehensive systematic review to develop a standardised analytical approach for interpreting resistance associated mutations for rifampicin, isoniazid, ofloxacin/levofloxacin, moxifloxacin, amikacin, kanamycin, capreomycin, streptomycin, ethionamide/prothionamide and pyrazinamide. Mutation frequencies in resistant and susceptible isolates were calculated, together with novel statistical measures to classify mutations as high, moderate, minimal or indeterminate confidence for predicting resistance.We identified 286 confidence-graded mutations associated with resistance. Compared to phenotypic methods, sensitivity (95% CI) for rifampicin was 90.3% (89.6-90.9%), while for isoniazid it was 78.2% (77.4-79.0%) and their specificities were 96.3% (95.7-96.8%) and 94.4% (93.1-95.5%), respectively. For second-line drugs, sensitivity varied from 67.4% (64.1-70.6%) for capreomycin to 88.2% (85.1-90.9%) for moxifloxacin, with specificity ranging from 90.0% (87.1-92.5%) for moxifloxacin to 99.5% (99.0-99.8%) for amikacin.This study provides a standardised and comprehensive approach for the interpretation of mutations as predictors of M. tuberculosis drug-resistant phenotypes. These data have implications for the clinical interpretation of molecular diagnostics and next-generation sequencing as well as efficient individualised therapy for patients with drug-resistant tuberculosis.

Toward an Evidence-Based Nonclinical Road Map for Evaluating the Efficacy of New Tuberculosis (TB) Drug Regimens: Proceedings of a Critical Path to TB Drug Regimens-National Institute of Allergy and Infectious Diseases In Vivo Pharmacology Workshop for TB Drug Development.

Novel tuberculosis (TB) drug regimens are urgently needed, and their development will be enabled by improved preclinical approaches that more effectively inform and ensure safe selection of clinical candidates and drug combination/regimens. An evidence-based approach for the assessment of nonclinical models supporting TB drug development has been proposed by a joint partnership between the National Institute of Allergy and Infectious Diseases (NIAID) and the Critical Path to TB Drug Regimens (CPTR) Consortium.

Nonclinical models for antituberculosis drug development: a landscape analysis.

BACKGROUND: Several nonclinical drug-development tools (DDTs) have been used for antituberculosis drug development over several decades. The role of the DDTs used for evaluating the efficacy of antituberculosis drug combinations and the gaps in the evidence base for which new tools or approaches are needed are as yet undefined. METHODS: We performed a landscape analysis based on a comprehensive literature review to create evidence based guidelines. RESULTS: There are 3 important questions that a DDT should answer with regard to antituberculosis drugs: What combination(s) of drugs will be most effective? What dose(s) and schedule(s) of each drug should be administered? and What duration(s) of treatment will be efficacious? Four DDTs were identified as having a track record to answer these questions: in vitro susceptibility tests, the hollow fiber system model of tuberculosis, mice, and guinea pigs. No single nonclinical in vitro or animal model recapitulates all aspects of human tuberculosis. Therefore, a combination of models is recommended for drug development. Gaps identified include the need for standardization of nonclinical model experiments, evaluation of animal models with pathology more similar to that in humans, and identification of experimental quantitative output in the DDTs that correlates with sterilizing effect in humans. CONCLUSIONS: There is a need for formal quantitative analyses of how well DDTs forecast clinical outcomes.

Integration of published information into a resistance-associated mutation database for Mycobacterium tuberculosis.

Tuberculosis remains a major global public health challenge. Although incidence is decreasing, the proportion of drug-resistant cases is increasing. Technical and operational complexities prevent Mycobacterium tuberculosis drug susceptibility phenotyping in the vast majority of new and retreatment cases. The advent of molecular technologies provides an opportunity to obtain results rapidly as compared to phenotypic culture. However, correlations between genetic mutations and resistance to multiple drugs have not been systematically evaluated. Molecular testing of M. tuberculosis sampled from a typical patient continues to provide a partial picture of drug resistance. A database of phenotypic and genotypic testing results, especially where prospectively collected, could document statistically significant associations and may reveal new, predictive molecular patterns. We examine the feasibility of integrating existing molecular and phenotypic drug susceptibility data to identify associations observed across multiple studies and demonstrate potential for well-integrated M. tuberculosis mutation data to reveal actionable findings.

Strategic Regulatory Evaluation and Endorsement of the Hollow Fiber Tuberculosis System as a Novel Drug Development Tool.

The first nonclinical drug development tool (DDT) advanced by the Critical Path to TB Drug Regimens (CPTR) Initiative through a regulatory review process has been endorsed by leading global regulatory authorities. DDTs with demonstrated predictive accuracy for clinical and microbiological outcomes are needed to support decision making. Regulatory endorsement of these DDTs is critical for drug developers, as it promotes confidence in their use in Investigational New Drug and New Drug Application filings. The in vitro hollow fiber system model of tuberculosis (HFS-TB) is able to recapitulate concentration-time profiles (exposure) observed in patients for single drugs and combinations, by evaluating exposure measures for the ability to kill tuberculosis in different physiologic conditions. Monte Carlo simulations make this quantitative output useful to inform susceptibility breakpoints, dosage, and optimal combination regimens in patients, and to design nonclinical experiments in animal models. The Pre-Clinical and Clinical Sciences Working Group within CPTR executed an evidence-based evaluation of the HFS-TB for predictive accuracy. This extensive effort was enabled through the collaboration of subject matter experts representing the pharmaceutical industry, academia, product development partnerships, and regulatory authorities including the Food and Drug Administration (FDA) and the European Medicines Agency (EMA). A comprehensive analysis plan following the regulatory guidance documents for DDT qualification was developed, followed by individual discussions with the FDA and the EMA. The results from the quantitative analyses were submitted to both agencies, pursuing regulatory DDT endorsement. The EMA Qualification Opinion for the HFS-TB DDT was published 26 January 2015 (available at: http://www.ema.europa.eu/ema/index.jsp?curl=pages/regulation/document_listing/document_listing_000319.jsp).

Translating the Tuberculosis Research Agenda: Much Accomplished, but Much More to Be Done.

Despite the availability of effective diagnostics and curative treatment regimens for tuberculosis, millions of people die each year of this disease. The steady global increase in the number of tuberculosis cases caused by multidrug-resistant and extensively drug-resistant strains of Mycobacterium tuberculosis are of major concern, especially in light of the thin tuberculosis drug pipeline. New tuberculosis drugs are undergoing clinical evaluation, and renewed hope comes from fresh approaches to improve treatment outcomes using a range of adjunct host-directed cellular and repurposed drug therapies. Current efforts in developing second-generation and new rapid point-of-care diagnostic assays take advantage of recent genetic and molecular advances. Slow progress in the development of prophylactic and therapeutic vaccines requires increased funding for basic as well as translational research. Although major challenges remain, these can be overcome by cementing our resolve, raising advocacy, bolstering global funder investments, and leveraging more effective collaborations through equitable public-private partnerships.

Systematic Analysis of Hollow Fiber Model of Tuberculosis Experiments.

BACKGROUND: The in vitro hollow fiber system model of tuberculosis (HFS-TB), in tandem with Monte Carlo experiments, was introduced more than a decade ago. Since then, it has been used to perform a large number of tuberculosis pharmacokinetics/pharmacodynamics (PK/PD) studies that have not been subjected to systematic analysis. METHODS: We performed a literature search to identify all HFS-TB experiments published between 1 January 2000 and 31 December 2012. There was no exclusion of articles by language. Bias minimization was according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA). Steps for reporting systematic reviews were followed. RESULTS: There were 22 HFS-TB studies published, of which 12 were combination therapy studies and 10 were monotherapy studies. There were 4 stand-alone Monte Carlo experiments that utilized quantitative output from the HFS-TB. All experiments reported drug pharmacokinetics, which recapitulated those encountered in humans. HFS-TB studies included log-phase growth studies under ambient air, semidormant bacteria at pH 5.8, and nonreplicating persisters at low oxygen tension of ≤ 10 parts per billion. The studies identified antibiotic exposures associated with optimal kill of Mycobacterium tuberculosis and suppression of acquired drug resistance (ADR) and informed predictions about optimal clinical doses, expected performance of standard doses and regimens in patients, and expected rates of ADR, as well as a proposal of new susceptibility breakpoints. CONCLUSIONS: The HFS-TB model offers the ability to perform PK/PD studies including humanlike drug exposures, to identify bactericidal and sterilizing effect rates, and to identify exposures associated with suppression of drug resistance. Because of the ability to perform repetitive sampling from the same unit over time, the HFS-TB vastly improves statistical power and facilitates the execution of time-to-event analyses and repeated event analyses, as well as dynamic system pharmacology mathematical models.

Correlations Between the Hollow Fiber Model of Tuberculosis and Therapeutic Events in Tuberculosis Patients: Learn and Confirm.

BACKGROUND: The hollow fiber system model of tuberculosis (HFS-TB) is designed to perform pharmacokinetics/pharmacodynamics (PK/PD) experiments, and hence the design of optimal doses and dose schedules for the treatment of tuberculosis. To determine if this model is useful for deriving PK/PD data relevant to clinical outcomes, we compared its quantitative output to that from clinical trials. METHODS: We performed a PubMed search to identify clinical studies performed with antituberculosis therapy in which PK/PD data and/or parameters were documented or a dose-scheduling study design was employed. The search period was from January 1943 to December 2012. All clinical studies were published prior to HFS-TB experiments. Bias minimization was done according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Clinical publications were scored for quality of evidence, with 1 as the highest score (randomized controlled trials or meta-analyses of such studies), and 4 as the lowest score. RESULTS: We identified 17 studies that examined the same parameters as in 8 HFS-TB studies. Fifteen of 17 studies had a quality-of-evidence score of 1. The sterilizing and bactericidal effect rates for isoniazid, rifampin, pyrazinamide, and ethambutol were the same in the HFS-TB as in patients. Time to emergence of resistance for monotherapy was the same as in patients. The PK/PD indices associated with efficacy were the same in HFS-TB as in patients for all drugs examined. CONCLUSIONS: The HFS-TB model is highly accurate at identifying optimal drug exposures, doses, and dosing schedules for use in the clinic.

Forecasting Accuracy of the Hollow Fiber Model of Tuberculosis for Clinical Therapeutic Outcomes.

BACKGROUND: The hollow fiber system model of tuberculosis (HFS-TB), in tandem with Monte Carlo experiments, represents a drug development tool (DDT) with the potential for use to develop tuberculosis treatment regimens. However, the predictive accuracy of the HFS-TB, or any other nonclinical DDT such as an animal model, has yet to be robustly evaluated. METHODS: To avoid hindsight bias, a literature search was performed to identify clinical studies published at least 6 months after HFS-TB experiments' quantitative predictions. Steps to minimize bias and for reporting systematic reviews were applied as outlined in the Preferred Reporting Items for Systematic Reviews and Meta-Analyses. Publications were scored for quality of evidence. Accuracy was calculated using the mean absolute percentage error, then summated with weighting assigned by sample size and quality-of-evidence score. Given the lack of a gold-standard tuberculosis DDT, the forecasting accuracy of a completely unreliable tool was also calculated from 1000 simulated experiments for a random or "total guesswork" model. RESULTS: The quantitative forecasting accuracy (95% confidence interval [CI]) for the "total guesswork" model was 15.6% (95% CI, 8.7%-22.5%); bias was -0.1% (95% CI, -2.5% to 2.2%). Twenty clinical studies were published after HFS-TB experiments predicted optimal drug exposures and doses, susceptibility breakpoints, and optimal combination regimens. Based on these clinical studies, the predictive accuracy of the HFS-TB was 94.4% (95% CI, 84.3%-99.9%), and bias was 1.8% (95% CI, -13.7% to 6.2%). CONCLUSIONS: The HFS-TB model is highly accurate at forecasting optimal drug exposures, doses, and dosing schedules for use in the clinic.

Collaborative Effort for a Centralized Worldwide Tuberculosis Relational Sequencing Data Platform.

Continued progress in addressing challenges associated with detection and management of tuberculosis requires new diagnostic tools. These tools must be able to provide rapid and accurate information for detecting resistance to guide selection of the treatment regimen for each patient. To achieve this goal, globally representative genotypic, phenotypic, and clinical data are needed in a standardized and curated data platform. A global partnership of academic institutions, public health agencies, and nongovernmental organizations has been established to develop a tuberculosis relational sequencing data platform (ReSeqTB) that seeks to increase understanding of the genetic basis of resistance by correlating molecular data with results from drug susceptibility testing and, optimally, associated patient outcomes. These data will inform development of new diagnostics, facilitate clinical decision making, and improve surveillance for drug resistance. ReSeqTB offers an opportunity for collaboration to achieve improved patient outcomes and to advance efforts to prevent and control this devastating disease.

Modeling and simulation for medical product development and evaluation: highlights from the FDA-C-Path-ISOP 2013 workshop.

Medical-product development has become increasingly challenging and resource-intensive. In 2004, the Food and Drug Administration (FDA) described critical challenges facing medical-product development by establishing the critical path initiative [1]. Priorities identified included the need for improved modeling and simulation tools, further emphasized in FDA's 2011 Strategic Plan for Regulatory Science [Appendix]. In an effort to support and advance model-informed medical-product development (MIMPD), the Critical Path Institute (C-Path) [www.c-path.org], FDA, and International Society of Pharmacometrics [www.go-isop.org] co-sponsored a workshop in Washington, D.C. on September 26, 2013, to examine integrated approaches to developing and applying model- MIMPD. The workshop brought together an international group of scientists from industry, academia, FDA, and the European Medicines Agency to discuss MIMPD strategies and their applications. A commentary on the proceedings of that workshop is presented here.

Translating Authentic Nursing Knowledge From One Era to Another.

As time passes, concepts change. The risk to nursing theories is that concepts can shift so far away from a theorist's originally intended meaning that future scholars might misunderstand or misuse what will become historically time-bound theories. To preserve authentic nursing knowledge, the process of conceptual matching and translation is proposed. Two thought experiments are used to demonstrate conceptual translation.