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  • Beyond the Randomized Clinical Trial: Innovative Data Science to Close the Pediatric Evidence Gap
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-22
    Sebastiaan C. Goulooze; Laura B. Zwep; Julia E. Vogt; Elke H.J. Krekels; Thomas Hankemeier; John N. van den Anker; Catherijne A.J. Knibbe

    Despite the application of advanced statistical and pharmacometric approaches to pediatric trial data, a large pediatric evidence gap still remains. Here, we discuss how to collect more data from children by using real‐world data from electronic health records, mobile applications, wearables, and social media. The large datasets collected with these approaches enable and may demand the use of artificial intelligence and machine learning to allow the data to be analyzed for decision making. Applications of this approach are presented, which include the prediction of future clinical complications, medical image analysis, identification of new pediatric end points and biomarkers, the prediction of treatment nonresponders, and the prediction of placebo‐responders for trial enrichment. Finally, we discuss how to bring machine learning from science to pediatric clinical practice. We conclude that advantage should be taken of the current opportunities offered by innovations in data science and machine learning to close the pediatric evidence gap.

  • Comparative Outcomes of Treatment Initiation With Brand vs. Generic Warfarin in Older Patients
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Rishi J. Desai; Chandrasekar Gopalakrishnan; Sara Dejene; Ameet S. Sarpatwari; Raisa Levin; Sarah K. Dutcher; Zhong Wang; Sara Wittayanukorn; Jessica M. Franklin; Joshua J. Gagne

    The anticoagulant response to warfarin, a narrow therapeutic index drug, increases with age, which may make older patients susceptible to adverse outcomes resulting from small differences in bioavailability between generic and brand products. Using US Medicare claims linked to electronic medical records from two large hospitals in Boston, we designed a cohort study of ≥ 65‐year‐old patients. Patients were followed for a composite effectiveness outcome of ischemic stroke or venous thromboembolism, a composite safety outcome, including major hemorrhage, and a 1‐year all‐cause mortality outcome. After propensity score fine‐stratification and weighting to account for > 90 confounders, hazard ratios comparing brand vs. generic warfarin initiators (95% confidence intervals) for the effectiveness, safety, and all‐cause mortality outcomes, were 0.97 (0.65–1.46), 0.94 (0.65–1.35), and 0.84 (0.62–1.13), respectively. Results from subgroup analyses of patients with atrial fibrillation, CHADS‐VASc score ≥ 3, and HAS‐BLED score ≥ 3 were consistent with the primary analysis.

  • Mechanistic Population Pharmacokinetic Model of Oseltamivir and Oseltamivir Carboxylate Accounting for Physiological Changes to Predict Exposures in Neonates and Infants
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-20
    Leonid Gibiansky; Patanjali Ravva; Neil John Parrott; Rajinder Bhardwaj; Elke Zwanziger; Paul Grimsey; Barry Clinch; Stefan Sturm

    A mechanistic population‐pharmacokinetic model was developed to predict oseltamivir exposures in neonates and infants accounting for physiological changes during the first 2 years of life. The model included data from 13 studies, comprising 436 subjects with normal renal function (317 pediatric subjects [≥ 38 weeks postmenstrual age (PMA), ≥ 13 days old] and 119 adult subjects < 40 years). Concentration–time profiles of oseltamivir and its active metabolite, oseltamivir carboxylate (OC), were characterized by a four‐compartment model, with absorption described by three additional compartments. Renal maturational changes were implemented by description of OC clearance with allometric function of weight and Hill function of postmenstrual age. Clearance of OC increased with weight up to 43 kg (allometric coefficient 0.75). Half the adult OC clearance was reached at a PMA of 45.6 weeks (95% CI: 41.6–49.6) with a Hill coefficient of 2.35 (95% CI: 1.67–3.04). The model supports the EU/USA‐approved 3 mg/kg twice‐daily oseltamivir dose for infants < 1 year (PMA ≥ 38 weeks) and allows prediction of exposures in preterm neonates.

  • Development of a System for Post‐marketing Population Pharmacokinetic and Pharmacodynamic Studies using Real‐World Data from Electronic Health Records
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-20
    Leena Choi; Cole Beck; Elizabeth McNeer; Hannah L. Weeks; Michael L. Williams; Nathan T. James; Xinnan Niu; Bassel W. Abou‐Khalil; Kelly A. Birdwell; Dan M. Roden; C. Michael Stein; Cosmin A. Bejan; Joshua C. Denny; Sara L. Van Driest

    Post‐marketing population pharmacokinetic (PK) and pharmacodynamic (PD) studies can be useful to capture patient characteristics affecting PK or PD in real‐world settings. These studies require longitudinally measured dose, outcomes, and covariates in large numbers of patients; however, prospective data collection is cost‐prohibitive. Electronic health records (EHRs) can be an excellent source for such data, but there are challenges, including accurate ascertainment of drug dose. We developed a standardized system to prepare datasets from EHRs for population PK/PD studies. Our system handles a variety of tasks involving data extraction from clinical text using a natural language processing algorithm, data processing, and data building. Applying this system, we performed a fentanyl population PK analysis, resulting in comparable parameter estimates to a prior study. This new system makes the EHR data extraction and preparation process more efficient and accurate, and provides a powerful tool to facilitate post‐marketing population PK/PD studies using information available in EHRs.

  • Data Integrity in Global Clinical Trials: Discussions from Joint US FDA and MHRA UK Good Clinical Practice Workshop
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-20
    Ni A. Khin; Gail Francis; Jean Mulinde; Cheryl Grandinetti; Rachel Skeete; Bei Yu; Kassa Ayalew; Seongeun‐Julia Cho; Andrew Fisher; Cynthia Kleppinger; Ruben Ayala; Charles Bonapace; Arindam Dasgupta; Phillip D. Kronstein; Stephen Vinter

    Good Clinical Practice (GCP) is an international ethical and scientific quality standard for designing, conducting, recording, and reporting clinical trials. Regulatory agencies conduct GCP inspections to verify the integrity of data generated in clinical trials and to assure the protection of human research subjects, in addition to ensuring that clinical trials are conducted according to the applicable regulations.

  • MID3: Mission Impossible or Model‐Informed Drug Discovery and Development? Point‐Counterpoint Discussions on Key Challenges
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Sriram Krishnaswami; Daren Austin; Oscar Della Pasqua; Marc R. Gastonguay; Jogarao Gobburu; Piet H. van der Graaf; Daniele Ouellet; Stacey Tannenbaum; Sandra A.G. Visser

    MID3: Mission Impossible, or Model‐Informed, Drug Discovery and Development? At the 2019 ASCPT annual meeting, point‐counterpoint discussions were held on key challenges that limit, and future directions that enhance the adoption of MID3 across the drug discovery, development, regulatory and utilization continuum. We envision that the opportunities discussed, and lessons learned from having contrasting perspectives on issues that lack consensus may aid our discipline in more effectively implementing MID3 principles.

  • “In‐House” Data on the Outside – A Mobile Health Approach
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Qinlei Huang; Tami Crumley; Christina Walters; Liesbeth Cluckers; Ingeborg Heirman; Radha Railkar; Gaurav Bhatia; Matthew Cantor; Christopher Benko; Elena S. Izmailova; Sylvie Rottey; S. Aubrey Stoch

    Mobile health (mHealth) technologies have the potential to capture dense patient data on the background of real‐life behavior. Merck & Co., Inc. (Kenilworth, NJ, USA), in collaboration with Koneksa Health, conducted a Phase I clinical trial to validate cardiovascular mHealth technologies for concordance with traditional approaches and to establish sensitivity to detect effects of pharmacological intervention. This two‐part study enrolled 18 healthy male subjects. Part I, a 5‐day study, compared mHealth measures of heart rate (HR) and blood pressure (BP) to those from traditional methods. Hypotheses of similarity, in the clinic and at home, were tested individually for HR, systolic blood pressure, and diastolic blood pressure, at a 2‐sided 0.05 alpha level, with a prespecified criterion for similarity being the percentage differences between the 2 measurements within 15%. Part II, a 7‐day, 3‐period randomized balanced crossover study, evaluated the mHealth technology’s ability to detect effects of bisoprolol and salbutamol. Hypotheses that the changes from baseline in HR were greater in the bisoprolol (reduction in HR) and salbutamol (increase in HR) groups compared to no treatment were tested, at a 1‐sided 0.05 alpha level. Linear mixed‐effects models, Pearson’s correlation coefficients, summary statistics, and exploratory plots were applied to analyze the data. The mHealth measures of HR and BP were demonstrated to be similar to those from traditional methods, and sensitive to changes in cardiovascular parameters induced by bisoprolol and salbutamol.

  • Integration of omics data sources to inform mechanistic modelling of immune‐oncology therapies: a tutorial for clinical pharmacologists
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Georgia Lazarou; Vijayalakshmi Chelliah; Ben G. Small; Michael Walker; Piet H. van der Graaf; Andrzej M. Kierzek

    Application of contemporary molecular biology techniques to clinical samples in oncology resulted in the accumulation of unprecedented experimental data. These “omics” data are mined for discovery of therapeutic target combinations and diagnostic biomarkers. It is less appreciated that omics resources could also revolutionise development of the mechanistic models informing clinical pharmacology quantitative decisions about dose amount, timing, and sequence. We discuss the integration of omics data to inform mechanistic models supporting drug development in immuno‐oncology. To illustrate our arguments we present a minimal clinical model of the Cancer Immunity Cycle (CIC), calibrated for Non‐Small Cell Lung Carcinoma using tumour microenvironment composition inferred from transcriptomics of clinical samples. We review omics data resources which can be integrated to parameterise mechanistic models of the CIC. We propose that virtual trial simulations with clinical Quantitative Systems Pharmacology platforms informed by omics data will be making increasing impact in the development of cancer immunotherapies.

  • An application of machine learning in pharmacovigilance: estimating likely patient genotype from phenotypical manifestations of fluoropyrimidine toxicity
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Luis Correia Pinheiro; Julie Durand; Jean‐Michel Dogné

    Dihydropyrimidine dehydrogenase (DPD) deficient patients might only become aware of their genotype after exposure to dihydropyrimidines, if testing is performed. Case reports to pharmacovigilance databases might only contain phenotypical manifestations of DPD, without information on the genotype. This poses a difficulty to estimating the cases due to DPD. Auto machine learning models were developed to train patterns of phenotypical manifestations of toxicity, which were then used as a surrogate to estimate the number of cases of DPD related toxicity. Results indicate that between 8,878 (7.0%) to 16,549 (13.1%) patients have a profile similar to DPD deficient status. Feature importance matches the known end‐organ damage of DPD related toxicity, however accuracies in the range of 90% suggest presence of overfitting, and thus results need to be interpreted carefully. This study shows the potential for use of machine learning in the regulatory context but additional studies are required.

  • Model‐Informed Artificial Intelligence: Reinforcement Learning for Precision Dosing
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Benjamin Ribba; Sherri Dudal; Thierry Lavé; Richard W. Peck

    The availability of multi‐dimensional data together with the development of modern techniques for data analysis represent an exceptional opportunity for clinical pharmacology. Data science ‐ defined in this special issue as the novel approaches to the collection, aggregation and analysis of data ‐ can significantly contribute to characterize drug‐response variability at the individual level thus enabling clinical pharmacology to become a critical contributor to personalized healthcare through precision dosing. We propose a mini‐review of methodologies for achieving precision dosing with a focus on an artificial intelligence technique called reinforcement learning which is currently used for individualizing dosing regimen in patients with life‐threatening diseases. We highlight the interplay of such techniques with conventional pharmacokinetic/pharmacodynamics approaches and discuss applicability in drug research and early development.

  • Pharmacokinetics and pharmacodynamics of intensive anti‐tuberculosis treatment of tuberculous meningitis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Junjie Ding; Nguyen Thuy Thuong Thuong; Pham Van Toi; Dorothee Heemskerk; Thomas Pouplin; Tran Thi Hong Chau; Nguyen Thi Hoang Mai; Nguyen Hoan Phu; Phan Phu Loc; Nguyen Van Vinh Chau; Guy Thwaites; Joel Tarning

    The most effective anti‐tuberculosis drug treatment regimen for tuberculous meningitis is uncertain. We conducted a randomised controlled trial comparing standard treatment with a regimen intensified by rifampin 15mg/kg and levofloxacin for the first 60 days. The intensified regimen did not improve survival or any other outcome. We therefore conducted a nested pharmacokinetic/pharmacodynamic study in 237 trial participants to define exposure‐response relationships that might explain the trial results and improve future therapy. Rifampin 15mg/kg increased plasma and CSF exposures compared to 10mg/kg: day 14 plasma AUC0‐24 increased from 48.2h∙mg/L (range 18.2‐93.8) to 82.5h∙mg/L (range 8.7‐161.0) and CSF AUC0‐24 from 3.5h∙mg/L (range 1.2‐9.6) to 6.0h∙mg/L (range 0.7‐15.1). However, there was no relationship between rifampin exposure and survival. In contrast, we found that isoniazid exposure was associated with survival, with low exposure predictive of death and linked to a fast metabolizer phenotype. Higher doses of isoniazid should be investigated, especially in fast metabolizers.

  • Can we rely on results from IQVIA Medical Research Data UK converted to the Observational Medical Outcome Partnership Common Data Model?
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Gianmario Candore; Karin Hedenmalm; Jim Slattery; Alison Cave; Xavier Kurz; Peter Arlett

    Exploring and combining results from more than one real world data (RWD) source might be necessary in order to explore variability and demonstrate generalisability of the results, or for regulatory requirements. However, the heterogeneous nature of RWD poses challenges when working with more than one source, some of which can be solved by analysing databases converted into a common data model (CDM). The main objective of the study was to evaluate the implementation of the Observational Medical Outcome Partnership (OMOP) CDM on IQVIA Medical Research Data (IMRD) UK data. A drug utilisation study describing the prescribing of codeine for pain in children was used as a case study to be replicated in IMRD‐UK and its corresponding OMOP CDM transformation. Differences between IMRD‐UK source and OMOP CDM were identified and investigated. In IMRD‐UK updated to May 2017, results were similar between source and transformed data with few discrepancies. These were the result of different conventions applied during the transformation regarding the date of birth for children younger than 15 years and the start of the observation period, and of a misclassification of two drug treatments. After the initial analysis and feedback provided, a re‐run of the analysis in IMRD‐UK updated to September 2018 showed almost identical results for all the measures analysed. For this study, the conversion to OMOP CDM was adequate. While some decisions and mapping could be improved, these impacted on the absolute results but not on the study inferences. This validation study supports six recommendations for good practice in transforming to CDMs.

  • A Simulation Approach to Evaluate the Impact of Patterns of Bioanalytical Bias Difference on the Outcome of Pharmacokinetic Similarity Studies
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Obinna N. Obianom; Olanrewaju O. Okusanya; Justin Earp; Theingi M. Thway

    Pharmacokinetic (PK) similarity studies are vital to assess the biosimilarity of a biosimilar to a reference product. Systematic bias in a bioanalytical method that quantify products could be a potential source of error affecting the variability of the data and influencing the outcome of a PK similarity study. We investigated the impact of six varying patterns of bioanalytical bias difference (BiasDiff) between the similar products on the probability passing the PK similarity test. A population PK model was used to simulate concentration‐time profiles for a biosimilar and a reference product and added BiasDiff ranging from 0% to 30%. The probability of achieving the PK similarity criteria (90% confidence‐interval between 0.8 and 1.25) for the maximum serum concentration (Cmax) and area‐under‐the‐curve (AUC) was assessed. The data indicate that an increase in absolute BiasDiff between products of ≥10% would decrease the power to assess the similarity criteria for Cmax and AUC.

  • Will Artificial Intelligence for Drug Discovery Impact Clinical Pharmacology?
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-19
    Alex Zhavoronkov; Quentin Vanhaelen; Tudor I. Oprea

    As the field of artificial intelligence and machine learning (AI/ML) for drug discovery is rapidly advancing, we address the question "what is the impact of recent AI/ML trends in the area of Clinical Pharmacology". We address difficulties and AI/ML developments for target identification, their use in generative chemistry for small molecule drug discovery, and the potential role of AI/ML in clinical trial outcome evaluation. We briefly discuss current trends in the use of AI/ML in healthcare and the impact of AI/ML context of the daily practice of clinical pharmacologists.

  • Selection of the Recommended Phase 2 Dose for Bintrafusp Alfa, a Bifunctional Fusion Protein Targeting TGF‐β and PD‐L1
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-18
    Yulia Vugmeyster; Justin Wilkins; Andre Koenig; Samer El Bawab; Isabelle Dussault; Laureen S. Ojalvo; Samrita De Banerjee; Lena Klopp‐Schulze; Akash Khandelwal

    Bintrafusp alfa, a first‐in‐class bifunctional fusion protein composed of the extracellular domain of the TGF‐βRII receptor (TGF‐β “trap”) fused to a human IgG1‐blocking PD‐L1, showed a manageable safety profile and clinical activity in phase 1 studies in patients with heavily pretreated advanced solid tumors. The recommended phase 2 dose (RP2D) was selected based on integration of modeling, simulations, and all available data. A 1200‐mg Q2W dose was predicted to maintain serum trough concentration (Ctrough) that inhibits all targets of bintrafusp alfa in circulation in >95% of patients, and a 2400‐mg Q3W dose was predicted to have similar Ctrough. A trend towards an association between exposure and efficacy variables and a relatively stronger inverse association between clearance and efficacy variables were observed. Exposure was either weakly or not correlated with probability of adverse events. The selected intravenous RP2D of bintrafusp alfa is 1200 mg Q2W or 2400 mg Q3W.

  • Challenges in Alzheimer Disease Drug Discovery and Development: The Role of Modeling, Simulation and Open Data
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-18
    Daniela J Conrado; Sridhar Duvvuri; Hugo Geerts; Jackson Burton; Carla Biesdorf; Malidi Ahamadi; Sreeraj Macha; Gregory Hather; Juan Francisco Morales; Jagdeep Podichetty; Timothy Nicholas; Diane Stephenson; Mirjam Trame; Klaus Romero; Brian Corrigan;

    Alzheimer disease (AD) is the leading cause of dementia worldwide. With 35 million people over 60 years of age with dementia, there is an urgent need to develop new treatments for AD. To streamline this process, it is imperative to apply insights and learnings from past failures to future drug development programs. In the present work, we focus on how modeling and simulation (M&S) tools can leverage open data to address drug development challenges in AD.

  • Ability of primary care health databases to assess medicinal products discussed by the European Union Pharmacovigilance Risk Assessment Committee
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-18
    Robert Flynn; Karin Hedenmalm; Tarita Murray‐Thomas; Alexandra Pacurariu; Peter Arlett; Hilary Shepherd; Puja Myles; Xavier Kurz

    This study measured the exposure to different categories of medicinal products discussed by the EU Pharmacovigilance Risk Assessment Committee from September to November 2018 in 4 electronic primary care health databases: IQVIA Medical Research Data‐UK, IQVIA Medical Research Data‐France, IQVIA Medical Research Data‐Germany, and Clinical Practice Research Datalink Aurum, in the entire lifespan of each database until 31 August 2018.

  • Physiologically‐Based Pharmacokinetic Modeling for Optimal Dosage Prediction of Quinine Coadministered With Ritonavir‐Boosted Lopinavir
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-12
    Teerachat Saeheng; Kesara Na‐Bangchang; Marco Siccardi; Rajith K.R. Rajoli; Juntra Karbwang

    The coformulated lopinavir/ritonavir significantly reduces quinine concentration in healthy volunteers due to potential drug–drug interactions (DDIs). However, DDI information in malaria and HIV coinfected patients are lacking. The objective of the study was to apply physiologically‐based pharmacokinetic (PBPK) modeling to predict optimal dosage regimens of quinine when coadministered with lopinavir/ritonavir in malaria and HIV coinfected patients with different conditions. The developed model was validated against literature. Model verification was evaluated using the accepted method. The verified PBPK models successfully predicted unbound quinine disposition when coadministered with lopinavir/ritonavir in coinfected patients with different conditions. Suitable dose adjustments to counteract with the DDIs have identified in patients with various situations (i.e., a 7‐day course at 1,800 mg t.i.d. in patients with malaria with HIV infection, 648 mg b.i.d. in chronic renal failure, 648 mg t.i.d. in hepatic insufficiency except for severe hepatic insufficiency (324 mg b.i.d.), and 648 mg t.i.d. in CYP3A4 polymorphism).

  • Pharmacometrics and machine learning partner to advance clinical data analysis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-12
    Gilbert Koch; Marc Pfister; Imant Daunhawer; Melanie Wilbaux; Sven Wellmann; Julia E. Vogt

    Clinical pharmacology is a multi‐disciplinary data sciences field that utilizes mathematical and statistical methods to generate maximal knowledge from data. Pharmacometrics (PMX) is a well‐recognized tool to characterize disease progression, pharmacokinetics and risk factors. Since the amount of data produced keeps growing with increasing pace, the computational effort necessary for PMX models is also increasing. Additionally, computationally efficient methods such as machine learning (ML) are becoming increasingly important in medicine. However, ML is currently not an integrated part of PMX, for various reasons. The goals of this article are to (i) provide an introduction to ML classification methods, (ii) provide examples for a ML classification analysis to identify covariates based on specific research questions, (iii) examine a clinically relevant example to investigate possible relationships of ML and PMX, and (iv) present a summary of ML and PMX tasks to develop clinical decision support tools.

  • Application of Machine Learning in Drug Development and Regulation: Current Status and Future Potential
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-11
    Qi Liu; Hao Zhu; Chao Liu; Daphney Jean; Shiew‐Mei Huang; M. Khair ElZarrad; Gideon Blumenthal; Yaning Wang

    Machine learning (ML), a field of data science with over 50 years of history, has gained momentum in the past decade due to the intersection of powerful computing tools and the increased availability of large data sets. Herein, we provide an overview of a sample of ML algorithms and describe areas where ML has been used to support drug development and regulatory submissions to US FDA, as well as to facilitate review and research.

  • A Scoping Review of the Evidence Behind CYP2D6 Inhibitor Classifications
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-07
    Emily J. Cicali; D. Max Smith; Benjamin Q. Duong; Lukas G. Kovar; Larisa H. Cavallari; Julie A. Johnson

    The FDA lists 22 medications as clinical inhibitors of CYP2D6, with classifications of strong, moderate, and weak. It is accepted that strong inhibitors result in nearly null enzymatic activity, but reduction caused by moderate and weak inhibitors is less well characterized. The objective was to identify if the classification of currently listed FDA moderate and weak inhibitors is supported by publicly available primary literature. We conducted a literature search and reviewed product labels (PLs) for AUC‐fold changes caused by inhibitors in humans and identified 89 inhibitor‐substrate pairs. Observed AUC‐fold change of the substrate was used to create an observed inhibitor classification per FDA‐defined AUC‐fold change thresholds. We then compared the observed inhibitor classification with the classification listed in the FDA Table of Inhibitors. We found 62% of the inhibitors within the pairs matched the listed FDA classification. We explored reasons for discordance and suggest modifications to the FDA table of clinical inhibitors for cimetidine, desvenlafaxine, and fluvoxamine.

  • Proton‐Pump Inhibitors Augment the Risk of Major Adverse Cardiovascular Events and End‐Stage Renal Disease in Patients with Acute Kidney Injury After Temporary Dialysis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-04
    I‐Jung Tsai; Tai‐Shuan Lai; Chih‐Chung Shiao; Tao‐Min Huang; Chih‐Hsien Wang; Liang‐Wen Chen; Yen‐Hung Lin; Likwang Chen; Vin‐Cent Wu; Tzong‐Shinn Chu;

    Proton‐pump inhibitors (PPIs) have been reported to increase the risk of acute and chronic renal disease. However, the data is unclear in patients with acute kidney injury (AKI) requiring dialysis (AKI‐D) who are often candidates for PPI. To investigate this important issue, we identified 26,052 patients from Taiwan’s National Health Insurance Research Database weaning dialysis from AKI‐D. During a mean follow‐up period of 3.52 years, the PPI users had a higher incidence of end‐stage renal disease (ESRD) than the PPI non‐users (P<.001). After propensity score matching and treating mortality as a competing risk factor, the PPIs users had a higher risk in ESRD (sHR 1.40; 95% CI 1.31‐1.50) and major adverse cardiac events (MACE, sHR1.53; 95 %CI 1.37‐1.71) compared to the PPI non‐users with AKI‐D survivors. In conclusion, the use of PPIs was associated with a higher risk of ESRD and MACE, compared to the PPI non‐users in AKI‐D patients.

  • Normalized testosterone glucuronide (TG/AG) as a potential urinary biomarker for highly variable UGT2B17 in children 7 to 18 years
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-03
    Haeyoung Zhang; Abdul Basit; Chris Wolford; Kuan‐Fu Chen; Andrea Gaedigk; Yvonne S. Lin; J Steven Leeder; Bhagwat Prasad

    UDP‐glucuronosyltransferase 2B17 (UGT2B17) is a highly variable androgen‐ and drug‐metabolizing enzyme. UGT2B17 exhibits a unique ontogeny profile characterized by a dramatic increase in hepatic protein expression from pre‐pubertal age to adulthood. Age, sex, copy number variation (CNV), and single nucleotide polymorphisms only explain 26% of variability in protein expression, highlighting the need for a phenotypic biomarker for predicting inter‐individual variability in glucuronidation of UGT2B17 substrates. Here we propose testosterone glucuronide (TG) normalized by androsterone glucuronide (TG/AG) as a urinary UGT2B17 biomarker, and examine the associations between urinary TG/AG and age, sex, and CNV. We performed targeted metabolomics of 12 androgen conjugates with LC‐MS/MS in 63 pediatric subjects ages 7 to 18 years followed over 7 visits in 3 years. Consistent with the reported developmental trajectory of UGT2B17 protein expression, urinary TG/AG is significantly associated with age, sex, and CNV. In conclusion, TG/AG shows promise as a phenotypic urinary UGT2B17 biomarker.

  • Does Hepatic Impairment Affect the Exposure of Monoclonal Antibodies?
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-03
    Qin Sun; Shirley Seo; Simbarashe Zvada; Chao Liu; Kellie Reynolds

    Limited information is available regarding the effect of hepatic impairment (HI) on the pharmacokinetics of monoclonal antibodies (mAbs). The results of an earlier report based on therapeutic proteins (TPs), including mAbs, approved through the end of 2012 were inconclusive due to limited HI data available at that time. New HI data for mAbs or antibody‐drug conjugates (ADCs; with a focus on the mAb component) available between 2013 and 2018 were evaluated. The investigation indicates there is almost no data for severe HI, limited data for moderate HI, and abundant data for mild HI. A significant exposure decrease was found for several mAbs or ADCs and a trend for decreasing AUC was observed for other mAbs. Multiple potential mechanisms may contribute to the exposure decrease. Dose may need to be adjusted for patients with HI, after taking into account the exposure‐response relationships for both efficacy and safety.

  • Hippocampal neuroimaging‐informed clinical trial enrichment tool for amnestic mild cognitive impairment using open data
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-03
    Daniela J. Conrado; Jackson Burton; Derek Hill; Brian Willis; Vikram Sinha; Julie Stone; Neva Coello; Wenping Wang; Danny Chen; Timothy Nicholas; Michael Gold; Emily Hartley; Volker D. Kern; Klaus Romero; ;

    Our goal was to assess the enrichment utility of hippocampal volume (HV) as an enrichment biomarker in amnestic mild cognitive impairment (aMCI) clinical trials, and, hence, develop a HV neuroimaging‐informed clinical trial enrichment tool. Modeling of integrated longitudinal patient‐level data came from open‐access natural history studies in patients diagnosed with aMCI – the Alzheimer's disease Neuroimaging Initiative (ADNI)‐1 and ADNI‐2 – and indicated that a decrease of 1cm3 with respect to the analysis dataset median baseline intracranial volume‐adjusted HV (ICV‐HV; ~5cm3) is associated with more than 50% increase in disease progression rate as measured by the Clinical Dementia Rating Scale ‐ Sum‐of‐Boxes (CDR‐SB). Clinical trial simulations showed that the inclusion of aMCI subjects with baseline ICV‐HV below the 84th or 50th percentile allowed an approximate reduction in trial size of at least 26% and 55%, respectively. This clinical trial enrichment tool can help design more efficient and informative clinical trials.

  • Dose‐Dependent Inhibition of OATP1B by Rifampicin in Healthy Volunteers: Comprehensive Evaluation of Candidate Biomarkers and OATP1B Probe Drugs
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2020-01-01
    Daiki Mori; Emi Kimoto; Brian Rago; Yusuke Kondo; Amanda King‐Ahmad; Ragu Ramanathan; Linda S. Wood; Jillian G. Johnson; Vu H. Le; Manoli Vourvahis; A. David Rodrigues; Chieko Muto; Kenichi Furihata; Yuichi Sugiyama; Hiroyuki Kusuhara

    To address the most appropriate endogenous biomarker for drug–drug interaction risk assessment, eight healthy subjects received an organic anion transporting polypeptide 1B (OATP1B) inhibitor (rifampicin, 150, 300, and 600 mg), and a probe drug cocktail (atorvastatin, pitavastatin, rosuvastatin, and valsartan). In addition to coproporphyrin I, a widely studied OATP1B biomarker, we identified at least 4 out of 28 compounds (direct bilirubin, glycochenodeoxycholate‐3‐glucuronide, glycochenodeoxycholate‐3‐sulfate, and hexadecanedioate) that presented good sensitivity and dynamic range in terms of the rifampicin dose‐dependent change in area under the plasma concentration‐time curve ratio (AUCR). Their suitability as OATP1B biomarkers was also supported by the good correlation of AUC0‐24h between the endogenous compounds and the probe drugs, and by nonlinear regression analysis (AUCR−1 vs. rifampicin plasma Cmax (maximum total concentration in plasma)) to yield an estimate of the inhibition constant of rifampicin. These endogenous substrates can complement existing OATP1B‐mediated drug–drug interaction risk assessment approaches based on agency guidelines in early clinical trials.

  • Adherence and Population Pharmacokinetic Properties of Amodiaquine When Used for Seasonal Malaria Chemoprevention in African Children
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-31
    Junjie Ding; Matthew E. Coldiron; Bachir Assao; Ousmane Guindo; Daniel Blessborn; Markus Winterberg; Rebecca F. Grais; Alena Koscalova; Celine Langendorf; Joel Tarning

    Poor adherence to seasonal malaria chemoprevention (SMC) might affect the protective effectiveness of SMC. Here, we evaluated the population pharmacokinetic properties of amodiaquine and its active metabolite, desethylamodiaquine, in children receiving SMC under directly observed ideal conditions (n = 136), and the adherence of SMC at an implementation phase in children participating in a case‐control study to evaluate SMC effectiveness (n = 869). Amodiaquine and desethylamodiaquine concentration‐time profiles were described simultaneously by two‐compartment and three‐compartment disposition models, respectively. The developed methodology to evaluate adherence showed a sensitivity of 65–71% when the first dose of SMC was directly observed and 71–73% when no doses were observed in a routine programmatic setting. Adherence simulations and measured desethylamodiaquine concentrations in the case‐control children showed complete adherence (all doses taken) in < 20% of children. This result suggests that more efforts are needed urgently to improve the adherence to SMC among children in this area.

  • Physiologically‐Based Pharmacokinetic Models for Evaluating Membrane Transporter Mediated Drug–Drug Interactions: Current Capabilities, Case Studies, Future Opportunities, and Recommendations
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-31
    Kunal S. Taskar; Venkatesh Pilla Reddy; Howard Burt; Maria M. Posada; Manthena Varma; Ming Zheng; Mohammed Ullah; Arian Emami Riedmaier; Ken‐ichi Umehara; Jan Snoeys; Masanori Nakakariya; Xiaoyan Chu; Maud Beneton; Yuan Chen; Felix Huth; Rangaraj Narayanan; Dwaipayan Mukherjee; Vaishali Dixit; Yuichi Sugiyama; Sibylle Neuhoff

    Physiologically‐based pharmacokinetic (PBPK) modeling has been extensively used to quantitatively translate in vitro data and evaluate temporal effects from drug–drug interactions (DDIs), arising due to reversible enzyme and transporter inhibition, irreversible time‐dependent inhibition, enzyme induction, and/or suppression. PBPK modeling has now gained reasonable acceptance with the regulatory authorities for the cytochrome‐P450‐mediated DDIs and is routinely used. However, the application of PBPK for transporter‐mediated DDIs (tDDI) in drug development is relatively uncommon. Because the predictive performance of PBPK models for tDDI is not well established, here, we represent and discuss examples of PBPK analyses included in regulatory submission (the US Food and Drug Administration (FDA), the European Medicines Agency (EMA), and the Pharmaceuticals and Medical Devices Agency (PMDA)) across various tDDIs. The goal of this collaborative effort (involving scientists representing 17 pharmaceutical companies in the Consortium and from academia) is to reflect on the use of current databases and models to address tDDIs. This challenges the common perceptions on applications of PBPK for tDDIs and further delves into the requirements to improve such PBPK predictions. This review provides a reflection on the current trends in PBPK modeling for tDDIs and provides a framework to promote continuous use, verification, and improvement in industrialization of the transporter PBPK modeling.

  • Inhibitory Effects of Probenecid on Pharmacokinetics of Tenofovir Disoproxil Fumarate and Emtricitabine for On‐Demand HIV Preexposure Prophylaxis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-31
    Stephanie N. Liu; Brandon T. Gufford; Jessica Bo Li Lu; Lane R. Bushman; Peter L. Anderson; Richard F. Bergstrom; Zeruesenay Desta; Samir K. Gupta

    In a randomized, crossover pharmacokinetic study in healthy volunteers (N = 14), a single dose of 2 g probenecid (PRO)‐boosted 600 mg tenofovir disoproxil fumarate (TDF)/400 mg emtricitabine (FTC) (test (T) +PRO) was compared with the current on‐demand HIV preexposure prophylaxis from the IPERGAY study (a 600 mg TDF/400 mg FTC on day 1 and 300 mg TDF/200 mg FTC on days 2 and 3) (control, C IPERGAY). PRO increased mean single‐dose area under the plasma concentration‐time curve extrapolated to infinity (AUC0–∞,SD) of tenofovir (TFV) and FTC by 61% and 68%, respectively. The TFV‐diphosphate (TFV‐DP) concentrations in peripheral blood mononuclear cells were higher (~30%) at 24 hours in T +PRO but then fell significantly lower (~40%) at 72 hours compared with C IPERGAY. The interaction between FTC and PRO was unexpected and novel. Further study is needed to determine if this PRO‐boosted TDF/FTC regimen would be clinically effective.

  • A model‐informed drug discovery and development (MID3) strategy for the novel glucose‐responsive insulin MK‐2640 enabled rapid decision making
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-30
    Sandra A.G. Visser; Bhargava Kandala; Craig Fancourt; Alexander W. Krug; Carolyn R. Cho

    A model‐informed drug discovery and development strategy played a key role in the novel glucose‐responsive insulin MK‐2640’s early clinical development strategy and supported a novel clinical trial paradigm to assess glucose responsiveness. The development and application of in‐silico modeling approaches by leveraging substantial published clinical insulin PKPD data and emerging (pre‐)clinical data enabled rapid quantitative decision‐making. Learnings can be applied to define PKPD properties of novel insulins that could become therapeutically meaningful for diabetic patients.

  • Safety, Pharmacokinetics, and Mosquito‐Lethal Effects of Ivermectin in Combination With Dihydroartemisinin‐Piperaquine and Primaquine in Healthy Adult Thai Subjects
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-27
    Kevin C. Kobylinski; Podjanee Jittamala; Borimas Hanboonkunupakarn; Sasithon Pukrittayakamee; Kanchana Pantuwatana; Siriporn Phasomkusolsil; Silas A. Davidson; Markus Winterberg; Richard M. Hoglund; Mavuto Mukaka; Rob W. van der Pluijm; Arjen Dondorp; Nicholas P.J. Day; Nicholas J. White; Joel Tarning

    Mass administration of antimalarial drugs and ivermectin are being considered as potential accelerators of malaria elimination. The safety, tolerability, pharmacokinetics, and mosquito‐lethal effects of combinations of ivermectin, dihydroartemisinin‐piperaquine, and primaquine were evaluated. Coadministration of ivermectin and dihydroartemisinin‐piperaquine resulted in increased ivermectin concentrations with corresponding increases in mosquito‐lethal effect across all subjects. Exposure to piperaquine was also increased when coadministered with ivermectin, but electrocardiograph QT‐interval prolongation was not increased. One subject had transiently impaired liver function. Ivermectin mosquito‐lethal effect was greater than predicted previously against the major Southeast Asian malaria vectors. Both Anopheles dirus and Anopheles minimus mosquito mortality was increased substantially (20‐fold and 35‐fold increase, respectively) when feeding on volunteer blood after ivermectin administration compared with in vitro ivermectin‐spiked blood. This suggests the presence of ivermectin metabolites that impart mosquito‐lethal effects. Further studies of this combined approach to accelerate malaria elimination are warranted.

  • Quantitative Proteomics and Mechanistic Modeling of Transporter‐Mediated Disposition in Nonalcoholic Fatty Liver Disease
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-26
    Anna Vildhede; Emi Kimoto; Ryan M. Pelis; A. David Rodrigues; Manthena V.S. Varma

    Understanding transporter‐mediated drug disposition and pharmacokinetics (PK) in patients with nonalcoholic fatty liver disease (NAFLD) is critical in developing treatment options. Here, we quantified the expression levels of major drug transporters in healthy, steatosis, and nonalcoholic steatohepatitis (NASH) liver samples, via liquid‐chromatography tandem mass spectrometry‐based proteomics, and used the data to predict the PK of substrate drugs in the disease state. Expression of organic anion transporting polypeptides (OATPs) and multidrug resistance‐associated protein (MRP)2 is significantly lower in NASH livers; whereas MRP3 is induced while no change was observed for organic cation transporter (OCT)1. Physiologically‐based pharmacokinetic models verified with PK data from healthy subjects well recovered the PK in NASH subjects for morphine (involving OCT1) and its glucuronide metabolites (MRP2/MRP3/OATP1B), 99mTC‐mebrofenen (OATP1B/MRP2/MRP3), and rosuvastatin (OATP1B/breast cancer resistance protein). Overall, considerations to altered protein expression can enable quantitative prediction of PK changes in subjects with NAFLD.

  • Pharmacodynamics of glyburide, metformin and glyburide/metformin combination therapy in the treatment of gestational diabetes mellitus
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Diana L. Shuster; Laura M. Shireman; Xiaosu Ma; Danny D. Shen; Shannon K. Flood Nichols; Mahmoud S. Ahmed; Shannon Clark; Steve Caritis; Raman Venkataramanan; David M. Haas; Sara K. Quinney; Laura S. Haneline; Alan T. Tita; Tracy A. Manuck; Kenneth E. Thummel; Linda Morris Brown; Zhaoxia Ren; Zane Brown; Thomas R. Easterling; Mary F. Hebert

    In gestational diabetes mellitus (GDM), women are unable to compensate for the increased insulin resistance during pregnancy. Data are limited regarding the pharmacodynamic effects of metformin and glyburide during pregnancy. This study characterized insulin sensitivity (SI), β‐cell responsivity, and disposition index (DI) in women with GDM utilizing a mixed‐meal tolerance test (MMTT) before and during treatment with GLY monotherapy (GLY, n=38), metformin monotherapy (MET, n=34), or glyburide and metformin combination therapy (COMBO; n=36). GLY significantly decreased dynamic β‐cell responsivity (31%). MET and COMBO significantly increased SI (121% and 83%, respectively). While GLY, MET, and COMBO improved DI, metformin (MET and COMBO) demonstrated a larger increase in DI (p=0.05) and a larger decrease in MMTT peak glucose concentrations (p=0.03) than subjects taking only GLY. Maximizing SI with MET followed by increasing β‐cell responsivity with GLY or supplementing with insulin might be a more optimal strategy for GDM management than monotherapy.

  • Assessment of maternal and fetal dolutegravir exposure by integrating ex vivo placental perfusion data and physiologically‐based pharmacokinetic modeling
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Jolien J.M. Freriksen; Stein Schalkwijk; Angela P. Colbers; Khaled Abduljalil; Frans G.M. Russel; David M. Burger; Rick Greupink

    Antiretroviral therapy during pregnancy reduces the risk of vertical HIV‐1 transmission. However, drug dosing is challenging as pharmacokinetics may be altered during pregnancy. We combined a pregnancy physiologically‐based pharmacokinetic (p‐PBPK) modeling approach with data on placental drug transfer to simulate maternal and fetal exposure to dolutegravir. First, a PBPK model for dolutegravir exposure in healthy volunteers was established based on physiological and dolutegravir pharmacokinetic data. Next, the model was extended with a fetoplacental unit using transplacental kinetics obtained by performing ex vivo dual‐side human cotyledon perfusion experiments. Simulations of fetal exposure after maternal dosing in third trimester were in accordance with clinically observed dolutegravir cord blood data. Furthermore, the predicted fetal Ctrough following 50mg QD dosing remained above the EC90 for viral inhibition. Our integrated approach enables simulation of maternal and fetal dolutegravir exposure, illustrating this to be a promising way to assess dolutegravir pharmacokinetics during pregnancy.

  • Pharmacokinetic Modeling of Intrathecally Administered Recombinant Human Arylsulfatase A (TAK‐611) in Children with Metachromatic Leukodystrophy (MLD)
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Steven Troy; Margaret Wasilewski; Jack Beusmans; CJ Godfrey

    Metachromatic leukodystrophy (MLD) is a lysosomal storage disease caused by deficient arylsulfatase A (ASA) activity, which leads to neuronal sulfatide accumulation and motor and cognitive deterioration. Intrathecal delivery of a recombinant human ASA (rhASA; TAK‐611, formerly SHP611) is under development as a potential therapy for MLD. We used serum and cerebrospinal fluid (CSF) TAK‐611 concentrations measured during the phase 1/2 trial of intrathecal TAK‐611 to develop a pharmacokinetic model describing drug disposition. CSF data were well characterized by a two‐compartment model in the central nervous system (CNS); a single central compartment described the serum data. Estimated parameters suggested rapid distribution of TAK‐611 from CSF into the putative brain tissue compartment, with persistence in the brain between doses (median distributive and terminal half‐lives in the CNS: 1.02 and 477 hours, respectively). This model provides a valuable basis for understanding the pharmacokinetic distribution of TAK‐611, and for pharmacokinetic/pharmacodynamic analyses of functional outcomes.

  • A new liver eQTL map from 1,183 individuals provides evidence for novel eQTLs of drug response, metabolic and sex‐biased phenotypes
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Amy S. Etheridge; Paul J. Gallins; Dereje Jima; K. Alaine Broadaway; Mark J. Ratain; Erin Schuetz; Eric Schadt; Adrian Schroder; Cliona Molony; Yihui Zhou; Karen L. Mohlke; Fred A. Wright; Federico Innocenti

    Expression quantitative trait locus (eQTL) studies in human liver are crucial for elucidating how genetic variation influences variability in disease risk and therapeutic outcomes and may help guide strategies to obtain maximal efficacy and safety of clinical interventions. Associations between expression microarray and genome‐wide genotype data from four human liver eQTL studies (n=1,183) were analyzed. More than 2.3 million cis‐eQTLs for 15,668 genes were identified. When eQTLs were filtered against a list of 1,496 drug response genes, 187,829 cis‐eQTLs for 1,191 genes were identified. Additionally, 1,683 sex‐biased cis‐eQTLs were identified, as well as 49 and 73 cis‐eQTLs that colocalized with GWAS signals for blood metabolite or lipid levels, respectively. Translational relevance of these results is evidenced by linking DPYD eQTLs to differences in safety of chemotherapy, linking the sex‐biased regulation of PCSK9 expression to anti‐lipid therapy, and identifying the G‐protein coupled receptor GPR180 as a novel drug target for hypertriglyceridemia.

  • Fine‐Needle Aspiration for the Evaluation of Hepatic Pharmacokinetics of Vaniprevir: A Randomized Trial in Patients With Hepatitis C Virus Infection
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Wei Gao; Andrea L. Webber; Jill Maxwell; Melanie Anderson; Luzelena Caro; Chris Chung; André M.M. Miltenburg; Serghei Popa; Kristien Van Dyck; Larissa Wenning; Eric Mangin; Christine Fandozzi; Radha Railkar; Norah J. Shire; Iain Fraser; Bonnie Howell; Andrew H. Talal; S.Aubrey Stoch

    Fine‐needle aspiration (FNA) for serial hepatic sampling may be an efficient and less invasive alternative to core needle biopsy (CNB), the current standard for liver tissue sampling. In this randomized, open‐label trial in 31 participants with hepatitis C virus genotype 1 infection (NCT01678131/Merck protocol PN048), we evaluated the feasibility of using FNA to obtain human liver tissue samples appropriate for measuring hepatic pharmacokinetics (PK), using vaniprevir as a tool compound. The primary endpoint was successful retrieval of liver tissue specimens with measurable vaniprevir concentrations at two of three specified FNA timepoints. Twenty‐nine patients met the primary endpoint and therefore were included in the PK analyses. Hepatic vaniprevir concentrations obtained with FNA were consistent with known vaniprevir PK properties. The shape of liver FNA and CNB concentration‐time profiles were comparable. In conclusion, FNA may be effective for serial tissue sampling to assess hepatic drug exposure in patients with liver disease.

  • Broad‐Spectrum Profiling of Drug Safety via Learning Complex Network
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Ke Liu; Ruo‐Fan Ding; Han Xu; Yang‐Mei Qin; Qiu‐Shun He; Fei Du; Yun Zhang; Li‐Xia Yao; Pan You; Yan‐Ping Xiang; Zhi‐Liang Ji

    Drug safety is a severe clinical pharmacology and toxicology problem that has caused immense medical and social burdens every year. Regretfully, there still misses a reproducible method to assess drug safety systematically and quantitatively. In this study, we developed an advanced machine learning model for de novo drug safety assessment by solving the multilayer drug‐gene‐adverse drug reaction (ADR) interaction network. For the first time, the drug safety was assessed in a broad landscape of 1,156 distinct ADRs. We also designed a parameter ToxicityScore to quantify the overall drug safety. Moreover, we determined association strength for every 3,807,631 gene‐ADR interactions, which clues mechanistic exploration of ADRs. For convenience, we deployed the model as a web service ADRAlert‐gene at http://www.bio-add.org/ADRAlert/. In summary, this study offers insights into prioritizing safe drug therapy. It helps to reduce the attrition rate of new drug discovery by providing reliable ADR profile in early pre‐clinical stage.

  • Analytic and data sharing options in real‐world multi‐database studies of comparative effectiveness and safety of medical products
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Sengwee Toh

    A wide range of analytic and data sharing options are available in non‐experimental multi‐database studies designed to assess the real‐world benefits and risks of medical products. Researchers often consider six scientific domains when choosing among these options – study design, exposure type, outcome type, covariate summarization technique, covariate adjustment method, and data sharing approach. This article reviews available analytic and data sharing options and discuss key scientific and practical considerations when choosing among these options in multi‐database studies of comparative effectiveness and safety of medical products. The scientific considerations must be balanced against what the data‐contributing sites are able or willing to share. While pooling of person‐level datasets remains the most familiar and analytically flexible approach, newer analytic and data sharing approaches that share less granular summary‐level information may be equally valid and preferred in some multi‐database studies, especially when sharing of person‐level data is challenging or infeasible.

  • Safety and effectiveness of dabigatran and other direct oral anticoagulants compared to warfarin in patients with atrial fibrillation
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Krista F. Huybrechts; Chandrasekar Gopalakrishnan; Dorothee B. Bartels; Kristina Zint; Venkatesh K. Gurusamy; Joan Landon; Sebastian Schneeweiss

    The study objective was to evaluate the safety and effectiveness of dabigatran and other direct oral anticoagulants (DOACs) compared to warfarin among patients with non‐valvular atrial fibrillation using a prospective monitoring program.

  • Genetic factors influencing warfarin dose in Black‐African patients: a systematic review and meta‐analysis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Innocent G. Asiimwe; Eunice J. Zhang; Rostam Osanlou; Amanda Krause; Chrisly Dillon; Guilherme Suarez‐Kurtz; Honghong Zhang; Jamila A Perini; Jessicca Y. Renta; Jorge Duconge; Larisa H Cavallari; Leiliane R. Marcatto; Mark T. Beasly; Minoli A Perera; Nita A. Limdi; Paulo C.J.L. Santos; Stephen E. Kimmel; Steven A. Lubitz; Stuart A. Scott; Vivian K. Kawai; Andrea L. Jorgensen; Munir Pirmohamed

    Warfarin is the most commonly used oral anticoagulant in sub‐Saharan Africa. Dosing is challenging due to a narrow therapeutic index and high inter‐individual variability in dose requirements. To evaluate the genetic factors affecting warfarin dosing in Black‐Africans, we performed a meta‐analysis of 48 studies (2,336 patients). Significant predictors for CYP2C9 and stable dose included rs1799853 (CYP2C9*2), rs1057910 (CYP2C9*3), rs28371686 (CYP2C9*5), rs9332131 (CYP2C9*6), and rs28371685 (CYP2C9*11) reducing dose by 6.8, 12.5, 13.4, 8.1, and 5.3 mg/week respectively. VKORC1 variants rs9923231 (‐1639G>A), rs9934438 (1173C>T), rs2359612 (2255C>T), rs8050894 (1542G>C), and rs2884737 (497T>G) decreased dose by 18.1, 21.6, 17.3, 11.7, and 19.6 mg/week, respectively while rs7294 (3730G>A) increased dose by 6.9 mg/week. Finally, rs12777823 (CYP2C gene cluster) was associated with a dose reduction of 12.7 mg/week. Few studies were conducted in Africa, and patient numbers were small, highlighting the need for further work in Black Africans to evaluate genetic factors determining warfarin response.

  • Timing of pediatric drug approval and clinical evidence submitted to regulatory authorities: International comparison among Japan, the US, and the EU
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-23
    Saeko Hirota; Takuhiro Yamaguchi

    Many prescription drugs approved for adult use lack pediatric labeling information, resulting in their off‐label use in children. Drug regulatory authorities have developed legal and regulatory frameworks to promote pediatric drug development. However, the current state of pediatric indication approval and quality of efficacy evidence, which forms the basis of regulatory approvals, are unknown. Here, we analyzed novel therapeutics approved in Japan, the United States (US), and European Union (EU) during 2005‐2014 to investigate the timing and frequency of pediatric indication approval, and characterized the design of pediatric studies supporting regulatory approval. We found that, the US and EU experienced higher frequency of supplemental indication approval in pediatrics based on better‐designed studies than Japan. The speed and efficiency of pediatric drug development will improve by coordinating pediatric studies on an international basis. The results also implied the necessity for a robust system of post‐marketing monitoring of pediatric efficacy and safety.

  • Translational Knowledge Discovery between Drug Interactions and Pharmacogenetics
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-21
    Heng‐Yi Wu; Aditi Shendre; Shijun Zhang; Pengyue Zhang; Lei Wang; Desta Zeruesenay; Luis M. Rocha; Hagit Shatkay; Sara K. Quinney; Xia Ning; Lang Li

    Clinical translation of drug‐drug interaction (DDI) studies is limited, and knowledge gaps across different types of DDI evidences make it difficult to consolidate and link them to clinical consequences. Consequently, we developed information retrieval (IR) models to retrieve DDI and drug‐gene interaction (DGI) evidences from 25 million PubMed abstracts, and distinguish DDI evidences into in‐vitro pharmacokinetics (PK), and clinical PK and pharmacodynamics (PD) studies for FDA‐approved and withdrawn drugs. Additionally, information extraction models were developed to extract DDI‐ and DGI‐pairs from the IR‐retrieved abstracts. An overlapping analysis identified 986 DDI‐pairs between all three types of evidences. Another 2,157 and 13,012 DDI‐pairs, and 3,173 DGI‐pairs were identified from known clinical PK‐PD DDI, clinical PD DDI, and DGI evidences, respectively. By integrating DDI and DGI evidences, we discovered 119 and 18 new pharmacogenetic hypotheses associated with CYP3A and CYP2D6, respectively. Some of these DGI evidences can also aid us in understanding DDI mechanisms.

  • Generalized Pharmacometric Modeling, a Novel Paradigm for Integrating Machine Learning Algorithms: A Case Study of Metabolomic Biomarkers
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-20
    Mason McComb; Murali Ramanathan

    There is an unmet need for identifying innovative machine learning (ML) strategies to improve drug treatment regimens and therapeutic outcomes. We investigate Generalized Pharmacometric Modeling (GPM), a novel paradigm that integrates ML algorithms with pharmacokinetic and pharmacodynamic (PK/PD) structural models, population covariate modeling, and “big data” and enables identification of patient‐specific factors contributing to drug disposition. We hypothesize that GPM will enhance forecasting of drug outcomes in diverse populations. We assessed random forest regression (RFR) in conjunction with Bayesian networks (BN) as the ML methods within GPM and used the NHANES population‐based study database. GPM was utilized to identify subject‐specific factors associated with cholesterol dynamics. Our results demonstrate the utility of GPM to enhance pharmacometrics modeling and its potential for modeling drug outcomes in diverse populations.

  • A Machine‐Learning Approach to Identify a Prognostic Cytokine Signature That Is Associated With Nivolumab Clearance in Patients With Advanced Melanoma
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-19
    Rui Wang; Xiao Shao; Junying Zheng; Abdel Saci; Xiaozhong Qian; Irene Pak; Amit Roy; Akintunde Bello; Jasmine I. Rizzo; Fareeda Hosein; Rebecca A. Moss; Megan Wind‐Rotolo; Yan Feng

    Lower clearance of immune checkpoint inhibitors is a predictor of improved overall survival (OS) in patients with advanced cancer. We investigated a novel approach using machine learning to identify a baseline composite cytokine signature via clearance, which, in turn, could be associated with OS in advanced melanoma. Peripheral nivolumab clearance and cytokine data from patients treated with nivolumab in two phase III studies (n = 468 (pooled)) and another phase III study (n = 158) were used for machine‐learning model development and validation, respectively. Random forest (Boruta) algorithm was used for feature selection and classification of nivolumab clearance. The 16 top‐ranking baseline inflammatory cytokines reflecting immune‐cell modulation were selected as a composite signature to predict nivolumab clearance (area under the curve (AUC) = 0.75; accuracy = 0.7). Predicted clearance (high vs. low) via the cytokine signature was significantly associated with OS across all three studies (P < 0.01), regardless of treatment (nivolumab vs. chemotherapy).

  • Association of Statin and Its Lipophilicity With Cardiovascular Events in Patients Receiving Chronic Dialysis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-18
    Shih‐Wei Wang; Lung‐Chih Li; Chien‐Hao Su; Yao‐Hsu Yang; Tsuen‐Wei Hsu; Chien‐Ning Hsu

    Lipophilicity of statins has been linked to extrahepatic cell penetration and inhibition of isoprenoid synthesis and coenzyme Q10, which may affect myocardial contraction. Whether statins' lipophilicity affects the risk of cardiovascular disease development in patients under dialysis is unclear. This population‐based study included 114,929 patients undergoing chronic dialysis, retrieved from the Registry for Catastrophic Illness Patients from the National Health Insurance Research Database in Taiwan from 2000 to 2013. Statins were initiated after dialysis and classified into hydrophilic and lipophilic by the duration of use. In total, 17,015 statin users and match controls were identified by using propensity score matching in 1:1 ratio. New statin use was associated with higher cardiovascular disease risk (adjusted hazard ratio (aHR): 1.2, 95% confidence interval (CI), 1.13–1.28) but lower all‐cause mortality (aHR: 0.93, 95% CI, 0.89–0.96). Hydrophilic statins were significantly associated with lower risk of cardiovascular disease compared with lipophilic statins (aHR: 0.91, 95% CI, 0.85–0.97).

  • Comparative Renoprotective Effect of Febuxostat and Allopurinol in Predialysis Stage 5 Chronic Kidney Disease Patients: A Nationwide Database Analysis
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-17
    Yun‐Shiuan O. Hsu; I‐Wen Wu; Shang‐Hung Chang; Cheng‐Chia Lee; Chung‐Ying Tsai; Chan‐Yu Lin; Wan‐Ting Lin; Yu‐Tung Huang; Chao‐Yi Wu; George Kuo; Chih‐Yen Hsiao; Hsing‐Lin Lin; Chih‐Chao Yang; Tzung‐Hai Yen; Yung‐Chang Chen; Cheng‐Chieh Hung; Ya‐Chong Tian; Chang‐Fu Kuo; Chih‐Wei Yang; Gerard F. Anderson; Huang‐Yu Yang

    Hyperuricemia has been associated with chronic kidney disease (CKD) progression. The antihyperuricemic febuxostat's potential renoprotective effect has been demonstrated in stage 1–3 CKD. Large‐scale studies comparing the renoprotective potential of febuxostat and allopurinol in advanced CKD are lacking. We exclusively selected 6,057 eligible patients with predialysis stage 5 CKD prescribed either febuxostat or allopurinol using the National Health Insurance Research Database in Taiwan during 2012–2015. There were 69.57% of allopurinol users and 42.01% febuxostat users who required long‐term dialysis (P < 0.0001). The adjusted hazard ratio (HR) of 0.65 (95% confidence interval (CI) 0.60–0.70) indicated near 35% lower hazards of long‐term dialysis with febuxostat use. The renal benefit of febuxostat was consistent across most patient subgroups and/or using the propensity score‐matched cohort. The adjusted HR was 0.66 (95% CI, 0.61–0.70) for long‐term dialysis or death. In conclusion, lower risk of progression to dialysis was observed in predialysis stage 5 CKD febuxostat users without compromising survival.

  • Beyond Randomized Clinical Trials: Use of External Controls
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-17
    Heinz Schmidli; Dieter A. Häring; Marius Thomas; Adrian Cassidy; Sebastian Weber; Frank Bretz

    Randomized controlled trials are the gold standard to investigate efficacy and safety of new treatments. In certain settings, however, randomizing patients to control may be difficult for ethical or feasibility reasons. Borrowing strength using relevant individual patient data on control from external trials or real‐world data (RWD) sources may then allow us to reduce, or even eliminate, the concurrent control group. Naive direct use of external control data is not valid due to differences in patient characteristics and other confounding factors. Instead, we suggest the rigorous application of meta‐analytic and propensity score methods to use external controls in a principled way. We illustrate these methods with two case studies: (i) a single‐arm trial in a rare cancer disease, using propensity score matching to construct an external control from RWD; (ii) a randomized trial in children with multiple sclerosis, borrowing strength from past trials using a Bayesian meta‐analytic approach.

  • Evaluation of Current Regulation and Guidelines of Pharmacogenomic Drug Labels: Opportunities for Improvements
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-17
    Rawan Shekhani; Linda Steinacher; Jesse J. Swen; Magnus Ingelman‐Sundberg

    Pharmacogenomic drug labels in the Summary of Product Characteristics (SmPC) provide an instrument for clinical implementation of pharmacogenomics. We compared pharmacogenomic guidance by Clinical Pharmacogenetics Implementation Consortium (CPIC), Dutch Pharmacogenetics Working Group (DPWG), the US Food and Drug Administration (FDA), and by the European agencies the European Medicines Agency (EMA), College ter Beoordeling van Geneesmiddelen Medicines Evaluation Board (CBG‐MEB), and Federal Institute for Drugs and Medical Devices (FIDMD), collectively assigned as EMA/FIDMD+MEB shortened as EMA/FM. Of 54 drugs with an actionable gene–drug interaction in the CPIC and DPWG guidelines, only 50% had actionable pharmacogenomic information in the SmPCs and the agencies were in agreement in only 18% of the cases. We further compared 450 additional drugs, lacking CPIC or DPWG guidance, and found 126 actionable gene–drug labels by the FDA and/or the EMA/FM. Based on these 126 drugs in addition to the 54 above, the consensus of actionable pharmacogenomic labeling between the FDA and the EMA/FM was only 54%. In conclusion, guidelines provided by CPIC/DPWG are only partly implemented into the SmPCs and the implementation of pharmacogenomic drug labels into the clinics would strongly gain from a higher extent of consensus between agencies.

  • Protein Abundance of Hepatic Drug Transporters in Patients With Different Forms of Liver Damage
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-17
    Marek Drozdzik; Sylwia Szelag‐Pieniek; Mariola Post; Samir Zeair; Maciej Wrzesinski; Mateusz Kurzawski; Jesus Prieto; Stefan Oswald

    Hepatocellular transporter levels were quantified using quantitative reverse transcription polymerase chain reaction and liquid chromatography–tandem mass spectrometry methods. Liver function deterioration (Child‐Pugh class C) produced significant protein abundance (mean values) increase (to healthy livers) in P‐gp (to 260% (CV (coefficient of variation) 82%)) and MRP4 (CV 230%) (not detected in healthy livers), decrease in MRP2 (to 30% (CV 126%)), NTCP (to 34% (CV 112%)), OCT1 (to 35% (CV 153%)), OATP1B1 (to 46% (CV 73%)), and OATP2B1 (to 27% (CV 230%)), whereas BSEP (CV 99%), MRP3 (CV 106%), OAT2 (CV 97%), OCT3 (CV 113%), and OATP1B3 (CV 144%) remained unchanged. Alcoholic liver disease produced significant protein downregulation of MRP2 (to 30% (CV 134%)), NTCP (to 76% (CV 78%)), OAT2 (to 26% (CV 117%)), OATP1B1 (to 61% (CV 76%)), OATP1B3 (to 79% (CV 160%)), and OATP2B1 (to 73% (CV 90%)) of healthy tissue values. Hepatitis C produced BSEP (to 47% (CV 99%)) and OATP2B1 (to 74% (CV 91%)) protein reduction. Primary biliary cholangitis and primary sclerosing cholangitis demonstrated P‐gp and MRP4 protein upregulation (to 350% (CV 47%) and 287% (CV 38%), respectively). Autoimmune hepatitis revealed P‐gp (to 410% (CV 49%)) and MRP4 (CV 96%) increase, and MRP2 (to 18% (CV 259%)) protein decrease. Drug transporters' protein abundance depends on liver pathology type and its functional state.

  • Big data – How to realise the promise
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-17
    Alison Cave; Nikolai C Brun; Fergus Sweeney; Guido Rasi; Thomas Senderovitz;

    The increasing volume and complexity of data now being captured across multiple settings and devices offers the opportunity to deliver a better characterisation of diseases, treatments and the performance of medicinal products in individual healthcare systems. Such data sources, commonly labelled as big data, are generally large, accumulating rapidly and incorporate multiple data types and forms. Determining the acceptability of these data to support regulatory decisions demands an understanding of data provenance and quality in addition to confirming the validity of new approaches and methods for processing and analysing these data. The HMA‐EMA Joint Big Data Taskforce was established to consider these issues from the regulatory perspective. This review reflects the thinking from its first Phase and describes the big data landscape from a regulatory perspective and the challenges to be addressed in order that regulators can know when and how to have confidence in the evidence generated from big data sets.

  • Single Therapeutic and Supratherapeutic Doses of Ubrogepant Do Not Affect Cardiac Repolarization in Healthy Adults: Results From a Randomized Trial
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-14
    Abhijeet Jakate; Ramesh Boinpally; Matthew Butler; Kaifeng Lu; Danielle McGeeney; Antonia Periclou

    Ubrogepant is a novel, oral calcitonin gene–related peptide receptor antagonist currently under US Food and Drug Administration (FDA) review for the acute treatment of migraine attacks. This double‐blind, four‐period crossover study compared the cardiac repolarization effect of therapeutic (100 mg) and supratherapeutic (400 mg) ubrogepant doses vs. placebo in healthy adults. Moxifloxacin 400 mg was used as an open‐label active control, and the primary end point was change from baseline in Fridericia‐corrected QT intervals (ΔQTcF). Assay sensitivity was demonstrated via statistically significant QTcF prolongation with moxifloxacin vs. placebo. After single oral doses of ubrogepant, the least squares mean placebo‐corrected ΔQTcF (ΔΔQTcF) and 90% confidence intervals (CIs) did not exceed the 10‐millisecond regulatory threshold at any timepoint. The 90% CI upper bounds were 2.46 milliseconds and 2.69 milliseconds for ubrogepant 100 and 400 mg, respectively. Categorical and concentration‐based analyses were consistent with the primary result, showing no significant impact of ubrogepant on cardiac repolarization.

  • Proposed Therapeutic Range of Treosulfan in Reduced Toxicity Pediatric Allogeneic Hematopoietic Stem Cell Transplant Conditioning: Results From a Prospective Trial
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-14
    Robert Chiesa; Joseph F. Standing; Robert Winter; Zohreh Nademi; Jan Chu; Danielle Pinner; Frank Kloprogge; Susan McLellen; Persis J. Amrolia; Kanchan Rao; Giovanna Lucchini; Juliana Silva; Oana Ciocarlie; Arina Lazareva; Andrew R. Gennery; Bilyana Doncheva; Andrew J. Cant; Sophie Hambleton; Terence Flood; Elizabeth Rogerson; Kirsty Devine; Helen Prunty; Simon Heales; Paul Veys; Mary Slatter

    Treosulfan is given off‐label in pediatric allogeneic hematopoietic stem cell transplant. This study investigated treosulfan's pharmacokinetics (PKs), efficacy, and safety in a prospective trial. Pediatric patients (n = 87) receiving treosulfan‐fludarabine conditioning were followed for at least 1 year posttransplant. PKs were described with a two‐compartment model. During follow‐up, 11 of 87 patients died and 12 of 87 patients had low engraftment (≤ 20% myeloid chimerism). For each increase in treosulfan area under the curve from zero to infinity (AUC(0‐∞)) of 1,000 mg hour/L the hazard ratio (95% confidence interval) for mortality increase was 1.46 (1.23–1.74), and the hazard ratio for low engraftment was 0.61 (0.36–1.04). A cumulative AUC(0‐∞) of 4,800 mg hour/L maximized the probability of success (> 20% engraftment and no mortality) at 82%. Probability of success with AUC(0‐∞) between 80% and 125% of this target were 78% and 79%. Measuring PK at the first dose and individualizing the third dose may be required in nonmalignant disease.

  • Human Tridimensional Neuronal Cultures for Phenotypic Drug Screening in Inherited Peripheral Neuropathies
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-14
    Renata Maciel; Renata Correa; Juliana Bosso Taniguchi; Igor Prufer Araujo; Mario A. Saporta

    Length‐dependent axonal degeneration is the pathologic hallmark of several neurodegenerative disorders, including inherited peripheral neuropathies (Charcot‐Marie‐Tooth (CMT) disease). CMT is currently an untreatable disorder. This is partially due to lack of translational models suitable for drug discovery. In vitro models of CMT have been hindered by the 2D configuration of neuronal cultures, which limits visualization and orientation of axons. To overcome these limitations, we cultured induced pluripotent stem cell (iPSC)‐derived spinal motor neurons as 3D spheroids, which grow axons in a centrifugal fashion when plated. Using these iPSC‐derived spinal spheroids, we demonstrate neurofilament deposits in motor neuron axons of three patients with CMT2E, caused by mutations in the NEFL gene. This phenotype is partially reversed by two kinase inhibitors. In summary, we developed a human tridimensional in vitro system that models length‐dependent axonopathies, recapitulates key pathophysiologic features of CMT2E, and should facilitate the identification of new therapeutic compounds for CMT.

  • Reproducing Protocol‐Based Studies Using Parameterizable Tools—Comparison of Analytic Approaches Used by Two Medical Product Surveillance Networks
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-12
    Ting‐Ying Huang; Emily C. Welch; Mayura U. Shinde; Robert W. Platt; Kristian B. Filion; Laurent Azoulay; Judith C. Maro; Richard Platt; Sengwee Toh

    The US Sentinel System and the Canadian Network for Observational Drug Effect Studies (CNODES) are two medical product safety surveillance networks. Using Sentinel's preprogrammed, parameterizable analytic tools, we reproduced two protocol‐based studies conducted by CNODES to assess the risks of acute pancreatitis and heart failure (HF) associated with the use of incretin‐based drugs, compared with use of ≥ 2 oral hypoglycemic agents. Results from the replication new‐user cohort analyses aligned with those from the CNODES nested case‐control studies. The adjusted hazard ratios were 0.95 (0.81–1.12; vs. 1.03 (0.87–1.22) in CNODES) for acute pancreatitis and 0.91 (0.84–1.00; vs. 0.82 (0.67–1.00) in CNODES) for HF among patients without HF history. The CNODES's common protocol approach allows studies tailored to specific safety questions, whereas the Sentinel's common data model plus pretested program approach enables more rapid analysis. Despite these differences, it is possible to obtain comparable results using both approaches.

  • Changes in Manufacturing Processes of Biologic Therapies Can Alter the Immunogenicity Profile of the Product
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-11
    Martin Vanderlaan; Aristides Maniatis; Robert Olney; Abdelkader Rahmaoui; Linda Yau; Valerie Quarmby; Craig Azzolino; Cynthia Woods; Dalia Moawad

    Manufacturing process changes may alter the characteristics of a protein therapeutic. In 2009, somatropin (version 1.0), a recombinant human growth hormone therapeutic, underwent a manufacturing update (version 1.1). The immunogenicity of somatropin version 1.1 as a daily subcutaneous injection was evaluated in 2014 in a prospective, open‐label, single‐arm clinical study of treatment‐naive pediatric patients with idiopathic human growth hormone deficiency for 1 year. The primary end point was the proportion of patients who developed antidrug antibodies (ADAs) after treatment. Eighty‐two patients were enrolled. The mean (SD) treatment duration was 347 (53) days. The incidence of ADAs was 3.7%. No neutralizing antibodies were observed in the three patients with ADA‐positive samples. Two patients (2.6%) had growth attenuation, but they were not ADA positive. The manufacturing changes for somatropin version 1.1 resulted in a similar safety and efficacy profile compared with somatropin version 1.0 and a different immunogenicity profile with a lower incidence of ADAs.

  • Electronic Health Record–Embedded Decision Support Platform for Morphine Precision Dosing in Neonates
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-11
    Alexander A. Vinks, Nieko C. Punt, Frank Menke, Eric Kirkendall, Dawn Butler, Thomas J. Duggan, DonnaMaria E. Cortezzo, Sam Kiger, Tom Dietrich, Paul Spencer, Rob Keefer, Kenneth D.R. Setchell, Junfang Zhao, Joshua C. Euteneuer, Tomoyuki Mizuno, Kevin R. Dufendach

    Morphine is the opioid most commonly used for neonatal pain management. In intravenous form, it is administered as continuous infusions and intermittent injections, mostly based on empirically established protocols. Inadequate pain control in neonates can cause long‐term adverse consequences; however, providing appropriate individualized morphine dosing is particularly challenging due to the interplay of rapid natural physiological changes and multiple life‐sustaining procedures in patients who cannot describe their symptoms. At most institutions, morphine dosing in neonates is largely carried out as an iterative process using a wide range of starting doses and then titrating to effect based on clinical response and side effects using pain scores and levels of sedation. Our background data show that neonates exhibit large variability in morphine clearance resulting in a wide range of exposures, which are poorly predicted by dose alone. Here, we describe the development and implementation of an electronic health record–integrated, model‐informed decision support platform for the precision dosing of morphine in the management of neonatal pain. The platform supports pharmacokinetic model‐informed dosing guidance and has functionality to incorporate real‐time drug concentration information. The feedback is inserted directly into prescribers' workflows so that they can make data‐informed decisions. The expected outcomes are better clinical efficacy and safety with fewer side effects in the neonatal population.

  • Vedolizumab for Inflammatory Bowel Disease: Two‐Year Results of the Initiative on Crohn and Colitis (ICC) Registry, A Nationwide Prospective Observational Cohort Study
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-11
    Vince B.C. Biemans, C. Janneke van der Woude, Gerard Dijkstra, Andrea E. van der Meulen‐de Jong, Bas Oldenburg, Nanne K. de Boer, Mark Löwenberg, Nidhi Srivastava, Alexander G.L. Bodelier, Rachel L. West, Jeroen M. Jansen, Annemarie C. de Vries, Jeoffrey J.L. Haans, Dirk J. de Jong, Marie J. Pierik, Frank Hoentjen

    Prospective data of vedolizumab treatment for patients with inflammatory bowel disease (IBD) beyond 1 year of treatment is scarce but needed for clinical decision making. We prospectively enrolled 310 patients with IBD (191 with Crohn's disease (CD) and 119 patients with ulcerative colitis (UC)) with a follow‐up period of 104 weeks (interquartile range: 103–104) in a nationwide registry. The corticosteroid‐free clinical remission rate (Harvey Bradshaw Index ≤ 4, Short Clinical Colitis Activity index ≤ 2) at weeks 52 and 104 were 28% and 19% for CD and 27% and 28% for UC, respectively. Fifty‐nine percent maintained corticosteroid‐free clinical remission between weeks 52 and 104. Vedolizumab with concomitant immunosuppression showed comparable effectiveness outcomes compared with vedolizumab monotherapy (week 104: 21% vs. 23%; P = 0.77), whereas 8 of 13 severe infections occurred in patients treated with concomitant immunosuppression. To conclude, the clinical effect was 19% for CD and 28% for UC after 2 years of follow‐up regardless of concomitant immunosuppression.

  • Protein Expression and Functional Relevance of Efflux and Uptake Drug Transporters at the Blood–Brain Barrier of Human Brain and Glioblastoma
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-10
    Xun Bao, Jianmei Wu, Youming Xie, Seongho Kim, Sharon Michelhaugh, Jun Jiang, Sandeep Mittal, Nader Sanai, Jing Li

    The knowledge of transporter protein expression and function at the human blood–brain barrier (BBB) is critical to prediction of drug BBB penetration and design of strategies for improving drug delivery to the brain or brain tumor. This study determined absolute transporter protein abundances in isolated microvessels of human normal brain (N = 30), glioblastoma (N = 47), rat (N = 10) and mouse brain (N = 10), and cell membranes of MDCKII cell lines, using targeted proteomics. In glioblastoma microvessels, efflux transporters (ABCB1 and ABCG2), monocarboxylate transporter 1 (MCT1), glucose transporter 1 (GLUT1), sodium–potassium pump (Na/K ATPase), and Claudin‐5 protein levels were significantly reduced, while large neutral amino acid transporter 1 (LAT1) was increased and GLU3 remained the same, as compared with human normal brain microvessels. ABCC4, OATP1A2, OATP2B1, and OAT3 were undetectable in microvessels of both human brain and glioblastoma. Species difference in BBB transporter abundances was noted. Cellular permeability experiments and modeling simulations suggested that not a single apical uptake transporter but a vectorial transport system consisting of an apical uptake transporter and basolateral efflux mechanism was required for efficient delivery of poor transmembrane permeability drugs from the blood to brain.

  • PharmVar GeneFocus: CYP2D6
    Clin. Pharmacol. Ther. (IF 6.336) Pub Date : 2019-12-09
    Charity Nofziger, Amy J. Turner, Katrin Sangkuhl, Michelle Whirl‐Carrillo, José A.G. Agúndez, John L. Black, Henry M. Dunnenberger, Gualberto Ruano, Martin A. Kennedy, Michael S. Phillips, Houda Hachad, Teri E. Klein, Andrea Gaedigk

    The Pharmacogene Variation Consortium (PharmVar) provides nomenclature for the highly polymorphic human CYP2D6 gene locus. CYP2D6 genetic variation impacts the metabolism of numerous drugs and, thus, can impact drug efficacy and safety. This GeneFocus provides a comprehensive overview and summary of CYP2D6 genetic variation and describes how the information provided by PharmVar is utilized by the Pharmacogenomics Knowledgebase (PharmGKB) and the Clinical Pharmacogenetics Implementation Consortium (CPIC).

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上海纽约大学William Glover