Journal Of Clinical Pharmacology Research Articles

Trends in clinical pharmacology as represented by international and specialized journals

Relevance. Clinical pharmacology is a rapidly evolving field of medicine. The advent of modern technologies has led. The continued evolution of clinical pharmacology, as reflected in publications in specialized medical journals.The aim of this study was to determine how new trends in clinical pharmacology were reflected in the publications of the leading clinical pharmacology journals in Russia during the period from 2015-2021, to conduct a comparative analysis of trends with international journals from 2015-2021.Materials and methods. Original articles published in leading Russian journals were analyzed and categorized into relevant key areas of interest, drug modalities, and therapeutic areas based on the content of the publications independently by three authors. Publications in which authors expressed divergent opinions were discussed until consensus was reached using a modified Delphi method. A comparative analysis was then performed with the results of a similar analysis published in journal “Clinical Pharmacology and Therapeutics”.Results. Most Russian journals and publications have focused on real-world data. The topics most frequently covered in international journals were pharmacometrics, machine learning, and pharmacogenetics. In third place were real-world data. The leading therapeutic areas represented in publications in both Russian and international journals were cardiology, oncology, and infectious diseases. Most publications have focused on various aspects of small molecule use.Conclusions. The novel trends in clinical pharmacology are reflected in the scientific articles published in specialized journals. The principal trends observed in Russian publications are consistent with international tendencies.

Withdrawal: Clinical Analysis of Immune-Related Adverse Events in 78 Patients with Advanced Metastatic Lung Cancer Treated with Immune Checkpoint Inhibitors, published in The Journal of Clinical Pharmacology, [10.1002/jcph.2395

The above article, published online on 14th December 2023 in Wiley Online Library (wileyonlinelibrary.com), has been withdrawn by agreement between the journal Editor in Chief, John van Den Anker, and Wiley Periodicals LLC. The withdrawal has been agreed following no response from the author to requests to sign the Journal's publishing license/to requests to approve their article proof for publication.

Nalmefene study: A faster alternative to naloxone

In the first head‐to‐head study of nalmefene nasal spray (OPVEE is the trade name) vs. naloxone to reverse opioid overdose conducted in volunteers, researchers found that nalmefene worked faster than a 4 milligram (mg) dose of naloxone. It worked much faster, in fact, 2.7 mgs of OPVEE reversed respiratory depression within five minutes, compared to 20 minutes for 4 mgs of naloxone. The study, “Reversal of Opioid‐Induced Respiratory Depression in Healthy Volunteers: Comparison of Intranasal Nalmefene and Intranasal Naloxone,” was published March 11 in the Journal of Clinical Pharmacology. The opioid that was given to the volunteers was remifentanil, a synthetic opioid.

Withdrawal: "Surgical site infection and antimicrobial prophylaxis prescribing pattern, and its determinants among hospitalized patients in northeast Ethiopia: a hospital based cross-sectional study" by Habteweld HA, Yimam M, Tsige AW, Teshome Y, Endalifer BL, Dires K.

The above article from Journal of Clinical Pharmacology, published online on 1 September 2023 in Wiley Online Library (http://wileyonlinelibrary.com) has been withdrawn by agreement among the authors, the Journal Editor-in-Chief Joseph S. Bertino Jr. and Wiley Periodicals, Inc. on behalf of the American College of Clinical Pharmacology. The withdrawal has been agreed because a dispute over authorship.

Abstract 6352: Combination treatment with recombinant murine IL-12 and anti-PD-1 antibody enhanced anti-tumor efficacy through the activation of cytotoxic T cell response

Abstract Introduction: Immune checkpoint inhibitors (ICIs) are widely used in cancer therapy. Among them, anti-PD-1 antibodies are the most used and have been approved by FDA for the treatment of many types of cancer (1). In our previous studies, combination of anti-PD-1 antibody with IL-12 demonstrated significant synergistic effect on tumor growth inhibition. The elevation of IFN-γ mRNA expression suggested the potential roles of CD8 T cells and NK cells in this process. In this study, we used two syngeneic mice tumor models to investigate the mechanisms of synergistic effect by the combination of IL-12 and anti-PD-1 antibody. Methods: We used syngeneic mice tumor models with mice cancer cell lines CT-26 and MC-38. The mice inoculated with tumor cells and were treated until tumors grew to 100 mm3. The mice were divided into three groups to receive the treatment, including rmIL-12 alone, anti-PD1-antibody alone, and the combination of rmIL-12 and anti-PD1-antibody (BIW x 3 weeks). At the end of the study, the mice were sacrificed and tumor resection and splenectomy were performed. The tumor infiltrating lymphocyte subpopulations within the tumor microenvironment were analyzed by flow cytometry and gene expression profile by RNA Seq. Results: The combination of rmIL-12 and anti-PD-1 antibody significantly inhibited tumor growth compared to the treatment with rmIL-12 and anti-PD-1 antibody alone. The combination group demonstrated more CD8+ T cell in the tumor microenvironment via flow cytometry. In addition, RNA Seq showed the combination group increased CD8+ T cells, NK cells, and Th1 populations. The levels of cytotoxicity related genes (IFN-γ, Granzyme B, Perforin) were also higher in combination group. Conclusion: Combination of rmIL-12 and anti-PD-1 antibody increased immune cells infiltration in the tumor microenvironment and enhanced anti-tumor response suggesting the potential of this combination for cancer treatment. Citation:(1). Watson, G.A. et al. (2020) “Novel strategies in immune checkpoint inhibitor drug development: How far are we from the paradigm shift?,” British Journal of Clinical Pharmacology, 86(9), pp. 1753-1768. https://doi.org/10.1111/bcp.14355. Citation Format: Yeng-Jey Yang, Pei-Yi Tsou, Shiuh-Dih Chou, Meng-Na Lee, San-Chi Chen. Combination treatment with recombinant murine IL-12 and anti-PD-1 antibody enhanced anti-tumor efficacy through the activation of cytotoxic T cell response [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2023; Part 1 (Regular and Invited Abstracts); 2023 Apr 14-19; Orlando, FL. Philadelphia (PA): AACR; Cancer Res 2023;83(7_Suppl):Abstract nr 6352.

Temporal changes in anticoagulant prescribing and atrial fibrillation: results of interrupted time-series analysis of openly available routine data in England

Abstract Introduction The use of anticoagulants for stroke prevention in patients with atrial fibrillation (AF) has been increasing in England in the recent years (1, 2). The changes in practice coincided with several developments in the area of anticoagulants and AF, including: the emergence of evidence supporting anticoagulant use for stroke prevention in AF, changes in guideline recommendations, and the licensing of direct oral anticoagulants (DOACs) as an alternative to warfarin, which was the mainstay of stroke prevention in AF. Currently, there are four DOACs available for use: dabigatran, rivaroxaban, apixaban, and edoxaban. Recent analyses of time trends of anticoagulant prescribing in England showed an increase in DOACs prescribing and a decrease in warfarin prescribing (1, 2). However, more recent exploration of recent anticoagulant prescribing trends is needed. Aim To explore the changes in anticoagulant prescribing for AF in England. Methods Interrupted time-series analysis (ITSA) of openly available data on anticoagulant prescribing and AF. Separate analyses were conducted for data from Sentinel Stroke National Audit Programme (SSNAP) and Quality and Outcomes Framework (QOF). The timeframe of the analysis and the length of time intervals depended on the characteristics of each dataset. Results Analysis of data from SSNAP showed that the proportion of stroke patients who have a diagnosis of AF who were taking an anticoagulant alone prior to admission increased from 32.51% in the third quarter of 2013 to 62.63% in the third quarter of 2020; this coincided with a decreased proportion of stroke patients who have a diagnosis of AF taking antiplatelets alone from 37.10% to 8.31% during the same period. Analysed QOF data on anticoagulants and AF included information about AF prevalence in QOF datasets, the eligibility of patients with AF for anticoagulant based on stroke risk assessment, and the use of anticoagulants among eligible patients. Prevalence of AF in England in QOF datasets increased from 1.52% in 2012/2013 to 2.05% in 2019/2020 (ITSA gradient=0.08, p-value<.001, 95% confidence interval: 0.07- 0.09). The proportion of patients with AF who are considered eligible for anticoagulation per all patients with AF in QOF datasets increased from 44.95% in 2012/2013 to 80.87% in 2019/2020; there was an increase by 25.24% between 2014/2015 and 2015/2016 which corresponds to modifying risk assessment scores to include additional criteria. The proportion of eligible patients with AF being prescribed anticoagulants also increased in the period between 2012/2013 and 2019/2020 (ITSA gradient = 1.98, p-value<.001, 95% confidence interval: 1.52- 2.44). Conclusion The analysis of data from different sources identified an increase in anticoagulant prescribing for patients with AF in England, which is likely to translate into health gains. However, the use of aggregate data in the analysis did not allow for detailed inspection of patient characteristics, and individual anticoagulants were not specified in the datasets. Therefore, quantitative analyses of primary care data of individual anticoagulant prescribing for different patient groups with AF are needed to further understand whether additional improvements are possible in the prevention of complications from atrial fibrillation. References (1) Adderley NJ, Ryan R, Nirantharakumar K, Marshall T. Prevalence and treatment of atrial fibrillation in UK general practice from 2000 to 2016. Heart. 2019;105(1):27-33. (2) Loo SY, Dell’Aniello S, Huiart L, Renoux C. Trends in the prescription of novel oral anticoagulants in UK primary care. British Journal of Clinical Pharmacology. 2017;83(9):2096-106.

Big Data Management in Drug–Drug Interaction: A Modern Deep Learning Approach for Smart Healthcare

The detection and classification of drug–drug interactions (DDI) from existing data are of high importance because recent reports show that DDIs are among the major causes of hospital-acquired conditions and readmissions and are also necessary for smart healthcare. Therefore, to avoid adverse drug interactions, it is necessary to have an up-to-date knowledge of DDIs. This knowledge could be extracted by applying text-processing techniques to the medical literature published in the form of ‘Big Data’ because, whenever a drug interaction is investigated, it is typically reported and published in healthcare and clinical pharmacology journals. However, it is crucial to automate the extraction of the interactions taking place between drugs because the medical literature is being published in immense volumes, and it is impossible for healthcare professionals to read and collect all of the investigated DDI reports from these Big Data. To avoid this time-consuming procedure, the Information Extraction (IE) and Relationship Extraction (RE) techniques that have been studied in depth in Natural Language Processing (NLP) could be very promising. Since 2011, a lot of research has been reported in this particular area, and there are many approaches that have been implemented that can also be applied to biomedical texts to extract DDI-related information. A benchmark corpus is also publicly available for the advancement of DDI extraction tasks. The current state-of-the-art implementations for extracting DDIs from biomedical texts has employed Support Vector Machines (SVM) or other machine learning methods that work on manually defined features and that might be the cause of the low precision and recall that have been achieved in this domain so far. Modern deep learning techniques have also been applied for the automatic extraction of DDIs from the scientific literature and have proven to be very promising for the advancement of DDI extraction tasks. As such, it is pertinent to investigate deep learning techniques for the extraction and classification of DDIs in order for them to be used in the smart healthcare domain. We proposed a deep neural network-based method (SEV-DDI: Severity-Drug–Drug Interaction) with some further-integrated units/layers to achieve higher precision and accuracy. After successfully outperforming other methods in the DDI classification task, we moved a step further and utilized the methods in a sentiment analysis task to investigate the severity of an interaction. The ability to determine the severity of a DDI will be very helpful for clinical decision support systems in making more accurate and informed decisions, ensuring the safety of the patients.

Pharmacist intervention significantly reduces cardiovascular risk factors, finds review

Pharmacist interventions improved patient cardiovascular (CV) health in more than two thirds of published studies analysed as part of a review published in the British Journal of Clinical Pharmacology on 16 February 2022. The authors looked at data from 24 studies with 85 meta-analyses that assessed CV-related patient outcomes after pharmacist intervention. The studies included […]

Drug shortages linked with medication errors, study results suggest

A French study of data on adverse drug reactions (ADRs) has highlighted a link between drug shortages and medication errors. In the study, published in the British Journal of Clinical Pharmacology on 29 September 2022, researchers considered 462 cases recorded in the French Pharmacovigilance Database between 1985 and 2019 that mentioned a drug shortage. Medication […]

Comparison of 0.5% levobupivacaine alone and 0.5% levobupivacaine with butorphanol given intrathecally in infraumbilical surgeries.

Introduction: Spinal anaesthesia is the most common neuraxial block used in surgical setting. The main advantage is the high success rate, safety record, rapid onset, predictable duration, minimal side effect and reliable offset. Study aimed to compare Levobupivacaine and Levobupivacaine with Butorphanol in terms of onset of sensory and motor blockade, duration of sensory and motor block, two segment regression time, hemodynamic changes, time for first rescue analgesia and complications in infraumbilical surgeries. Materials and methods: 60 patients of ASA class 1 and 2 of age between 19 to 65 years were selected in the study and divided them into two groups with 30 patients each. Group A - 15 mg (3 ml) of 0.5% Levobupivacaine + 0.1 ml Normal saline. Group B- 15 mg (3 ml) of 0.5% Levobupivacaine + 100 g (0.1 ml) of Butorphanol. All groups received drug at L2-L3 intervertebral space. Result: On comparing both the groups, the duration of sensory and motor blockade was more in group B. The two-segment regression time was more isn group B and the time for the first rescue analgesia was also more in group B. Hemodynamic stability was achieved in group B with minimal change in the parameters and with fewer complications. Conclusion: we concluded that addition of injection Butorphanol with Levobupivacaine gives hemodynamic stability as compared to Levobupivacaine alone intrathecally and also provides longer duration of sensory and motor blockade and superior analgesia than intrathecal levobupivacaine alone. Keywords: spinal anesthesia, analgesia, intrathecal, Levobupivacaine, Butorphanol. Reference: 1. Casey WF. Spinal anaesthesia-A practical guide. Update Anaesth. 2000;12:1-7. 2. Foster RH, Markham A. Levobupivacaine. Drugs. 2000 Mar;59(3):551-79. 3. Attri JP, Kaur G, Kaur S, Kaur R, Mohan B, Kashyap K. Comparison of levobupivacaine and levobupivacaine with fentanyl in infraumbilical surgeries under spinal anaesthesia. Anesthesia, essays and researches. 2015 May;9(2):178. 4. Stoelting RK, Hillier SC. Pharmacology and physiology in anesthetic practice. Lippincott Williams & Wilkins; 2012 Jan 11. 5. Eledjam JJ, de la Coussaye JE, Bassoul B, Brugada J. Mechanisms of the cardiac toxicity of bupivacaine. InAnnales Francaises D'anesthesie et de Reanimation 1988 Jan 1 (Vol. 7, No. 3, pp. 204-210). 6. Bardsley H, Gristwood R, Baker H, Watson N, Nimmo W. A comparison of the cardiovascular effects of levobupivacaine and rac‐bupivacaine following intravenous administration to healthy volunteers. British journal of clinical pharmacology. 1998 Sep;46(3):245-9 7. McLeod GA. Density of spinal anaesthetic solutions of bupivacaine, levobupivacaine, and ropivacaine with and without dextrose. British Journal of Anaesthesia. 2004 Apr 1;92(4):547-51. 8. Singh A, Gupta A, Datta PK, Pandey M. Intrathecal levobupivacaine versus bupivacaine for inguinal hernia surgery: a randomized controlled trial. Korean Journal of Anesthesiology. 2018 Jun;71(3):220. 9. Fattorini F, Ricci Z, Rocco A, Romano R, Pascarella MA, Pinto G. Levobupivacaine versus racemic bupivacaine for spinal anaesthesia in orthopaedic major surgery. Minerva Anestesiologica. 2006 Jul 1;72(7-8):637-44. 10. Şahin AS, Türker G, Bekar A, Bilgin H, Korfalı G. A comparison of spinal anesthesia characteristics following intrathecal bupivacaine or levobupivacaine in lumbar disc surgery. European Spine Journal. 2014 Mar;23(3):695-700. 11. Glaser C, Marhofer P, Zimpfer G, Heinz MT, Sitzwohl C, Kapral S, Schindler I. Levobupivacaine versus racemic bupivacaine for spinal anesthesia. Anesthesia & Analgesia. 2002 Jan 1;94(1):194-8. 12. Singh V, Gupta LK, Singh GP. Comparison among intrathecal fentanyl and butorphanol in combination with bupivacaine for lower limb surgeries. Journal of Anaesthesiology Clinical Pharmacology. 2006 Oct 1;22(4):371- 13. Singh SN, Subedi A, Prasad JN, Regmi MC. A comparative study to assess the effect of intrathecal bupivacaine with morphine or butorphanol

New pediatric analysis establishes novel dosing framework for the future

Pharmacists have all heard the phrase “children are not little adults.” It’s popular for a reason: it represents the dangers of simply scaling adult drug dosages to children. Adult physiology, however, has historically been used to scale pediatric dose recommendations. Currently, the most accurate way to determine the initial dosage of a drug is to use a physiologically based pharmacokinetic model (PBPK) to mathematically extrapolate drug dosing from an adult to a child population. Unfortunately, the development of a PBPK remains a challenge, as it requires a deep level of raw, quantitative, physiological data related to developmental stage, disease processes, and any other variable that can affect the pharmacokinetics of a drug. This task may have become significantly less herculean, however, thanks to an open-source, comprehensive, quantitative database, published in March 2021 in the Journal of the American Association of Pharmaceutical Scientists, on the mathematical age relationships among weight, height, organ weight, and organ blood flow—all critical parameters needed when designing a pediatric PBPK. Until recently, this kind of data have been difficult to consolidate or have been locked tightly behind proprietary software. The authors hope that by making it open-source, their database will encourage the creation of widespread pediatric PBPK models that can help predict optimal dosing for pediatric patients with both old and new drugs. One of the first steps in the clinical development for most drugs seeking a pediatric indication is to demonstrate similar exposure levels at various dosages. The first dose is informed by adult pharmacokinetic data leveraged in mathematical models that rely on assumptions regarding the drug’s pharmacokinetics. These data are then scaled down to different child age groups using allometric functions of basal metabolic rates and body weight. Although this is usually sufficient, it may be inaccurate for non-small drug molecules that do not exhibit linear kinetics with time-dependent clearance or target-mediated drug disposition. Biologics pose a particular problem. Using a PBPK model to achieve more accurate results presents a solution. The general process involves creating a simulation of a population of adults whose pharmacokinetics of a particular drug is expressed as rate-based equations. The adults are then swapped with virtual children with all other pharmacokinetic parameters being held constant and their drug exposure metrics compared. If the virtual pediatric exposures are similar to that of the virtual adult population, the presumed first-in-pediatric dose can progress to a more practical application. Chang and colleagues created a comprehensive database of physiological parameters in children from newborns to 20 years. They found a singular function that described the relationships between body weight and age, height and age, organ weight and age, and organ blood flow and age. The formula can be used to estimate any of these parameters—as they relate to age—by referencing the appropriate tables and variable values in the author’s library. The analysis also includes functions predicting pediatric organ weight and blood flow for a library of organs—including heart, lung, muscle, skin, fat, bone, bone marrow, brain, kidney, liver, intestine, pancreas, thymus, and spleen—as well as blood volume and extracellular water. In fact, Chang and colleagues published a follow-up study in June 2021 in the British Journal of Clinical Pharmacology, in which they put the database to the test using it to develop their own PBPK model to characterize monoclonal antibody (mAb) pharmacokinetics in pediatric patients. The results of the investigation were in concordance with the rest of the literature: that mAb pharmacokinetics often require higher doses or more frequent dosing in order to achieve therapeutic levels. The confirmatory results appear to demonstrate a practical application of their database for use in PKPB modeling and will hopefully serve as an accessible framework for pediatric pharmacologists—particularly for biologics—in the years to come.

The International Journal of Clinical Pharmacology and Therapeutics: Medical-scientific publishing tradition with adaptability, innovation, and momentum.

The International Journal of Clinical Pharmacology and Therapeutics: Medical-scientific publishing tradition with adaptability, innovation, and momentum.

ACCP publishes supplement on drugs of abuse

The American College of Clinical Pharmacology (ACCP) has published a “Drugs of Abuse” supplement for its Journal of Clinical Pharmacology. Covering all substances from tobacco and alcohol to prescription and illicit drugs, the supplement is designed to fill in clinical trial gaps with mechanistic insight to allow clinicians to better assess and treat complex patients,” according to the editors. “Primary care, psychiatric, toxicological and emergency/critical care clinicians will all benefit from understanding how these substances of abuse cause their pharmacologic effects and how best to counteract it.” The co‐editors for the supplement (Drs. C. Michael White and Anne Nafziger) jointly stated, “We see many instances where clinicians are confused about why patients experience the effects they do from substances of abuse and how best to care for them. We wanted to draw the combined wisdom of international experts in clinical pharmacology to break down the pharmacologic and pharmacokinetic underpinnings for why these effects occur, the time course for these effects and why there is variability in response.” For the supplement, go to https://accp1.onlinelibrary.wiley.com/toc/15524604/2021/61/S2.

Drugs of Abuse: How Clinical Pharmacology Brings Clarity to the Shadows.

Drugs of Abuse: How Clinical Pharmacology Brings Clarity to the Shadows.

Statistical inference in abstracts of three influential clinical pharmacology journals analyzed using a text-mining algorithm.

To describe the trend in the prevalence of statistical inference in three influential clinical pharmacology journals METHODS: We applied a computer-based algorithm to abstracts of three clinical pharmacology journals published in 1976 to 2016 to identify statistical inference and its subtypes. Furthermore, we manually reviewed a random sample of 300 articles to access algorithm's performance in finding statistical inference in abstracts and as a screening tool for presence and absence of statistical inference in full text. The algorithm identified 59% (13,375/22,516 [mid p 95% CI, 59%-60%]) article abstracts with statistical inference. The percentage of abstracts with statistical inference was similar in 1976 and 2016, 48% (179/377 [mid p 95%CI, 42%-52%]) versus 49% (386/791 [mid p 95%CI, 45%-52%]). Statistical reporting pattern varied among journals. Among abstracts containing any statistical inference in the publications from 1976 to 2016 null-hypothesis significance testing was the most prevalent reported statistical inference. The algorithm had high sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV) for finding statistical inferences in abstract. While PPV for predicting the statistical inference in full text (including abstract, text, tables and figures) was high, NPV was low. Despite journal's editorials and statistical associations' guidelines, most authors focused on testing rather than estimation. In future, a better statistical reporting might be ensured by improving the statistical knowledge of authors and an addition of statistical guides to journals' instruction to authors to the extent that editors would like their statistical inference preferences to be incorporated into submitted manuscripts.

The Journal of Clinical Pharmacology Adds 2 Associate Editors

Drs. Bertino (Editor-in-Chief) and Reed (Associate Editor), Ms. Marshall (Managing Editor), and The Journal of Clinical Pharmacology (JCP) are pleased to announce the addition of 2 associate editors: Joan Korth-Bradley, PharmD, PhD, received her BSc at the University of Toronto and completed a residency in hospital pharmacy at Ottawa General Hospital. She then received her PharmD from the University of Minnesota, completed a clinical pharmacy fellowship at the University of Texas at Austin, and then completed a PhD under Dr. Tom Ludden in the Division of Pharmaceutics at the University of Texas at Austin. After a brief career in academia and hospital pharmacy, Dr. Korth-Bradley joined Wyeth-Ayerst in 1991 and then Pfizer Inc. (which acquired Wyeth-Ayerst) in 2009. She is currently a Senior Director in Clinical Pharmacology at Pfizer Inc. Dr. Korth-Bradley is a Fellow of the American College of Clinical Pharmacology, the American College of Clinical Pharmacy, and the American Association of Pharmaceutical Scientists. She has served on numerous ACCP committees and is currently an ACCP Regent. She has also been a member of the Editorial Board of JCP. She has an extensive track record of publications and presentations in clinical pharmacology. Janice E. Sullivan, MD, started her career in nursing (as a nurse practitioner) and then received her MD from the University of Minnesota. She completed a pediatric residency at the University of Arkansas and a Fellowship in Pediatric Pharmacology and Critical Care from Case Western Reserve University. Dr. Sullivan is currently a Professor at the University of Louisville, the Vice Chair of Research in the Department of Pediatrics at the University of Louisville, and a consultant at the Kentucky Regional Poison Center of Norton Children's Hospital. She has recently stopped her many years of pediatric critical care work to focus on her research activities. Dr. Sullivan is board-certified in Pediatrics, Pediatric Critical Care, and Clinical Pharmacology. She holds fellowships in the American Academy of Pediatrics and the Society of Critical Care Medicine. She has an extensive record of extramural research funding as well as a long record of publications and presentations. We welcome Drs. Korth-Bradley and Sullivan as Associate Editors for The Journal of Clinical Pharmacology.

Population Pharmacokinetic Analyses of Isoniazid in Tuberculosis Treatment: a Systematic Review

The aims of this systematic review are to provide knowledge concerning population pharmacokinetics of isoniazid (INH) and to identify factors influencing INH pharmacokinetic variability. Pubmed and Embase databases were systematically searched from inception to July, 2017. Relevant articles from reference lists were also included. All population pharmacokinetic studies of INH written in English, conducted in human (either healthy subjects or pulmonary tuberculosis patients) were included in this review. Ten studies were included in this review. Most studies characterized a two-compartment model with first-order kinetics for INH with a transit-compartment model for absorption suggested. Frequently reported significant predictors for INH clearance is NAT2 acetylator types (slow/intermediate/fast), while weight is a significant covariate for INH volume of distribution (both central and peripheral). In children, enzyme maturation had a profound affect on INH clearance.
 Keywords:
 Population pharmacokinetics, Isoniazid.
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Pharmacy-led interventions successful in deprescribing of high-risk medication, review suggests

Community pharmacist-led interventions can lead to successful deprescribing of high-risk medication, as well as improving quality of life in patients with severe mental illness, a review published in the British Journal of Clinical Pharmacology has suggested. Researchers carried out a review of 24 studies, investigating community pharmacy-led deprescribing interventions in a total of 4,231 adults. […]

Does renal function matter for polymyxin B?

Does renal function matter for polymyxin B?

Withdrawn: Effectiveness and safety of toripalimab, camrelizumab and sintilimab in a real-world cohort of hepatitis B virus associated hepatocellular carcinoma patients.

The above article from British Journal of Clinical Pharmacology, published online on July 5, 2020 in Wiley Online Library (http://wileyonlinelibrary.com) has been withdrawn by agreement among the authors and John Wiley & Sons Ltd on behalf of the British Pharmacology Society. The withdrawal has been agreed in accordance with the authors' decision to revise their study providing the latest data.