ReviewClinical pharmacology and therapeutics2021
Drug Dosing Recommendations for All Patients: A Roadmap for Change.
Review in Clinical pharmacology and therapeutics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 19 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
19 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Pharmacokinetics and Associated Efficacy of Emicizumab in Humans: A Systematic Review.Clinical pharmacokinetics · 2021Pooled it
- [Structured Annotation and Information Extraction of Epilepsy Clinical Texts].Sichuan da xue xue bao. Yi xue ban = Journal of Sichuan University. Medical science edition · 2026Article
- PKGPT: Expert-Orchestrated Recursive LLM Agent for Automated NONMEM PopPK Modeling with Human Benchmarking.Pharmaceutics · 2026Article
- The Spectrum of Clinical Pharmacy Services in a Non-University Hospital-A Comprehensive Characterization Including a Risk Assessment for Drug-Related Problems and Adverse Drug Reactions.Pharmacy (Basel, Switzerland) · 2025Article
- How Clinical Pharmacology Can Support Clinical Trial Diversity and Inclusion.Clinical and translational science · 2025Review
- Focused Insights into Liposomal Nanotherapeutics for Antimicrobial Treatment.Current medicinal chemistry · 2025Review
- A weighted Bayesian integration method for predicting drug combination using heterogeneous data.Journal of translational medicine · 2024Article
- Does Sample Size, Sampling Strategy, or Handling of Concentrations Below the Lower Limit of Quantification Matter When Externally Evaluating Population Pharmacokinetic Models?European journal of drug metabolism and pharmacokinetics · 2024Article
- Synthetic Model Combination: A new machine-learning method for pharmacometric model ensembling.CPT: pharmacometrics & systems pharmacology · 2023Article
- Diabetes medication recommendation system using patient similarity analytics.Scientific reports · 2022Article
- Individualized Patient Care Through Model-Informed Precision Dosing: Reflections on Training Future Practitioners.The AAPS journal · 2022Article
- Personalised Dosing Using the CURATE.AI Algorithm: Protocol for a Feasibility Study in Patients with Hypertension and Type II Diabetes Mellitus.International journal of environmental research and public health · 2022Article
- Extracellular vesicles and lipoproteins - Smart messengers of blood cells in the circulation.Journal of extracellular biology · 2022Review
- A continued learning approach for model-informed precision dosing: Updating models in clinical practice.CPT: pharmacometrics & systems pharmacology · 2022Article
- Drug-Related Deaths in China: An Analysis of a Spontaneous Reporting System.Frontiers in pharmacology · 2022Article
- Regarding Combined Pediatric and Adult Trials Submitted to the US Food and Drug Administration 2012-2018.Clinical pharmacology and therapeutics · 2021Article
- Physiologically-Based Pharmacokinetic Models as Enablers of Precision Dosing in Drug Development: Pivotal Role of the Human Mass Balance Study.Clinical pharmacology and therapeutics · 2021Review
- Development of Extracellular Vesicle Therapeutics: Challenges, Considerations, and Opportunities.Frontiers in cell and developmental biology · 2021Review
- A Real-World Evidence Framework for Optimizing Dosing in All Patients With COVID-19.Clinical pharmacology and therapeutics · 2020Article
Corrections and comments
- Commented on by
- Commented on by
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Most drug labels do not contain dosing recommendations for a significant portion of real-world patients for whom the drug is prescribed. Current label recommendations predominately reflect the population studied in pivotal trials that typically exclude patients who are very young or old, emaciated or morbidly obese, pregnant, or have multiple characteristics likely to influence dosing. As a result, physicians may need to guess the correct dose and regimen for these patients. It is now feasible to provide dose and regimen recommendations for these patients by integrating available scientific knowledge and by utilizing or modifying current regulatory agency-industry practices. The purpose of this commentary is to explore several factors that should be considered in creating a process that will provide more effective, safe, and timely drug dosing recommendations for most, if not all, patients. These factors include the availability of real-world data, development of predictive models, experience with the US Food and Drug Administration (FDA)'s pediatric exclusivity program, development of clinical decision software, funding mechanisms like the Prescription Drug Users Fee Act (PDUFA), and harmonization of global regulatory policies. From an examination of these factors, we recommend a relatively simple, efficient expansion of current practices designed to predict, confirm, and continuously improve drug dosing for more patients. We believe implementing these recommendations will benefit patients, payers, industry, and regulatory agencies.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.