ReviewClinical and translational science2022
Model-informed assessment of ethnic sensitivity and dosage justification for Asian populations in the global clinical development and use of cladribine tablets.
Review in Clinical and translational science, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.
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
4 citing papers in PubMed, 4 citations in OpenAlex.
- Effect of Cladribine Tablets on the Pharmacokinetics of a Combined Oral Contraceptive in Pre-Menopausal Women With Relapsing Multiple Sclerosis.Clinical and translational science · 2025Trial
- Ethnic Bridging of Sepiapterin in Chinese and Korean Populations Based on Predictions From Genetic Polymorphism of Breast Cancer Resistance Protein.Clinical and translational science · 2026Article
- Asia-inclusive drug development leveraging principles of ICH E5 and E17 guidelines: Case studies illustrating quantitative clinical pharmacology as a foundational enabler.Clinical and translational science · 2024Review
- Model-informed assessment of ethnic sensitivity and dosage justification for Asian populations in the global clinical development and use of cladribine tablets.Clinical and translational science · 2022Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors at 4 institutions in 4 countries.
Funding
Abstract
Cladribine tablets have been approved in many countries for the treatment of patients with various forms of relapsing multiple sclerosis (MS). Cladribine has a unique pharmacokinetic/pharmacodynamic (PK/PD) profile with a short elimination half-life (~ 1 day) relative to a prolonged PD effect on specific immune cells (most notably a reversible reduction in B and T lymphocyte counts). This results in a short dosing schedule (up to 20 days over 2 years of treatment) to sustain efficacy for at least another 2 years. Global clinical studies were conducted primarily in White patients, in part due to the distinctly higher prevalence of MS in White patients. Given the very low prevalence in Asian countries, MS is considered as a rare disease there. In spite of the limited participation of Asian patients, to demonstrate favorable benefit/risk profile in the treatment of MS demanded application of a Totality of Evidence approach to assess ethnic sensitivity for informing regulatory filings in Asian countries and supporting clinical use of cladribine in Asian patients. Population PD modeling and simulation of treatment-related reduction in absolute lymphocyte count, as a mechanism-related biomarker of drug effect, confirmed consistent PDs in Asian and non-Asian patients with MS, supporting absence of ethnic sensitivity and a common dosage across populations. Through this example, we demonstrate the value of holistic integration of all available data using a model-informed drug development (MIDD) framework and a Totality of Evidence mindset to evaluate ethnic sensitivity in support of Asia-inclusive development and use of the drug across populations.
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.