ReviewThe AAPS journal2017
Microdialysis: the Key to Physiologically Based Model Prediction of Human CNS Target Site Concentrations.
Review in The AAPS journal, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. An erratum has been issued. Cited by 26 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
26 citing papers in PubMed.
- Boron-Doped Nano-Crystalline Coated Carbon Fibers for Phasic Dopamine Sensing.Advanced healthcare materials · 2026Article
- The 4-alkyl chain length of 2,5-dimethoxyamphetamines differentially affects in vitro serotonin receptor actions versus in vivo psychedelic-like effects.Molecular psychiatry · 2026Article
- Electrical stimulation of stem cell-derived human neural networks for evaluating anti-seizure medications.Epilepsia · 2025Article
- Distribution of ganciclovir in the porcine central nervous system.Antimicrobial agents and chemotherapy · 2025Article
- Prediction of the Extent of Blood-Brain Barrier Transport Using Machine Learning and Integration into the LeiCNS-PK3.0 Model.Pharmaceutical research · 2025Article
- Collagen I Microfiber Promotes Brain Capillary Network Formation in Three-Dimensional Blood-Brain Barrier Microphysiological Systems.Biomedicines · 2024Article
- Population Pharmacokinetic Analysis of Rifampicin in Plasma, Cerebrospinal Fluid, and Brain Extracellular Fluid in South African Children with Tuberculous Meningitis.Antimicrobial agents and chemotherapy · 2023Article
- The Extension of the LeiCNS-PK3.0 Model in Combination with the "Handshake" Approach to Understand Brain Tumor Pathophysiology.Pharmaceutical research · 2022Article
- Understanding the Blood-Brain Barrier and Beyond: Challenges and Opportunities for Novel CNS Therapeutics.Clinical pharmacology and therapeutics · 2022Review
- In Vitro to In Vivo Extrapolation Linked to Physiologically Based Pharmacokinetic Models for Assessing the Brain Drug Disposition.The AAPS journal · 2022Review
- In Vivo Studies of Drug BBB Transport: Translational Challenges and the Role of Brain Imaging.Handbook of experimental pharmacology · 2022Article
- New In Vitro Methodology for Kinetics Distribution Prediction in the Brain. An Additional Step towards an Animal-Free Approach.Animals : an open access journal from MDPI · 2021Article
- Understanding Drug Delivery to the Brain Using Liposome-Based Strategies: Studies that Provide Mechanistic Insights Are Essential.The AAPS journal · 2021Review
- Addressing the instability issue of dopamine during microdialysis: the determination of dopamine, serotonin, methamphetamine and its metabolites in rat brain.Journal of chromatography. A · 2020Article
- Design and Application in Delivery System of Intranasal Antidepressants.Frontiers in bioengineering and biotechnology · 2020Review
- A 3D brain unit model to further improve prediction of local drug distribution within the brain.PloS one · 2020Article
- Phase 0 Clinical Trial Strategies for the Neurosurgical Oncologist.Neurosurgery · 2019Article
- Accumulation of uremic solutes in the cerebrospinal fluid in experimental acute renal failure.American journal of physiology. Renal physiology · 2019Article
- Mind the Gaps: Ontogeny of Human Brain P-gp and Its Impact on Drug Toxicity.The AAPS journal · 2019Review
- Physiologically Based Modeling Approach to Predict Dopamine D2 Receptor Occupancy of Antipsychotics in Brain: Translation From Rat to Human.Journal of clinical pharmacology · 2019Article
Corrections and comments
- Erratum issued
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Despite the enormous research efforts that have been put into the development of central nervous system (CNS) drugs, the success rate in this area is still disappointing. To increase the successful rate in the clinical trials, first the problem of predicting human CNS drug distribution should be solved. As it is the unbound drug that equilibrates over membranes and is able to interact with targets, especially knowledge on unbound extracellular drug concentration-time profiles in different CNS compartments is important. The only technique able to provide such information in vivo is microdialysis. Also, obtaining CNS drug distribution data from human subjects is highly limited, and therefore, we have to rely on preclinical approaches combined with physiologically based pharmacokinetic (PBPK) modeling, taking unbound drug CNS concentrations into account. The next step is then to link local CNS pharmacokinetics to target interaction kinetics and CNS drug effects. In this review, system properties and small-molecule drug properties that together govern CNS drug distribution are summarized. Furthermore, the currently available approaches on prediction of CNS pharmacokinetics are discussed, including in vitro, in vivo, ex vivo, and in silico approaches, with special focus on the powerful combination of in vivo microdialysis and PBPK modeling. Also, sources of variability on drug kinetics in the CNS are discussed. Finally, remaining gaps and challenges are highlighted and future directions are suggested.
Indexed as
Identifiers
28281195What 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.