ReviewThe AAPS journal2010
Prediction of exposure-response relationships to support first-in-human study design.
Review in The AAPS journal, 2010. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 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
13 citing papers in PubMed.
- Trial
- An Open-Access Dialysis Membrane-Integrated Microfluidic Device for Generating Drug Exposure Profiles Through Molecular-Weight-Dependent Transport.Micromachines · 2026Article
- Computational analysis of 5-fluorouracil anti-tumor activity in colon cancer using a mechanistic pharmacokinetic/pharmacodynamic model.PLoS computational biology · 2022Article
- How translational modeling in oncology needs to get the mechanism just right.Clinical and translational science · 2022Review
- A Microfluidic Perfusion Platform for In Vitro Analysis of Drug Pharmacokinetic-Pharmacodynamic (PK-PD) Relationships.The AAPS journal · 2020Article
- A pre-clinical quantitative model predicts the pharmacokinetics/pharmacodynamics of an anti-BDCA2 monoclonal antibody in humans.Journal of pharmacokinetics and pharmacodynamics · 2018Article
- Translational mixed-effects PKPD modelling of recombinant human growth hormone - from hypophysectomized rat to patients.British journal of pharmacology · 2016Article
- Immunotherapy and Novel Combinations in Oncology: Current Landscape, Challenges, and Opportunities.Clinical and translational science · 2016Review
- Prediction of clinical pharmacokinetics of AMG 181, a human anti-α 4 β 7 monoclonal antibody for treating inflammatory bowel diseases.Pharmacology research & perspectives · 2015Article
- Developing Exposure/Response Models for Anticancer Drug Treatment: Special Considerations.CPT: pharmacometrics & systems pharmacology · 2015Article
- On translation of antibody drug conjugates efficacy from mouse experimental tumors to the clinic: a PK/PD approach.Journal of pharmacokinetics and pharmacodynamics · 2013Article
- Antiretroviral pharmacology in mucosal tissues.Journal of acquired immune deficiency syndromes (1999) · 2013Review
- Modeling and predicting clinical efficacy for drugs targeting the tumor milieu.Nature biotechnology · 2012Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
In drug development, phase 1 first-in-human studies represent a major milestone as the drug moves from preclinical discovery to clinical development activities. The safety of human subjects is paramount to the conduct of these studies and regulatory considerations guide activities. Forces of evolution on the pharmaceutical industry are re-shaping the first-in-human dose selection strategy. Namely, high attrition rates in part due to lack of efficacy have led to the re-organization of research and development organizations around the umbrella of translational research. Translational research strives to bring basic research advances into the clinic and support the reverse transfer of information to enhance compound selection strategies. Pharmacokinetic/pharmacodynamic (PK/PD) modeling holds a unique position in translational research by attempting to integrate diverse sets of information. PK/PD modeling has demonstrated utility in dose selection and trial design for later stages of drug development and is now being employed with greater prevalence in the translational research setting to manage risk (i.e., oncology and inflammation/immunology). Moving from empirical E (max) models to more mechanistic representations of the biological system, a higher fidelity of human predictions is expected. Strategies that have proven useful for PK predictions are being applied to PK/PD predictions. This review article examines examples of the application of PK/PD modeling in establishing target concentrations for supporting first-in-human study design.
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.