ArticleCPT: pharmacometrics & systems pharmacology2013
White paper: landscape on technical and conceptual requirements and competence framework in drug/disease modeling and simulation.
Article in CPT: pharmacometrics & systems pharmacology, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 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
12 citing papers in PubMed, 20 citations in OpenAlex.
- Application of a Stochastic Simulation-estimation Approach to Optimize Pharmacokinetic Study Design in the Context of Paediatric Extrapolation: A Tool to Support Decision-making by Drug Sponsors and Regulators.Pharmaceutical research · 2026Article
- Training the next generation of pharmacometric modelers: a multisector perspective.Journal of pharmacokinetics and pharmacodynamics · 2024Article
- Barriers to global pharmacometrics: educational challenges and opportunities across the globe.CPT: pharmacometrics & systems pharmacology · 2023Article
- Impact of Hospital Characteristics and Governance Structure on the Adoption of Tracking Technologies for Clinical and Supply Chain Use: Longitudinal Study of US Hospitals.Journal of medical Internet research · 2022Review
- Assessing parameter uncertainty in small-n pharmacometric analyses: value of the log-likelihood profiling-based sampling importance resampling (LLP-SIR) technique.Journal of pharmacokinetics and pharmacodynamics · 2020Article
- MID3: Mission Impossible or Model-Informed Drug Discovery and Development? Point-Counterpoint Discussions on Key Challenges.Clinical pharmacology and therapeutics · 2020Article
- A Survey of Software Tool Utilization and Capabilities for Quantitative Systems Pharmacology: What We Have and What We Need.CPT: pharmacometrics & systems pharmacology · 2019Article
- Deducing Mucosal Pharmacokinetics and Pharmacodynamics of the Anti-HIV Molecule Tenofovir from Measurements in Blood.Scientific reports · 2019Article
- MatVPC: A User-Friendly MATLAB-Based Tool for the Simulation and Evaluation of Systems Pharmacology Models.CPT: pharmacometrics & systems pharmacology · 2015Article
- Pharmacometric Models for Characterizing the Pharmacokinetics of Orally Inhaled Drugs.The AAPS journal · 2015Review
- Preclinical pharmacokinetic/pharmacodynamic modeling and simulation in the pharmaceutical industry: an IQ consortium survey examining the current landscape.The AAPS journal · 2015Article
- Modeling and Simulation Workbench for NONMEM: Tutorial on Pirana, PsN, and Xpose.CPT: pharmacometrics & systems pharmacology · 2013Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 6 institutions in 6 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Pharmaceutical sciences experts and regulators acknowledge that pharmaceutical development as well as drug usage requires more than scientific advancements to cope with current attrition rates/therapeutic failures. Drug disease modeling and simulation (DDM&S) creates a paradigm to enable an integrated and higher-level understanding of drugs, (diseased)systems, and their interactions (systems pharmacology) through mathematical/statistical models (pharmacometrics)(1)-hence facilitating decision making during drug development and therapeutic usage of medicines. To identify gaps and challenges in DDM&S, an inventory of skills and competencies currently available in academia, industry, and clinical practice was obtained through survey. The survey outcomes revealed benefits, weaknesses, and hurdles for the implementation of DDM&S. In addition, the survey indicated that no consensus exists about the knowledge, skills, and attributes required to perform DDM&S activities effectively. Hence, a landscape of technical and conceptual requirements for DDM&S was identified and serves as a basis for developing a framework of competencies to guide future education and training in DDM&S.CPT: Pharmacometrics & Systems Pharmacology (2013) 2, e40; doi:10.1038/psp.2013.16; advance online publication 1 May 2013.
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.