Jump to content

Pharmacometrics: Difference between revisions

From Wikipedia, the free encyclopedia
Browse history interactively
← Previous editNext edit →
Content deleted Content added
VisualWikitext
→Disease progression: section was updated and elaborated. A couple of references was added.
Line 23: Line 23:


=== Disease progression ===
=== Disease progression ===
The natural time course of a disease is often dynamic, with the tendency to become worse without treatment. Disease progression models are mainly used to understand the relationship between treatment, biomarker changes and clinical outcomes. These models describe the disease trajectory, by observing the change in the biomarker level, or the other clinically relevant endpoint that reflects the disease status, over time.<ref>{{Cite book|url=https://www.worldcat.org/oclc/124040246|title=Pharmacometrics : the science of quantitative pharmacology|date=2007|publisher=John Wiley & Sons|others=Ene I. Ette, Paul J. Williams|isbn=978-0-470-08796-1|location=Hoboken, N.J.|oclc=124040246}}</ref> There are three key classes of disease progression models: [[Empirical modelling|empirical]], semi-mechanistic, and systems biology.<ref>{{Cite journal|last=Cook|first=Sarah F.|last2=Bies|first2=Robert R.|date=2016-10|title=Disease Progression Modeling: Key Concepts and Recent Developments|url=http://link.springer.com/10.1007/s40495-016-0066-x|journal=Current Pharmacology Reports|language=en|volume=2|issue=5|pages=221–230|doi=10.1007/s40495-016-0066-x|issn=2198-641X|pmc=PMC5602534|pmid=28936389}}</ref> Most of the disease progression models are empirical, describing disease trajectory rather then the physiological background of the disease.<ref>{{Cite book|url=https://www.worldcat.org/oclc/897466424|title=Applied pharmacometrics|date=2014|others=Stephan Schmidt, Hartmut Derendorf|isbn=978-1-4939-1304-6|location=New York|oclc=897466424}}</ref> The simplest model that is used to describe disease progression is a [[Linear regression|linear model]], when the change of disease status over time is assumed to be constant.
Disease progression models describe the time course of disease and [[placebo]] effects. Disease and exposure-response models are used to understand the relationship between treatment, biomarker changes and clinical outcomes.


=== Trial ===
=== Trial ===

Revision as of 17:45, 19 September 2021

Pharmacometrics is a field of study of the methodology and application of models for disease and pharmacological measurement. It uses mathematical models of biology, pharmacology, disease, and physiology to describe and quantify interactions between xenobiotics and patients (human and non-human), including beneficial effects and adverse effects.[1] It is normally applied to quantify drug, disease and trial information to aid efficient drug development, regulatory decisions and rational drug treatment in patients.

Pharmacometrics uses models based on pharmacology, physiology and disease for quantitative analysis of interactions between drugs and patients. This involves Systems pharmacology, pharmacokinetics, pharmacodynamics and disease progression with a focus on populations and variability.

Mould and Upton provide an overview of basic concepts in population modeling, simulation, and model-based drug development.[2]

A major focus of pharmacometrics is to understand variability in drug response. Variability may be predictable (e.g. due to differences in body weight or kidney function) or apparently unpredictable (a reflection of current lack of knowledge).

Types of models

Pharmacokinetics (PK)

Models of pharmacokinetic processes.

Pharmacodynamics (PD)

Models of pharmacodynamic processes.

Physiologically based Pharmacokinetics

Physiologically based pharmacokinetic models

Exposure-response

Exposure-response models describe the relationship between exposure (or pharmacokinetics), response (or pharmacodynamics) for both desired and undesired effects. See also dose-response.

Disease progression

The natural time course of a disease is often dynamic, with the tendency to become worse without treatment. Disease progression models are mainly used to understand the relationship between treatment, biomarker changes and clinical outcomes. These models describe the disease trajectory, by observing the change in the biomarker level, or the other clinically relevant endpoint that reflects the disease status, over time.[3] There are three key classes of disease progression models: empirical, semi-mechanistic, and systems biology.[4] Most of the disease progression models are empirical, describing disease trajectory rather then the physiological background of the disease.[5] The simplest model that is used to describe disease progression is a linear model, when the change of disease status over time is assumed to be constant.

Trial

Trial models describe variations from the nominal trial protocol due to things such as patient dropout and lack of adherence to the dosing regimen.

Organizations

Historically, pharmacometrics has been represented in related clinical pharmacology and statistics organizations. A number of smaller local organizations in Europe, United States, and New Zealand/Australia held local meetings. In the early 1990s, The PAGE meeting was organized and has been held yearly since then, although no official organization was present. Ette and Williams have provided a historical context from which the evolution of pharmacometrics can be appreciated.[6]

In 2011, the American Society of Pharmacometrics (ASoP) was founded from a number of local American groups, and over 600 members worldwide joined ASoP within 6 months. In 2012, ASoP evolved to the International Society of Pharmacometrics (ISoP) to reflect the increasing number of international members. ISoP’s growth continues and the Society currently represents over 1000 members from almost 30 countries around the world.[7] Regional groups include PAGE in Europe[8] and PAGANZ in Australia and New Zealand.[9]

Pharmacometricians typically come from disciplines such as Pharmacy, Clinical pharmacology, Statistics, Medicine, or Engineering.

The first professor of pharmacometrics was Mats Karlsson, Uppsala University.[10]

Journals

Scientific meetings

PhD programs

References

  1. ^ Barrett, Jeffrey (2008). "Pharmacometrics: A Multidisciplinary Field to Facilitate Critical Thinking in Drug Development and Translational Research Settings". The Journal of Clinical Pharmacology. 48 (5): 632–49. doi:10.1177/0091270008315318. PMID 18440922.
  2. ^ Mould DR, Upton RN Basic concepts in population modeling, simulation, and model-based drug development CPT: Pharmacometrics & Systems Pharmacology September 2012 doi:10.1038/psp.2012.4
  3. ^ Pharmacometrics : the science of quantitative pharmacology. Ene I. Ette, Paul J. Williams. Hoboken, N.J.: John Wiley & Sons. 2007. ISBN 978-0-470-08796-1. OCLC 124040246.{{cite book}}: CS1 maint: others (link)
  4. ^ Cook, Sarah F.; Bies, Robert R. (2016-10). "Disease Progression Modeling: Key Concepts and Recent Developments". Current Pharmacology Reports. 2 (5): 221–230. doi:10.1007/s40495-016-0066-x. ISSN 2198-641X. PMC 5602534. PMID 28936389. {{cite journal}}: Check date values in: |date= (help)CS1 maint: PMC format (link)
  5. ^ Applied pharmacometrics. Stephan Schmidt, Hartmut Derendorf. New York. 2014. ISBN 978-1-4939-1304-6. OCLC 897466424.{{cite book}}: CS1 maint: location missing publisher (link) CS1 maint: others (link)
  6. ^ Williams, PJ (2007). Pharmacometrics: The Science of Quantitative Pharmacology. John Wiley & Sons. p. 1.
  7. ^ International Society of Pharmacometrics (ISoP)
  8. ^ Population Approach Group Europe (PAGE)
  9. ^ *Population Approach Group of Australia and New Zealand (PAGANZ)
  10. ^ http://www.uppsala-pharmacometrics.com/
Retrieved from "https://en.wikipedia.org/w/index.php?title=Pharmacometrics&oldid=1045262428"