Adverse event prediction
Encyclopedia
Adverse event
(or Adverse effect
) prediction is the process of identifying potential adverse events of an investigational drug
before they actually occur in a clinical trial.
Predicting adverse events accurately represents a significant challenge to both the pharmaceutical industry
and academia, the reason being that our existing knowledge of biology
, disease
mechanisms (i.e. how a disease affects the healthy state of a human) and drug design is incomplete and sometimes incorrect. On top of that, the biological complexity and differences between living organisms is such that even if a treatment appears to work in the laboratory it may not work in humans.
The occurrence of an adverse event during a clinical trial
is a significant event, not only because of the risk to humans but also from a financial point of view for the organization (usually a pharmaceutical company
) sponsoring the development of the drug in question. As a result a lot of effort is continuously invested in this area and there are a number of approaches to predicting adverse events including cell line assays, animal models and computer based in silico
models.
In silico
models are usually developed by extracting interactions and behaviors of biological systems either from the literature or from experimental data on a specific disease
or biological system and integrating this information in some kind of a mathematical model
that can be used to understand and predict the behavior of a drug in an organism. Another relatively recent method is based on mining the scientific literature
and correlating evidence from seemingly unrelated drugs or medical conditions. If done correctly this type of analysis can offer quite good predictive accuracy and significant lead times which translates to lower cost and development times for new drugs.
While in silico methods aim to capture in depth the current knowledge of a biological system or a disease mechanism, they are still subject to the accuracy of that knowledge and may miss information that while seemingly unrelated, could a multiply interconnected complex biological system prove highly relevant. This gap is addressed by the literature-based discovery
approach which does not capture details to the same extent but compensates by offering complete coverage of the available knowledge from all potentially related fields.
Adverse event
An adverse event is any adverse change in health or side effect that occurs in a person who participates in a clinical trial while the patient is receiving the treatment or within a previously specified period of time after the treatment has been completed.AEs in patients participating in...
(or Adverse effect
Adverse effect
In medicine, an adverse effect is a harmful and undesired effect resulting from a medication or other intervention such as surgery.An adverse effect may be termed a "side effect", when judged to be secondary to a main or therapeutic effect. If it results from an unsuitable or incorrect dosage or...
) prediction is the process of identifying potential adverse events of an investigational drug
Investigational New Drug
The United States Food and Drug Administration's Investigational New Drug program is the means by which a pharmaceutical company obtains permission to ship an experimental drug across state lines before a marketing application for the drug has been approved...
before they actually occur in a clinical trial.
Predicting adverse events accurately represents a significant challenge to both the pharmaceutical industry
Pharmaceutical company
The pharmaceutical industry develops, produces, and markets drugs licensed for use as medications. Pharmaceutical companies are allowed to deal in generic and/or brand medications and medical devices...
and academia, the reason being that our existing knowledge of biology
Biology
Biology is a natural science concerned with the study of life and living organisms, including their structure, function, growth, origin, evolution, distribution, and taxonomy. Biology is a vast subject containing many subdivisions, topics, and disciplines...
, disease
Disease
A disease is an abnormal condition affecting the body of an organism. It is often construed to be a medical condition associated with specific symptoms and signs. It may be caused by external factors, such as infectious disease, or it may be caused by internal dysfunctions, such as autoimmune...
mechanisms (i.e. how a disease affects the healthy state of a human) and drug design is incomplete and sometimes incorrect. On top of that, the biological complexity and differences between living organisms is such that even if a treatment appears to work in the laboratory it may not work in humans.
The occurrence of an adverse event during a clinical trial
Clinical trial
Clinical trials are a set of procedures in medical research and drug development that are conducted to allow safety and efficacy data to be collected for health interventions...
is a significant event, not only because of the risk to humans but also from a financial point of view for the organization (usually a pharmaceutical company
Pharmaceutical company
The pharmaceutical industry develops, produces, and markets drugs licensed for use as medications. Pharmaceutical companies are allowed to deal in generic and/or brand medications and medical devices...
) sponsoring the development of the drug in question. As a result a lot of effort is continuously invested in this area and there are a number of approaches to predicting adverse events including cell line assays, animal models and computer based in silico
In silico
In silico is an expression used to mean "performed on computer or via computer simulation." The phrase was coined in 1989 as an analogy to the Latin phrases in vivo and in vitro which are commonly used in biology and refer to experiments done in living organisms and outside of living organisms,...
models.
In silico
In silico
In silico is an expression used to mean "performed on computer or via computer simulation." The phrase was coined in 1989 as an analogy to the Latin phrases in vivo and in vitro which are commonly used in biology and refer to experiments done in living organisms and outside of living organisms,...
models are usually developed by extracting interactions and behaviors of biological systems either from the literature or from experimental data on a specific disease
Disease
A disease is an abnormal condition affecting the body of an organism. It is often construed to be a medical condition associated with specific symptoms and signs. It may be caused by external factors, such as infectious disease, or it may be caused by internal dysfunctions, such as autoimmune...
or biological system and integrating this information in some kind of a mathematical model
Mathematical model
A mathematical model is a description of a system using mathematical concepts and language. The process of developing a mathematical model is termed mathematical modeling. Mathematical models are used not only in the natural sciences and engineering disciplines A mathematical model is a...
that can be used to understand and predict the behavior of a drug in an organism. Another relatively recent method is based on mining the scientific literature
Biomedical text mining
Biomedical text mining refers to text mining applied to texts and literature of the biomedical and molecular biology domain...
and correlating evidence from seemingly unrelated drugs or medical conditions. If done correctly this type of analysis can offer quite good predictive accuracy and significant lead times which translates to lower cost and development times for new drugs.
While in silico methods aim to capture in depth the current knowledge of a biological system or a disease mechanism, they are still subject to the accuracy of that knowledge and may miss information that while seemingly unrelated, could a multiply interconnected complex biological system prove highly relevant. This gap is addressed by the literature-based discovery
Literature-based discovery
Literature-based discovery refers to the use of papers and other academic publications to find new relationships between existing knowledge . The technique was pioneered by Don R...
approach which does not capture details to the same extent but compensates by offering complete coverage of the available knowledge from all potentially related fields.