In silico clinical trials

An in silico clinical trial is an individualised computer simulation used in the development or regulatory evaluation of a medicinal product, device, or intervention. While completely simulated clinical trials are not feasible with current technology and understanding of biology, its development would be expected to have major benefits over current in vivo clinical trials, and research on it is being pursued. An in silico clinical trial is an individualised computer simulation used in the development or regulatory evaluation of a medicinal product, device, or intervention. While completely simulated clinical trials are not feasible with current technology and understanding of biology, its development would be expected to have major benefits over current in vivo clinical trials, and research on it is being pursued. The term in silico indicates any use of computers in clinical trials, even if limited to management of clinical information in a database. The traditional model for the development of medical treatments and devices begins with pre-clinical development. In laboratories, test-tube and other in vitro experiments establish the plausibility for the efficacy of the treatment. Then in vivo animal models, with different species, provide guidance on the efficacy and safety of the product for humans. With success in both in vitro and in vivo studies, scientist can propose that clinical trials test whether the product be made available for humans. Clinical trials are often divided into four phases. Phase 3 involves testing a large number of people. When a medication fails at this stage, the financial losses can be catastrophic. Predicting low-frequency side effects has been difficult, because such side effects need not become apparent until the treatment is adopted by many patients. The appearance of severe side-effects in phase three often causes development to stop, for ethical and economic reasons. Also, in recent years many candidate drugs failed in phase 3 trials because of lack of efficacy rather than for safety reasons. One reason for failure is that traditional trials aim to establish efficacy and safety for most subjects, rather than for individual subjects, and so efficacy is determined by a statistic of central tendency for the trial. Traditional trials do not adapt the treatment to the covariates of subjects: Accurate computer models of a treatment and its deployment, as well as patient characteristics, are necessary precursors for the development of in silico clinical trials. In such a scenario, ‘virtual’ patients would be given a ‘virtual’ treatment, enabling observation through a computer simulation of how the candidate biomedical product performs and whether it produces the intended effect, without inducing adverse effects. Such in silico clinical trials could help to reduce, refine, and partially replace real clinical trials by: In addition, real clinical trials may indicate that a product is unsafe or ineffective, but rarely indicate why or suggest how it might be improved. As such, a product that fails during clinical trials may simply be abandoned, even if a small modification would solve the problem. This stifles innovation, decreasing the number of truly original biomedical products presented to the market every year, and at the same time increasing the cost of development.Analysis through in silico clinical trials is expected to provide a better understanding of the mechanism that caused the product to fail in testing, and may be able to provide information that could be used to refine the product to such a degree that it could successfully complete clinical trials. In silico clinical trials would also provide significant benefits over current pre-clinical practices. Unlike animal models, the virtual human models can be re-used indefinitely, providing significant cost savings. Compared to trials in animals or a small sample of humans, in silico trials might more effectively predict the behaviour of the drug or device in large-scale trials, identifying side effects that were previously difficult or impossible to detect, helping to prevent unsuitable candidates from progressing to the costly phase 3 trials.  This article incorporates text available under the CC BY 4.0 license.