bBefore a drug or medical device is approved for use in humans, it must undergo a clinical trial. Clinical trials ultimately aim to answer two simple questions: Is the drug or device safe? And does it do what it’s supposed to do?
The downside of clinical trials is that they are complicated, take years to complete and are extremely expensive. However, a recent development called “in silico clinical trials” (trials using computer simulation) are beginning to show their ability to significantly accelerate trials and significantly reduce their costs. And drug regulators are starting to pay attention.
Indeed, evidence from an in silico clinical trial has already been used to gain approval for a new type of pacemaker.
about 75% of patients At some stage an MRI scan will be needed if a pacemaker is attached, but these devices carry a risk of overheating and burning of the heart tissue in the MRI machine. In 2011 a new pacemaker was developed and approved that was safe to use in MRI machines.
Testing this new pacemaker using a standard clinical test would require thousands of participants to capture the few occasions where the pacemaker had overheated. Instead, the evidence for in silico clinical trials was accepted by the US Food and Drug Administration (FDA) and the device was Approved,
In silico tests have also been used to reduce the amount of animal testing. In 2008, the FDA approved one such test to replace the use of dogs when testing an insulin control loop (a device that lets an insulin pump communicate with a continuous glucose monitor) in type 1 diabetes. Since then, more than 140 control loops have been tested in this way, avoiding Experiments on hundreds of dogs,
Since then there has been a flurry of efforts to develop in silico clinical trials. the strokesTo irregular heartbeat (a potentially life-threatening irregular heartbeat), to assess drug toxicity, While none of these recent computer tests have attempted to gain regulatory approval, they are leading the way in future in silico clinical trials to be used in regulatory approval of a drug or device.
These simulations have the potential to reduce the estimate 90% failure rate of new drugs in the market. Changes in drug design or dosage may improve clinical trial outcomes and reduce failure rates, but these are often not detected due to the enormous cost of re-running clinical trials. . But they can be used cheaply in in silico trials.
widely used in other industries
Manufacturing industries have long used computer simulation. Cars, planes and nuclear reactors are designed and tested on computers before construction begins. What’s new is the use of these simulations to predict disease for a general population, and the effect of a drug or medical device on that disease.
Medical regulators such as the FDA are more interested in evaluating in silico clinical trials because they can reduce cost, time, and failure rates when developing a new treatment. Estimates of drug or medical device development costs range from US$50 million (£41 million) plus US$1 billion (£828 million). Any reduction in these costs should result in cheaper drugs.
Research has reached a point where the computational power and understanding of biology allows for highly specific predictions of how a drug will affect the human body. However, this in no way means that these in silico clinical trials will completely replace human trials. There are a lot of “unknown unknowns” in understanding medical interventions, which means that 100% accuracy is not guaranteed in simulating reality.
Regulatory approval is another hurdle that must be overcome. While there are promising signs from the FDA that in silico trials may be accepted as evidence, it still needs clear regulatory guidance for this to become the norm. As more in silico trials become successful, regulators around the world will probably accept them as valid evidence.
While in silico clinical trials will never completely replace real-world clinical trials, two questions – is the drug safe, and does it do what it is supposed to? – Will be answered rapidly by a combination of humans and computer simulations of humans.
Wahbi K. Al-Bourikresearch Fellow, Liverpool University
This article is republished from Conversation Under Creative Commons license. read the original article,
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