No animal testing, human volunteers – how new era ‘in silico’ trials will make drugs cheaper

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 disadvantage of clinical trials is that they are complex, take years and are extremely expensive. However, a recent development called “in silico clinical trials” (trials conducted by computer simulation) is beginning to show their potential to dramatically speed up trials and drastically 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 with pacemakers will need an MRI at some point, but these devices may overheat in an MRI machine and burn heart tissue. A new pacemaker was developed and approved in 2011 that could be safely used in MRI machines.

Testing this new pacemaker using a standard clinical trial would have required thousands of participants to catch those few occasions when the pacemaker overheated. Instead, the evidence from the in silico clinical trial was accepted by the US Food and Drug Administration (FDA) and the device was approved.

In silico assays have also been used to reduce the number of animal tests. In 2008, the FDA approved such a trial to replace the use of dogs when testing insulin control loops in type 1 diabetes (a device that allows an insulin pump to communicate with a continuous glucose). Since then, more than 140 control loops have been tested, avoiding experimentation on hundreds of dogs.

Since then, there has been a flurry of attempts to develop in silico clinical trials in conditions ranging from stroke to atrial fibrillation (a life-threatening irregular heartbeat) to evaluating the toxicity of medications. Although none of these recent computational trials attempted to gain regulatory approval, they pave the way for future in silico clinical trials that will be used for regulatory approval of the drug or device.

These simulations have the potential to reduce the estimated 90% failure rate of new drugs reaching the market. Changes to drug design or dosage can improve clinical trial outcomes and reduce failure rates, but these are often not explored due to the huge costs of re-running clinical trials. But they can be explored inexpensively using in silico trials.

Widely used in other industries

Manufacturing industries have long used computer simulations. Cars, planes, and nuclear reactors are all designed and computer tested before construction begins. What is new is the use of these simulations to predict disease and the effect of a drug or medical device on that disease, for a general population.

Medical regulators such as the FDA are increasingly interested in evaluating in silico clinical trials because they can reduce the cost, time, and failure rate when developing a new treatment. Estimates of drug or medical device development costs range from US$50m (£41m) to over US$1bn (£828m). Any reduction in these costs should translate into cheaper drugs.

Research has reached a point where computing power and understanding of biology allow very accurate predictions of how a drug will affect the human body. However, this does not in any way mean that these in silico clinical trials will completely replace human trials. There are too many “unknown unknowns” in understanding medical interventions, meaning 100% accuracy in simulating reality is never guaranteed.

Regulatory acceptance is another hurdle to overcome. While there are promising signs from the FDA that in silico testing can be accepted as evidence, clear regulatory guidance is still needed for this to become the norm. As more successful in silico trials are developed, regulators around the world will likely accept them as valid evidence.

While in silico clinical trials will never fully replace real-world clinical trials, the two questions are: is the drug safe and does it do what it’s supposed to? – will increasingly be answered by a combination of humans and computer simulations of humans.

Wahbi K. El-Bouri, researcher, University of Liverpool

This article is republished from The Conversation under a Creative Commons license. Read the original article.


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