Robots and computers making drugs of the future

Can computers develop the drugs of the future? The short answer is probably, but not yet.

Computer simulation is a cornerstone in the development and optimization of “mission-critical” elements in industries ranging from aerospace to finance. Even the smooth functioning of nuclear reactors—where failure would be catastrophic—relies on a computational model called a Virtual Reactor, which allows scientists and engineers to observe the reactor’s real-time response to operating conditions.

The analogous model in medicine—a “virtual human”—doesn’t yet exist. We still rely on living, breathing animals and humans to test drugs and devices. Discoveries are made largely by trial and error. But the age-old approach that led to the discovery of antibiotics, cardiac catheterization, and organ transplantation is becoming increasingly unsustainable.

According to the Tufts Center for the Study of Drug Development, the development of a new drug now exceeds $2.5 billion, 75% of which is spent in various phases of development. Lesser known than the price tag of successful drugs is the failure of most; 90% of potential drugs that are backed by funding of this magnitude fail in late-stage clinical trials before making it to market. Perhaps most worrisome of all is that when a drug or device fails, no one really understands why. The traditional clinical trial simply isn’t designed to tell us why an adverse event occurred, or why the expected efficacy was strikingly less than predicted. The failed therapeutics are largely abandoned in an all-or-nothing mentality that ultimately dampens the innovative process.


A virtual alternative to clinical trials


Enter in silico clinical trials. Avicenna, the European Commission-funded coalition dedicated to the support and development of in silico technology, defines in silico clinical trials (ISCT) as “the use of individualized computer simulation in the development or regulatory evaluation of a medicinal product, medical device, or medical intervention.”  In other words, test the idea on a computer, not a person.

In all fairness, computer modeling in drug and device development isn’t particularly groundbreaking. A handful of pharmaceutical companies uses computational methods to model pharmacodynamics and pharmacokinetics in preclinical studies. And medical device companies use computational fluid dynamics to model how blood moves around an implanted device.

What’s missing is a model that can be tailored to each patient with the option to punch in a patient’s physiologic parameters and learn how the individual will respond. The goal is to create—you guessed it—a Virtual Physiologic Human, or VPH.


The virtual physiologic human

Although the VPH model is far from attaining the reliability needed to meaningfully transform the clinical trial process, it isn’t just science fiction. A recent UCSF computer model, for instance, correctly predicted side effects of over 650 drugs. Another study of 300 virtual type 1 diabetics accurately predicted trends in blood glucose after “meals” and with “insulin.” And a computer model in patients with sepsis identified subgroups of virtual patients for whom TNF-α inhibitors could be life-saving and those in whom the immunomodulatory drug did more harm than good.

In the not-so-distant future, ISCT could be used to answer questions that current clinical trials can’t. How will the effect of the drug change if the body weight is 20% above normal? What genetic profile is most likely to respond best to what drug? What would happen if the dose were doubled or halved? Ultimately, the hope is that ISCT technology could reduce the size and duration of clinical trials, refine clinical outcomes with greater explanatory power, and even partially replace clinical trials in cases where ISCT can generate sound and reliable evidence.

If successful, the implications of in silico trials—from individualized drug development to massive cost savings to much-needed and overdue development of orphan drugs—are hard to overestimate.


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