Millions of people take upwards of five medications a day, but testing the side effects of such combinations is impractical. Now, Stanford computer scientists have figured out how to predict side effects using artificial intelligence.
Last month alone, 23 percent of Americans took two or more prescription drugs, according to one CDC estimate. Furthermore, 39 percent over age 65 take five or more, a number that’s increased three-fold in the last several decades. And if that isn’t surprising enough, try this one: in many cases, doctors have no idea what side effects might arise from adding another drug to a patient’s personal pharmacy.
The problem is that with so many drugs currently on the U.S. pharmaceutical market, “it’s practically impossible to test a new drug in combination with all other drugs, because just for one drug that would be five thousand new experiments,” said Marinka Zitnik, a postdoctoral fellow in computer science. With some new drug combinations, she said, “truly we don’t know what will happen.”
But computer science may be able to help. In a paper presented July 10 at the 2018 meeting of the International Society for Computational Biology in Chicago. Zitnik and colleagues Monica Agrawal, a master’s student, and Jure Leskovec, an associate professor of computer science, describe an artificial intelligence system for predicting, not simply tracking, potential side effects from drug combinations. That system, called Decagon, could help doctors make better decisions about which drugs to prescribe and help researchers find better combinations of drugs to treat complex diseases.
Too many combinations
Once it’s available to doctors in a more user-friendly form, Decagon’s predictions would be an improvement over what’s available now, which essentially comes down to chance – a patient takes one drug, starts taking another and then develops a headache or worse. There are about 1,000 known side effects and 5,000 drugs on the market, making for nearly 125 billion possible side effects between all possible pairs of drugs. Most of these have never been prescribed together, let alone systematically studied.
Zitnik, Agrawal and Leskovec realized they could get around that problem by studying how drugs affect the underlying cellular machinery in the body. They composed a massive network describing how the more than 19,000 proteins in our bodies interact with each other and how different drugs affect these proteins. Using more than 4 million known associations between drugs and side effects, the team then designed a method to identify patterns in how side effects arise based on how drugs target different proteins.
To do that, the team turned to deep learning, a kind of artificial intelligence modeled after the brain. In essence, deep learning looks at complex data and extracts from them abstract, sometimes counterintuitive patterns in the data. In this case, the researchers designed their system to infer patterns about drug interaction side effects and predict previously unseen consequences from taking two drugs together.
Just because Decagon found a pattern doesn’t necessarily make it real, so the group looked to see if its predictions came true In many cases, they did. For example, there was no indication in the team’s data that the combination of atorvastatin, a cholesterol drug, and amlopidine, a blood pressure medication, could lead to muscle inflammation. Yet Decagon predicted that it would, and it was right. Although it did not appear in the original data, a case report from 2017 suggested the drug combination had led to a dangerous kind of muscle inflammation.
That example was born out in other cases as well. When they searched the medical literature for evidence of 10 side effects predicted by Decagon but not in their original data, the team members found that five out of the ten have recently been confirmed, lending further credence to Decagon’s predictions.
“It was surprising that protein interaction networks reveal so much about drug side effects,” said Leskovec, who is a member of Stanford Bio-X, Stanford Neurosciences Institute and the Chan Zuckerberg Biohub.
Right now, Decagon only considers side effects associated with pairs of drugs. In the future, the team members hope to extend their results to include more complex regimens, Leskovec said. They also hope to create a more user-friendly tool to give doctors guidance on whether it’s a good idea to prescribe a particular drug to a particular patient and to help researchers developing drug regimens for complex diseases with fewer side effects.
“Today, drug side effects are discovered essentially by accident,” Leskovec said, “and our approach has the potential to lead to more effective and safer health care.”
The Latest on: Drug side effects
via Google News
The Latest on: Drug side effects
- When a Cancer Therapy Stops Working: Experimental Drug Addresses Resistance on April 17, 2019 at 12:59 pm
Most side effects seemed to vary with the amount of drug given, with LOXO-195 being very well tolerated at lower to moderate doses. The side effects were reversible. “This research shows the value of ... […]
- Is Taking a Legal Smart Drug Stupid? on April 17, 2019 at 11:00 am
However, smart drugs do appear to increase cognition ... much to the alarm of her 75-year-old husband. Another reported side effect is severe headaches, which was clearly something this woman ... […]
- Couple’s Mesa center first in state for drug babies on April 17, 2019 at 9:13 am
Medical officials warned he may have been exposed to drugs during his mother’s pregnancy, but other than that, no resources or information regarding the possible long-term side effects were provided. ... […]
- Ribociclib in advanced breast cancer: Survival advantages, but also severe side effects on April 17, 2019 at 7:29 am
Combination of the drug is not restricted to an aromatase ... outcome category "adverse events", commonly referred to as side effects: Women who had been treated with ribociclib developed severe ... […]
- Depression Drugs Market : Side Effects and Vulnerability to Addiction Create Reluctance among Patients on April 12, 2019 at 7:07 am
FactMR analysis the global depression drugs market for the forecast period 2018 – 2026. The exhaustive study is aimed at recognizing lucrative opportunities available in the global depression drugs ... […]
- Master Your Medicine: How to Ease Your Worries About Side Effects on April 5, 2019 at 6:35 pm
Hearing about potential side effects may make you nervous and cause you to not want ... reaction Or you’re concerned from a family member’s experience with a similar drug. Remember: “Medicines affect ... […]
- Existing drug found to dampen chemo side effects in breast cancer — in a dish on April 5, 2019 at 6:07 pm
Patients with HER2-positive breast cancer face something of a predicament: The most effective drug to treat the cancer is also the most toxic. Trastuzumab, sold under the brand name Herceptin ... […]
- UCI discovery may lead to mitigation of side effects caused by erectile dysfunction drugs on April 5, 2019 at 5:41 pm
In a study published in Science Advances magazine, researchers from the University of California, Irvine have captured, for the first time, the full-length structure of the rod photoreceptor ... […]
- New discovery provides key to side effects caused by erectile dysfunction drugs on April 5, 2019 at 2:30 pm
A new study reveals several features of PDE6 that were previously unseen. Included among them were some very promising regions of PDE6 that resemble fish-hooks and are responsible for controlling PDE ... […]
- Phenotypes associated with genes encoding drug targets are predictive of clinical trial side effects on April 5, 2019 at 4:15 am
Only a small fraction of early drug programs progress to the market, due to safety and efficacy failures, despite extensive efforts to predict safety. Characterizing the effect of natural variation in ... […]
via Bing News