--- title: Health Workers See Promise in Software for Drug-Resistant Bacteria description: New software may predict genetic changes in bacteria before they occur canonical: https://time.com/3653464/software-antibiotic-resistance-research/ author: Alexandra Sifferlin article:opinion: false article:content_tier: free article:published_time: 2015-01-05T15:22:51.000Z article:modified_time: 2026-08-04T08:00:07.325Z article:section: Health og:title: Health Workers See Promise in Software for Drug-Resistant Bacteria og:description: New software may predict genetic changes in bacteria before they occur og:url: https://time.com/3653464/software-antibiotic-resistance-research/ og:site_name: TIME og:image: https://static.time.com/v3/assets/bltea6093859af6183b/blt63851736629d5abf/69877812f887dc0908e89525/173299384-copy.jpg?branch=production&width=1200&quality=75&auto=webp&crop=16:9 og:image:width: 3646 og:image:height: 2051 og:image:alt: 173299384 og:type: article twitter:card: summary_large_image twitter:title: Health Workers See Promise in Software for Drug-Resistant Bacteria twitter:description: New software may predict genetic changes in bacteria before they occur twitter:image: https://static.time.com/v3/assets/bltea6093859af6183b/blt63851736629d5abf/69877812f887dc0908e89525/173299384-copy.jpg?branch=production&width=1200&quality=75&auto=webp&crop=16:9 ---  # Health Workers See Promise in Software to Tackle Drug-Resistant Bacteria > Sponsored content. 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Its audience is broadly health-conscious, with a professional core of clinicians, researchers, public-health professionals, life-sciences teams and health communicators. ### Sources * TIME Newsletters: [time.com/newsletters](/c/time-nl-health-2026q3/newsletters?i=7dd9d6dc-8ca6-4f3a-8d60-6e867153715c&cr=time-nl-health-2026q3-v1) ## Video: This Flu Shot Is Not Like the Others [Watch (HLS stream): This Flu Shot Is Not Like the Others](https://cdn.jwplayer.com/manifests/1thSi60s.m3u8) (2:09)  _Published 2014-10-30. Some people may get a new flu shot that’s made with dog cells instead of chicken eggs_ by [Alexandra Sifferlin](https://time.com/author/alexandra-sifferlin/) ## Alexandra Sifferlin Jan 5, 2015 3:22 PM UTC  MRSA bacteria, artwork MRSA bacteria, artwork Getty Images by [Alexandra Sifferlin](https://time.com/author/alexandra-sifferlin/) ## Alexandra Sifferlin Jan 5, 2015 3:22 PM UTC Researchers have developed a new software that predicts changes in bacteria that can make them drug-resistant. Drug resistance happens when disease-causing bacteria adapts to antibiotics and becomes less responsive to treatment. Antibiotic-resistant bacteria [cause](http://www.cdc.gov/drugresistance/national-strategy/) at least 2 million infections and 23,000 deaths in the United States each year, but because the bacteria are constantly reproducing, it’s hard to determine what changes and mutations will occur. Concern about drug resistance has caused doctors to prescribe bacteria-killing drugs more sparingly. Now a team of researchers at Duke University may have alighted on a solution. In a recently published [study](http://www.pnas.org/content/early/2014/12/31/1411548112) in the journal _Proceedings of the National Academy of Sciences,_ the researchers’ software, OSPREY, was able to predict the most likely mutations to come out of certain bacteria. Researchers were able to then test treatment with drugs that are still in the experimental phase. Identifying the most likely mutations while drugs are still under development, the team believes, means the medicine is better positioned for success when it hits the market. “If we can somehow predict how bacteria might respond to a particular drug ahead of time, we can change the drug, or plan for the next one, or rule out therapies that are unlikely to remain effective for long,” said study co-author Pablo Gainza-Cirauqui [in a statement](http://www.eurekalert.org/pub%5Freleases/2015-01/du-psc010215.php). The scientists looked specifically at a common drug-resistant bacteria called methicillin-resistant Staphylococcus aureus, or MRSA–a common cause of infections in health care settings like hospitals. They used their software to successfully predict that genetic changes that would occur in the bacteria when treated with drugs. The researchers are now testing their software on other bacteria, but have made the software open for use by any researcher. The hope is that with time and practice the software algorithm will be able to predict genetic changes more than one mutation ahead. ## Transcript [ MUSIC ] This year, your annual flu shot might be more high tech than the ones you've had before. For decades, flu shots could only be made with the help of hundreds of thousands of chicken eggs. Scientists grew the influenza virus in the chicken eggs. Then purified and modified it to go into the flu vaccine. But that process took months for the virus to grow. In 2012 the U. S. Food and Drug Administration approved an entirely new way of making flu vaccines. Bypassing chicken eggs altogether and using animal cells instead. The Novartis Plant in Holly Springs, North Carolina is the only facility in the U. S.. Approved to produce a cell culture- based flu vaccine known as Flucelvax. This Influenza vaccine is grown using cells from dog kidneys. And the process is much faster. Taking 65 to 75 hours. Compared to the months it took to grow with [ UNKNOWN ] [ MUSIC ] The process begins with growing enough kidney cells to serve as the viruses incubators. Over 20 days the cells are put into a culture that encourages them to divide rapidly. And as the cells grow in number they are moved into increasingly larger vats. They start out in 5 liter. Containers and end up in a 5000 liter tank. Once there, the cells are infected with the flu virus. These samples of virus arrive frozen and are chosen each year by the World Health Organization in the spring. They determine which flu strains they believe will be circulating later that year. Year. After the cells produce enough virus, the viral particles are strained out, purified, and treated so they can't actually cause flu but can still alert the immune system to mount a response against the virus. 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