Makers of first ALS drug in 22 years announce availability
JERSEY CITY, N.J. — The first drug for ALS approved in 22 years is now available. Mitsubishi Tanabe Pharma America this week announced the introduction of its Radicava (edaravone), an intravenous treatment for ALS that the Food and Drug Administration approved on May 5.
“After 13 years of clinical research and investment, we have reached a seminal moment, which may shift the treatment paradigm for this terrible disease," Mitsubishi Tanabe Pharma America chief commercial officer Tom Larson said. “As of today, all across the country, conversations between ALS specialists and patients may be substantially different. We are all extremely proud and excited to be a part of bringing Radicava and new hope to patients in the U.S.”
In clinical trials, 33% of patients treated with Radicava showed a lower rate of decline in the loss of physical function, compared with those on a placebo. Currently, between 5,000 and 6,000 patients are diagnosed with ALS every year.
"This new treatment may give hope to every person suffering from ALS, and we pray the positive result from this trial will set the tone for more therapies going forward. We all remain committed," said Dr. Jonathan Katz, ALS Clinic Director of the Forbes Norris MDA/ALS Research and Treatment at California Pacific Medical Center.
Pharmacy efficiency among 5 ways Walmart uses big data
BENTONVILLE, Ark. — Walmart is bullish on big data — especially when it comes to finding ways to better serve its shoppers.
Big data volume continues to grow, but Walmart is using it to the company’s — and its customers’ — advantage. By analyzing the robust information flowing throughout its operations, the discounter has gained a real-time view of workflow across its pharmacy, distribution centers, stores and e-commerce, according to a company blog.
Here are five ways that Walmart is using big data to enhance, optimize and customize the shopping experience:
1. To make Walmart pharmacies more efficient. By analyzing simulations, the discount giant can understand how many prescriptions are filled in a day, and determine the busiest times during each day or month. Big data also helps Walmart schedule associates more efficiently, and reduce the time and labor needed to fill prescriptions.
2. To improve store checkout. While it is still only testing the process, Walmart is using predictive analytics to anticipate store demand and determine how many associates are needed to man registers. The data also reveals the best form of checkout at each store: traditional stations or self-checkout.
3. To manage the supply chain. The company uses simulations to track the number of steps from the dock to the store. The result: more optimized routes to the shipping dock. The strategy also pinpoints the number of times a product gets touched along the way to the customer. Big data also reveals transportation lanes and routes for the company’s fleet of trucks. This insight helps Walmart keep transportation costs down and more accurately schedule driver times, according to the blog.
4. To optimize product assortment. By analyzing customer preferences and shopping patterns, Walmart can optimize how to stock shelves and display merchandise. Big data also provides insight into new items, discontinued products and which brands to carry, the blog said.
5. To personalize the shopping experience. By analyzing shopper’s preferences, Walmart can develop a more consistent, tailored shopping experience. If a customer is shopping for baby products for example, Walmart can use data analytics to anticipate their needs then create personalized mobile rollback deals for these shoppers.
Whether it’s analyzing the transportation route for a supply chain or using data to optimize pricing, big data analytics will continue to be a key way for Walmart to enhance the customer experience, according to the company.