Formula 1 know how speeds up clinical drug tests and toothpaste manufacturing

During each of the 19 F1 Grand Prix races held in cities worldwide each year, McLaren engineers use continuous telemetry, or wireless telecommunication systems, to monitor cars streaking around tracks at speeds up to 220 mph in all kinds of weather. They gather information on everything from aerodynamics, fuel consumption, road conditions and tyre life. Those pieces of data are then streamed to McLaren’s servers back in Woking, suburban London, and fed into an algorithmic model that can instantly run thousands of possible scenarios and spit out predictive intelligence that its trackside crew uses to make super-fast decisions—when to schedule a pit stop, for instance—in races where milliseconds rule.

The main focus of the McLaren Applied Technologies (MAT) division is selling this ability to capture vast amounts of data in real time, feed it into models and run simulations that can be used to solve problems, aid decision making, design products and increase efficiency, all at blinding speed. McLaren’s expansion into applied technologies was instigated five years ago by Ron Dennis, McLaren’s chairman and CEO. In the decades since it was founded in 1968, McLaren has amassed technical expertise in the many areas required to keep complex race cars running as efficiently and safely as possible. Dennis wondered, Why not market that trackside-honed know-how to other industries? So McLaren is now applying its technological expertise—in areas that include exotic materials, aerodynamics and electronics—in sectors far removed from motor sports, ranging from health care and public transportation to data centers and oil-and-gas exploration.

This type of real-time data monitoring and response could have a tremendous impact on one of the biggest choke points in the drug development processes: testing efficiency. Patients in clinical trials for new drugs usually have their vital signs checked every few weeks or so, when they visit their doctor. Data collected at checkups are used by manufacturers to determine the efficacy of the drugs. It’s an inherently slow process: Many months are needed to gather enough patient data to be useful. It’s also a big reason why it usually takes 10 long and costly years to bring a drug to market after it’s discovered.

But that doesn’t mean the process can’t be improved. Last year, consultants McKinsey & Co. urged U.S. drugmakers to make better use of big data—for instance, to improve clinical trials or to model biological processes—claiming it “could generate up to $100 billion in value annually across the U.S. health care system.”

McLaren and the British multinational pharmaceutical company GlaxoSmithKline (GSK) are attempting to answer this call with a big-data experiment using a technology called “biotelemetry.” McLaren has customized the telemetrics technology that studies the “health” of its race cars to measure 24/7 the vital signs and mobility of patients involved in drug trials—in this case for arthritis and stroke-recovery therapies—so researchers can determine more quickly if a drug is or isn’t working, or is causing troubling side effects. If a trial needs to be stopped or altered, the faster that’s known, the more it saves time and money—and the more it can help patients. “Speed is a real imperative for [patients],” says Steve Mayhew, GSK’s head of research and development strategy, since some new drugs, like cancer therapies, might prolong lives by months and years.

Moreover, says Geoff McGrath, vice president in charge of MAT at McLaren, data streamed from patients in real time are a much richer source of intelligence than vital stats taken every few weeks at a doctor’s office. “When [a patient] goes to a clinic, it’s not really a real-world test.”

Now imagine applying the consistent efficiency of an F1 pit crew to a team of workers that runs a toothpaste manufacturing line. As improbable as that sounds, that’s what happened when GSK also began working with the McLaren Group to help it cut production times at its Sensodyne toothpaste plant in Maidenhead, England.

Formula One race cars barrel into the pit lane, decelerating rapidly from around 200 mph in the track to 50 mph in the lane, just before stopping in front of a 20-man team standing and squatting at the ready. Instantly, the team springs into its well-rehearsed and elaborately choreographed routine, and in just about 2.3 seconds, it’s done: four tires removed and replaced, the car ready to streak back onto the track. Sneeze and you miss it. To carry out this complex choreography with the speed and precision of an atomic clock clearly requires some serious planning.  After each stop, the team holds a debriefing session, going over what went right and what could have been improved.

McLaren engineers applied their pit stop processes initially to one production line. They grabbed data from the line’s machines, fed it into a model and ran simulations. They discovered that one of the biggest bottlenecks was changeover time—stopping the line to make a product change, say, to a different flavor—which took around 39 minutes. The line’s workers were then tutored in the kinds of time-saving procedures developed by McLaren pit crews. And they worked. The line’s downtime was halved, enabling it to boost production by nearly 7 million additional tubes a year.That’s why, this year, GSK will roll out McLaren-derived efficiency procedures at its consumer product manufacturing plants worldwide, beginning in three of its eight global regions: the U.S., U.K. and Spain.

 Source: News Week

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