Personalized medicine — a second megatrend affecting automation and robotics in Life Sciences — employs diagnostic testing to help select the most appropriate therapy based on the genetic makeup of an individual patient. It's being driven by a combination of multiple technology innovations that are now colliding to change the potential future of medicine.
What are the technology enablers?
Along with precision automation and robotics, Big Data is a foundation technology enabling the personalized medicine megatrend. Big Data refers to the collection and use of data sets that are so large that, just a few years ago, they were impossible to manage with traditional computing and data processing applications. Because personalized medicine requires the processing and storage of huge data sets, a prerequisite was cost effective Big Data capability.
What are the technology drivers?
We are quickly approaching and surpassing the global target of $1000 to sequence an individual’s whole genome. This change brings the cost to a level where it is becoming possible to understand an individual’s genetic makeup to predict their responsiveness to certain drugs and therapies, allowing the best individualized care.
Precision motion is integral to the sequencing process and is one of the key factors in the parallel processing that has radically reduced costs. Robotics are helping the drug discovery process keep pace through around-the-clock research. Without this level of automation, scientists are hampered by manual testing. Today’s automated high-throughput screening is granting scientists access to an abundant amount of data—with little to no manual interaction.
One technology transformation on the horizon is patient specific cellular therapy. Because manufacture of patient specific cellular therapy is a discrete process compared to the batch manufacturing processes typically employed in pharmaceutical manufacturing environment, it will drive a mindset change from “scale up” (increase batch sizes) to “scale out” (increase capacity at the bottleneck).
What specific changes will personalized medicine require in instrument and automation design?
Automation and 24/7 processing have created an environment where personalized medicine is becoming commercially viable for the masses. Broader use of whole genome sequencing for individuals and continued development of drugs proven effective for particular genetic dispositions will continue to accelerate this trend.
Modularity and scalability really mean lean automation, which is a prerequisite for personalized medicine. In lean automation, instruments run unattended with some level of operator load and unload. This minimal level of operator intervention keeps capital costs to a minimum and makes increasing capacity a simple matter of adding another instrument to the system.
When operating around-the-clock, mean time between failure (MTBF) is critical in today’s laboratory robotics, especially in remote locations that may not have onsite maintenance teams. The ability to leverage industry proven designs that have thousands of hours of operation greatly reduces the risks associated with a new design.
Precision is another critical element at the solution level and is very specific to application requirements. Micron and nano levels of precision are enabling factors in specific personalized medicine applications such as DNA sequencing, digital pathology, and live cell imaging and manipulation.
This post continues our series focusing on the drivers of robotics and automation in Life Science and how the market is changing. The series digs into three megatrends that are transforming when, where, and how automation and robotics are being used across the Life Sciences.
The final part in our series on megatrends will be posted next week. If you missed the first part, which focused on the demographic changes driving increasing demand, you can find the link below.
Article contributed by Brian Handerhan, business development manager for Parker Hannifin Corporation, Electromechanical Division North America, Automation Group.