GE Healthcare's recently announced "cellular pharmacogenomics" partnership with the Phoenix, Ariz.-based Translational Genomics Research Institute may show HCS to be a useful tool for genomics-based drug development and eventually, personalized medicine.
The alliance, which is built around GE's IN Cell Analyzer high-content screening platform, is also part of the firm's broader strategy to partner with research institutions that can push its technologies into personalized medicine.
"Applying tools that were previously only used for screening now to genomic profiling and characterization of drug response is probably the most powerful thing we could be doing in terms of improving drug development," Spyro Mousses, director of pharmaceutical genomics and cancer drug development at TGen, told CBA News this week.
"There are very few groups that are combining RNAi, high-content analysis, cell-based screening, and genomics toward drug development," he added. "As we move forward, we hope to generate proof-of-concept results for a systems medicine approach to drug development. Hopefully we will generate this new field of research where you put this effort up front into understanding genetic determinants of drug response, which saves an incredible amount of time, effort, and cost during clinical development."
Mousses said that TGen is not necessarily looking to drive HCS into clinical testing, "but to do this early work to make the later work go faster and cheaper."
GE, meanwhile, is eyeing the clinic, and sees translational genomics as a stepping stone to personalized medicine, Mike Honeysett, manager of strategic alliances for GE Healthcare Life Sciences, told CBA News sister publication BioCommerce Week this week. Its partnership with non-profit TGen is one of several the firm has already established and plans to establish to advance its technologies into personalized medicine.
"We're not trying to focus on any one area, but we're trying to provide technologies that will enable us to get at this common goal … which is personalized medicine," Honeysett said. The TGen collaboration "really dovetails into our key initiatives in working in this space. GE Healthcare has decided that translational medicine, or personalized medicine, is really a key focus for the entire product line going from clinical diagnostics all the way upstream to proteomics and genomics."
Under the partnership, TGen researchers are using GE's IN Cell 1000 and 3000 cell analyzers along with siRNA knockdown to interrogate the human genome and identify and characterize cancer-associated genes that could be used to develop targeted drugs. TGen researchers will use the tools as part of a new strategy for pharmacogenomic development called cellular genomics, or cellular pharmacogenomics, Mousses said.
"This means that we're knocking down genes one at a time in a highly parallel fashion to understand how that knockdown changes the response in a living cell," he said. "Rather than just trying to make an association between the expression of a gene and drug response, we're knocking a gene down and asking whether the cancer cell is more sensitive or more resistant to a particular cancer drug."
Mousses said TGen has been using an IN Cell 1000 for approximately one year and is now using the 3000, as well. "The data that we're getting out of the IN Cell 3000 is in many ways superior," he said. "It's faster, but it's not just speed. We're getting better signal to noise, and it's allowed us to take high-content analysis to a very industrial level, where we can do millions of measurements rather than thousands."
Both GE and TGen view the collaboration as a true partnership, not just a traditional vendor-customer relationship. As such, GE stands to benefit from TGen's input about what does and doesn't work with regards to genomics-based drug screening.
"Hopefully we will generate this new field of research where you put this effort up front into understanding genetic determinants of drug response, which saves an incredible amount of time, effort, and cost during clinical development."
"Our alliance with GE has been largely not just to do things better and faster, but to develop new applications for high-content analysis," said Mousses. "Being able to knock down genes and genomics [applications] are a little different than the intended applications for these instruments."
According to Honeysett, TGen has "provided us with some tremendous feedback, which our software engineers in particular have been able to respond to." Asked if GE would own the rights to any discoveries made during the collaboration, he said, "We're providing the hardware and technical infrastructure to do the analysis, and naturally if we develop any, say, software tools, for example, that enable TGen to get to their answers … in certain instances we would own the IP. In other instances they would own the IP, and of course in a final scenario we would share the IP."
Honeysett said the collaboration with TGen is similar to ones the firm recently established with an undisclosed Canadian cancer research center and the California Institute for Quantitative Biomedical Research. He said that under the collaboration with QB3, GE is providing tools for genomic, proteomic, and high-content screening applications, as well as an MRI machine, with the goal of moving discoveries into the clinic. He also said GE plans to pen additional collaborations like these.
TGen had many options for choosing high-content analyzers, including instruments sold by GE Healthcare rivals Fisher Scientific's Cellomics unit, BD Biosciences, Evotec, and Molecular Devices. Although these firms have been competing to shave off a few dollars here and there from the cost of these platforms, none of the options is cheap, at least by non-profit standards.
Mousses conceded that point, but also said that TGen benefits from multiple drug-discovery collaborations with industry.
"We're a private non-profit, but we're working in drug development, and we have collaborations with a lot of large pharmaceutical companies," he said. "Our focus is very much on improving drug development across the board, and we run very large genome-wide projects, or look at multiple drugs, concentrations, and cell lines, so you can imagine the number of high-throughput RNA screens. Let's just say we run a lot. We found ourselves limited by the speed of high-content analysis, and we really needed to move into this next phase."
GE Healthcare does not disclose pricing for the IN Cell 3000, but according to various customers, the lower-end IN Cell 1000 costs approximately $450,000. Evotec has said that its Opera, which is comparable in performance to the IN Cell 3000, can cost as much as $855,000 for a fully equipped version, and Molecular Devices has said it aims to sell the "fully loaded" version of its ImageXpress Ultra confocal imaging system for just under $500,000, while less equipped models — for example, those with fewer lasers — may sell for less.
Mousses said a combination of factors led TGen to choose GE. "We found them to be very progressive and innovative — very good partners," he said. "I don't want to compare to anyone else, but in terms of the quality of images, the speed, and the software, it's just outstanding. I think the other thing is that they are really committed to this field, and we wanted to work with someone who was going to be around for a while."
Honeysett said GE tries "to put systems in place that are long-term and sustainable for both companies. The vision is so solid with TGen. I could see this [collaboration] going out many, many years."