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Feb 1, 2011 (Vol. 31, No. 3)

Cell-Based Assays Move to Fore

Cell Quality, Growth Environment, and Analytical Capability Upgrades Are All Being Pursued by Companies

  • Cell and Substrate

    Heisenberg’s uncertainty principle states that the very process of measuring something necessarily alters it. The biological corollary is perhaps that the less manipulation done to a system, the more likely a cell-based assay will reflect what goes on in vivo.

    SRU Biosystems uses its label-free BIND technology to detect the interaction between cell and substrate. “Any contact the cell has on the sensor surface, any increase in cell adhesion with the sensor surface, causes the wavelength of light that reflects back off the surface of the sensor to shift in the positive direction,” explained Shamah. “We measure that shift.”

    Cells either change their adhesion or undergo morphological changes as “responses to a variety of different classes of receptors and stimuli, like G-protein-coupled receptors, receptor tyrosine kinases, things that activate certain classes of ion channels, just to name a few.”

    The BIND Reader allows for high-throughput snapshots of an entire 96-, 384-, or 1,536-well plate—a 384-well plate can be read in 15 seconds. And because cells are not modified or perturbed by labeling, Shamah noted, it can also document real-time kinetic responses to stimuli as well.

    SRU Biosystems plans to introduce the BIND Scanner, capable of imaging at a resolution of about 4 microns per pixel, in Q1. It allows cells plated at low densities, or in mixed populations, to be followed individually as they respond to different stimuli.

  • Online Analysis

    For those focused more on the visual, Wimasis offers online analysis of optical cell-based assays without the need to buy hardware or install software. “We provide image-analysis algorithms that are available through a web-based analysis system,” says CEO and co-founder Kilian Schramm. “You receive the analysis results automatically, without the need of parameterization or adaptation to your specific needs, enabling an objective comparison through your different lab hardware setups.”

    Wimasis currently offers analyses in several different areas, including angiogenesis and cell migration, and is developing others in apoptosis, autophagy, and chemotaxis. Wound-healing parameters, for example, include currently cell covered area, speed of closure, and acceleration characteristics determined from a time-lapse image series.

    The company also works with researchers, companies, and institutions to customize algorithms to their specific needs. Suppose there’s a multisite clinical trial, for example. “We develop an intuitive analysis setup that can detect what needs to be detected and we develop a metric system that quantifies those objects correctly—maybe in size, in shape, in amount of pointy tube-like edges, which indicates a metastasis building, and so on,” Schramm explained. “Basically, anything in the image you can see we can quantify as well.”

    Wimasis’ cloud-computing platform utilizes a fully scalable architecture in parallel, allowing it to handle a nearly unlimited number of images in almost any still photo format, Schramm said, nearly in real time. He expects the system to be able to accept actual movie formats beginning in Q2, 2011.

  • Decision Analytics

    Once the data is generated and crunched, then what? Can we accurately rank our compounds? Do we have confidence in that ranking?

    SimuGen’s raison d’etre is to include a third stage after biological modeling and data modeling—which Wills calls “decision modeling.” Its web-based algorithms are designed to be agnostic: To seamlessly combine into a single model gene and protein-expression data, cell viability and impedance assays, and high-resolution microscopic imagery, for example, “in an easy way that everybody can understand, and in a way that helps us make a decision,” he explained.

    Researchers can implement their own model, utilizing their favorite cell types, assays, and endpoints. The software allows researchers to combine those into a screen that can be sold or used in-house.

    Others may want to utilize SimuGen’s own models, currently focused on six major liver toxicity endpoints. “Liver is by a long stretch the biggest reason for drug failure on the market,” noted Wills. Experiments can be performed in-house, or by the company’s service partners, and then analyzed for six different endpoints.

    The software will perform quality control and will rank the chemicals, showing which toxicities are occurring and at what concentration toxicity begins to occur, he explained. “It will then also show you at a global level how all the chemicals are looking relative to each other, so that you can start spotting patterns of chemicals that are behaving similarly in terms of their toxic profiles.”

    The latest version of SimuGen’s software, Wills said, includes the ability to weight models—for example, downgrading certain endpoints relative to others. “Phospholipidosis should be far less of a flag compared with carcinogenesis.” This version also allows thresholds to be included. If blood levels of a compound aren’t likely to be seen at greater than 10 micromolars, “as a rule any toxicity we pick up at 100 micromolars is really irrelevant.”


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