When Predix Pharmaceuticals merged with Physiome Sciences in August, Physiome’s flagship modeling technology was basically swept under the rug: Predix said it planned to use the company’s substantial cash holdings to move its first compound into clinical trials, and that while it planned to retain Physiome’s ion channel modeling technology, it had not yet decided on the fate of the rest of the company’s intellectual property [BioInform 09-01-03].
It turned out that Predix didn’t have to look very far to find a new home for Physiome’s remaining technology assets. In early October, G. Scott Lett and Dean Bottino — formerly director of software development and senior modeling scientist at Physiome — arranged for their new firm, the BioAnalytics Group, to license from Predix key technologies that they helped develop under Physiome.
The licensing agreement includes Physiome’s PathwayPrism, CardioPrism, and CellEditor software, as well as around 80 biological simulation models, and the transfer of ownership of several pending patents for technology developed by Lett and his colleagues [see box, below].
But Lett, president of the BioAnalytics Group, said his new company doesn’t plan to build a neo-Physiome around the newly acquired technology. Rather, it will merge Physiome’s software with a technology platform it has been developing called Model-Based Assays, which simulates biological systems within the context of experimental protocols for cell-based assays and other platforms.
The idea for the Model-Based Assays approach sprouted while Lett and Bottino were still at Physiome. “We knew the budgets in the pharmaceutical industry were less around in silico technologies, and more around doing the experiments and gathering the data … We also knew that Physiome had been really challenged in identifying what would inspire the pharmaceutical industry to take advantage of what simulation promised to do for them,” Lett said.
Lett and Bottino began developing the Model-Based Assay technology around a year ago, “knowing that we might very well be spinning it out, and even starting to set up new branding that could be spun off from Physiome, or whatever they became,” Lett said. Licensing talks began with Predix before the merger, he added.
Moving the Modeling Upstream
Physiome’s approach required potential pharmaceutical and biotech customers to place a great deal of faith in the predictive power of biological simulations, and few drug discovery firms were willing to place their bets on the still-unproven technology, Lett said. By taking a few steps back up the pipeline, and coupling the modeling technology with the experimental process, however, “it suddenly becomes a tool that scientists in the laboratory can use on experiments that they’re already doing,” Lett said. “Physiome was saying, ‘Here’s an area where you should start experimenting because the simulations suggest that it’s a good therapeutic or a good idea for treating a particular disease.’ Now, instead of guiding the entire drug discovery process, it’s helping with specific steps in that process.”
The BioAnalytics Group is currently in discussions with a number of potential customers for collaborations based on its simulation-assisted experimental methodology. The company also plans to approach cellular assay instrumentation companies and contract research labs that might be interested in adding Model-Based Assays to their own technology portfolios. Lett said that the company already has several paying customers, but none that it can disclose.
In another departure from Physiome’s business model, Lett said that the BioAnalytic Group has relaxed the terms of its collaboration agreements in order to make it easier for customers to do business with them. While Physiome sought a share in any intellectual property or biological discoveries that arose from its collaborations, the BioAnalytics Group has tried to simplify that, “so we’re not trying to take a chunk out of the customer’s intellectual property,” Lett said.
In addition to Lett and Bottino, the BioAnalytics Group currently employees three people who are working under contract on specific projects. The company is self-funded, and so far supported solely by customer revenues — another departure from its first incarnation. Physiome, which raised more than $60 million in venture capital funding since it was founded in 1994, was unable to justify that level of investment due to the small potential customer base for its technology, and found discovery firms reluctant to sign off on the seven-digit deals it required to keep its investors happy.
“There are two things that the whole in silico industry had to face, and one of them is that there’s a natural growth rate, and no amount of throwing venture capital at that can change that,” Lett said. In addition, he said, “the growth rate depends on identifying real-world problems that can be solved … So that really means changing the model from something that may bear fruit twelve or thirteen years in the future to something that can bear fruit now.”
Lett said that he’s confident that the BioAnalytics Group’s expanded technology platform and revamped business model will help it overcome the challenges that Physiome faced in the marketplace, and credited his former employer for blazing the path that his new venture is now following — in the company of a growing number of competitors. “Now we have a more educated market to work with, and we’re more educated on what things slowed down doing deals, and what size business is possible over the next one year or two years,” he said.
In Silico, In Limbo: Physiome Sciences’ Pending IP Portfolio
The BioAnalytics Group is currently in negotiations with Predix Pharmaceuticals to acquire Physiome’s pending patents. The following patent applications list Physiome Sciences as their assignees and G. Scott Lett as inventor or co-inventor:
US Patent Application 20030033127. Automated hypothesis testing. Inventor: Gregory Scott Lett.
Protects a method and system for automatically constructing computer simulation models of biological systems in which a series of simulation models are created, or selected from a repository of standard models, preferably based on experimental data. The models are then calibrated, based upon experimental data, and then compared to each other for goodness of fit to a set of experimental data.
US Patent Application 20030018457. Biological modeling utilizing image data. Inventors: Gregory Scott Lett, Dean Bottino.
Covers a method and system for quantitative and semi-quantitative modeling of biological and physiological systems using time-series image data to improve the accuracy of the predictions made by a simulation model that forecasts the spatiotemporal evolution of a biological or physiological system.
US Patent Application 20030009099. System and method for modeling biological systems. Inventors: Gregory Scott Lett, Haoyu Yu, Jian Li.
Protects the use of a component-based architecture for biological modeling software that enhances the extensibility of the software and the reusability of the software components.
US Patent Application 20020091666. Method and system for modeling biological systems. Inventors: John Jeremy Rice, Gregory Scott Lett.
Protects a method and system for quantitative and semi-quantitative modeling of biological and physiological systems that uses overlays to store and manipulate computational biological models.