A recent white paper from the US Food and Drug Administration urging drugmakers to adopt new technologies could spark a biosimulation boom, according to Mikhail Gishizky, chief scientific officer at Entelos.
Gishizky told BioInform that the white paper, “Innovation or Stagnation — Challenge and Opportunity on the Critical Path to New Medical Products,” which the FDA released in March, has spurred a new level of interest in Entelos’ technology — particularly from prospective customers who had been reluctant to use the company’s PhysioLab biosimulation platform. Previously, “all of our contacts said this is really cool, really interesting, but we’re not quite sure how to apply it, and where it could make immediate impact in terms of dollars and cents,” Gishizky said. “But now with the FDA coming out and saying that they encourage companies to include modeling and simulation data in their [drug submission] packages, it certainly has changed pharma’s perspective and added a greater imperative to bring in additional, new technologies.”
The white paper (available at http://www.fda.gov/oc/initiatives/criticalpath/whitepaper.pdf), does not bear the same weight as a guidance document, but signals the FDA’s willingness to consider new technologies and data sources in order to speed the drug approval process. The paper cites “computer-based predictive models” among a number of new methods that should be included in pharma’s “new product development toolkit” — more than ample encouragement for proponents of the approach. Scott Lett, president of the BioAnalytics Group, another biosimulation firm, told BioInform that his company has also seen a marked rise in interest since the paper was released. “Some of our customers and prospective customers have actually sent a copy to us and told us that they were using it internally,” Lett said. Colin Hill, CEO of Gene Network Sciences, also views the white paper as a positive sign, but expressed a bit more caution in his assessment. The FDA’s recognition of computational systems biology “is clearly a factor in the increased deal flow that we’ve been seeing, but I can’t see it as a smoking gun,” he said. Hill noted that any regulatory policy the agency might be planning in the area could take months or even years to finalize, and even then would require time to “percolate” through the industry. “It would be great if they would mandate the need for simulation next week, but I don’t see that happening,” he said.
But having the FDA in its corner — even indirectly — couldn’t come at a better time for Entelos. Gishizky said the company is in the early stages of creating an in-house drug development program in an effort to expand its business model beyond the platform-based collaborations it has relied on since it was founded in 1996. Gishizky, formerly vice president of discovery at Pfizer, joined Entelos last November. One of the primary reasons he was brought on board, he said, “was to evolve [the company] beyond just the collaborative service model, [to] be a biotech company of our own. So we’re using our technology to help us screen in-licensing opportunities for compounds.”
Gishizky said that this effort is still “developing” within the firm, and is based on its PhysioLab models for metabolism, rheumatoid arthritis, asthma, and HIV. The plan, he said, is to start with a target, and use the simulation platform to predict the precise pharmacological characteristics that a compound would require. “We can ask specifically how long we need to affect that particular target, what type of dosage schedule do we have to have to get efficacy in a given patient population that eats three meals a day, when do they have to be dosed, what are the pharmacological profiles — so we really lay out the exact criteria that our compound has to fit into,” he said.
Entelos is currently working with several contract research firms in an effort to in-license promising compounds that meet its criteria for given targets. While acknowledging that the move to drug development carries the risk that collaborators will view Entelos as a potential competitor, Gishizky said that customers “may also view us as an opportunity to lay off some of their own risk” and “cherry-pick” the most promising compounds that Entelos validates for Phase II and Phase III trials. “Realistically, for a small company to take on an in-licensing opportunity and drive it all the way through FDA approval — in particular in an indication like metabolic syndrome — that’s not financially possible. So you’re going to have to partner it out,” he said.
Entelos is not looking to seek additional funding to support its in-house development programs in the immediate future. The privately held company has raised more than $45 million in three rounds of financing since 1996, and is “very financially stable,” Gishizky said.
Entelos also plans to extend the application of PhysioLab further downstream in the drug development pipeline — to Phase III and Phase IV trials. Gishizky said that the company’s growing foothold in pharma R&D has served as a solid jumping-off point for downstream applications. “It took the company a while to gain respect and credibility in the discovery area before being able to transfer that credibility to marketing and clinical trials,” he said, adding that these later-stage applications are where the “big money” is in the development process.
Gishizky said that PhysioLab’s capabilities would not change dramatically for downstream applications, but the platform would be used to answer a different set of questions. In discovery, for example, he said that typical questions might focus on whether a target is involved in a disease process, whether it is necessary to inhibit the target to get a clinical effect, and what the potential toxic effect of inhibiting the target might be. In Phase IV, however, “the question is, ‘Do I have an advantage over my competitor in this space, does my drug give me a differentiation or a strategic advantage, or can I leverage my drug into another indication?’” Gishizky said that biological modeling won’t replace clinical experimentation in answering these questions, but it can be used to reduce the time and expense required for designing the experiments to do so.
Gishizky said that Entelos’ Phase IV collaborators “want to keep things confidential for now,” so he was unable to provide further details on the company’s work in this area.
The expansion of its efforts into in-house development and late-stage trials, however, doesn’t mean that Entelos is turning its back on its core business model. On June 5, Entelos announced that it had extended its collaboration with the American Diabetes Association to use PhysioLab to build a model for type 1 diabetes. The agreement builds upon a two-year partnership between Entelos and ADA to build a model for type 2 diabetes — a model that Johnson & Johnson has already used to predict the proper dosage for a Phase I clinical trial.
Under the new agreement, Entelos and ADA will build an in silico model of the non-obese diabetic mouse, which should be completed in about a year, Gishizky said. So far, Entelos has built a solid customer base around similar models for obesity, asthma, and rheumatoid arthritis, with a client list that includes AstraZeneca, Aventis, Bayer, Bristol-Myers Squibb, Johnson & Johnson, Organon, and Pfizer.
Gishizky said that he joined Entelos “at a very opportune time in that initially they had a problem gaining acceptance, and the adoption curve was very shallow.” However, he said, slow but steady progress over the last several years — coupled with the FDA’s recent blessing in the white paper — has positioned the company for a new era of growth. In pharma, he said, “you’re kind of trained to do what has been successful in the past, and not necessarily take a high risk” — a cultural quagmire that has hampered the acceptance of biosimulation. “Getting people in the door to really open their minds and try it out is a big hurdle,” he added, “and that’s why the FDA white paper really helps break through that ice.”