By Vivien Marx
The French government's tech transfer and funding agency OSEO is funding a public-private consortium that aims to adapt a data-management strategy commonly used in the manufacturing industry to the life science sector.
The five-year project, called BioIntelligence, will be coordinated by French industrial firm Dassault Systèmes and will bring together pharma firms, software companies, and academic and government research labs to adapt product lifecycle management, or PLM, tools for use in the life sciences.
In a mid-June announcement, OSEO said the stakeholders will create a computing environment called BioPLM that will be applicable to drug discovery and development as well the cosmetics and personal care industries.
The idea is to apply product lifecycle management approaches to the life sciences, which are facing "growing complexity" in research, OSEO said.
OSEO has contributed €46.3 million ($64.8 million) to the project's total budget of €118.2 million ($165.4 million). Of the OSEO funding, €14.5 million, including €6.4 million in "repayable advances," will go to Dassault, while bioinformatics firm Sophia BioSystems will receive €12.9 million, €7 million of which will be in repayable advances.
The funding level and the reputation of the participants "amply demonstrate the project's ambitions," Thierry Bur, IT project manager of the OSEO strategic innovation program, told BioInform via e-mail.
In addition to Dassault and Sophia BioSystems, other BioIntelligence partners include the French pharmaceutical firms Ipsen, Pierre Fabre, Servier, Sobios, Aureus Pharma, and Bayer CropScience; and scientists from the government agencies Genopole, the French National Institute for Research in Computer Science, and the French National Institute for Health and Medical Research. The funding amounts the other participants will receive were not disclosed in OSEO documents.
Dassault Systèmes, which was spun out of Dassault Aviation in 1981, is active in a range of vertical markets, including automotive, aerospace, industrial equipment, and the life sciences. Its focus is on developing software platforms to help companies manage data and computationally adapt their logistics along the product development pipeline.
Patrick Johnson, head of research at Dassault, told BioInform that the life science market is still a relatively small area for the company, and its activity in that area to date has mainly been in the medical devices sector.
However, the firm sees the market as a promising opportunity. Noting that R&D spending in healthcare is larger than automotive and aerospace added together, he said, "our customers are the R&D spenders, not the IT spenders," because they focus on optimizing research.
Johnson said that several pharma companies whom he declined to identify have already approached Dassault because they were "curious to see" how the firm could help them.
BioIntelligence is "important" to Dassault, he said, but declined to disclose the size of the company's project team. The firm has 7,500 employees worldwide and reported €1.3 billion in revenues for full-year 2008.
BioIntellligence envisions BioPLM as a platform that will integrate new and existing software developed collaboratively by partners in the consortium. The life science researchers in the consortium will "challenge" that environment, test it, and help it evolve, Johnson said. The hope is that the platform will be adopted in the pharmaceutical industry, he said.
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Academic researchers affiliated with the project, who are working on a variety of "hard computer science topics," such as ontology mapping and algorithm development, will be able to plug in any desired software through application programming interfaces, Johnson said.
"We will also support external standards, not ours, to allow other people to plug [their applications] into the platform," he said, citing as an example World Wide Web Consortium standards.
As BioIntelligence participants set out to develop BioPLM, the idea "is to revisit and rethink some of the foundations in PLM to make them relevant and useful for life sciences," Johnson said.
Part of the work will involve adapting elements of Dassault's PLM solutions.
Johnson likened the evolution of PLM from a linear tool to "a spiral, along which everyone has a voice." Just as manufacturing is changing to include iterative steps and feedback loops on the way to a fully developed product, so, too, is the life sciences, and each sub-discipline — such as bioinformatics, chemistry, genomics, and transcriptomics — will be able to integrate its vocabularies and process, Johnson said.
The first part of BioIntelligence involves pinpointing interaction points between research teams throughout the discovery pipeline, tasks his firm has tackled previously in the automotive and aviation industries, he said. "We are not saying we know how to reproduce that for the pharmaceutical companies; we are proposing as a research project to rethink them and work with some organizations to build new collaborative solutions."
The pharma researchers know their own bottlenecks best, he said, so "we need to co-design, to co-build a new solution." Following the flow and revision of data is what his firm calls the data lifecycle, Johnson said.
The Dassault team is looking at life sciences to see which processes are "time-focused" or "content-driven," he said. Nicholas Froloff, R&D leader for life sciences diversification at the company, explained that he and his colleagues are asking life science researchers to identify siloed activities in their R&D pipeline and to explain the degree to which external researchers deliver input for the R&D process.
"Do they share expertise on potential adverse effects that may come from other pathways? Do you capitalize on knowledge gained, especially failures? [To what extent] do you re-use data or information collected from hospitals, in clinical trials or from pharmacovigilance [studies] to re-inject that knowledge, either failure or success into drug discovery?" Froloff said. "Basically, their answers were 'no.'"
Johnson said Daussault is most well-known for its computer-aided design suite, but that the firm has moved beyond CAD to manufacturing, scientific simulation, and collaboration platforms, in addition to PLM.
"CAD was for 3D modeling and design whereas PLM covers the whole process — from design down to manufacturing," Johnson said. The Boeing 777, for example, was designed with the firm's software platform.
'A Different Jungle'
"We are in a totally different jungle here — a different domain with different challenges," Johnson said of life sciences, but added that he believes the firm can translate its engineering expertise to the new field.
Around 10 years ago, he said, Dassault had clients who, much like pharma today, needed to work together but had different database schemas, albeit with a "simpler data structure" and divergent data flow. In some cases, engineers and manufacturers had information silos and "almost didn't communicate at all," he said, nor did they want to share data for "as many reasons as you can imagine" because it might create "dependencies" or make the process too visible outside one department.
By introducing a platform that fostered "new collaborative practices," his firm progressively bridged the two spheres, he said. "After 10 years they were totally collaborating in the same space, with the same databases, same data model," Johnson said. Establishing similar progress in agrochemicals, pharma, and life sciences will "take at least that long," Johnson said, which is why a research project to explore "innovative ideas" is important.
The life sciences industry is fragmented, and "frankly speaking, we are not saying two years from now the industry will have found a solution," he said.
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BioIntelligence will be unlike Microsoft's SharePoint and existing vendor workflow platforms, he said, describing PLM as a "richer model for collaboration." While SharePoint helps to manage documents, Johnson said, "what we want to do is go down to the data level," to the information in all "its granularity."
"If we want to manage the complexity of the data, the inter-relationships between all the data, we need a rich model or one that can be enriched, and I am not so sure that SharePoint could apply to every data point," Froloff said.
That granularity plays an important role in sharing data with regulatory agencies, for example, Froloff said, as well as for feedback loops internal to an enterprise, when "a company needs to agree on the next milestone" early in the development cycle, not "when it's too late, the project is a failure, and it is too costly."
He said that BioPLM is intended to expose "the right data at the right moment to the right person."
BioIntelligence is part of an OSEO applied research program that supports industrial innovation.
OSEO's Bur said that Dassault initially proposed the project and it was then reviewed by external experts.
The open integrated platform was chosen "because it allows efficient two-directional information flow in the R&D pipeline," Bur said. For example, if in the course of clinical trials a drug candidate reveals a toxicity, "all research connected to this molecule will be alerted in a type of feedback control loop," within the platform.
Without computational integration, it is "impossible" to forecast events in research and development, Bur said. Daussault's PLM architecture, meantime, "has shown its strengths" in its deployment at firms like Boeing, for example, where information can move back through the R&D pipeline all the way to the suppliers.
"This knowledge about this lifecycle of data lends BioIntelligence its power," Bur said.
The first phase of the project will focus on exploring to what degree it is possible "to reproduce in vitro experiments in silico," he said. "Our real judge of success will be with the life science companies who deploy this system; the commercial success will be telling."
Even though it is funded by a French agency, BioIntelligence required approval from the European Commission due to rules about potential competition between government funding and market forces. According to an EC framework issued in 2006 called IP-06-1600, EU member states can fund applied R&D as long as the aid "address[es] a well-defined market failure" and doesn't "distort" trade.
In a statement, EU Competition Commissioner Neelie Kroes said that BioIntelligence does indeed address a "market failure" and stands to improve "the efficiency" of life science research.
BioIntelligence, according to OSEO, will have "positive external effects" for Europe's bioinformatics and public health sectors. The market would "never" have given rise to such a program, OSEO said, because of "the significant technological and economic risks involved."