Alex Philippidis Senior News Editor Genetic Engineering & Biotechnology News
Programs cover clinical trials and data sharing to enable quicker drug R&D.
Biopharma companies are pursuing open-innovation collaborations with an eye on speeding up research and discovery work. Academic and independent research institutions are also teaming up with industry to discover new treatments under this open-source model.
Cost-cutting pressures and the desire for faster-to-market medicine are some of the driving forces behind open-collaboration efforts. Academic-based organizations seem so far to focus more on strengthening clinical development and improving research infrastructure, namely through data sharing initiatives.
Earlier this year the Archipelago to Proof of Concept in Medicine (Arch2POCM) was organized through a partnership of Sage Bionetworks, the Structural Genomics Consortium, and several others. Arch2POCM envisions creating a scientific and clinical network for taking high-risk disease targets through to clinical validation. Members of the network would use shared research free of claims to intellectual property to conduct trials leading to proof-of-concept.
“It allows us to give that material to anyone to learn anything about it in any disease, in a way that is very distinct from what companies can do because they protect that for filing in a particular indication,” H. Friend, M.D., Ph.D., president, co-founder, and director of Sage Bionetworks, told GEN. “This concept of not just open source but no IP on the target going forward gives an ability to share not just the data but share the compound, get insights, get the knowledge out there.”
The partnership is working on two broad disease areas: a neuroscience project that will focus on autism and schizophrenia and an oncology project focused on drugs that can act on new epigenetic targets. “The goal is to have the program launch in the first half of 2012,” Dr. Friend said.
Arch2POCM plans to raise public and private funds for research, with Dr. Friend saying that should add up to hundreds of millions of dollars over a five-year period. He added that researchers from seven pharma giants, which he would not name, are represented on Arch2POCM strategic design teams charged with defining project workflow and timeline details.
Not all open-source efforts are aimed at advancing new medicines from lab to clinic to market. Members of the Coalition Against Major Diseases (CAMD) agree to fully share precompetitive data and knowledge. The focus is on Alzheimer, Parkinson, Huntington, and other neurodegenerative diseases.
Of the coalition’s 21 members, 16 come from the biopharma and medical device spheres—from companies to research institutions—with another five members consisting of patient advocacy groups and voluntary health associations. CAMD is led and managed by the nonprofit Critical Path Institute (C-Path), funded by a cooperative agreement with the FDA and a matching grant from Science Foundation Arizona.
Last year CAMD released a database of more than 4,000 Alzheimer patients who have participated in 11 industry-sponsored clinical trials, the first database of combined clinical trials to be openly shared by pharmaceutical companies and made available to qualified researchers around the world. That database has grown to more than 4,100 patients, a number expected to reach close to 6,000 by late October. “We have a lot of data that has been submitted, and that is in the quality assurance process right now,” Steve Broadbent, C-Path’s director of consortia operations, told GEN.
About 200 scientists have been granted access to the Alzheimer database. For whatever they glean from the database, scientists agree in return to recognize CAMD and cite their use of the database.
Broadbent said the model aids scientists by providing them with an alternative method for sample size calculations; a determination of optimal trial durations and measurement times; a comparison of the sensitivity of competing trial designs to assumptions about the types of expected treatment effects; information on the impact of inclusion criteria/disease severity on treatment effect and required trial length; and a determination of the most appropriate data analytic methods for novel trial designs.
CAMD has also built, but has yet to load data into, a database of Parkinson patients, reflecting data from a half dozen trials. “It is safe to say it will have over 1,000 patients but may not be multiple thousands initially,” Broadbent noted.
He added that CAMD is also working with a sister consortium, CDISC (the Clinical Data Interchange Standards Consortium), to create data standards. “We have identified clinical trials we want to remap and put into the database,” Broadbent reported. “We’ve got the database in development right now, and we’re in the process of finding either in-kind effort or funds to pay for the remapping of the clinical trials into the new standard so we can aggregate them into the Parkinson database.”
Member companies in CAMD and several physicians have committed to using the standards, one set of which has been completed for Alzheimer disease: “We’ve also nearly completed one for polycystic kidney disease and Parkinson disease, and we’re working on one for tuberculosis as well.”
Uniform standards for conducting clinical trials and classifying data will certainly help streamline open-collaboration efforts. The biggest catalyst for such arrangements will remain the need by biopharma companies and, increasingly these days, academic and independent research institutions to reduce costs. As that need increases, so too should the number of open-source collaborations as well as the willingness of normally self-contained institutions to join with others in developing new medicines.
Alex Philippidis is senior news editor at Genetic Engineering & Biotechnology News.