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Site: www.scientificcomputing.com

CAMBRIDGE, MA — The Broad Institute of MIT and Harvard has entered into an agreement with Arxspan for use of its ArxLab cloud-based suite of biological and chemical discovery information management tools. The partnership will support the institute's efforts to electronically manage and share both biological and chemical research information internally and with external collaborators. The ArxLab suite of tools will be used for managing the Institute's electronic laboratory notebook, compound and assay registration, scientific analysis and search, biological visualization, and inventory management functions. "We are pleased to be transitioning to the ArxLab software to take advantage of new ELN, compound registration and inventory management functionalities," said Andy Phillips, Senior Director of the Center for the Development of Therapeutics and Broad Institute Scholar in Residence. “The ArxLab platform will enable Broad scientists to leverage their data in new ways across a spectrum of research in biology and chemistry. Integration of data is at the heart of what Broad does, and partnering with Arxspan allows us to further increase the velocity of our research.” The partnership covers use of Arxspan's ArxLab Notebook, ArxLab Inventory for inventory management, ArxLab Registration for chemical and biological registration, ArxLab Assay for assay data management, ArxLab FT for scientific analysis and search, and ArxDraw for biological visualization. The cloud-based nature of the system allows for secure and efficient sharing of information with external parties. “The Broad Institute is a leading global biomedical research institute, and we are pleased that they have engaged Arxspan for management and sharing of their chemical and biological research data.” said Peter Rosati, CEO of Arxspan. “We look forward to working together to enable Broad scientists to advance their research programs and share information with the global scientific community.” Arxspan provides cloud-based solutions to meet the scientific data management needs of life sciences organizations globally. Arxspan offers a suite of Web-based informatics applications, including electronic laboratory notebook (ELN), chemical/biological registration, assay registration, scientific search and decision support, and inventory management for project-based research and development data management and collaboration. Users can track internal research, manage incoming collaborator data, and integrate Arxspan's Web-based, platform-independent user interface with existing enterprise knowledge management tools. Arxspan offers a robust, secure, and 21 CFR Part 11-compliant platform with zero-footprint client profiles, serving as an ideal hosting partner for research, intellectual property, and other proprietary and confidential data. About the Broad Institute of MIT and Harvard The Eli and Edythe L. Broad Institute of MIT and Harvard was launched in 2004 to empower this generation of creative scientists to transform medicine. The Broad Institute seeks to describe all the molecular components of life and their connections; discover the molecular basis of major human diseases; develop effective new approaches to diagnostics and therapeutics; and disseminate discoveries, tools, methods and data openly to the entire scientific community. Founded by MIT, Harvard and its affiliated hospitals, and the visionary Los Angeles philanthropists Eli and Edythe L. Broad, the Broad Institute includes faculty, professional staff and students from throughout the MIT and Harvard biomedical research communities and beyond, with collaborations spanning over a hundred private and public institutions in more than 40 countries worldwide.


News Article
Site: www.nature.com

A versatile technique for editing genomes has been called the biggest biotechnology advance since the polymerase chain reaction (PCR), and the US Patent and Trademark Office (USPTO) is set to determine who will reap the rewards. On 11 January, the USPTO granted a request to review a key patent awarded for the technique, known as CRISPR–Cas9. The outcome of the ensuing proceedings, called a patent interference, could be worth millions to the research institutions that are at war over the relevant patents. It might also influence who is allowed to use the technology — and under what terms. “This is an absolutely humungous biotech patent dispute,” says legal scholar Jacob Sherkow of New York Law School. “We’re all waiting with bated breath.” CRISPR–Cas9 is a bacterial defence system that uses the enzyme Cas9 to snip DNA at sites determined by the sequence of a ‘guide’ strand of RNA. Scientists can disable, replace or tweak genes by using the technique to rewrite snippets of DNA sequences. Use of the technology in research has exploded, thanks to CRISPR–Cas9’s relative simplicity and versatility compared to other gene-editing methods. Several companies have sprung up to harness the technique for generating improved crops, research reagents and therapies for human genetic diseases. The roots of the CRISPR–Cas9 dispute date back to 2012, when researchers reported that they had reprogrammed the system to cut strands of isolated DNA at sites of their choosing1. The team, led by biologists Jennifer Doudna at the University of California, Berkeley, and Emmanuelle Charpentier, now at the Max Planck Institute for Infection Biology in Berlin and Umeå University in Sweden, filed a patent application on 15 March 2013. By then, publications had emerged from other groups showing that the method works in human cells2–4 and bolstering dreams of CRISPR-based gene therapies — the basis for several companies that have sprung up to capitalize on the technique. One of those groups, led by synthetic biologist Feng Zhang of the Broad Institute and the Massachusetts Institute of Technology, both in Cambridge, filed a patent application for the CRISPR–Cas9 technique in October 2013. The institutions filed the patent under a special expedited review programme, and it was granted in April 2014. Zhang has since been awarded additional patents on the technology. The original Doudna–Charpentier patent remains under review. In April 2015, the Berkeley team asked the USPTO to begin an interference proceeding to determine which team was the first to invent the technique. The proceedings will be much like a court case, with both sides presenting evidence culled from publications and laboratory notebooks. “Once the [USPTO] declares an interference, that’s really when the fur is going to fly,” Sherkow predicted in a June interview. The patent interference is also a testament to the high stakes involved: companies aiming to use CRISPR–Cas9 for gene therapy have raised hundreds of millions in venture capital and other funds in under three years. One company, Editas Medicine in Cambridge, Massachusetts, has already filed to go public. Arti Rai, a legal scholar at Duke University in Durham, North Carolina, says that it is unusual for academic research institutions to battle so intensely over a patent. Instead, such institutions usually come to an agreement to share rights to the invention. “This seems more bitter than disputes I’ve heard of in the past,” she adds. The two patents in question make broad claims to 'foundational' intellectual property thought to be necessary for most lucrative CRISPR–Cas9 applications. But many patents have been filed on CRISPR–Cas9 technologies, and there is still the chance that the winner of the interference will face additional challenges in court. Zhang's group has also reported another enzyme, called Cpf1, that could provide an alternative to Cas9. Researchers expect other alternatives to emerge with time. As for the various CRISPR–Cas9 companies, Zhang remains involved in Editas, which was founded by both Zhang and Doudna, among others, in 2013. Doudna has since severed ties with Editas and thrown her support behind Intellia Therapeutics, also in Cambridge. Charpentier, meanwhile, co-founded CRISPR Therapeutics of Basel, Switzerland. For now, it is unclear how the dispute will affect researchers who use CRISPR–Cas9, if it does so at all. Academics who might use the technology for basic research make unattractive targets for patent lawsuits, says Rodney Sparks, a biotechnology patent counsel at the University of Virginia in Charlottesville. “Patent holders might send out a few cease-and-desist letters, but they probably won’t sue academic researchers,” he says. Doing so would take time and money with little reward: the spoils in a patent lawsuit are typically damages or a share of royalties from a marketed product. That leaves little to gain from suing academics who are not selling anything. But those who intend to use their research as the basis for a start-up company will need to be wary, Sparks says. Some patent holders do ask that even scientists doing basic research take out a licence on a patented technology, typically for a fairly small fee. Such was the case for PCR, says Warren Woessner, a lawyer at Schwegman Lundberg and Woessner in Minneapolis, Minnesota. Woessner recalls how, during his previous career as a scientist, his institution decided to patent a method he developed. Officials at the institution later noticed that someone had published a paper that used the technique without a licence. “They sent the professor a little note,” recalls Woessner. “‘We have a patent on this. Pay up.’” The professor did. The Broad Institute has noted on its website that it will continue to make CRISPR–Cas9 reagents available to the community, and has given no indication that it will pursue licensing fees from academics. But Sherkow warns against assuming that the spirit of academic camaraderie will prevail: licensing revenue has become increasingly important, particularly for major research institutions, he says. “We’re just living in a brave new world these days.”


Now Genometry has commercialized a high-throughput gene-expression assay developed at the Broad Institute of MIT and Harvard, which operates at a fraction of the cost of conventional methods. It does so by using measurements of 1,000 genes to accurately and quickly estimate the activity of all the 20,000 or so genes expressed in a cell. The fast, low-cost assay allows for much larger experiments than previously possible, and for gene-expression profiling to be used much earlier in the drug-discovery process—which could speed things up, says Genometry co-founder, president, and CEO Justin Lamb, a former Broad Institute researcher. "Rather than profiling only a handful of compounds at the end of the search for a new drug to confirm that you got what you wanted, you can use profiling right at the start of the search, and hence do the search in much more efficient ways, because you have much more information," he says. A dozen pharmaceutical firms and other companies are now using the assay. Last October, Genometry signed a multiyear contract with Janssen Pharmaceutica to generate gene-expression profiles for 250,000 compounds in the Belgian firm's small-molecule library. This represents the first time gene-expression profiling has been applied at such a large scale. The data will be used for drug screening and improving the selection of candidate drugs before clinical studies. Lamb co-developed the assay, called L1000, with researchers in Broad Institute Chief Scientific Officer Todd Golub's group, including Genometry co-founder Aravind Subramanian and David Peck, both currently researchers at the Broad. For gene-expression profiling, researchers have traditionally used microarrays, pieces of DNA arranged on silicon wafers, or polymerase chain reaction (PCR), which copies DNA fragments in test tubes. PCR is more accurate, but microarrays are faster: It takes the same amount of time to measure a few dozen genes using PCR as it does to measure an entire transcriptome—the full range of genes expressed in a cell —using microarrays. But these experiments, Subramanian says, can cost up to $500 to generate the cellular response to a single drug or other "perturbagen." Matching signatures against libraries of a million or so drug candidates and different cell types, adds up. L1000 takes advantage of the fact "that genes don't act independently of each other. They travel in clusters," according to Subramanian. Instead of recording all the gene expression in a cell, L1000 measures the expression of approximately 1,000 so-called landmark genes that have been selected because they have special qualities, such as being minimally redundant across the genome or widely expressed in different cell types. According to Subramanian, because of these properties, the landmark genes together contain around 80 percent of the information in the entire transcriptome. Genometry provides L1000 as a service. Clients send lysate—a fluid of broken-apart cells—in 384-well plates, usually dozens at a time, to Genometry's headquarters and lab in Kendall Square. After some initial processing, the samples are mixed with microscopic beads of different colors coated with DNA from landmark genes, before being run through a version of a flow cytometer. Varying fluorescence intensity of each bead denotes varying degrees of each gene's expression. Based on those measurements, a computational inference model infers how all other genes will behave. With fewer measurements, throughput increases and the price drops to a few dollars per sample, compared with $500 by other methods. Pharmaceutical firms will use L1000 data from potentially hundred of thousands of compounds as an initial screen, or to characterize their entire library of chemicals, as is the case with Janssen. Firms could also use the data for "hit selection" to narrow down the number of viable candidate drugs, Lamb says. A firm may have, say, 1,000 compounds to potentially treat a certain disease. Running those through L1000 will quickly reduce that number to perhaps 50 of most selective compounds and the ones with the fewest off-target effects. "It's a convenient way to prioritize compounds for drug development," Lamb says. In 2012, Lamb and Subramanian formed Genometry to commercialize L1000, only after it had proven its mettle at Broad Institute. "The purpose of [Genometry] was not so much to take a hand-wavy academic idea and make it into a product—it was to take a tried, tested, and proven technology and come up with a mechanism by which the outside world can get easy and effective access to that innovation," Lamb says. L1000 was developed for—and has become an integral component of—an ongoing Broad Institute project called the Connectivity Map, which aims to become, essentially, "Google for drug discovery," according to the project's website. The Connectivity Map, launched in 2005, is a collection of gene-expression responses to perturbagens, including chemical and genetic manipulations. "If you describe the actions of drugs, the effects of genetic manipulation, and disease states in a common language, connecting a disease with a potential remedy, for example, is a relatively easy pattern-matching problem. Gene expression provides a particularly good vocabulary for this," Lamb explains. Users of the Connectivity Map, for instance, can upload a list of genes whose expression pattern characterizes a disease and, with one click, receive a list of compounds ranked by their effect on those genes. It's similar to using keywords in Google to call up pages ranked by their relevance, Subramanian says. At the Broad Institute, L1000 has now helped researchers archive profiles for around 5,000 drugs—about half the drugs ever tested in humans—and perturbation of 3,000 genes using CRISPR genome editing and other tools. The Broad Institute hopes to amass data on the connections among all drugs, genes, and diseases in the near future, Subramanian says. Lamb says Genometry aims to help pharmaceutical firms use gene-expression data to effectively digitize their compound collections. In doing so, firms can use various tools to "search for compounds with desirable characteristics, determine if new chemical matter will be effective against various diseases, or if they are too similar to existing drugs to be commercially viable," he says. "It's important to not just digitize libraries available to academics," Subramanian adds, "but to also make sure companies are achieving the impact they want."


News Article
Site: www.nature.com

Last month, in an extraordinary dispute before the US Patent and Trademark Office (USPTO), university lawyers laid out their clients' legal strategies for claiming patents that cover the celebrated gene-editing technology CRISPR–Cas9. Over the next year, the USPTO will receive volumes of evidence centred on who first invented the technology. Battles over scientific priority are as old as science itself. But the CRISPR–Cas9 patent dispute is unusual because it pits two leading research institutions against one another for the control and industrial development of a foundational technology: the University of California, Berkeley (UC Berkeley), and the Broad Institute of MIT and Harvard in Cambridge, Massachusetts. As scientific institutions increase their involvement in the commercialization of research1, it is worth considering the potential consequences for science if more institutions follow the path of UC Berkeley and the Broad Institute. In May 2012, researchers at UC Berkeley, led by Jennifer Doudna and her collaborator, Emmanuelle Charpentier (then located at the University of Vienna in Austria) filed a patent application in the United States for CRISPR–Cas9. Seven months later, Feng Zhang, a researcher at the Broad Institute, filed a competing application that covered similar uses of the technology. After Zhang's lawyers requested that his application be fast-tracked, the USPTO awarded one patent to Zhang in April 2014, followed by a dozen more in the subsequent 12 months. Meanwhile, the application made by Doudna and her colleagues languished. Last April, Doudna's lawyers requested that the USPTO conduct a specialized legal trial, known as a patent interference, to determine the ownership of the US patents that cover the CRISPR–Cas9 system. This January, the USPTO formally agreed to carry out the proceeding. One conspicuous aspect of this case, in my opinion, is the degree to which UC Berkeley and the Broad Institute have weighed in on what is essentially a dispute over scientific priority. The Broad Institute has produced press releases, videos and a slick feature on its website that stress the importance of Zhang's contributions to the development of the CRISPR–Cas9 technology. And earlier this year, the central positioning of Zhang's work in a historical perspective of CRISPR published in Cell2 by the president and director of the Broad Institute, Eric Lander, prompted a storm of angry responses from scientists, including Doudna and Charpentier. Meanwhile, at UC Berkeley, a press release that discussed the potential of CRISPR described Doudna as “the inventor of the CRISPR–Cas9 technology”. The financial stakes are high. The CRISPR–Cas9 patents are widely viewed to be worth hundreds of millions, if not billions, of dollars. Both organizations have invested directly in spin-off companies that were co-founded by their researchers — the Broad Institute in Editas Medicine, co-founded by Zhang, and UC Berkeley in Caribou Biosciences, co-founded by Doudna. A report submitted by Editas in January to the US Securities and Exchange Commission lists the Broad Institute and other Harvard-affiliated institutions as owning a major equity stake in the company: about 4.2% of its common shares. Efforts to commercialize the research output from universities played out differently in the past. Since 1980, US universities have been able to patent the inventions of their researchers, thanks to the Bayh–Dole Act — legislation that determines the ownership of intellectual property arising from federally funded research. But for the most part, institutions have kept their distance from disputes over scientific priority. In fact, after factoring in the costs of filing patents and staffing, university technology-transfer offices have generally been money losers for their institutions3. Even in the case of lucrative patents, commercial development has frequently been left to venture capitalists and the researchers themselves. Take the Cohen–Boyer patents, which covered early gene-splicing technology and netted Stanford University and the University of California, San Francisco (UCSF), both in California, hundreds of millions of dollars in licensing fees during the 1980s and 1990s. In this instance, Genentech, the company in South San Francisco, California, that was formed to commercialize the underlying technology, sprung from the efforts of Herbert Boyer, one of the founding researchers, and the financier Robert Swanson. The company was neither owned by, nor an exclusive licensee of, Stanford or UCSF. Research institutions in general are starting to play a bigger part in shepherding their researchers' projects through the commercialization process. A 2014 report from the Association of University Technology Managers in Oakbrook Terrace, Illinois — an organization that supports managers of intellectual property at academic research institutions, non-profit organizations and government agencies worldwide — documented that universities are increasing equity investments in their researchers' start-up companies. Of the patent licences granted by universities in 2014, 10% were tied to such investments1, compared with 6.7% in 1999 (ref. 4). I am concerned that such involvement in commercialization has the potential to clash with the broader, educational mission of research institutions. Universities worldwide have long strived to foster a culture of scientific collaboration. Even when universities have obtained broad patents, as the Carnegie Institute of Washington in Washington DC did in the early 2000s for a gene-expression control technology known as RNA interference, licences have been cheap and easy for researchers to obtain5. In other cases, scientists have simply ignored patents that cover fundamental technologies6. Academic research institutions now seem less shy about taking each other to court for patent infringement. In 2011, the University of Utah in Salt Lake City sued the Max Planck Society for the Advancement of Science in Germany over claims to a patent that covered a technology called short interfering RNA, which inhibits gene expression (see go.nature.com/vyujnp). And over the past four years, Stanford University and the Chinese University of Hong Kong in Sha Tin have engaged in a heated patent litigation over prenatal genetic diagnostic blood tests, a market that was worth US$530 million in 2013. In the current era of budget tightening, universities of all stripes might be tempted to use licensing fees as another funding mechanism. The University of South Florida in Tampa, for example — a public institution that had its state funding cut by $48 million in 2012 — holds a substantial number of patents that have not yet been licensed and has a famously low ratio of patent-licence revenue to research expenditure7. If its financial situation were to deteriorate further, the university might be compelled to extract licence fees from other research institutions for those patents. It would be wrong to suggest that patents, writ large, are failing educational research institutions. In the cases of gene splicing, RNA interference and human embryonic stem cells, patents have been major earners for institutions and researchers without damaging the scientific enterprise5. But an obvious danger of increasing the focus on commercialization is that educational institutions will view scientific research as a path to profit, above all else. It is not hard to imagine that patent disputes might lead to university administrators pushing certain views on their scientists, denigrating collaboration with researchers from competing institutions and tasking tenure committees with valuing patents over publications. Where scientific advances have the potential to be profitable, universities should support researchers to bring that work to fruition. This might include helping them to secure patents. But it is my view that serious commercialization efforts — such as granting exclusive licences or receiving equity ownership in researchers' start-ups — should be left to industry. The CRISPR–Cas9 dispute could have played out very differently. Zhang and Doudna were both co-founders of Editas. And UC Berkeley and the Broad Institute could have filed patent applications that listed the research teams from both institutions as co-inventors. Any resulting patents could then have been freely or cheaply licensed to other research institutions, or used to fund a joint academic organization dedicated to studying the technology. The patents could also have been widely, but not exclusively, licensed to a variety of industry competitors — promoting a robust, competitive market for commercial CRISPR–Cas9 applications and creating a funding stream for further academic research. Biomedical research in educational institutions has long prided itself on a culture of openness and sharing — one that both Zhang and Doudna have exercised by donating various components of the CRISPR–Cas9 system to the open-science consortium Addgene in Cambridge, Massachusetts. The incentives that patents create for educational institutions should not be allowed to erode scientific collaboration.


News Article
Site: www.biosciencetechnology.com

For pharmaceutical firms, gene-expression profiling has become a valuable tool for drug discovery. This process involves measuring the activity of a cell’s genes in response to drugs, to determine the compounds’ effectiveness, toxicity, and other characteristics. Conventional profiling methods, however, are inefficient or expensive, sometimes costing millions of dollars. Now Genometry has commercialized a high-throughput gene-expression assay developed at the Broad Institute of MIT and Harvard, which operates at a fraction of the cost of conventional methods. It does so by using measurements of 1,000 genes to accurately and quickly estimate the activity of all the 20,000 or so genes expressed in a cell. The fast, low-cost assay allows for much larger experiments than previously possible, and for gene-expression profiling to be used much earlier in the drug-discovery process — which could speed things up, said Genometry co-founder, president, and CEO Justin Lamb, a former Broad Institute researcher. “Rather than profiling only a handful of compounds at the end of the search for a new drug to confirm that you got what you wanted, you can use profiling right at the start of the search, and hence do the search in much more efficient ways, because you have much more information,” he said. A dozen pharmaceutical firms and other companies are now using the assay. Last October, Genometry signed a multiyear contract with Janssen Pharmaceutica to generate gene-expression profiles for 250,000 compounds in the Belgian firm’s small-molecule library. This represents the first time gene-expression profiling has been applied at such a large scale. The data will be used for drug screening and improving the selection of candidate drugs before clinical studies. Lamb co-developed the assay, called L1000, with researchers in Broad Institute Chief Scientific Officer Todd Golub’s group, including Genometry co-founder Aravind Subramanian and David Peck, both currently researchers at the Broad. For gene-expression profiling, researchers have traditionally used microarrays, pieces of DNA arranged on silicon wafers, or polymerase chain reaction (PCR), which copies DNA fragments in test tubes. PCR is more accurate, but microarrays are faster: It takes the same amount of time to measure a few dozen genes using PCR as it does to measure an entire transcriptome — the full range of genes expressed in a cell —using microarrays. But these experiments, Subramanian said, can cost up to $500 to generate the cellular response to a single drug or other “perturbagen.” Matching signatures against libraries of a million or so drug candidates and different cell types, adds up. L1000 takes advantage of the fact “that genes don’t act independently of each other. They travel in clusters,” according to Subramanian. Instead of recording all the gene expression in a cell, L1000 measures the expression of approximately 1,000 so-called landmark genes that have been selected because they have special qualities, such as being minimally redundant across the genome or widely expressed in different cell types. According to Subramanian, because of these properties, the landmark genes together contain around 80 percent of the information in the entire transcriptome. Genometry provides L1000 as a service. Clients send lysate — a fluid of broken-apart cells — in 384-well plates, usually dozens at a time, to Genometry’s headquarters and lab in Kendall Square. After some initial processing, the samples are mixed with microscopic beads of different colors coated with DNA from landmark genes, before being run through a version of a flow cytometer. Varying fluorescence intensity of each bead denotes varying degrees of each gene’s expression. Based on those measurements, a computational inference model infers how all other genes will behave. With fewer measurements, throughput increases and the price drops to a few dollars per sample, compared with $500 by other methods. Pharmaceutical firms will use L1000 data from potentially hundred of thousands of compounds as an initial screen, or to characterize their entire library of chemicals, as is the case with Janssen. Firms could also use the data for “hit selection” to narrow down the number of viable candidate drugs, Lamb said. A firm may have, say, 1,000 compounds to potentially treat a certain disease. Running those through L1000 will quickly reduce that number to perhaps 50 of most selective compounds and the ones with the fewest off-target effects. “It’s a convenient way to prioritize compounds for drug development,” Lamb said. In 2012, Lamb and Subramanian formed Genometry to commercialize L1000, only after it had proven its mettle at Broad Institute. “The purpose of [Genometry] was not so much to take a hand-wavy academic idea and make it into a product — it was to take a tried, tested, and proven technology and come up with a mechanism by which the outside world can get easy and effective access to that innovation,” Lamb said. L1000 was developed for — and has become an integral component of — an ongoing Broad Institute project called the Connectivity Map, which aims to become, essentially, “Google for drug discovery,” according to the project’s website. The Connectivity Map, launched in 2005, is a collection of gene-expression responses to perturbagens, including chemical and genetic manipulations. “If you describe the actions of drugs, the effects of genetic manipulation, and disease states in a common language, connecting a disease with a potential remedy, for example, is a relatively easy pattern-matching problem. Gene expression provides a particularly good vocabulary for this,” Lamb explains. Users of the Connectivity Map, for instance, can upload a list of genes whose expression pattern characterizes a disease and, with one click, receive a list of compounds ranked by their effect on those genes. It’s similar to using keywords in Google to call up pages ranked by their relevance, Subramanian said. At the Broad Institute, L1000 has now helped researchers archive profiles for around 5,000 drugs — about half the drugs ever tested in humans — and perturbation of 3,000 genes using CRISPR genome editing and other tools. The Broad Institute hopes to amass data on the connections among all drugs, genes, and diseases in the near future, Subramanian said. Lamb said Genometry aims to help pharmaceutical firms use gene-expression data to effectively digitize their compound collections. In doing so, firms can use various tools to “search for compounds with desirable characteristics, determine if new chemical matter will be effective against various diseases, or if they are too similar to existing drugs to be commercially viable,” he said. “It’s important to not just digitize libraries available to academics,” Subramanian adds, “but to also make sure companies are achieving the impact they want.”

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