077 | Mergers, grants and machines

Welcome to another episode of Biotechnology Focus radio. This week we are discussing some of the recent mergers and acquisitions that have been rocking the headlines, some recently awarded grants and how machines are moving fast. I am your host Michelle Currie, here to bring you the lowdown on the Canadian biotech scene.  +++++  Celgene, a biotech giant, has merged with and acquired Juno Therapeutics and their leading blockbuster drug cancer therapy in one of their largest deals ever. For a total of $9 billion, Celgene will pay $87 a share in cash for those not already owned by this corporation.  Celgene and Juno have been collaborating since June 2015 under which the two companies would leverage T cell therapeutic strategies to develop treatments for patients with cancer and autoimmune diseases with an initial focus on CAR-T and TCR technologies. In April 2016, Celgene exercised its option to develop and commercialize the Juno CD19 program outside of North America and China.  Juno develops cell-based cancer immunotherapies based on chimeric antigen receptor and high-affinity T cell (CAR-T cell) receptor technologies to genetically engineer T cells to recognize and kill cancer. Several product candidates have shown compelling clinical responses in clinical trials in refractory leukemia and lymphoma conducted to date.  This acquisition will position Celgene to become a preeminent cellular immunotherapy company with a platform to be at the forefront of future advances. JCAR017, a pivotal stage asset, with an emerging favorable profile in DLBCL, is expected to add approximately $3 billion in peak sales and significantly strengthen Celgene’s lymphoma portfolio, and JCARH125 will enhance Celgene’s campaign against BCMA (B-cell maturation antigen), a key target in multiple myeloma.  +++++  The global pharma industry is undergoing a dramatic transition from a quest for blockbusters to the design of a precision medicine based drug design. Artificial intelligence is one of the most prominent elements that has been adopted as part of the transition from a fully integrated pharmaceutical company model of drug design to extensive interaction with smaller innovative R&D; companies as well as academic institutions.  Artificial Intelligence (AI) is the activity devoted to making machines intelligent, and intelligence is that quality that enables an entity to function appropriately and with foresight in its environment (definition proposed by Nils J. Nillson, Stanford U.). Even though there are numerous definitions for AI, this one fits nicely into the goal of using machine learning for improving the rate of success in the design of novel and cost-effective therapeutics.  One of the primary reasons that AI has such a great potential in drug development is that there is a huge amount of health data available right now in the public health system. Clinical trials’ data, electronic medical records (EMR), genetic profiles and much more is the wealth representing the notion of BIG DATA in healthcare. The main challenge regarding the processing of big data is the need to process it in a meaningful and cost-effective fashion. That is why training a machine to fulfill the task becomes so attractive. Selecting and adjusting the right algorithms is the first essential step but once it is in place, training machines to find optimal patterns between the structure of “druggable molecules” and their optimal activity is within reach.  Canada has established a leadership position in training of machines to learn how to perform complex tasks, in a relatively short period of time. Based on recent commitments to the space, it is expected that we will witness in the foreseeable future designs of novel and much more specific therapeutics with higher potency and lesser side effects. The prospects are quite encouraging in light of the shift global pharma industry is adopting towards precision medicine. That shift will rely on sifting through patients’ medical records. Canadian AI machines are learning fast and are expected to become a key player in advancing academic concepts into standard and streamlined processes and organizations. In Ontario, the University of Toronto has emerged as a world-leading hub for research and entrepreneurship in this area. A potent combination of long-standing academic research in conjunction with the adoption of machine learning methodologies have already proven to be game-changing opportunities. Interactive approaches to computer science and medical research, combined with emerging best in class entrepreneurship programming and training is already yielding some fascinating fruits in the area of AI for drug discovery.  Companies like Structura Bio are taking the complex computational challenge of reducing noisy images from cryo-electron microscopes into readable highly accurate 3D structures of proteins and are doing what used to take a server room filled with computers a week, in a matter of seconds. Similarly, Phenomic AI (a recently incorporated UTEST company) uses a technique called deep learning to analyze data from high-throughput phenomic screens to analyze cell and tissue phenotypes in microscopy data with incredible accuracy. It holds out the potential for eliminating human intervention in the assessment of all that data. In some cases, companies like Deep Genomics and Atomwise are going all the way by leveraging their respective AI technologies to become drug discovery engines themselves. Our awareness of the impact of the AI revolution in drug discovery is already enormous and we’re only at the beginning of its adoption cycle. Future advances in Canada will be buoyed further by strong academic and institutional foundations that have been put in place to assist Canada in sustaining this advantage. The Vector Institute, as an example, was established in 2017 in partnership with Canada’s largest companies and the Federal and Provincial Government’s to attract and retain world-leading research talent and to promote cutting-edge research in the field.  Recently, partnerships have been established between the MaRS Innovation research healthcare ecosystem (UHN, Sickkids, Sunnybrook) with global players in the space of machine learning based drug design and developments. Partnerships with Schrödinger and Evotec have been established to capture the enormous potential of “fishing in the pond” of EMR’s rich source of unraveling the tissue/cellular architecture as a baseline for the discovery of novel disease targets, which thereby establishes a mechanism for better drugs.  The field of AI in the service of medical research is still in its infancy, but the initial avalanche of results is already starting to give us an idea of the great potential that machine learning can offer to those embarking on advancing drug development. Reducing screening times, aiding new drug candidates and finding the most effective drugs for specific diseases at a speed that humans cannot achieve is compelling, and we believe that AI will increasingly become part of the medical landscape. Once hurdles such as data standardized collection and storage as well as data privacy concerned are addressed, it is expected that we will witness an exponential inclination in the implementation of machine learning as a powerful tool in the design of more potent drugs with lesser side-effects. The FDA and Health Canada are encouraging pharmaceutical companies to join the choir.  To conclude, rephrasing from Eric Topol of the Scripps Research Institute (CNBC, May 2017), “The potential of artificial intelligence has probably the biggest impact of any type of technology on healthcare.”  +++++  Two of Canada’s largest producers of cannabis have struck a deal after months of negotiations and a hostile takeover bid. The board of directors and the special committee of the CanniMed board have agreed to support a new offer made by Aurora for the acquisition of all of the issued and outstanding shares of CanniMed not owned by Aurora.   Terry Booth, the CEO of Aurora Cannabis says, “We are very pleased to have come to terms with CanniMed on this powerful strategic combination that will establish a best-in-class cannabis company with operations across Canada and around the world.”   The new offer for CanniMed is approximately $1.1 billion based on Aurora’s implied share price of $12.65. The maximum amount of cash available under the amended offer will be $140 million, and the number of Aurora shares to be issued will be between approximately 72 million and 84 million. Assuming maximum cash elections, each CanniMed shareholder would receive $5.70 in cash and 2.9493 Aurora shares.  Despite CanniMed filing a law suit against Aurora earlier this month, this deal provides the optimum outcome for both companies.  +++++  The Ottawa Hospital has been awarded $12.7 million in the most recent project grant competition from the Canadian Institutes of Health Research (CIHR). The grant funding will be going to sixteen research groups at the hospital who are in affiliation with the University of Ottawa. This represents an enormous success rate of 30 per cent, doubling the national average.  The new funding will provide researchers the much-needed capital to delve deeper into their studies ranging on a plethora of subjects – anywhere from oncolytic viruses as immunotherapy treatments, using a holistic approach to improving the quality of life for the homeless, to understanding the role of liquid metabolism in the brain.  “I’m delighted that our researchers have once again achieved such a high success rate,” says Dr. Duncan Stewart, executive vice president of research at The Ottawa Hospital and professor of medicine at the University of Ottawa. “These new research projects have the potential to redefine the future of health-care, both at home and around the world.”  The Ottawa Hospital has scored above the national average in CIHR grant competitions for the past several years, including 2015, 2016, and 2017. This research centre shows great promise and innovative studies for the years ahead.  For the summaries of all the projects please visit biotechnologyfocus.ca   +++++  Well that wraps up another episode of Biotechnology Focus radio. If you have any questions, comments or story ideas, please contact us at [email protected], and don’t forget to follow us on our twitter handle @BiotechFocus. From my desk to yours – this is Michelle Currie.