May 8, 2019 While artificial intelligence (AI) still tends to be underfunded by big pharma, machine learning (ML) is creating efficiencies in the drug development process and collaboration between biologists and ML experts is becoming more commonplace. Companies are still formulating their overall AI strategy, but hopes are high for a future with "killer apps" for predicting toxicity and drug response. Those were among the themes that emerged from an "AI in Practice" keynote panel session at the recent Bio-IT World Congress & Expo in Boston. Participating panelists were Anne E. Carpenter, PhD, senior director of the Imaging Platform at Broad Institute of Harvard and MIT; Iya Khalil, PhD, chief commercial officer and co-founder of GNS Healthcare; Mariana Nacht, PhD, chief scientific officer, Vivid Biosciences; and Susie Stephens, PhD, senior director of Oncology & Vaccine R&D Information Technology at Pfizer. Increasingly, more user-friendly AI tools are getting into the hands of people with domain knowledge who understand the problems that most need solving, says Carpenter.

The healthcare industry is not immune to software and technological advancements. In fact, the use of emerging technologies like artificial intelligence (AI) has gradually begun to revolutionize research activities in the industry. Major advances in science and technology are also likely to improve diagnosis and treatment in the future. The pharma/biotech industry has started adopting artificial intelligence, the simulation of human intelligence processes by machines, especially computer systems, albeit slowly. It is touted as the next big emerging technology in the biotech industry as it can drastically reduce time and costs involved in developing life-saving drugs.

Earlier today, Alexion Pharmaceuticals was granted the licensing rights to operate GNS Healthcare's Reverse Engineering and Forward Simulation (REFS) casual machine learning and simulation platform. Alexion intends to use the platform to accelerate both the research of rare diseases and the development of novel therapies. Earlier this year, it was instrumental in finding a new target for breast cancer. In May, GNS published data in the American Association for Cancer Research's (AACR) journal Cancer Research in which they announced the discovery of novel targets, including TRIB1, which had positive implications for the treatment of triple-negative breast cancer. In June, it was announced that the company would be teaming up with Genentech to improve the capability to clarify disease mechanisms, recognize new targets, and diagnose patient populations more accurately.

The service and license arrangement with GNS Healthcare (GNS) gives Celgene Corporation rights to operate the GNS Healthcare REFS (Reverse Engineering and Forward Simulation) causal machine learning and simulation platform. As part of the arrangement, several GNS causal modeling experts will be brought in-house at Celgene sites to operate the platform. Additionally, Celgene has made a second equity investment in GNS. The core GNS Healthcare technology, REFS, is "fundamentally different from all other types of machine learning approaches," said Colin Hill, CEO, chairman and co-founder of GNS Healthcare. "Causal modeling and simulation is the only type of technology capable of answering the'holy grail' questions that are necessary to better match drugs and other health interventions to individual patients and discover new pathways for intervention," he told us.

WIRE)--GNS Healthcare (GNS), a leading precision medicine company that applies causal machine learning technology to massive and diverse data streams to better match drugs and other health interventions to individual patients, today announced that Celgene Corporation has entered into a service and license arrangement for the rights to operate the GNS Healthcare REFS (Reverse Engineering and Forward Simulation) causal machine learning and simulation platform for applications across drug discovery, clinical development, and commercialization and market access. In addition, several GNS causal modeling experts will be brought in-house at Celgene sites to operate the platform. GNS also announced that Celgene has made a second equity investment in GNS. "Companies that embrace data-driven frameworks and culture such as Celgene are gaining a competitive advantage to rapidly generate insights that are simply not possible with any other analytics methodology." This service and license arrangement with embedded GNS employees is a linking of people, process and technology.