This week Insilico Medicine announced the launch of Life Star - their AI powered 6th generation robotics lab for drug discovery. This state of the art lab is equipped with several types of autonomous guided vehicles (AGVs) and advanced imaging devices. The AGV robots are driven by AI and guided by radar. The robots - which are completely controlled by AI - connect all of the automation modules in the lab. Insilico's lab is different from every other lab because Life Star is a 6th generation lab, meaning it does not require any human intervention.

The MIT School of Engineering and Pillar VC today announced the MIT-Pillar AI Collective, a one-year pilot program funded by a gift from Pillar VC that will provide seed grants for projects in artificial intelligence, machine learning, and data science with the goal of supporting translational research. The program will support graduate students and postdocs through access to funding, mentorship, and customer discovery. Graduate students and postdocs will aim to emerge from the program having built minimum viable products, with support from Pillar VC and experienced industry leaders. "We are grateful for this support from Pillar VC and to join forces to converge the commercialization of translational research in AI, data science, and machine learning, with an emphasis on identifying and cultivating prospective entrepreneurs," says Anantha Chandrakasan, dean of the MIT School of Engineering and Vannevar Bush Professor of Electrical Engineering and Computer Science. "Pillar's focus on mentorship for our graduate students and postdoctoral researchers, and centering the program within the Deshpande Center, will undoubtedly foster big ideas in AI and create an environment for prospective companies to launch and thrive."

Alphabet subsidiary and precision health company Verily recently announced a breakthrough in its AI drug discovery GPCR research collaboration with Sosei Heptares. A mere six months ago Verily launched the study with Sosei Heptares – a global leader in GPCR structure-based drug design – with an aim to "prioritise protein targets for therapeutic targeting in immune-mediated disease". Now, Verily has announced that early results from its "next generation immune mapping technology" Immune Profiler platform have already identified "more effective therapeutic options against G protein-coupled receptors (GPCR) in autoimmune and other immune-mediated diseases". The companies hope that in the year to come those data targets will be entered for validation, hit generation, and lead selection. With approximately one third of all current FDA-approved drugs targeting GPCRs, Verily/Sosei Heptares are looking to expedite GPCR research within not only immunology, but also gastroenterology and immuno-oncology as well, and the latest data bodes well for future development of therapeutic options in these areas.

AI pathology specialist PathAI has announced a multi-year expanded collaboration agreement with Bristol Myers Squibb. The initial work within this extended agreement will focus on key translational research in oncology, fibrosis, and immunology, with an overall goal to forward these into clinical trials. PathAI develops quantitative pathology algorithms for drug discovery and development. "We look forward to collaborating with PathAI to expand the potential application of AI in the drug development process to include translational research, clinical trials, and diagnostic advancements," said Robert Plenge, MD, PhD, senior vice president of Bristol Myers Squibb, head of Immunology, Cardiovascular, and Fibrosis Thematic Research Center, and head of Translational Medicine. "We feel that PathAI will be a productive collaborator given digital pathology represents a growing area for BMS, PathAI is a leader in the field, and the fact that we have a long-standing productive relationship with the company," he added.

Advanced cyberinfrastructure (CI) is critical to science and engineering (S&E) research. For example, over the past two years, CI resources (including those provided by the COVID-19 HPC Consortiuma) enabled research that dramatically accelerated efforts to understand, respond to, and mitigate near- and longer-term impacts of the novel coronavirus disease 2019 (COVID-19) pandemic.b Computer-based epidemiology models informed public policy in the U.S., and in countries throughout the world, and newly studied transmission models for the virus have been used to forecast resource availability and mortality stratified by age group at the county level.c Artificial intelligence and machine learning approaches accelerated drug screening to find candidate medicines from trillions of possible chemical compounds,d and differential gene expressions among COVID-19 patient populations have been analyzed with important implications for treatment planning.e Structural modeling of the virus has led to new insights, speeding the development of vaccines and antigens.

Deepcell, a life science company pioneering AI-powered cell classification and isolation for cell biology and translational research, today announced the appointment of Kevin Jacobs as the Vice President of Bioinformatics. Jacobs will be responsible for the company's bioinformatics strategy, implementation and its integration with other areas and into the company's offerings. This appointment is the latest addition to Deepcell's rapidly expanding team of scientists, engineers and computer science experts. Deepcell had acquired $20 million in Series A funding last year. Currently, Deepcell is helping to advance precision medicine by combining advances in AI, cell classification and capture, and single-cell analysis to deliver novel insights through an unprecedented view of cell biology.

The below blog is a transcript of James Cai, Head of Data Science at Roche Innovation Centre, presenting on the application of AI in the clinical development of drugs, a topic which is extremely prevalent in the current environment. AI is transforming many industries including healthcare and pharma. Where are the opportunities for AI in the early clinical development of new drugs, where scientific hypotheses first meet real patients in clinical trials? Can AI generate new insights to inform translational research or improve the efficiency of clinical trials? In this talk, I will highlight opportunities created by big data and AI, e.g., digital biomarkers for neurological diseases, and share my thoughts on what it will take to operationalize AI in drug development.

PathAI, a leading provider of AI-powered technology for advancing pathology research, announced that it has appointed translational medicine and digital pathology leader, Michael C. Montalto, PhD, as Chief Science Officer. Dr. Montalto joins PathAI from Bristol-Myers Squibb (BMS), where he was Vice President and Head of Translational Sciences, Translational Medicine. "We are incredibly fortunate and excited to welcome Mike onto our leadership team," said Andrew Beck, MD, PhD, co-founder and Chief Executive Officer of PathAI. "Mike brings tremendous experience developing digital pathology diagnostic products and driving cutting-edge translational research in a large biopharmaceutical setting. We are thrilled to be working with Mike at PathAI to use AI-powered pathology to support the development of new therapies and diagnostics for patients."

According to the Centers for Disease Control and Prevention (CDC), an estimated 50 million adults in the U.S. suffered from chronic pain in 2016, and according to the Substance Abuse and Mental Health Services Administration (SAMHSA), an estimated 10.3 million people in the U.S. ages 12 and older misused opioids in 2018. As such, the National Institutes of Health (NIH) have announced the awarding of $945 million in research grants to tackle the national opioid crisis through NIH HEAL Initiative (Helping to End Addiction Long-term Initiative). The UC San Francisco Department of Radiology and Biomedical Imaging is pleased to announce that one such project is the Back Pain Consortium (BACPAC) Research Program of which Sharmila Majumdar, PhD, vice chair for Research, is a part of. At this time, chronic low back pain is one of the most common forms of chronic pain in adults, and current treatments are ineffective, leading to increased use of opioids. This research will also lay the foundation for NIH funded research at the newly established Center for Intelligent Imaging, using artificial intelligence fueled algorithms for fast image acquisition, data analysis, quantitative sensory assessments, brain imaging, and biomechanical evaluation of the spine.