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FDA Convenes Medical Device Workshop Focused on Artificial Intelligence and Machine Learning Transparency

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On October 14, 2021, the U.S. Food and Drug Administration ("FDA" or the "Agency") held a virtual workshop entitled, Transparency of Artificial Intelligence ("AI")/Machine Learning ("ML")-enabled Medical Devices. The workshop builds upon previous Agency efforts in the AI/ML space. Back in 2019, FDA issued a discussion paper and request for feedback called, Proposed Regulatory Framework for Modifications to AI/ML-Based Software as a Medical Device ("SaMD"). To support continued framework development and to increase collaboration and innovation between key stakeholders and specialists, FDA created the Digital Health Center of Excellence in 2020. And, in January 2021, FDA published an AI/ML Action Plan, based, in part, on stakeholder feedback to the 2019 discussion paper.


Machine learning uncovers 'genes of importance' in agriculture

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Machine learning can pinpoint "genes of importance" that help crops to grow with less fertilizer, according to a new study published in Nature Communications. It can also predict additional traits in plants and disease outcomes in animals, illustrating its applications beyond agriculture. Using genomic data to predict outcomes in agriculture and medicine is both a promise and challenge for systems biology. Researchers have been working to determine how to best use the vast amount of genomic data available to predict how organisms respond to changes in nutrition, toxins and pathogen exposure--which in turn would inform crop improvement, disease prognosis, epidemiology and public health. However, accurately predicting such complex outcomes in agriculture and medicine from genome-scale information remains a significant challenge.


Informatica Plans to Raise Nearly $1 Billion in IPO

WSJ.com: WSJD - Technology

The Morning Ledger provides daily news and insights on corporate finance from the CFO Journal team. Private-equity firm Permira and the Canadian Pension Plan Investment Board in 2015 took the company private in a transaction valued at $5.3 billion after roughly 15 years as a public company. The company has since moved its on-premises products to a cloud-based platform and built a subscription business. Permira and CPPIB will control about 85% of the company after its IPO. Informatica, which lists drugmaker Eli Lilly & Co., consumer-goods giant Unilever PLC and supermarket chain Kroger Co. among its customers, helps companies connect and manage their data across the cloud and on-premise systems, allowing organizations to better analyze the data they collect.


Three Analysts Initiate Coverage On This AI-Based Pharmatech

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BofA initiated coverage on Exscientia Plc (NASDAQ:EXAI) with a Buy and $27 price target, implying a 25.5% upside. Analyst Michael Ryskin believes Exscientia stands out from other tech-enabled biotechs, as it uses AI to develop better drugs in a shorter period. Ryskin adds that the company's lead compounds remain in the early Phase 1 trials as the platform validation continues. Goldman Sachs also initiated Exscientia with a Buy and $30 price target, suggesting a 39.5% upside. Analyst Chris Shibutani believes the company is well-positioned to become a "pharmatech leader" in end-to-end artificial intelligence-enhanced drug discovery and development.


Using artificial intelligence as an alternative to animal testing

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The use of animals in science experiments is a double-edged sword: while this study has saved many lives and increased our scientific understanding, it has come at a great expense to the animals involved. Over 100 million animals, including mice, frogs, dogs, rabbits, primates, cats, and other species, are killed in animal testing. According to a study, some animal testing is inadequate in predicting the behaviour of medicines in human bodies. There is a significant waste of time, money, animal life, and other resources. As a result, AI models are appropriate and advantageous for those experiments.


Lantern Pharma to Host Third Quarter 2021 Operating & Financial Results Conference Call … – KY3

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… RADR® artificial intelligence ("A.I.") platform to transform the cost, … A.I. platform and machine learning to discover biomarker signatures …


GeneDisco: A Benchmark for Experimental Design in Drug Discovery

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In vitro cellular experimentation with genetic interventions, using for example CRISPR technologies, is an essential step in early-stage drug discovery and target validation that serves to assess initial hypotheses about causal associations between biological mechanisms and disease pathologies. With billions of potential hypotheses to test, the experimental design space for in vitro genetic experiments is extremely vast, and the available experimental capacity - even at the largest research institutions in the world - pales in relation to the size of this biological hypothesis space. Machine learning methods, such as active and reinforcement learning, could aid in optimally exploring the vast biological space by integrating prior knowledge from various information sources as well as extrapolating to yet unexplored areas of the experimental design space based on available data. However, there exist no standardised benchmarks and data sets for this challenging task and little research has been conducted in this area to date. Here, we introduce GeneDisco, a benchmark suite for evaluating active learning algorithms for experimental design in drug discovery.


The State of AI in 2021: Language models, healthcare, ethics, and AI agnosticism

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AI is expanding in two key areas of human activity and market investment -- health and language. Picking up the conversation from where we left off last week, we discussed AI applications and research in those areas with AI investors and authors of the State of AI 2021 report, Nathan Benaich and Ian Hogarth. After releasing what probably was the most comprehensive report on the State of AI in 2020, Air Street Capital and RAAIS founder Nathan Benaich and AI angel investor and UCL IIPP visiting professor Ian Hogarth are back for more. Last week, we discussed AI's underpinning: Machine learning in production, MLOps, and data-centric AI. This week we elaborate on specific areas of applications, investment, and growth.


The State of AI in 2021: Language models, healthcare, ethics, and AI agnosticism

ZDNet

AI is expanding in two key areas of human activity and market investment -- health and language. Picking up the conversation from where we left off last week, we discussed AI applications and research in those areas with AI investors and authors of the State of AI 2021 report, Nathan Benaich and Ian Hogarth. After releasing what probably was the most comprehensive report on the State of AI in 2020, Air Street Capital and RAAIS founder Nathan Benaich and AI angel investor and UCL IIPP visiting professor Ian Hogarth are back for more. Last week, we discussed AI's underpinning: Machine learning in production, MLOps, and data-centric AI. This week we elaborate on specific areas of applications, investment, and growth.


Artificial Intelligence Has Found an Unknown 'Ghost' Ancestor in The Human Genome

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Nobody knows who she was, just that she was different: a teenage girl from over 50,000 years ago of such strange uniqueness she looked to be a'hybrid' ancestor to modern humans that scientists had never seen before. Only recently, researchers have uncovered evidence she wasn't alone. In a 2019 study analysing the complex mess of humanity's prehistory, scientists used artificial intelligence (AI) to identify an unknown human ancestor species that modern humans encountered – and shared dalliances with – on the long trek out of Africa millennia ago. "About 80,000 years ago, the so-called Out of Africa occurred, when part of the human population, which already consisted of modern humans, abandoned the African continent and migrated to other continents, giving rise to all the current populations", explained evolutionary biologist Jaume Bertranpetit from the Universitat Pompeu Fabra in Spain. As modern humans forged this path into the landmass of Eurasia, they forged some other things too – breeding with ancient and extinct hominids from other species. Up until recently, these occasional sexual partners were thought to include Neanderthals and Denisovans, the latter of which were unknown until 2010.