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Artificial Intelligence

Section: Biopharma Insights     View all sections


Major VC Rounds For AI-driven Biotechs in 2020

   by Andrii Buvailo    350
Major VC Rounds For AI-driven Biotechs in 2020

The ongoing COVID19 crisis forced biotech-oriented venture capitalists (VC) to somewhat slow down the pace of their usual deal-flow -- according to data by PitchBook biopharma venture deals in 2020 are down roughly 16% compared to last year. 

However, there is still a lot going on in drug discovery and healthcare, and here I would like to specifically focus on artificial intelligence (AI)-driven biotech and health tech startups who managed to raise notable rounds in 2020, so far (based on our report “A Landscape of Artificial Intelligence (AI) In Drug Discovery and Development”). The deals are ordered by the amount of money raised 

11 Inspiring Women Advancing Artificial Intelligence In Life Sciences

   by BiopharmaTrend    2995
11 Inspiring Women Advancing Artificial Intelligence In Life Sciences

In this post, we decided to highlight eleven entrepreneurial women, leading the way in applying advanced computational technologies, such as machine learning (ML), deep learning (DL), and other artificial intelligence (AI) components, for tackling some of the hardest challenges of science -- in drug discovery and healthcare. This list is composed in alphabetical order. 

[Interview] Hacking Metabolomics With AI To Improve Clinical Research

   by Andrii Buvailo    449
[Interview] Hacking Metabolomics With AI To Improve Clinical Research

Personalized medicine has become a paradigm-shifting trend in healthcare - the hegemony of  “one-size-fits-all” drugs is increasingly challenged by novel innovative modalities and therapies, laser-sharped for a specific group of patients, or even a single patient in some cases. This is a complex story, and the progress in personalized medicine will take time and tectonic shifts in the pharmaceutical research workflow. 

On the other hand, the advent of personalized medicine is only possible with a more personalized system for health assessment, new robust biomarkers, and novel approaches to run and monitor clinical trials. This will require diagnostics that can provide sufficient insight into the metabolic status of individuals, and relatively new science of metabolomics is now taking off in the biotech industry.  

[Interview] Shaping European Life Sciences with AI

   by Andrii Buvailo    484
[Interview] Shaping European Life Sciences with AI

There is a great deal of hype and a lot of misconceptions among life science experts as to how AI can or can’t be applied in pharmaceutical research and business. Judging by the rapidly increasing number of AI-involved deals and partnerships tapped by big pharma recently, it becomes obvious that life sciences decision-makers are eager to understand what this new and disruptive technology can bring to the table, and how it can be adopted efficiently with tangible ROI.

In order to get valuable first-hand insight and new ideas about the technology and its emerging role in the life sciences industry, I have asked several questions to Dr. Loubna Bouarfa, Founder and CEO at ​OKRA Technologies ― a leading AI company for healthcare, which builds a sophisticated AI-driven engine specialized in supporting faster and more accurate decisions for life science executives and field teams. Loubna is also a member of the European Union AI High-Level Expert Group (HLEG) and the winner of several prestigious awards, such as MIT Innovator Under 35 and Forbes Top 50 European Women in Technology. Last year, OKRA was named the Best Female-Led Startup at the StartUp Europe Awards.

[Interview] Using Generative AI to Rapidly Identify Novel Therapies for COVID-19

   by Andrii Buvailo    528
[Interview] Using Generative AI to Rapidly Identify Novel Therapies for COVID-19

Generative models have become one of the hottest areas in de-novo molecular design over just several years, basically revolutionizing our perception of what can be done with artificial intelligence in this area. One important aspect of generative models is that they can produce new quality hit molecules using combined data from various experimental and theoretical sources -- and output results rapidly. 

One notable drug discovery startup betting on deep learning and generative models for innovative drug design is Vancouver-based Variational AI.