While the history of Artificial Intelligence (AI) field began in the distant 1950s, its practical value had largely …
What do antibiotic-resistant bacteria (“superbugs”) and coronaviruses have in common? They both can kill lots of people globally, …
The ongoing COVID19 crisis forced biotech-oriented venture capitalists (VC) to somewhat slow down the pace of their usual …
Biopharma companies are now racing to find much-needed cures against SARS-CoV-2, a virus that caused the largest global …
In The Spotlight
[Interview] How COVID-19 Catalyzed AI-assisted Open Science Drug Discovery
This Congress has a reputation for advancing pathology practice by exploring the implementation of digital pathology and artificial intelligence to advance patient care.
40+ presentations over two days offer the opportunity to discover more about the latest advances and applications of digital pathology. Learn how artificial intelligence and machine learning is being applied to primary diagnosis and clinical research and how the image-based information environment is transforming the laboratory.
The world's leading AI in Medicine Summit
Intelligent Health is the only large-scale, global summit series focused purely on AI in healthcare! Our CPD accredited summits bring the global AI and health community together to advance discussions on how to apply AI and drive technological collaboration in healthcare.
The Future is Now
The UK’s most forward thinking event, dedicated to exhibiting technology which is really just beginning to be introduced across hospital services, this truly is a pioneering event that will shape the future of healthcare.
Co-located with the Medical Imaging Convention and the Oncology Convention, join over 4000 medical professionals at the UK’s leading medical event for AI & Machine Learning.
Pharmaceutical companies are increasingly outsourcing their R&D activities, including early-stage research programs, to third party organizations -- academic institutions, biotech startups, and private contract research organizations (CROs) -- as a means to stay competitive, flexible, and profitable against all odds.
Economically, there are factors such as increasing downward pressure on drug pricing by governments, an impending “patent cliff” threatening $198 billion worth of sales during 2019-2024), and downturns in income due to the increasing competition from generics and biosimilars.
From the innovation's point of view, there is a boom in life sciences, stimulating the emergence of novel biological targets, therapeutic modalities, and even whole new areas of drug discovery -- adding opportunities, but also complexity and uncertainty to research programs. In fact, according to Deloitte’s report, return on late-stage pipelines dropped for the top 12 pharma companies from 10.1% in 2010 down to 3.7% in 2016.
Technologically, there is an unfolding “digital revolution”, bringing even further complexity and investment cost to the table -- in a form of artificial intelligence (AI), data mining and big data technologies, data-driven diagnostics, and digital health.
Finally, the rise of the personalized medicine paradigm forces companies to rethink their research pipelines and “one-size-fits-all” product development programs, as well as reconsider their market strategies.
A transformative technology for gene editing - clustered regularly interspaced short palindromic repeats (CRISPR) -- has become ubiquitous, at least in research laboratories, where scientists efficiently adopted CRISPR technology to manipulate genes of interest. Still, applying it for humans is associated with greater risks and faces ethical issues. However, alongside a too reckless experiment of a Chinese scientist who edited babies’ genomes, plenty of companies have made well-thought progress toward transferring gene editing technologies into the clinic. Here we make a brief but pithy review on up-to-date gene editing approaches and start-up companies active in this area.
Computer-aided drug design (CADD) is a central part of so-called “rational drug design”, pioneered in the last century by companies like Vertex. Over the last decades, CADD had great influence on the way new therapeutics are discovered, however, it also showed limitations due to modest accuracy of computational tools.
The majority of software tools used for computational chemistry and biology rely on molecular mechanics -- a simplified representation of molecules, essentially reducing them down to “balls and sticks”: atoms and bonds between them. In this way it is easier to compute, but accuracy suffers greatly.
In order to gain adequate accuracy, one has to account for the electronic behavior of atoms and molecules, i.e. consider subatomic particles -- electrons and protons. This is what quantum mechanical (QM) methods are all about -- and the theory is not new, dating back to the early decades of the 20th century.
Interviews with experts
While the history of Artificial Intelligence (AI) field began in the distant 1950s, its practical value had largely remained limited all the way until the emergence of powerful hardware (GPUs) in the late 1990s. Other complementary technologies played an important role in the AI progress too: new data storage capabilities, cheap cloud infrastructures, advanced deep learning algorithms -- all these things became reality only in the 21st century, effectively setting AI field for exponential development trajectory and commercial practical utility.
Today AI tech has matured to an extent it has become a strategic factor, a competitive differentiator, not only for individual companies but for the whole industries and countries. Needless to say, healthcare -- one of the major industries -- is an important end-user of AI technologies. Countries that care to adopt AI in their healthcare strategies today will have major competitive benefits for public health and safety tomorrow.
Biopharma companies are now racing to find much-needed cures against SARS-CoV-2, a virus that caused the largest global pandemic of our time. One notable effort is the COVID Moonshot project, organized by an international consortium of scientists from academia, biotechs, contract research organizations (CROs), and pharma -- all working pro bono or via crowdfunding, philanthropy, and grants.
The aim of the project is to rapidly develop easily manufacturable antiviral drugs that can inhibit the SARS-CoV-2 main protease, which is believed to be an Achilles heel of the coronavirus. The project is managed by PostEra, a startup company that uses artificial intelligence (AI) algorithms to map routes for chemical synthesis to speed the drug-discovery process.
Mesoblast Limited (Nasdaq:MESO; ASX:MSB), a world leader in developing allogeneic (off-the-shelf) cellular medicines, just announced that the first COVID-19 infected patients have been dosed with remestemcel-L, the company’s proprietary allogeneic cellular medicine. This study is conducted within the framework of the 300-patient randomized placebo-controlled Phase 3 trial underway in North America which focuses on patients with moderate to severe acute respiratory distress syndrome (ARDS) on ventilator support.
Editor's Pick: A Video Blog
The team at MIT created the most comprehensive database of metabolites, their interactions with proteins, protein-protein interactions, drug-protein interactions, and associations of metabolites with diseases. They then use the obtained interactions map to make inferences about the disease mechanisms and novel targets. With this new technology, the team launched a biotech startup ReviveMed in 2016 having raised $1.5M of funding so far.
“One-target-one-disease” paradigm has been around for decades, prompting numerous drug discovery programs focusing on identifying small molecules for targeting only one specific protein (or other targets) believed to be responsible for the disease mechanism.
Evaxion Biotech uses its machine learning-based platform to compare DNAs of tumor cells and DNAs healthy cells and identify mutations that are critical for the disease. This data is further used to design anticancer vaccines.
Artificial Intelligence Machine Learning Small Molecules Biopharma news Pharmaceutical industry trends In Silico Biotech Startup Big Data MedChem Interviews Healthcare coronavirus R&D Outsourcing Digital Technologies AI in Healthcare Database